ABSTRACT Title of Dissertation: PRINCIPALS AS STRATEGIC VOLUNTEER TALENT MANAGERS: MATCHING TALENTS AND TASKS Amy Joy Alonso, Doctor of Education, 2015 Dissertation directed by: Dr. Thomas Davis, Assistant Professor, Department of Teaching and Learning, Policy and Leadership This quantitative research study was designed to investigate the extent to which principals are implementing strategic volunteer talent management strategies and how that work is correlated to student achievement and school climate. Public school leaders face increasingly complex work environments due to fiscal constraints and changing student demographics. Greater numbers of students live in poverty, exhibit multiple learning styles, require individualized educational programs, and come to school as second language English learners (Crouch, Zakariya, & Jiandani, 2012). Therefore, the study sought to assist principals enhance their knowledge and inform their practice of volunteer management in order to meet the diverse needs of students today. The study examined how elementary principals managed volunteers in their school buildings using a researcher-created strategic volunteer talent management survey, school-level volunteer and student poverty data, and publicly available student achievement (reading and math) and parent engagement data. The study produced mixed results. The most significant findings were: (1) a positive correlation between parent engagement and volunteer program management; (2) a link between math achievement and schools that reported volunteer hours; and (3) a positive statistically significant correlation between math achievement and overall satisfaction. Given the variation in principals’ survey responses, they should follow three key steps outlined in volunteer management literature: (1) identify and prioritize which student needs remain unmet before they develop volunteer tasks, (2) develop a clear understanding of the talents and experience of each volunteer, and (3) prioritize placing volunteers in school-based tasks that best align with their unique talents. Suggestions for further research include studying how elementary principals manage volunteers in multiple districts, studying how all levels of principals manage volunteers, surveying volunteers about their experiences and perceptions working in schools, studying the distribution of volunteers within a district, and performing a cost analysis based on the volunteer distribution within a district. PRINCIPALS AS STRATEGIC VOLUNTEER TALENT MANAGERS: MATCHING TALENTS AND TASKS By Amy Joy Alonso Dissertation submitted to the Faculty of the Graduate School of the University of Maryland, College Park, in partial fulfillment of the requirements for the degree of Doctor of Education December 2014 Dissertation Committee: Chair: Thomas Davis, Assistant Professor Carol S. Parham, Dean’s Representative Dennis Kivlighan, Professor Olivia Saracho, Professor Helena Cohen, Senior Lecturer © Copyright by Amy Joy Alonso 2014 ii Acknowledgements Thank you to my family who has taken this long journey with me. Although my family lives far away, I know that they are so excited for this to happen. I always told my sisters that I was going to be a Doctor so I could “boss them around.” It turned out slightly different from how my 8-year-old self planned it, but I am still going to accomplish that goal. To the two greatest beings who have brought me joy and comfort during this process, Rufus and Drusilla, I love you. My family of friends has been my cheerleaders, editors, co-conspirators and timekeepers during this process. There are too many to name, but you each earned a piece of this with me...so thank you. Thank you to my dear friend, Dr. Cindy Eldridge. You have been a continuous source of laughter, support, and sanity since we had our first class together long before this program began. We did it and one day, my friend, I will see your name in lights. I would like to acknowledge my committee at the University of Maryland for their expertise, flexibility, and commitment to academic excellence, especially Dr. Carol Parham who has always supported me. Thank you to Dr. Tammy Kolbe who began me on my exploration of volunteers in schools. I know she would be so happy to see that this is happening. Finally, I would like to thank Dr. Tom Davis who has stuck with me over the years and was always there and ready to work with me even when I strayed from the path. Your patience, kindness, and acceptance made this possible. I truly appreciate you and the support you gave me in accomplishing this goal. iii Table of Contents Acknowledgements……………………………………………………………………….. ii Table of Contents…………………………………………………………………………. iii List of Tables……………………………………………………………………………... vii List of Figures…………………………………………………………………………….. ix Chapter One: Introduction………………………………………………………................ 1 Introduction to the Problem……………………………………………………….. 1 Background of the Study…….………………………………………………......... 2 Statement of the Problem…………………………………………………….......... 8 Understanding Volunteer Talent……………………………………………….. 8 Task Assignment Procedures…..………………………………………………. 9 Study Purpose……………………………………………………………............... 9 Research Questions……………………………………………………….............. 10 Study Significance……………………………………………………………….... 10 Definitions of Terms……………………………………………………………..... 12 Study Limitations………………………………………………………………….. 13 Chapter Two: Literature Review………………………………………………………...... 15 Resources in Education……………………………………………………………. 15 Benefits of Volunteers…………………………………………………………. 18 Volunteers Characteristics and Tasks……..………………………………………. 20 Volunteer Characteristics…………………………………………..………….. 22 Volunteer Tasks…………………………………………………….………….. 24 Strategic Talent Management……………………………..………………………. 27 Volunteer Management………………………………………………………….... 29 Planning……………………………………………………………..…………. 30 Recruiting……………………………………………………………..……….. 31 Training………………………………………………………………………… 31 Assigning and Supporting.…….…………………………..…………………… 32 Celebrating…………………………………………………………………….. 33 Retaining……………………………………………………………..……….... 33 Evaluating...…………………………………………………….. …………….. 34 Challenges of managing volunteers……..……………………………………. 34 Mid-Atlantic Volunteer Management Policies………………………………… 36 Applying Strategic Talent Management to Volunteer Management…………….... 37 Educational Needs of Schools and Students………………………………………. 39 Educational Alignment and Productivity………..…………………………...……. 41 Student Achievement………………………………………...……………….... 43 School Climate………………………………………...……………………….. 44 Theoretical Framework ………………………………………………………….... 46 iv Chapter Three: Design and Methodology………………………………………………… 47 Introduction………………………………………………………………………... 47 Rationale for Study………………………………………………………………... 47 Research Design…………………………………………………………………... 48 Conceptual Framework ………………………………………………………….... 48 Research Questions...……..……………………………………………………….. 50 Location of the Study………..…………………………………………………….. 51 Overview of Research Methods and Procedures………………………….............. 52 Phase One: Sample and Variables……………………………………………... 52 Phase Two: Data Collection and Instrumentation…………………………….. 53 Orange Leaf Public Schools Volunteer Management Survey……………. 53 Strategic Volunteer Talent Management………...………………………... 56 Orange Leaf Public Schools Parent Engagement Survey……………....…. 58 State Assessment Data………...……………………………………........... 59 Phase Three: Data analysis………...…………………………………….......... 59 Research Question 1………...…………………………………….............. 61 Research Question 2………...…………………………………….............. 61 Research Question 3………...…………………………………….............. 64 Parent Engagement and Strategic Volunteer Talent Management Conceptual Framework Model…………………………………………. 65 Research Question 4………...…………………………………….............. 69 Ethical Considerations………...……………………………………....................... 74 Summary………...……………………………………........................................... 75 Chapter Four: Findings………...……………………………………................................. 76 Procedures and Data Collection………...…………………………………………. 76 Validity and Reliability………...……………………………………..................... 78 Proper Implementation of Data Collection Procedures………...…………………. 78 Research Questions………...……………………………………............................ 79 Research Question 1………...……………………………………..................... 79 General Demographics………...……..………………................................ 79 Volunteer Management Planning………...……..………………................. 82 Volunteer Program Management………...……..………………................. 83 Volunteer Management Alignment………...……..………………............. 84 Volunteer Management Evaluation………...……..………………............. 88 Research Question 2………….…...………..…………………………............. 89 Strategic Volunteer Talent Management………...………………………... 89 Free and Reduced Meals………...………………................................... 90 Volunteer Hours………...……………………………………................ 91 Strategic Volunteer Talent Management and Student Poverty, Volunteer Hours, and Leadership Experience…………………............. 92 Research Question 3………...…………………………………....……............. 93 Parent Engagement………...………………………………………............ 93 Parent Engagement and Student Poverty, Volunteer Hours, and Leadership Experience………...………………………………..…............. 94 Parent Engagement and Strategic Volunteer Talent Management……....... 95 v Total Parent Engagement and Total Strategic Volunteer Talent Management………...……………………………………..................... 96 Two-Way Communication and Total Strategic Volunteer Talent Management………...……………………………………..................... 96 Respectful Climate and Total Strategic Volunteer Talent Management 96 Overall Satisfaction and Total Strategic Volunteer Talent Management 97 Total Parent Engagement and Strategic Volunteer Talent Management 98 Two-Way Communication and Strategic Volunteer Talent Management………...……………………………………..................... 98 Respectful Climate and Strategic Volunteer Talent Management…….. 98 Overall Satisfaction and Strategic Volunteer Talent Management……. 98 Research Question 4………...……………………………………..................... 100 Student Achievement and Strategic Volunteer Talent Management, Parent Engagement, Student Poverty, and Leadership Experience………………. 101 Student Achievement and Strategic Volunteer Talent Management……… 102 Student Achievement and Parent Engagement……………………............. 104 Student Achievement and Strategic Volunteer Talent Management, Overall Satisfaction, Two-Way Communication, Student Poverty, and Leadership Experience………...…………..………………………............. 106 Summary………...…………………………………….............…………............... 107 Chapter Five: Conclusions and Recommendations………...……………………............... 111 Discussion………...…………………………………….......................................... 111 Strategic Volunteer Talent Management in Orange Leaf Public Schools……... 112 Volunteer Management Planning………...……………..…………............. 112 Volunteer Program Management………...………………..………............. 113 Volunteer Management Alignment………...…………………………........ 115 Volunteer Management Evaluation………...……..………………............. 116 Strategic Volunteer Talent Management and Student Poverty, Volunteer Hours, and Leadership Experience………...………………..…………............. 117 Volunteer Hours………...…………………………………………............. 117 Volunteer Management and Student Poverty, Volunteer Hours, and Leadership Experience…………………………………….………............. 117 Parent Engagement and Student Poverty, Volunteer Hours, and Leadership Experience………...…………………………………….................................... 118 Parent Engagement and Strategic Volunteer Talent Management………... 119 Student Achievement and Strategic Volunteer Talent Management, Parent Engagement, Student Poverty, and Leadership Experience………...….. 119 Student Achievement and Strategic Volunteer Talent Management, Parent Engagement, Student Poverty, and Leadership Experience………...…….. 120 Conclusions………...……………………………………....................................... 122 Recommendations for Practice………...…………………………………….......... 124 Researcher Reflection………...……………………………………....................... 125 Suggestions for Further Research………...……………………………………….. 125 Suggestion 1………...…………………………………….............……............ 125 Suggestion 2………...…………………………………….............……............ 125 vi Suggestion 3………...……………………………………............……............. 125 Suggestion 4………...…………………………………….............……............ 126 Suggestion 5………...…………………………………….............……............ 126 Final Thoughts………...……………………………………................................... 127 Appendix A………………………………………………………………………………... 128 Appendix B…………………………………………………………………………….….. 129 Appendix C………………………………………………………………………………... 130 Appendix D…………………………………………………………………………….….. 135 Appendix E………………………………………………………………………….…….. 136 Appendix F……………………………………………………………………………..….. 137 Appendix G…………………………………………………………………………..…... 139 Bibliography……………………………………………………………………………….. 140 vii List of Tables Table 2.1 Framework of Volunteer Tasks 25 Table 2.2 Information Publicly Available to Community Members About Volunteers 36 Table 3.1 Conceptual Framework Variables 50 Table 3.2 Questions included in each Strategic Volunteer Talent Management Composites 57 Table 3.3 Data Collection and Analysis Chart 60 Table 4.1 Volunteer Management Planning 83 Table 4.2 Volunteer Program Management 84 Table 4.3 Volunteer Management Alignment 86 Table 4.4 Volunteer Management Evaluation 89 Table 4.5 Basic Descriptive Statistics for Volunteer Management Survey Composites 90 Table 4.6 Number of Volunteers Hours for Schools with Survey Responses 91 Table 4.7 Least Square Regression Results for Strategic Volunteer Talent Management and Student Poverty, Volunteer Hours, and Leadership Experience 93 Table 4.8 Summary Statistics for Parent Engagement Composites 94 Table 4.9 Least Square Regression Results for Parent Engagement and Student Poverty, Volunteer Hours, and Leadership Experience 95 Table 4.10 Least Square Regression Results for Parent Engagement and Total Strategic Volunteer Talent Management 97 Table 4.11 Least Square Regression Results for Parent Engagement and Individual Strategic Volunteer Talent Management 99 viii Table 4.12 Least Square Regression Results for Student Achievement and Strategic Volunteer Talent Management, Parent Engagement, Student Poverty, and Leadership Experience 102 Table 4.13 Least Square Regression Results for Student Achievement and Strategic Volunteer Talent Management 104 Table 4.14 Least Square Regression Results for Student Achievement and Parent Engagement 105 Table 4.15 Least Square Regression Results for Student Achievement and Strategic Volunteer Talent Management, Overall Satisfaction, Two-way Communication, Student Poverty, and Leadership Experience 107 ix List of Figures Figure 2.1 A Theoretical Framework for Productivity 46 Figure 3.1 A Conceptual Framework for Productivity 49 Figure 3.2 Research Question 1 Conceptual Framework Model 61 Figure 3.3 Research Question 2 Conceptual Framework Model 62 Figure 3.4 Research Question 3 Conceptual Framework Model 64 Figure 3.5 Parent Engagement and Strategic Volunteer Talent Management Conceptual Framework Model 66 Figure 3.6 Research Question 4 Conceptual Framework Model 70 Figure 4.1 Enrollment for Schools with Survey Responses 80 Figure 4.2 Leadership Experience of Administrators 81 Figure 4.3 Number of Schools by Volunteer Type 82 Figure 4.4 Percent of Volunteers Assigned to Each Task Type 87 Figure 4.5 Number of Schools in each FARMS Quartile 91 1 CHAPTER ONE: INTRODUCTION Introduction to the Problem Public school leaders face increasingly complex work environments due to changing student demographics. Greater numbers of students live in poverty, exhibit multiple learning styles, require individualized educational programs, and come to school as second language English learners (Crouch et al., 2012). In an educational environment with stretched budgets, school principals may not have all the resources necessary to meet each student’s unique needs. O’Reilly & Tushman (2011) contend that to survive in these changing times, organizational leaders must exploit and reconfigure their existing resources while they explore other possible strategies. School leaders have greater need identify and utilize available resources that can aid in efforts to meet the diverse needs of students today. To fill this void, volunteers have stepped in to play a crucial role in school- based program delivery. The use of volunteers in schools is not a new practice (Brent, 2000b; Burke, 2001; Ruffin, Lambert, & Kerr, 1985), but the way school staff view these volunteers has changed in recent years. Traditionally, principals and teachers may have viewed volunteers, especially parents, as incidental benefits to the school program. As of late, however, they have become a necessary part of educational programming, and as such, they fall under the purview and responsibility of the school principal. Today’s principal manages more than staff, students, parents, and budgets; they serve as the strategic talent managers of their own volunteer workforce and as good stewards, they must allocate volunteer resources strategically to maximize student learning. 2 While school principals may be adept at strategic talent management of staff, there is limited literature about their competencies in managing the unique challenges of volunteers resulting from flexible schedules, varied skill sets, and non-monetary compensation. To become more adept at utilizing the talents of volunteers to meet the educational needs of students, school administrators may need specific training in many areas of education management (Duke, 2010). These skills can help principals use volunteers more effectively and increase their school’s productivity. Such training in areas like securing and utilizing additional resources and strategic talent management will help ensure that educational leaders meet their school goals. Thus, we need a better understanding of how principals function as strategic volunteer talent managers who work to increase volunteer productivity by purposefully matching each volunteer’s talents to school-related tasks. Background of the Study Schools need to educate an increasingly diverse student body without increasing financial expenditures. Odden (2011) estimated that school leaders allocate more than 80% of their educational budgets to salaries and benefits, which leaves less money available for administrators to purchase other necessary resources. Increasing the pool of volunteers may be an important strategy for marshaling additional resources without adding fiscal burden. Because volunteers donate time, rather than money, the contribution they make is through their personal talents (Monk & Brent, 1997). In many cases, volunteers are a valuable resource capable of supplementing or even supplanting existing personnel in ways rarely reflected in school budgets (Michael, 1990). 3 Each task completed by a volunteer eliminates a corresponding task assigned to a salaried staff member. Within the school building, such volunteers donate their time and services through their work with parent-teacher associations, booster clubs, athletics, and other special school events (Brent, 2000b; DeCusati & Johnson, 2004) and perform a wide array of student-focused, teacher-focused, and administrative tasks. They may work directly with students to provide small group instruction, technology education, and classroom material preparation (Brent, 2000b; Burke, 2001; Michael, 1990; Shalaway, 1994; White-Hood, 1998), or they may offer enrichment and remediation opportunities (Bogan, 1997; Brent, 2000b; Burke, 2001; Castro, Bryant, Peisner-Feinberg, & Skinner, 2004; Tingley, 2001; White-Hood, 1998). Photocopying and preparing teaching materials (Allen, 1999; Brent, 2001a), assisting with grading (Butler & Grier, 2000), and library support (Michael, 1990) are all ways that volunteers directly support teachers. Volunteers also support school operations by supervising students during transition times, lunch, and recess, and by completing administrative tasks for the school and district central offices (Bogan, 1997; Brent, 2000b; Burke, 2001; Castro et al., 2004; Michael, 1990; Tingley, 2001; White-Hood, 1998). A number of factors motivate school-based volunteers. Some volunteers are parents motivated to support their children’s school, others volunteer through their employer’s business partnership (Monk & Brent, 1997; Pijanowski & Monk, 1996; Schwartz, Bel Hadj Amor, & Fruchter, 2002), and still others are members of the local community (Monk & Brent, 1997). No matter how volunteers come to support a school, there is typically a genuine interest in helping the school and its students achieve success. 4 Volunteers present with different talents and skill sets that influence the type and quality of their contributions to school operations. The value of volunteer contributions depends on both the level of volunteerism in a school and the principal’s ability to align volunteers’ talents with school tasks in order to meet the needs of the school. Wasik (1998) found that many volunteers had the skills to facilitate student learning. A volunteer who is a retired teacher with years of instructional experience, for instance, may be better suited to support classroom instruction than a volunteer who does not possess the same type of training. At times, school leaders may assign volunteers various administrative tasks, such as clerical duties, recess supervision, and hall monitoring regardless of their background or expertise. When a volunteer has instructional experience, this assignment may not prove an optimal use of the volunteer’s time and talents. The practice of placing volunteers in tasks with little regard for each individual’s unique talents is unproductive. This study will examine the ways that principals apply strategic volunteer talent management concepts to volunteer management in a manner that helps them streamline their processes to make better use of this valuable resource. For example, school leaders may want to determine a common language for the knowledge, skills, and talents needed to complete school tasks based on volunteer job descriptions developed at the school level. Systematically aligning volunteer services within the school building is one way to meet student needs without increasing financial expenditures. Pullen, Lane, and Monaghan (2004) stated, “An intervention that can be implemented effectively by volunteers can provide schools with an important resource and an inexpensive way to 5 help struggling [students]” (p. 25). By using volunteers, schools can redesign instructional opportunities for students and focus on using resources in the “most strategic and efficient ways to boost student learning and close existing achievement gaps” (Odden & Picus, 2011, p. 48). For example, a school principal may be able to reduce the student-to-adult ratio in a classroom and provide additional individualized instruction by strategically matching volunteer talents to student needs and freeing up other resources. The ultimate goal is to help principals create strategic processes that seamlessly match volunteers to the needs of the school. The productivity of a school’s volunteer resources depends on how well volunteer talents align with the work of the school. In operationalizing productivity in schools, we are looking at how schools use a set of resources to satisfy the needs of the school (e.g., reducing the student-to-adult ratio or increasing individualized instruction). Therefore, this study defines productivity as the practice of decreasing a school’s unmet needs by the work of volunteers (Rebok et al., 2011). To achieve higher levels of productivity within schools, volunteer tasks should align closely with volunteer talents. In fact, a direct link exists between productivity and the effective use of key resources “to produce certain outcomes” (Consortium on Productivity in the Schools, 1995, p. 10). A misalignment between volunteer talents and tasks may result in the underutilization of resources and correspondingly lower productivity. The concept of resource alignment closely relates to strategic talent management. According to Heidrick and Struggles (2012), companies that align their work with their human resource talent have a greater chance of sustainable success (p. 4). 6 Likewise, if school principals align the work of volunteers to the needs of their schools an increase in productivity may occur. Olsen (2010) asserted that schools can achieve high productivity when “actions, behaviors, and resources are utilized in such a way that they ultimately improve over time” (p. 2). To measure productivity, this study will look at both student achievement and school climate. First, schools can use student achievement as an indicator to whether they are utilizing productive volunteer management practices to improve students’ academic learning. Federal legislation provides states, districts, and schools with pre-determined goals and a built in accountability framework. The use of student achievement as a productivity measure for other educational areas, including school-level programs and practices, is common. Second, the study will use school climate as a productivity indicator because it can measure how the “quality and character of school life” (Cohen & Pickeral, 2007, p. 3) or school climate improves as school leaders utilize targeted actions, behaviors, and practices. Faster and Lopez (2013 ) stated that, Extensive research supports that a healthy school climate is essential to positive student development, and directly links to other key indicators for success, such as academic achievement, graduation rates, effective risk prevention, and teacher retention. When children feel safe, supported, and engaged they are better able to learn and are more fully equipped with the skills they need to succeed in school and beyond. (p. 1) Educational leaders establish positive school climates by creating and promoting trust, responsiveness, respect, safety, fairness, high expectations, and a welcoming 7 environment. Principals can approach how they manage volunteers with the same purposefulness with which they promote a positive climate. As such, they must think “about the communications, connections, and coordinated actions that they must conduct with families and community partners to help more students – indeed, all students – succeed to their full potential” (Epstein & Sheldon, 2006, p. 120). According to Perkins-Gough (2008), “Parents’ feelings about their child’s school, whether positive or negative, influence how deeply they get involved in school activities and research indicates that the right kinds of parent involvement can boost student achievement” (p. 89). Schools can use climate data to promote practices that support engagement between all stakeholders (students, staff, and parents) and enhance multiple aspects of school life (Cohen, Pickeral, & McCloskey, 2009). According to Fan, Williams, & Corkin (2011), [U]nderstanding and examining school climate seems imperative, given the significant amount of research suggesting that positive school climate is associated with various student outcomes, including academic achievement and performance, adaptive psychosocial adjustment, satisfaction with school, sense of belonging at school academic value and self-concept, motivation to learn, and student school behavior. (p. 632) This study looks to explore if the practice of strategic volunteer talent management by principals correlates to either student achievement or school climate. 8 Statement of the Problem Managing resources in schools is a complex task. School principals are becoming skilled strategic volunteer talent managers who need the skills to recruit, train, assign, and sustain their volunteer workforce. Therefore, we need to study the current practices and procedures of school principals, so that we can determine if there are ways to utilize volunteers more productively in an effort to improve student achievement. Understanding volunteer talent. Do school principals know what volunteer talents are available to them? If they do not, this lack of awareness may lead to a misalignment in volunteer assignments. A thorough review of the existing literature revealed that there is very little research to guide principals in identifying such talents. The literature on volunteers that is available focuses on smaller, targeted programs that reach specific populations, and does not explore the school principal’s knowledge of volunteers’ talents and their work. Brent (2000b) stated, Thus far, the research literature offers policy makers little insight into the nature, scope, and efficacy of volunteer activities. Most studies of school volunteerism are descriptive, speculative, and tend to report only on exemplary programs, thereby providing an exaggerated view of volunteers’ contributions to schools. (p. 494) Michael (1990) and Brent (2001a; 2000b) are the seminal studies that began to provide insight into volunteer characteristics and their work in schools. According to these studies, volunteers are generally females between the ages of 30 and 60, and most did not work when they began volunteering. Although, these studies provided 9 demographic overviews of sets of volunteers, they did not highlight how principals managed the volunteers. Task assignment procedures. School leaders historically have not developed procedures that facilitate the alignment of talents and tasks. The lack of such formal processes may lead to low levels of productivity. While existing studies provide useful information about possible volunteer tasks, they do not offer an assessment of the alignment between individual volunteer talents and assigned tasks, and focus instead on the operation of volunteer programs and the process of recruitment, orientation, and program evaluation (Grossman & Furano, 2002; Ilsley & Niemi, 1981; Shalaway, 1994; Steward & Goff, 2007). If volunteer managers do not make task assignments using an established process for matching talents to task, they may assign experienced educators to office duty, while entrusting the role of academic tutor to a high-school student. Without a clear understanding of the skills and talents of each volunteer, managers run the risk of generating misalignments in volunteer assignments. The present study will help fill the research gap on this issue by providing an exploration of the processes school leaders use to ensure alignment between volunteer talent and school-related tasks. Study Purpose The purpose of this study is to expand the body of knowledge about how Orange Leaf Public Schools (a pseudonym) principals manage school-level volunteers and if this management correlates to individual schools’ climate and student achievement. This study provides (a) a descriptive profile of the volunteer management practices implemented by a sampling of school leaders, (b) an 10 examination of any differences on how principals manage volunteers by school-level and principal characteristics, and (c) an analysis of the relationship between student achievement and strategic volunteer talent management, parent engagement, student poverty, and leadership experience. Research Questions This study will address four research questions: 1. How do principals manage volunteers across Orange Leaf Public Schools? 2. Are there correlations between volunteer management and student poverty, volunteer hours, and leadership experience? 3. Are there correlations between climate and student poverty, volunteer hours, and leadership experience? 4. Are there correlations between student achievement and volunteer management, parent engagement, student poverty, and leadership experience? Study Significance Research indicates that in recent years, volunteers have become an integral part of daily operations in schools. Because of the critical role that volunteers play in the educational setting, we need to expand the literature and deepen public understanding of the resources volunteers provide, the tasks they undertake within a school, and how to strategically manage volunteers. This information may help us develop a greater knowledge base about the work of volunteers as schools institutionalize and establish standard procedures for recruiting, training, and assigning volunteers. Though school employees continue to rely on volunteers, there 11 is little research on strategies for increasing productivity among volunteers. Efficient operations are particularly important in today’s economic climate because “schools will be pressed to stretch their educational dollars further for years, perhaps decades” due to the economic downturn (Boser, 2011, p. 13). This study will make conceptual and empirical contributions to what we know about how principals manage school- based volunteers, so that other school leaders may be able to improve their management of volunteers to support students. Results of this study have the potential to improve the policies and processes that school systems and leaders use to manage volunteers. Most school districts have policies regarding the use of volunteers, but the policies do not provide school leaders with specific talent management strategies. These policies may include procedures for establishing local school volunteer programs, the role of local school staff (e.g., the volunteer coordinator and teacher), the role of a district-level volunteer coordinator, and the mechanism for evaluating the local program, as needed. For example, Orange Leaf Public Schools (OLPS) (1999) policy on the use of volunteers is limited to (a) defining school-based volunteers as “persons who are willing to donate their time and energies to assist principals, teachers, and other school personnel in implementing various phases of school programs”; (b) recommendation that volunteers “… receive orientation, training, and supervision from school personnel to ensure effective use of their services”; and (c) “Sequential Steps in Developing and Establishing a Volunteer Program.” The policy does not address the clear need to align volunteer talents with school-based tasks. Developing processes and policies that match volunteer talents to school-related tasks improves alignment 12 and productivity at only the cost of time to develop the process and policies. This study seeks to enhance school leaders’ knowledge of strategic volunteer talent management as a recognized human resource within the school building. Definitions of Terms General administration volunteer tasks. Volunteer activities including, but not limited to, helping with field trips, working in the administrative office, monitoring the halls, and other supervisory duties (Brent, 2000b & 2001 and Michael, 1990). Productivity. This study defines productivity by how schools use a set of resources to meet goals and “…when actions, behaviors, and resources are utilized in such a way that they ultimately improve over time” (Olsen, 2010, p.2). This study uses average student achievement on standardized assessments and school climate and engagement data as productivity indicators. School climate and engagement. For this study, the researcher examined the parents’ perspectives of school climate and did not include student and staff perspectives. The words climate and engagement are used interchangeably throughout the study because OLPS uses a parent engagement survey to measure parent perspectives of school climate. Climate is the perceptions of the school learning environment based on “… the character and quality of life within a school that is shaped by its organizational structure, physical environment, instructional practices, interpersonal relationships, and overarching values, objectives, and customs” (Fan et al., 2011, p. 632). This study uses school climate and engagement data as an indicator of productivity. 13 Strategic volunteer talent management. Principals use of volunteer management strategies (planning, program management, alignment, and evaluation) to align the work of volunteers to address the unmet needs of schools and students. Student-focused volunteer tasks. Volunteer activities including, but not limited to, assisting students with reading/writing activities, math activities, science activities, computer activities, making up work, and other classroom support (includes tutoring) (Brent, 2000b & 2001 and Michael, 1990). Student achievement. A student’s knowledge and understandings of a subject-matter at one point in time (Student Learning: Student Achievement Task Force, 2014). This study uses average student achievement on standardized assessments as an indicator of productivity. Teacher-focused volunteer tasks. Volunteer activities including, but not limited to, preparing games and teaching materials, photocopying, assisting with grading, and decorating the classroom (Brent, 2000b & 2001 and Michael, 1990). Volunteer talents. Volunteer talents including, but not limited to, educational and work experiences, general life experiences and characteristics, commitment level (as measured by the amount of time spent working within the school), the relationship the volunteer has to the school, and if there are any other related skills (e.g., specialized training, second language). Study Limitations This study has several limitations. First, the research focuses solely on elementary schools in a single public school district in the Mid-Atlantic region; and as a result, the findings may not be generalizable to other school districts in the state, 14 region, or nation. Second, the scope of the research is limited to the work of school- based volunteers who support schools and local school programs during the typical school day and year. The work of volunteers who support schools through affiliated programs after school is an important area of research, but the researcher will not address that work in this study. Third, the study also examines volunteerism over the period of one school year; a longitudinal study may result in different findings. For example, a change in demographics at a local school or the development of local volunteer programs could affect the number of volunteers and the work that they do. Finally, the study will include direct data from principals collected through voluntary surveys on volunteer programming. Some respondents may have less knowledge about the volunteer resources in their schools than do others, and this disparity in information may affect the data. 15 CHAPTER TWO: LITERATURE REVIEW The study's literature review includes eight sections. The first section presents an overview of resources in education. The second section reviews the existing research literature on school volunteer characteristics and the tasks schools assign to them. The third section highlights research on strategic talent management. The fourth section details the research on the practice of volunteer management. The fifth section discusses how strategic talent management applies to volunteer management. The sixth section presents the literature on the educational needs of today’s schools. The seventh section focuses on educational alignment and productivity and their application to the utilization of volunteer resources and the chapter's final section discusses the study’s theoretical framework. Resources in Education Schools in the United States rely on a combination of resources to support instruction. School programs traditionally receive funding through monies from three main sources—federal, state, and local governments. These funds cover the costs of school operating expenses, including instructional expenditures (e.g., teacher salaries and benefits, books, etc.), administration, and other expenditures associated with school operations. Prior to 1990, public schools enjoyed steady funding through continued growth in revenue across all categories (Addonizio, 1999; National Research Council, 1999). More recently, the flow of revenue has slowed due to changes in both the political and social climates. Factors that constrain fiscal resources include: shifting demographics (e.g., increased number of households without children, which creates a powerful political group that may not have a vested 16 interest in local schools); growing populations; shared housing situations; increased demand for special education, social and health services, and wrap-around programs; and an increase in the diversity and needs of the students the public schools now serve (Consortium on Productivity in the Schools, 1995; Keller, 2000). Additionally, the cost of employee compensation, especially medical insurance, has created a challenging fiscal situation for schools. The Educational Research Service (2009) found that system leaders allocate almost 80% of all funds to employee salaries and benefits. During 2012 – 2013, Orange Leaf Public Schools (2012) earmarked 66% of its entire budget for the salary and benefits of administrative, business/operations administrative, professional, and supporting services personnel. This fiscal situation, coupled with the changes in the landscape of schools and students, has lead school district leaders to realign budgets and make cuts to programs and/or staff in order to continue spending at least as much per student as they did the previous year in order to meet student needs. School administrators have felt this change directly, and have had to reorganize and seek new resources to accommodate the gap between the fiscal resources available to schools and the outcomes that schools need to meet (Odden & Picus, 2011). School systems and local governments typically do not allocate non- traditional or non-fiscal resources, but these sources do provide schools with additional services and human capital. According to the U.S. Department of Education (2011a), “…pulling in external services and resources to support learning can effectively maximize opportunities for students” (p. 5). These varied resources include partnerships with individuals, businesses, educational foundations, non- 17 profits, and government agencies (Monk & Brent, 1997; Pijanowski & Monk, 1996; Schwartz et al., 2002); cooperative activities (whereby universities or agencies pool resources with schools to lower costs) (Addonizio, 1999; Meno, 1984); and in-kind donations [e.g., goods, services, time] (Addonizio, 1999, 2000; Meno, 1984; Ruffin, Lambert, & Kerr, 1985). In most cases, these resources are not monitored as closely as revenue from traditional sources (e.g., from state and local governments), and often go unreported. In fact, most districts do not mandate that schools report non- traditional resources (Addonizio, 1999; Schwartz et al., 2002). According to both Addonizio (2000) and Pijawoski and Monk (1996), the increased use of non-fiscal resources by schools has become uneven and limited; although in both studies, the researchers maintained that in some schools, non-fiscal resources represent a potential budget increase of seven to nine percent. These additional resources are crucial because schools use them to support school operations and programs, yet their budgets do not reflect the fiscal value of these supplementary assets. Therefore, we do not have an accurate picture of the true costs of operating a school. School-based volunteers are one key non-fiscal resource. Conceptually, volunteers provide an “in-kind” donation of individual time and talent. In many cases, schools cultivate individual, community, and business partnerships that emphasize donating individual time and talents, rather than monetary contributions (Monk & Brent, 1997; Pijanowski & Monk, 1996; Schwartz et al., 2002). The use of volunteer resources in schools is not a new practice. Harshfield (1996) considered volunteers to be valuable resources that contribute to the education of children through the services they provide. However, increased demands on schools, together 18 with limited fiscal resources provided by state and local educational agencies, have increased the importance of non-purchased resources like volunteers. This study looks to understand better the management of volunteers in schools. Benefits of volunteers. School volunteers perform a variety of non- instructional and instructional services. To evaluate the value of volunteers, we must first determine the school-level positions that are commensurate with volunteer efforts and identify the staff whose workloads may decrease through the employment of this non-fiscal resource. Typically, the work that volunteers undertake closely aligns with that of the paraeducator, teacher assistant, or paraprofessional (National Education Association, 2005). Paraeducators, often under the supervision of a certified employee, support the same aspects of the school program that a volunteer would. According to French (2003), paraeducators reduce the student-teacher ratio, which allows for a greater number of students to receive individualized attention and more differentiated instruction. Additionally, paraeducators increase instructional time for students, reduce adult-to-student response time, help create positive and compassionate adult and student interactions to support the emotional and behavioral needs of students, provide different strengths than the teacher alone, and serve as positive role models. Because of their skills and contributions, paraeducators often are highly valued within the school building. According to the National Education Association website (2012), in today’s schools, “… paraeducators are active members in teams that provide instruction and other direct services to students and their parents.” Like paraeducators, volunteers can provide one-on-one tutoring, assist with organizing instructional materials, provide support at lunch and recess, and act as a 19 translator. Based on what we know about the work of volunteers, these individuals provide schools with a non-salaried person who may perform tasks similar to those performed by paraeducators. Not only do volunteers directly support school operations, they provide other indirect benefits to the school in their roles as informal public relations agents for the school with their neighbors, friends, and businesses in the broader community (Monk & Brent, 1997). According to Epstein et al. (2002), the presence of parent volunteers “tells students, faculty, and the community that parents care about the quality of the school and the success of all students” (p. 51). Brent (2000b) found that both volunteers and principals felt that school-community relations improved because of volunteer initiatives. Relationships formed through volunteer programs led to an increased understanding among community members of how the school operated and helped to foster shared respect between school and community. Currently, school leaders encourage school staff to reach out to the community to harness its knowledge for the benefit of students (Monk & Brent, 1997). Brent’s (2000a) findings showed a similar benefit, especially within districts where schools rely heavily on local tax funding for their programming. He suggested that as the “goodwill” of the volunteer-school relationship increased, so would the fiscal and political support. “Leveraging these alternative resources can help provide students with necessary supports and services. Integrating quality services and funding streams can support the healthy development of students and in turn support their academic achievement” (U.S. Department of Education, 2011b). Consequently, the return on investment from building relationships with community volunteers may 20 increase the resources, both fiscal and non-fiscal, that schools can use to meet programming needs. Volunteer Characteristics and Tasks Volunteers are an established feature in the landscape of American education. One early documented case of organized volunteering in the school building occurred in the 1950s in the New York public school system with 20 volunteers who offered their support at least once a week (Michael, 1990). The volunteers’ purpose was to support the education of children challenged by their circumstance (e.g., poverty, limited English language skills). This movement expanded, in part, because of the growth of organizations like the Junior League and the National Parent Teachers Association. While volunteer numbers increase, the growing needs of students and schools accelerated at an even faster rate, especially as the lackluster economic forecast has continued to put pressure on school budgets. Wessely (1995) argued that the great advantage of using volunteers to further a school’s agenda is that volunteers are near- free resources, which is of considerable benefit with continued increases in budgetary cutbacks. According to Johnson, Guinagn, Bel, and Estroff (2001), with an “increased emphasis on accountability and an equally strong emphasis on individualized instruction, school systems are viewing the volunteer as a viable element in improving the quality of education” (p. 17). School leaders must incorporate productive practices to make better use of their resources (Odden & Clune, 1995). To accomplish this goal, principals can develop a deeper 21 understanding of the volunteers who serve as valuable resources and the key skills they bring to the school building. Research on school-based volunteerism is limited in scope and volume. Both Michael (1990) and Brent (2000b) found that the published studies that existed at the time of their reviews focused on specific programs and/or groups and their impact on student achievement. Michael (1990) analyzed over 12,000 public and private schools across the United States in an attempt to evaluate school volunteers in a systematic way. Brent (2000a, 2001b) completed two comprehensive studies of volunteers and their work at the local school level. His 2000 study looked at 575 volunteers in 57 elementary schools and his 2001 study looked at 708 volunteers in 68 schools. Brent and Michael both studied the characteristics of school volunteers and the tasks they accomplish, but neither looked at the methods school leaders used to match volunteer traits to assigned tasks. Beyond these seminal works, the research on the process of matching volunteers to various tasks is almost non-existent. Pickeral, Evans, Hughes, and Hutchison (2009) stated, “Fragmented programming and school improvement efforts are common at building, district and often state levels. Fragmentation or a lack of coordinated educational… efforts are perhaps the most common and powerful factors that undermine school improvement efforts” (p. 7). Although these studies are over 20 years old, researchers have not conducted any recent or more comprehensive studies of volunteers in schools. While we acknowledge this research, we have to recognize that due to changes in economic, social, and family constructs, a comprehensive study today may look different from those conducted in the past because of the unique norms and practices prevalent in 22 today’s society and educational settings. The alignment of policies and practices within school operations may positively affect school improvement efforts. This study aims to fill the gap in the existing literature regarding principals’ alignment and management practices used with school-level volunteers. Volunteer characteristics. Existing research provides limited information about the talents and demographics of volunteers in schools, beyond their primary association with the school. We know that volunteers can be community members (Allen, 1999; Bogan, 1997; Butler & Grier, 2000; Galley, 2003; Pullen et al., 2004; Ruffin et al., 1985; Van Scotter, Dusen, & Worthen, 1996; Wasik, 1997; White- Hood, 1998); cross-age volunteers (Bogan, 1997); peer volunteers (Bogan, 1997; Ruffin et al., 1985; Wasik, 1997); business leaders; county council members; board of education members; school system employees (White-Hood, 1998); or, as is most often the case, parents or family members (Allen, 1999; Burke, 2001; Castro et al., 2004; DeCusati & Johnson, 2004; Ruffin et al., 1985; Shipman, 1999; Wasik, 1997; White-Hood, 1998). In fact, Brent (2000a) and Michael (1990) found that approximately one-third of volunteers are parents. DeCusati and Johnson (2004) concluded that parents of lower socioeconomic status and parents of English language learners are less likely to volunteer at their child’s school. As volunteer managers, principals will want to examine volunteers’ general life experiences and characteristics to gain a deeper understanding of how they may interact with their volunteer assignments. This information facilitates the process of assigning volunteers to appropriate tasks and helps leaders fully utilize their skills and experience. For example, the availability of volunteers who are not working or who 23 have more free time during the school day increases the opportunity for schools to match volunteers to tasks that are more complex or longer in duration (e.g., working with a small group of students two or three times per week on math concepts). Michael (1990) found that almost a quarter of his volunteers were of retirement age, which is consistent with trends in volunteer participation. Although a volunteer’s age may not be as important to schools, availability will be crucial to understanding the extent to which volunteers are able to support school programs. As the baby boomer generation ages, schools will have a large and talented pool of well-educated volunteer resources available (Shipman, 1999; Stetnzer, 2001; Wessely, 1995). Volunteers who are retired and/or not currently working may be able to provide schools with additional volunteer hours, which in turn would increase the number of school-level tasks that are completed. Furthermore, relationships with volunteers from this growing pool have the potential to lead to the development of supportive partnerships with politically active groups and individuals (Shipman, 1999). Identifying volunteers’ time commitment is critical to aligning talents and tasks. Volunteer managers must know what a volunteer’s time commitment will be before assigning available tasks. Working with a small group of students for multiple sessions, for example, necessitates a greater commitment over time than chaperoning a single field trip. Volunteers’ time commitments vary based on the work they undertake and their general characteristics, as discussed earlier. Michael (1990) found that volunteers averaged three hours a week, although the majority of school volunteers work approximately one hour a week during a nine-month school year. (Brent, 2000a, 2001b). Knowing the length of time a volunteer will be available to 24 work is essential in assigning tasks productively, so for this study, the researcher will categorize time commitment as a talent. Finally, schools need to know if volunteers possess any specific skills or abilities (e.g., specialized training or a second language). Understanding these volunteer characteristics is important, but unfortunately, there is limited empirical research in this area. If school leaders do not take the time to understand their volunteer base and the talents that they bring to the school, they may fail to utilize them productively. Because of the varied nature of the tasks involved in a school’s daily operations, matching the skills of a volunteer with the most appropriate task requires detailed information about the individual donating their time and talents. This study will attempt to provide insight into what information principals gather about volunteers’ skills and talents before they assign them to school-level tasks. Volunteer tasks. This study will use three categories to describe volunteer services to schools: student-focused tasks (DeCusati & Johnson, 2004; Grossman & Furano, 2002; Michael, 1990; Pinnell & Fountas, 1997; Van Scotter et al., 1996), teacher-focused tasks (Allen, 1999; Brent 2000b, 2001; Butler & Grier, 2000; Edgar, 1997; Michael, 1990), and general administrative tasks (Brent, 2000b, 2001; DaSilva & Lucas, 1974; DeCusati & Johnson, 2004; Michael, 1990; Odden & Picus, 2011). Volunteers carry out a number of tasks within these broad categories. Table 2.1 provides a general framework for understanding the tasks that volunteers undertake. 25 Table 2.1 Framework of Volunteer Tasks Broad volunteer task category Specific tasks Student-focused Assist students with reading/writing activities Assist students with math activities Assist students with science activities Assist students with technology activities Tutor students and support classroom activities Teacher-focused Prepare games and teaching materials Photocopy and prepare materials Assist with grading Decorate classroom Create bulletin boards Assist with library activities General administrative Help with field trips Support the administrative office Monitor students during transitions Supervise recess and lunch duty Monitor students during arrival, dismissal, and on the bus Serve on advisory committees Sponsor extracurricular support (athletics, clubs, trips, newspapers, fundraising, and special events) 26 This volunteer tasks framework provides a depiction of the variety of work assigned to volunteers within schools. However, there is still a gap in the literature about who typically assigns volunteer tasks and the strategies (if any) utilized during the process of aligning volunteer talents with assigned tasks to enhance productivity. This study will add to the volunteer management literature by helping school leaders understand what practices principals use to align volunteer talents and school-based tasks to meet the needs of the school program. The complexity of the tasks assigned to volunteers and the decrease in fiscal resources available to schools has created circumstances where school leaders must be purposeful and systematic in their use of volunteers to support the education of students. This task has evolved with the increase in the number and complexity of instructional tasks (Grossman & Furano, 2002). School leaders have found that utilizing volunteers to implement academic interventions for students is a cost effective way to use available resources (Pullen et al., 2004). By accessing the donated labor of volunteers, schools can reach more students and provide more services. Volunteers have begun to perform school tasks previously reserved for staff members (Grossman & Furano, 2002) and the trend will likely increase as accountability demands on schools increase. As educators across the country work to meet adequate yearly progress goals in state accountability systems and as they seek affordable ways to offer additional services to students at risk of not meeting annual academic goals, it would be worthwhile to consider structured, reading-focused volunteer 27 tutoring programs as strategies to improve reading and language skills. (Ritter, Denny, Albin, Barnett, & Blankenship, 2006, p. 24) In summary, volunteers are no longer the past idea of the nice old ladies who read stories to students; they are working members of the school community who supplement a school’s workforce (Michael, 1990). Strategic Talent Management To streamline volunteer management procedures, administrators should be knowledgeable about the educational management concepts of strategic talent/human capital management—a new, more focused approach to human resource management than they may have historically used with volunteers. According to Collings and Mellahi (2009), within the world of human resources research, there has been an evolution from traditional human resource research to strategic human resource management and strategic talent management. The focus is on knowing and applying the strategies for identifying, recruiting, developing, and maintaining talent within an organization. Strategic human resource management focuses on everyone in an organization, while strategic talent management focuses on how individual employees can use their unique talents in specific and targeted positions. This shift in managing talent within an organization supports the primary focus of this study: developing principals as strategic volunteer talent mangers who productively apply strategies for utilizing volunteers’ talents to complete targeted school-based tasks. Schools typically need two key elements to operate successfully: talented people and strategic management of those people to support the organization’s goals (Odden, 2011). Principals can utilize their talent systematically to ensure maximum 28 productivity. In short, principals “…are the lead managers of human capital at the site” (Odden, 2011, p. 11). Managers must be involved in defining personnel tasks within an organization and assigning employees to complete those tasks (Dresang, 2009). Research on low-performing schools showed the need for administrators to assess faculty and staff strengths and weaknesses and redeploy those who are in positions where “their skills are not well utilized” (Duke, 2010, p. 69). Within schools, this talent applies not only to teaching and non-professional staff, but also to volunteers recruited to support the schools goals because of their unique skills. There must be an alignment between skills and assigned tasks so that volunteers are “placed strategically” (Odden, 2011, p. 9). The highest performing organizations manage individuals “in ways that support the organization’s strategic direction” (Odden, 2011, p. 9). Mello (2002) identified five key objectives in human resource planning, two of which are applicable to this study: (a) “[e]nsure the organization has the right employees with the right skills in the right places at the right times” and (b) “[p]rovide direction and coherence to all HR activities and systems” (p. 135). Principals should anticipate the needs of their schools, in terms of projected school tasks and demand, volunteer skills and training needs, and the fit of individual volunteers. Resource management requires accurate inventory of skills and talent, demand forecasting, capacity planning, and workforce rebalancing (Boudreau, 2010, p. 3). Dresang (2009) stated, …securing a match between the skills and interests of individual employees and the needs of the organization can contribute to both productivity and 29 diversity…Ideally, managers should have an information system that includes an inventory of the various skills and interests of employees. These skills and interests should go beyond those used or required for current jobs and current technologies. With a more complete inventory in hand, one can then respond readily when there are changes in mission, technology, or organization. (p. 130) The research that supports strategic talent/human capital management aligns in many ways with volunteer management research. Like leaders who work to develop strategic talent/human capital within business organizations, principals as volunteer managers should focus more on strategic utilization of volunteers to meet organizational goals. Principals must be as strategic in the use of their volunteer resources as they are with salaried school staff. Volunteer Management Volunteer management is steeped with traditional human resource management theory, but the two management areas have significant differences, the greatest being compensation for work provided. Much like human resource theory, volunteer management typically involves seven main steps: planning (Berger, 2000; Steward & Goff, 2007; Wessely, 1995), recruiting (Allington & Cunningham, 2007; Million, 2004; RGK Center for Philanthropy and Community Service, 2014; Wessely, 1995), training (Burke, 2001; Johnson et al., 2001; Million, 2004; Rebok et al., 2011; Skoglund, 2006; Steward & Goff, 2007), assigning and supporting (Million, 2004; Rebok et al., 2011; RGK Center for Philanthropy and Community Service, 2014; Steward & Goff, 2007), celebrating (Hager & Brudney, 2011; Johnson et al., 30 2001; Steward & Goff, 2007; Wessely, 1995), retaining (RGK Center for Philanthropy and Community Service, 2014; Skoglund, 2006; Warner, Newland, & Green, 2011; Wessely, 1995), and evaluating (Johnson et al., 2001; RGK Center for Philanthropy and Community Service, 2014; Wessely, 1995; White-Hood, 1998). Each step consists of many smaller steps, and may occur in different orders based on the school, the skills and experience of the volunteer coordinator, and/or the age of the volunteer program. Other identified practices involved in the effective use of volunteers include: having certified specialists supervising volunteers, giving volunteers ongoing feedback and trainings, structuring volunteer sessions in accordance with the curriculum, ensuring volunteering sessions are consistent, and providing ongoing assessments of the students’ progress (Pullen et al., 2004). Planning. Planning is critical in establishing a volunteer program. The first step is to define the needs of the school (Berger, 2000). Knowing this key information will determine how effectively the volunteer program functions and what the volunteer needs are for the program’s operations. Fisher and Cole (1993) stated that as school administrators develop volunteer programs, they must decide how to involve volunteers, enhance the value of volunteers to programs and to paid employees, include volunteers in program planning and decision making, evaluate volunteer performance, provide feedback, help volunteers avoid burnout, and create a climate in which volunteers will be most productive. In short, strategic planning is necessary to guarantee longevity and sustainability of both the volunteer program and the volunteers themselves; school leaders must plan volunteer program development purposefully to ensure a quality of alignment that will benefit the school. 31 Recruiting. Recruitment is the next step in volunteer management. Volunteer screening, interviews, interest surveys, applications, finger printing, and background checks may all be part of this process, depending on the school, district, or state requirements. Once school principals know their individual school’s needs, and how they will attempt to meet those needs, they must begin recruiting volunteers. The recruitment process begins with creating materials that entice volunteers to support the school program. Focusing on areas of knowledge and skill allows for traditionally non-involved parents to feel that they too can make a contribution (Allington & Cunningham, 2007; Brent, 2000b). For instance, you may have a limited-English-speaking parent who owns his own home improvement company. If the school has this information, staff can invite the parent in to explain how he uses math in his everyday work. Therefore, the parent engages with the school and is able to make real life math connections for students. This type of focused recruitment allows a mutually beneficial relationship to develop between the volunteer and the school while also meeting the needs of students. Training. Providing training and orientation can have a positive impact on the relationship between a school and its volunteers. According to the Morton (2013), this process allows volunteers to see the impact they are having on the agency and its clients, feel a greater part of a whole when they see all the services the agency provides, better understand the critical needs of the community, and better understand how to effect change within the issue being addressed. (p. 30) 32 Training may include offering information on school routines and policies, general expectations about dependability, confidentiality, and following identified procedures (Berger, 2000; Brent, 2000b). When preparing volunteers for school-based service, managers should provide general orientation and training, as well as pedagogical training. Although this step may seem logical within volunteer management, Brent (2000b) found that none of the schools in his study “…offered volunteers training in pedagogy. This is disconcerting given that the few examples of effective volunteer tutoring programs attribute their success to highly structured training practices” (p. 505). According to Skogland (2006), one of the main reasons volunteers stop volunteering is inadequate training. Skogland found that the volunteers in his study felt their initial training was a positive experience, but he noted that it was “unreasonable to assume that once a volunteer has completed the training, he or she is equipped with appropriate and adequate knowledge for the duration” of the volunteer experience (p. 219). Setting a strong foundation for the ongoing relationship the school will have with the volunteers is a primary objective of training (Edgar, 1997). Without this foundation, the school may not be able to maintain sustained volunteer efforts. Assigning and supporting. Matching the volunteers’ experiences and expertise to the identified school tasks is essential (Berger, 2000). Once volunteers complete their training, they can receive their placement into volunteer roles within the school’s program. As the volunteer works with the school, staff must work to provide an atmosphere of support and supervision. This environment should include the monitoring of staff and volunteer relations (RGK Center for Philanthropy and 33 Community Service, 2014), feedback, additional training if needed, coaching, and efforts to quickly address any problems that arise. Supporting and recognizing volunteers are essential aspects of maintaining a consistent volunteer base over time. The time it takes to recruit and train each new volunteer takes time away from other important priorities, so maintaining and building on the existing group of volunteers is important. Of course, bringing in new volunteers, just like staff, keeps a fresh outlook; but a constant turnover can create a lack of consistency that will not help the school or its programs. Celebrating. Celebrating volunteers is an essential step in the volunteer management process. Celebrations may look different in various schools, but can include certificates, awards, small tokens of appreciation, or other personnel recognition ideas. This step in the volunteer management cycle is crucial to retaining volunteers and is a common strategy used to offer extrinsic compensation to school- based volunteers. School principals must determine and then capitalize upon the incentives that motivate their volunteers (M. A. Hager & Brudney, 2011). Motivation to serve, whether for personal fulfillment or to support their children’s school, serves as intrinsic compensation for many volunteers. This non-monetary recompense is the largest difference between managing staff and managing volunteers. Retaining. It is crucial that administrators discover what motivates their volunteers. Warner, Newland, and Green (2011) suggested that by better understanding the volunteers’ experiences and satisfaction, school leaders can increase the overall benefit of volunteer programs as a whole. Principals should determine which conditions must be present to motivate unpaid workers to continue 34 serving in a volunteer capacity because retention of volunteers means a continuation of services and less principal time spent recruiting, training, and assigning new volunteers. Evaluating. Lastly, an effective volunteer program evaluates its volunteers, along with its processes and procedures (Fisher & Cole, 1993; Morton, 2009; RGK Center for Philanthropy and Community Service, 2014). An evaluation of the program can also help identify motivational factors for volunteers. If the local school system does not have a volunteer office, many states, county, and city governments have volunteer management programs and /or offices that offer support. Challenges of managing volunteers. Managing volunteers brings its own set of challenges to school leaders. Hager and Brudney (2004) found eight common obstacles facing volunteer managers: volunteer recruitment, volunteers without the needed skills or expertise, limited number of volunteers available during the workday, lack of funding to support volunteer management, time constraints for staff to train and supervise volunteers, unreliable or absent volunteers, legal and liability constraints, and an overflow of volunteers that the organization cannot accommodate. School leaders face similar issues in recruiting volunteers to meet school needs. Hager and Brudney (2011) studied over 1,300 organizations that work with volunteers and found that 24% report significant problems recruiting enough volunteers and 25% report significant problems recruiting volunteers during the workday. Merrill (2005) refers to this challenge as time poverty. Today people feel that they do not have enough time to do all of the things that are required or that they would like to do because their schedules are over committed. “In a time of time 35 poverty people are increasingly weighing their return on investment. They are seriously gauging what is required of them and what they will get in return for that investment of time and energy” (Merrill, 2005, para 5). School leaders need to help school volunteers understand that there are opportunities for volunteer that may not require long-term commitments or may occur during non-work hours like preparing materials for a classroom or bulletin board. Another concern principals have in managing volunteers is what legal or liability issues may occur. School leaders can take preventive measures by screening, training, and supervising all volunteers (Brent, 2000c; Harshfield, 1996: Wren, 2000). Some school systems require fingerprints, personal references, medical clearance (chest x-rays and tuberculin skin tests), and other screening processes (Harshfield, 1996). However, some school systems do not. Therefore, school leaders acting as volunteer managers must ensure that volunteers have clear training on expectations and responsibilities as well as be vigilant in providing constant supervision of volunteers as they work with students and in school buildings. Brent (2000c) found that although none of the schools he studied were involved in litigation regarding volunteer negligence, two schools are involved in legal proceedings due to volunteer injuries that occurred while at school and involved in volunteer work. A unique challenge in manage volunteers stems from the fact that many volunteers are parents and they may have an “ulterior motive for volunteering” (McGown, 2007, p. 13). She continues that staff need to remember that, “It is extremely important…to monitor carefully what is said to parents about the school, its programs, and faculty” (McGown, 2007, p. 13). Principals can help minimalize 36 any potential issues by having volunteers focus on supporting students other than their own, perhaps in different grade levels, and continue to stress student confidentiality at all volunteer orientations and trainings (Shalaway, 1994). Additionally, volunteers must be aware of possible consequences if they do not implement school policies and procedures or violate student confidentiality. Mid-Atlantic volunteer management policies. The last sections detailed the steps involved in effective volunteer management. Since this study takes place within the Orange Leaf Public School District (located within the Mid-Atlantic region), it may be helpful to understand volunteer management practices in other Mid-Atlantic public school systems. Table 2.2 provides useful information on the volunteer programs in a number of Mid-Atlantic public school districts listed by pseudonym. This information is publicly available. Table 2.2 Information Publicly Available to Community Members About Volunteers Red Hook Public Schools Blue Flower Public Schools Orange Leaf Public Schools Green Tree Public Schools Contact office listed X X X Tasks needed X X Limited Policy/Regulation X X Parent Involvement Application X X X Handbook X Volunteer responsibilities X X X Volunteer Coordinator Responsibilities X X X Principal responsibilities X Background checks required for non-parents X X 37 Applying Strategic Talent Management to Volunteer Management School principals must be well versed in understanding how to run a volunteer program that meets the school’s needs. To be successful, principals should be agile in their planning and decision making regarding the human capital that supports their school’s mission. Collings and Mellahi (2009) contend stakeholders make a strong argument that within today’s market, talent management is important at all levels of an organization’s leadership. This concept applies to schools and their volunteer management practices, as well. Most districts have volunteer policies and processes, but the induction, placement, and success of volunteers within a school lies generally with the school-based administrator or volunteer manager. To deploy volunteers successfully, school leaders must develop a model that drives their work. This study will attempt to understand what practices principals in one district use to manage volunteers and how that management is correlated to student achievement and school climate. The literature on strategic talent management and volunteer management generally focuses on different disciplines (M. A. Hager & Brudney, 2011). Strategic talent management research typically focuses on business practices, while the nonprofit sector publishes the most volunteer management literature. Hager and Brudney (2011) found ”…differences in values, mission, identity, social goals, outcomes, and ideological characteristics compromise direct applications of human resource research and theory from business to nonprofit organizations,” while others have argued that “...human resource management is largely absent from nonprofit organizations” (p. 138). However, the application of the theory behind strategic 38 talent management is applicable to the nonprofit and educational sector. What we do know is that strategic talent management …addresses how all aspects of the human resource management system (typically called personnel administration in most school districts) can be aligned, including recruitment, screening, selection, placement, induction, professional developed (focused on curriculum and classroom practice), evaluation, compensation and promotion into instructional leadership. The goal is to redesign the entire human capital systems so that top talent is acquired, strategically placed and equitably distributed in key roles in schools and districts, developed and retained over time, all driven by metrics on teacher and leadership performance and effectiveness. (Odden and Kelly, 2008, p. 2) These two fields of research have much in common, but with a focus on different audiences and potentially different motivators. This study aims to identify how principals manage volunteers and determine whether they apply any identified strategic talent management strategies in their volunteer management practices. When IBM looked to streamline their talent supply chain, they created a decision framework that linked “logical connection between decisions about the resources and the organization’s goals…The framework would also be built upon logical principles of supply chain management that would show how decisions in one area connect to important outcomes” (Boudreau, 2010, p. 5). IBM created an employment life-cycle model that managers could use as they worked. The cycle includes developing strategy (how can we do this), identifying supply and demand 39 (understanding what resources are available and how to get more), planning (looking at capacity), acquiring and transitioning staff (recruit and onboard staff), developing all organizational areas (programs and people), deploying (modify, select, and assign) and classifying employee programs (salary, benefits, and incentives). The present study seeks to evaluate how principals serve as strategic volunteer talent managers. Educational Needs of Schools and Students In an age of increased accountability, students need more individualized attention; yet budget constraints have forced school leaders to cut staff and programs, leaving the educational needs of students unmet. Looking across schools, districts, and states, one can see consistent trends in these unmet needs, which typically include additional academic support, lower class sizes, individualized instruction, lower adult-to-student ratios for non-structured times (e.g., recess/lunch), specialized knowledge bases, and improvements in other areas of the school program. Odden and Picus (2011) proposed a comprehensive recommendation to improve teaching and learning, even during an economic downturn. They advocated for a reduction in teacher-student ratios (15:1 in grades K – 3 and 25:1 ratio in grades 5 – 12), the provision of multiple resources for struggling students (tutoring positions based on the number of students living in poverty and paraeducators to support students with learning disabilities), and the addition of administrative and clerical support staff (to cover recess, lunch, and bus supervision). Despite their helpfulness, these proposed reforms are very expensive; however, principals may offset the cost by using volunteers to fulfill some of the suggested tasks and duties. Vadasy (2011) asserted that schools, when their human and monetary resources are spent, must look for ways 40 to “provide more intensive attention to students who experience problems learning to read. Often schools find ways to offer supplemental reading instruction or tutoring to their neediest students” (p. 300). In the current economic climate, both schools and students face a number of immediate educational needs. Today, students come to school with greater individual needs resulting from poverty, non-traditional family structures, language barriers, interrupted instruction, and high mobility. Administrators must prioritize their efforts to meet the diverse needs of their students given these increases in need, coupled with lack of adequate funding. School leaders typically base this prioritization of student needs on district policies; consequently, leaving other needs unmet such as reducing adult-to-student ratios. Austin Partners in Education (2012) shared their successes in reducing class size through focused volunteer support: Our Classroom Coaching model transforms whole class instruction (with student to teacher ratios of 25:1 or higher) to small interactive learning teams with one adult volunteer matched to three or fewer students (3:1). Trained coaches work with the same groups of children for 45 minutes, once weekly, throughout the school year. Students are supported with high engagement learning activities in reading or math that are targeted to their individual needs, and because this support is integrated into the classroom, a deep connection with the AISD curriculum and teacher-led instruction is established. (p. 7) Meeting these burgeoning needs with fewer resources is not an easy task. In essence, school leaders must produce higher outcome levels with lower input levels. 41 According to the San Francisco Education Fund (2011), an organization that provides hundreds of volunteers to select San Francisco schools, 92% of teachers reported an increase in their ability to address goals and priorities as a result of the volunteers; and 91% of teachers reported an increase in student academic skills after working with volunteers. Bringing in additional resources like volunteers begins to alleviate needs that may otherwise go unmet. Accomplishing this task will “require leaders at every level—from the classroom to the statehouse—to work together to rethink the policies, processes, tools, business models, and funding structures that have been ingrained in our education system for decades” (U.S. Department of Education, 2012). Educational Alignment and Productivity It seems unlikely that the current financial demands on American schools will improve quickly. As such, schools may continue to face budget limitations, while expectations for student achievement will remain high. According to Odden (interviewed by Lockwood, 1996), given that the economy may remain weak for some time, “...the only way we can accomplish the goals of education reform is to create a more productive education system” (p. 9). To meet the demand of providing a high-quality educational experience for students, school leaders must continue to improve human capital policies and practices. Principals can continue to develop non-fiscal resources by cultivating relationships with a varied pool of volunteers. Once these relationships are established, it is critical that schools align the strengths of these resources to the needs of the school. “The fundamental challenge facing American primary and secondary education is thus to figure out how to make better 42 use of its resources – in other words, how to be more productive” (Ball Foundation, 1995, p. 4). Dresang (2009) argued that managers at all levels have to use their formal and informal authority and influence to encourage staff to align their work to meet organizational goals. School leaders must standardize their use of non-purchased inputs like volunteers to help provide services and programs they either cannot offer at all or cannot offer at the same adult-to-student ratio. According to the US Department of Education website (2011c), Leveraging community resources and local partnerships supports high-quality academic and enrichment opportunities by broadening the experiences that may be typically offered to students and by expanding access to local expertise. Better aligning and utilizing these resources can also help school systems identify and access low-cost services or facilities to support learning opportunities on and off school sites. Pulling in local resources such as health and human services agencies, departments of public safety and parks and recreation, community colleges, businesses, community-based organizations, and other entities can effectively maximize opportunities for students and school systems. (Better Use of Community Resources, para 1) Enhancing volunteer productivity by aligning talents to tasks is one way to maximize student access and achievement, but we first need to establish how schools use the non-fiscal resource of volunteers (e.g., volunteers’ duties and contributions). According to Odden and Clune (1995), the only way to meet student needs may be to increase productivity, in part, through managing resources. This effort may require a 43 new way of looking at alignment and productivity. School leaders need to lessen the unmet needs in their buildings, and starting with the end in mind may help principals prioritize assigning volunteers in an aligned and strategic manner that lessens those needs. This study looks directly at the information principals gather about their volunteers’ talents, the tasks assigned to volunteers, the processes in place to assign these tasks, and if these practices are correlated to two productivity measures: student achievement and school climate. Student achievement. Historically, United States citizens value student achievement and academic success in their educational system because of the link to positive outcomes portrayed in the American dream. According Nichols, Glass, and Berliner (2005), the publication of A Nation at Risk in 1983 caused the American educational system to come under scrutiny for not meeting the nation’s expectations and in turn led to the development of high-stakes testing as a measure used to ensure schools are accountable for student learning. Currently, the nation’s education legislation, the No Child Left Behind Act of 2001, requires the annual testing of students in grades 3 – 8 in both reading and mathematics. Students have to make adequate yearly progress towards proficiency goals established by each state’s legislature. This legislation requires that states provide sanctions for schools that are continually not meeting the set state standard, especially those that receive Title 1 funding. The use of student achievement as a productivity measure for other areas of school programming is not new. In fact, student achievement measures the productivity of many different school-level programs and practices including, but not limited to class size (Phelps, 2011), principal leadership (Gordon, 2013), and teacher 44 beliefs (Ross & Gray, 2006). This study uses student achievement data to examine the productivity of principals’ strategic volunteer talent management practices. School climate. Many school leaders are expanding the measures they use to qualify success and productivity. One such complementary measure is school climate. Creating a climate that is welcoming to partnerships, even to those not traditionally involved in the school, is essential. “School climate is defined as the character and quality of life within a school that is shaped by its organizational structure, physical environment, instructional practices, interpersonal relationships, and overarching values, objectives, and customs” (Fan et al., 2011, p. 632). Parker, Grenville, and Flessa (2011) studied school community and climate in a number of schools for one year. They found that schools with positive climates understood the importance of partnerships and bringing in family and community members to work with students and other school-related persons (Parker et al., 2011). In one school, Parker at al. found an exemplar of a school and volunteer partnership: Sometimes all it took was one dynamic person to make a difference. At one inner-city school, a single, teenage mother was the driving force behind many school-based initiatives and school improvement plans. She organized school- wide trips, she planned fundraisers, and she recommended that the school newsletter be translated into multiple languages. Great things were possible because the administration recognized a natural leader that the community identified with and assisted her in any way possible. (p. 139) 45 Miller (1981) found that the climate of the school can have a positive effect on pupil attitudes and student achievement. A welcoming and nurturing school volunteer program is one way to improve the climate. Assessments of school climate can occur in multiple ways. Climate surveys, an often-used tool, are effective for “…recognizing student, parent, and school personnel voice and assessing all the dimensions that color and shape the process of teaching and learning and educators’ and students’ experiences in the school building” (Cohen, Pickeral, & McCloskey, 2009, p. 45). Orange Leaf Public Schools collects this type of data annually from students, parents, and staff. Although we know that volunteers are not always parents, both research and practice indicate that most volunteers and students have a familial relationship. Perkins-Gough’s (2008) report “reconfirms the importance of building direct, personal relationships with parents to strengthen their support and increase their involvement in their child’s education” (p. 90). Therefore, using climate data from parents or guardians will provide an understanding of many volunteers’ perceptions of the school. These data also are appropriate for examining productivity. As Miller (1981) stated, The importance and interrelatedness of staff morale, school climate, and educational productivity to pupil learning and effective staff performance cannot be denied. The impact of the leader’s behavior as a key element in establishing good morale is strongly supported…behaviors which will improve staff and student moral and produce an improved school climate must be fostered. If efforts are to be successful, there must be participating of staff and the resources…must be marshaled. (p. 486) 46 Education involves more than reading and math; it provides students with a healthy and safe environment, while improving processes and practices that develop and nurture partnerships. For this study, the researcher will adapt Fan et al.’s (2011) model of school climate. This model will help the researcher to examine the relationship between volunteer management, school climate, and student achievement. Theoretical Framework Fan et al.’s (2011) model of school climate illustrated the connectedness of individual-level variables for students (e.g., parental education level, enrollment in one or more schools, behavior issues), school-level variables (e.g., percent of Free And Reduced Meals (FARMS), type of school, enrollment numbers) and perceived school climate (e.g., safety, fairness of rules, and relationships). This study’s theoretical framework model incorporates student achievement as the definitive productivity measure. Figure 2.1 depicts this study’s productivity model. Figure 2.1 A Theoretical Framework for Productivity STRATEGIC VOLUNTEER TALENT MANAGEMENT STUDENT ACHIEVEMENT SCHOOL VARIABLES VOLUNTEER VARIABLES ADMINISTRATOR VARIABLES CLIMATE VARIABLES 47 CHAPTER THREE: DESIGN AND METHODOLOGY Introduction Volunteers are a growing resource within schools and it is important to understand how leaders use them to support a schools’ work. This study seeks to understand better what volunteer resources are available within Orange Leaf Public Schools, how principals are managing these resources, and if that management is correlated to school climate and student achievement. The researcher analyzed the relationships between strategic volunteer talent management data, individual leadership and school characteristics, school-level parent climate data, and student achievement data. By understanding and evaluating the processes and practices these principals used to align school volunteer resources, other school leaders may be able to create stronger alignment of resources at their schools to increase volunteer productivity. The following sections describe the study’s rationale and research design, conceptual framework, research questions, location, research methods and procedures used to collect and analyze data, and ethical considerations. Rationale for Study Managing volunteers in schools is a complex task. This study examines what school leaders know about volunteer work in their schools and if this work correlates to school engagement and student achievement. This study seeks to enhance school leaders’ knowledge of strategic volunteer talent management and to inform the practice of volunteer management. 48 Research Design First, the researcher investigated elementary school principals’ strategic volunteer talent management practices for aligning volunteer talents to volunteer tasks through the Orange Leaf Public Schools Volunteer Management Survey. Creswell (2009) states that a survey instrument allows for the researcher to measure both attitudes and behaviors. This study used the Orange Leaf Public Schools Volunteer Management Survey data to develop a profile of principals’ attitudes and behaviors with regard to volunteers. The researcher analyzed the data to provide a summary of how principals manage volunteers in OLPS. Second, the researcher looked at engagement survey data from parents. By studying engagement data, the researcher gained a more robust perspective on the climate of the elementary schools. The researcher then examined any possible correlations between the data from the volunteer management survey and school-level engagement data. Third, the researcher measured productivity using student achievement data as the dependent variable. The researcher ran several multiple regression models with data from the principal’s survey, school-level variables, parent engagement results, and student achievement. Conceptual Framework This study seeks to increase knowledge of how school principals employ volunteers to meet the needs of their schools to increase student success (Rebok et al., 2011). Figure 3.1 details the operationalization of this study’s theoretical framework into a conceptual framework. As stated earlier, school climate and parent 49 engagement are interchangeable within this study, as are principal tenure and leadership experience. Table 3.1 provides labels for the framework’s variables. Figure 3.1 A Conceptual Framework for Productivity STRATEGIC VOLUNTEER TALENT MANAGEMENT STUDENT ACHIEVEMENT SCHOOL VARIABLES VOLUNTEER VARIABLES ADMINISTRATOR VARIABLES CLIMATE VARIABLES 50 Table 3.1 Conceptual Framework Variables Area Variables Student achievement  Average school-level standardized testing results – reading  Average school-level standardized testing results – math School climate  Parent engagement survey results Strategic volunteer talent management  Total strategic volunteer talent management variable  Planning variable (application, establishing school needs, task description, identifying volunteer coordinator/team, recruitment)  Program management variable (orientation, training, recognition, on-going feedback)  Alignment variable (matching volunteer talents and tasks)  Evaluation variable (program and process evaluated) School characteristics  FARMS rate Leadership experience  Total tenure as an administrator Volunteer  Volunteer hours School characteristics are often not within the control of school leaders, while alignment and productivity are active management issues. Mismatches in the policies and procedures school leaders use to align volunteers and their work may cause a decrease in productivity. This study will add to existing research by focusing on principals as volunteer managers and their efforts to align the work of volunteers to address the unmet needs of schools and students. Research Questions 1. How do principals manage volunteers across Orange Leaf Public Schools? 51 2. Are there correlations between volunteer management and student poverty, volunteer hours, and leadership experience? 3. Are there correlations between climate and student poverty, volunteer hours, and leadership experience? 4. Are there correlations between student achievement and volunteer management, parent engagement, student poverty, and leadership experience? Location of the Study This study occurred in the large Mid-Atlantic school district known as Orange Leaf Public Schools. The school district is one of the 20 largest school systems in the United States and the largest within its state. OLPS serves over 150,000 students from more than 150 countries. The school district is diverse in its geographic makeup including students from suburban, urban, and rural areas. Orange Leaf Public Schools student population is extremely diverse. Of the students enrolled in 2012 -2013, almost 70% were from an ethnic minority. Students within OLPS receive the following services:  Over 40% participate in the free and reduced-price meals program;  Over 10% receive special education services;  Almost 15% receive English for speakers of other languages services. Nationally recognized for its graduation performance, success in raising student achievement and closing the achievement gap, and system-wide excellence, including multiple National Blue Ribbon Schools, OLPS is known for its students’ achievement. The percentage of students taking the SAT, ACT, and AP exams 52 exceeds national benchmarks. This same level of academic performance is seen across ethnicity groups (Orange Leaf Public Schools, 2013). Overview of Research Methods and Procedures After the approval of the dissertation proposal by the research committee and the University's Human Subjects Review Board (Appendix A), the researcher requested permission from OLPS accountability office to conduct the study (Appendix B). The researcher conducted the study in three phases: (1) sample selection; (2) data collection; and (3) an analysis of all data. The next sections describe each phase. Phase One: Sample and Variables. The researcher sent the Orange Leaf Public Schools Volunteer Management Survey to the 132 elementary school principals in OLPS. This survey solicited data on: (a) strategic volunteer talent management; (b) school demographics; and (c) leadership experience. The OLPS accountability office provided the volunteer variable and school climate variables. The researcher obtained public domain data for one school demographic variable and the student achievement variables. The description of each variable follows. Leadership experience variable. Administrators self-identify how long they served as administrators at any school (tenure). The variable is divided into five bands ranging from 1 (0 – 5 years) to 5 (>20 years). Strategic volunteer talent management variables. Variables generated from the Orange Leaf Public Schools Volunteer Management Survey data based on the four 53 identified strategic volunteer talent management areas: planning, program management, alignment, and evaluation. Volunteer variable. The total number of volunteer hours each elementary school self-reported. School climate variables. A principal components analysis found that there were three common themes across the engagement questions: (1) two-way communication, (2) respectful climate, and (3) overall satisfaction. School characteristics variable. Percent of student poverty based on Free and Reduced Meals eligibility. Student achievement variables. The average school-level standardized testing results for reading and math. Phase Two: Survey data collection and instrumentation. The following section describes the instrumentation used to collect the study’s survey data. Orange Leaf Public Schools Volunteer Management Survey. The researcher created four strategic volunteer talent management areas for this study from the seven steps typically found in volunteer management literature. They are: (1) volunteer management planning (application, establishing school needs, task description, identifying volunteer coordinator/team, and recruitment); (2) volunteer management alignment (matching volunteer talents and tasks); (3) volunteer program management (orientation, training, recognition, and on-going feedback) (4) and volunteer management evaluation (program and process evaluated). The researcher designed the survey to analyze how principals use these components to manage volunteers within a school. Creswell (2009) supported the use of surveys to provide “a 54 quantitative or numeric description of trends, attitudes, or opinions of a population by studying a sample of the population” (p. 145). Principals are the leaders in schools and their beliefs and practices affect all school programs. The researcher, when using this data collection technique, assumes that the respondents are knowledgeable and have meaningful information to share. These data will show how administrators’ thinking and behaviors support or do not support alignment of strategic volunteer talent management resources. This survey is a one-time, cross-sectional Web-based survey allowing for rapid turnaround in data collection and evaluation of the sample to understand how administrators manage volunteers in their school programs. The researcher provided principals with written information about the study. This communication invited them to participate voluntarily in completing the online survey. The invitation letter included a Web address that participants used to access the survey. The letter also included contact information in case the prospective participant had any questions about participating in the study. No principals contacted the researcher with questions. Completion of the survey signified that the participant is at least 18 years of age and consented to his/her participation in this study. Additional attempts to collect data occurred through second emails and the use of the interoffice mail system established in OLPS. The Orange Leaf Public Schools Volunteer Management Survey is available in Appendix C. Because the researcher constructed the survey, the tool needed validation. Gall, Gall, and Borg (2010) stated that the researcher must test the survey to analyze the responses and to address any questions raised, so that the survey may be refined. 55 The researcher chose to use cognitive testing. According to Harrison (2008), cognitive testing potentially avoids any problems in answering survey questions, including, failure to comprehend, problems summarizing, and problems reporting answers. If respondents fail to comprehend questions or interpret them differently, it is likely the researcher will receive inaccurate answers. Problems summarizing and problems reporting answers include when “respondents are thinking about a lot of things, they can inconsistently summarize” and “confusing or vague answer formats lead to variability” (Harrison, 2008, p. 1). For this study, the researcher interviewed two OLPS assistant principals because of the limited number of elementary principals in OLPS. They provided the researcher with feedback closest to that of an actual principal. The researcher could not use OLPS principals in the cognitive testing phase because it would have limited the sample available for the actual study. Orange Leaf Public Schools assistant principals assist in the management of schools and are closest to the principal. They work under the guidance and direction of their school principals or supervisors. They assist with many of the tasks involved in administering and supervising the total school program and providing educational leadership for the students and staff members consistent with the educational goals of the community. Their functions may include: establishing a climate conducive to learning; planning and coordinating programs; decision-making; and monitoring student progress. It is expected that they demonstrate initiative and be able to problem-solve using their best professional judgment (Orange Leaf Public Schools, 2011). 56 These interviews allowed the researcher to understand better the thought process of respondents, including “how they understood a question and how they arrived at their answer” (Washington Group on Disability Statistics, 2005, p. 1) and for the identification of specific problems with questions. The use of the active probing strategy during cognitive interviews allowed the researcher to play a more active role in the interview and identify specific problems with questions. The interview also allowed the researcher to understand the perspective of the school leader, the cognitive strategies used to answer questions, the interpretation of questions, and the assistant principal’s understandings of the concepts. Based on the data collected at the interviews, the researcher analyzed the data collected from these interviews and made minor adjustments to wording or the type of question that would remain in the survey. Strategic volunteer talent management. To develop the strategic volunteer talent management composite variable, the researcher ran a principal components analysis using SPSS software, but found that the analysis created too many factors that did not correspond to the data on volunteer management. Because of this and the relatively small sample size, the researcher developed composite variables manually by summing together selected questions from the strategic volunteer talent management survey’s four management areas (volunteer management planning, volunteer program management, volunteer management alignment, and volunteer management evaluation). The researcher omitted questions that did not use a four point Likert scale to improve reliability. Next, the researcher verified that all questions had a positive correlation so no recoding was necessary. Table 3.2 displays 57 which questions were included in each strategic talent management area: volunteer management planning, volunteer program management, volunteer management alignment, and volunteer management evaluation. Table 3.2 Questions included in each Strategic Volunteer Talent Management Composites Question Volunteer management planning composite 6. Volunteers have to complete an application to volunteer. 7. My school compiles a list of school needs/tasks that volunteers can support. 8. My school has a description of what skills are needed to complete the tasks identified. 9. My school actively recruits volunteers. Volunteer program management composite 12. Volunteers are interviewed before being assigned. 13. Volunteers are required to attend an initial training. 14. Volunteers receive ongoing training. 15. I facilitate the volunteer training. 16. I do not facilitate the training, but I attend. 17. ALL volunteers are recognized for their work. Volunteer management alignment composite 18. My school’s priorities for placing volunteers are: Additional Academic Support Lower Class Lower Adult to Student Ratios in Non- Structured Areas for Safety (e.g., Recess/Lunch) Other Areas of the School Program 19. Volunteers help my school meet its priorities. 23. My school uses the information gathered from volunteers when assigning them to tasks. 24. Volunteers are assigned to a particular student or student group. 25. Volunteers are assigned to a particular teacher. 26. Volunteers are assigned to a particular recess or lunch period. 27. Volunteers meet with assigned student(s) before beginning their assigned task. 58 28. Volunteers meet with assigned teacher before beginning their assigned task. Volunteer management evaluation composite 29. My school reviews the processes used for assigning volunteers. 31. Volunteers are provided with an exit interview. Last, the researcher created a total volunteer management composite, which was the sum of the four individual composites. The five variables are included in the regression models discussed later in the chapter. Orange Leaf Public Schools parent engagement survey. Second, the researcher obtained the publicly available parent engagement data from the 2012 – 2013 Gallup Engagement Survey from the district’s accountability office. The survey has 21 questions on parent engagement and two questions on overall perception. OLPS sends home the survey purpose, general information, and access information for the Web-based survey to a random sampling of families, but survey questions are in English only, which may be problematic because of the 138 languages spoken in OLPS. It is likely that many of the selected households were not able to complete the survey. According to the Orange Leaf Public Schools website (2014), survey “…surveys are important sources of information about the perceptions of the school learning environment …findings can be used to monitor continuous improvement efforts and inform school improvement goals.” (School Survey Results, para 1). These results provide one of this study’s measures for productivity, school climate or engagement. According to Kelley (1981), “school climate involves more than morale. It’s the interaction between satisfaction and productivity for everyone in the school” (p. 180). The researcher relied on the OLPS accountability office for the validity of the engagement survey. 59 The researcher examined the raw engagement data provided by the district’s accountability office and created a total parent engagement composite, which was the sum of the averages for 21 questions. Then, she chose to implement an analysis of the data using statistical software to develop composite variable(s) for engagement to use in the regressions models analyzed for research question 3 and 4. The researcher ran the principal components analysis using SPSS software. The results of the principal components analysis are in Appendix D. After the analysis was completed, the researcher reviewed the individual questions under each component to determine if any themes emerged. The researcher found that there were three common themes across the engagement questions as they loaded onto the three primary factors: (1) two-way communication, (2) respectful climate, and (3) overall satisfaction. The researcher chose to eliminate a fourth factor, based on questions 16 and 23, due to a weak loading reflected in a small eigenvalue. The questions for each factor are in Appendix E. State assessment data. The annual state assessment measures how well students are learning concepts and skills specified in the state curriculum. These assessments meet the federal testing requirements of No Child Left Behind Act and measure students’ yearly progress. The assessment administered annually in the spring measures students’ achievement in reading and mathematics. The researcher used building-level mean achievement data in reading and mathematics to test correlations between strategic volunteer talent management, school engagement, and student achievement variables. The researcher relied on OLPS state department of education office for the validity of the student achievement data. 60 Phase Three: Data analysis. Using the aforementioned data, the researcher analyzed the correlation between student achievement, school engagement, strategic volunteer talent management, school characteristics, leadership experience, and volunteer variables. The researcher constructed a bilateral correlation table found in Appendix F. Table 3.3 provides an overview of data sources, methods of collection, nature of data, and data analysis procedures for each question. Table 3.3 Data Collection and Analysis Chart Research Question Data Source Method of Collection Nature of Data Data Analysis Procedure(s) How do principals manage volunteers across Orange Leaf Public Schools? Voluntary principal survey Survey Quantitative Summary Statistics Are there correlations between volunteer management and student poverty, volunteer hours, and leadership experience? Voluntary principal survey Data file Survey Quantitative OLS Regression Analysis Are there correlations between climate and student poverty, volunteer hours, and leadership experience? District-level data on the number of volunteers hours Voluntary principal survey District-level data on selected engagement survey questions from parents Data file Survey Survey Quantitative OLS Regression Analysis 61 Are there correlations between student achievement and volunteer management, parent engagement, student poverty, and leadership experience? District-level data on student achievement performance District-level data on selected engagement survey questions from parents Data file Survey Quantitative OLS Regression Analysis Research Question 1. The researcher analyzed the data results from the Orange Leaf Public Schools Volunteer Management Survey. Summary statistics will illustrate how OLPS principals manage each of the strategic volunteer talent management areas (planning, program management, alignment, and evaluation), school characteristics, and leadership experience in chapter four. Figure 3.2 represents the corresponding part of the study’s conceptual framework model addressing this research question. Figure 3.2 Research Question 1 Conceptual Framework Model STRATEGIC VOLUNTEER TALENT MANAGEMENT STUDENT ACHIEVEMENT SCHOOL VARIABLES VOLUNTEER VARIABLES ADMINISTRATOR VARIABLES CLIMATE VARIABLES 62 Research Question 2. The researcher tested for possible correlations between volunteer management and student poverty, volunteer hours, and leadership experience. Figure 3.3 represents the corresponding part of the study’s conceptual framework model addressing this research question. Figure 3.3 Research Question 2 Conceptual Framework Model Model 1 – Total strategic volunteer talent management and student poverty, volunteer hours, and leadership experience. The researcher tested for a correlation between the total strategic volunteer talent management composite (dependent variable (Y)) and the school-level FARMS rate, school-level volunteer hours, and administrator tenure using the following regression model: Y[Total Volunteer Management (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership SCHOOL VARIABLES VOLUNTEER VARIABLES ADMINISTRATOR VARIABLES STRATEGIC VOLUNTEER TALENT MANAGEMENT STUDENT ACHIEVEMENT CLIMATE VARIABLES 63 (2013) + ε. (3.1) Model 2 – Volunteer management planning and student poverty, volunteer hours, and leadership experience. The researcher tested for a correlation between the volunteer management planning composite (dependent variable (Y)) and the school-level FARMS rate, school-level volunteer hours, and administrator tenure using the following regression model: Y[Planning (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (3.2) Model 3 – Volunteer program management and student poverty, volunteer hours, and leadership experience. The researcher tested for a correlation between the volunteer program management composite (dependent variable (Y)) and the school-level FARMS rate, school-level volunteer hours, and administrator tenure using the following regression model: Y[Program Management (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (3.3) Model 4 – Volunteer management alignment and student poverty, volunteer hours, and leadership experience. The researcher tested for a correlation between the volunteer management alignment composite (dependent variable (Y)) and the school-level FARMS rate, school-level volunteer hours, and administrator tenure using the following regression model: Y[Alignment (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (3.4) 64 Model 5 – Volunteer management evaluation and student poverty, volunteer hours, and leadership experience. The researcher tested for a correlation between the volunteer management evaluation composite (dependent variable (Y)) and the school-level FARMS rate, school-level volunteer hours, and administrator tenure using the following regression model: Y[Evaluation (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2* Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (3.5) Research Question 3. The researcher tested for possible correlations between school climate and student poverty, volunteer hours, and leadership experience. Figure 3.4 represents the corresponding part of the study’s conceptual framework model addressing this research question. Figure 3.4 Research Question 3 Conceptual Framework Model Model 6 – Total parent engagement and student poverty, volunteer hours, and leadership experience. The researcher tested for a correlation between the total STRATEGIC VOLUNTEER TALENT MANAGEMENT STUDENT ACHIEVEMENT SCHOOL VARIABLES VOLUNTEER VARIABLES ADMINISTRATOR VARIABLES CLIMATE VARIABLES 65 parent engagement composite (dependent variable (Y)) and the school-level FARMS rate, school-level volunteer hours, and administrator tenure using the following regression model: Y[Total Engagement Comp (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (3.6) Model 7 – Two-way communication and student poverty, volunteer hours, and leadership experience. The researcher tested for a correlation between two-way communication (dependent variable (Y)) and the school-level FARMS rate, school- level volunteer hours, and administrator tenure using the following regression model: Y[Two-way Communication (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (3.7) Model 8 – Respectful climate and student poverty, volunteer hours, and leadership experience. The researcher tested for a correlation between respectful climate (dependent variable (Y)) and the school-level FARMS rate, school-level volunteer hours, and administrator tenure using the following regression model: Y[Respectful Climate (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (3.8) Model 9 – Overall satisfaction and student poverty, volunteer hours, and leadership experience. The researcher tested for a correlation between overall satisfaction (dependent variable (Y)) and the school-level FARMS rate, school-level volunteer hours, and administrator tenure using the following regression model: Y[Overall Satisfaction (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total 66 Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (3.9) Parent Engagement and Strategic Volunteer Talent Management. Prior to answering research question 4, the researcher investigated the correlation between parent engagement and strategic volunteer management. Figure 3.5 highlights the relationships analyzed in the following eight models. Figure 3.5 Parent Engagement and Strategic Volunteer Talent Management Conceptual Framework Model Model 10 – Total parent engagement and total strategic volunteer talent management. The researcher tested for a correlation between the total parent engagement composite (dependent variable (Y)) and total strategic volunteer talent management and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y[Total Engagement Comp (2013)] = β0 + β1*Total Volunteer Management (2013) + Β2*Volunteer Hours Dummy (2013) + ε. (3.10) STRATEGIC VOLUNTEER TALENT MANAGEMENT STUDENT ACHIEVEMENT SCHOOL VARIABLES VOLUNTEER VARIABLES ADMINISTRATOR VARIABLES CLIMATE VARIABLES 67 Model 11 – Two-way communication and total strategic volunteer talent management. The researcher tested for a correlation between two-way communication (dependent variable (Y)) and total strategic volunteer talent management and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y[Two-way Communication (2013)] = β0 + β1*Total Volunteer Management (2013) + Β2*Volunteer Hours Dummy (2013) + ε. (3.11) Model 12 – Respectful climate and total strategic volunteer talent management. The researcher tested for a correlation between respectful climate (dependent variable (Y)) and total strategic volunteer talent management, and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y[Respectful Climate (2013)] = β0 + β1*Total Volunteer Management (2013) + Β2*Volunteer Hours Dummy (2013) + ε. (3.12) Model 13 – Overall satisfaction and total strategic volunteer talent management. The researcher tested for a correlation between overall satisfaction (dependent variable (Y)) and total strategic volunteer talent management and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y[Overall Satisfaction (2013)] = β0 + β1*Total Volunteer Management (2013) + Β2*Volunteer Hours Dummy (2013) + ε. (3.13) Model 14 – Total parent engagement and strategic volunteer talent management. The researcher tested for a correlation between the total parent engagement composite (dependent variable (Y)) and volunteer management planning, 68 volunteer program management, volunteer management alignment, volunteer management evaluation, and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y[Total Engagement Comp (2013)] = β0 + β1* Planning (2013) + β2*Program Management (2013) + β3*Alignment (2013) + β4*Evaluation (2013) + Β5*Volunteer Hours Dummy (2013) + ε. (3.14) Model 15 – Two-way communication and strategic volunteer talent management. The researcher tested for a correlation between two-way communication (dependent variable (Y)) and volunteer management planning, volunteer program management, volunteer management alignment, volunteer management evaluation, and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y[Two-way Communication (2013)] = β0 + β1* Planning (2013) + β2*Program Management (2013) + β3*Alignment (2013) + β4*Evaluation (2013) + Β5*Volunteer Hours Dummy (2013) + ε. (3.15) Model 16 – Respectful climate and strategic volunteer talent management. The researcher tested for a correlation between respectful climate (dependent variable (Y)) and volunteer management planning, volunteer program management, volunteer management alignment, volunteer management evaluation, and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: 69 Y[Respectful Climate (2013)] = β0 + β1* Planning (2013) + β2*Program Management (2013) + β3*Alignment (2013) + β4*Evaluation (2013) + Β5*Volunteer Hours Dummy (2013) + ε. (3.16) Model 17 – Overall satisfaction and strategic volunteer talent management. The researcher tested for a correlation between overall satisfaction (dependent variable (Y)) and volunteer management planning, volunteer program management, volunteer management alignment, volunteer management evaluation, and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y[Overall Satisfaction (2013)] = β0 + β1* Planning (2013) + β2*Program Management (2013) + β3*Alignment (2013) + β4*Evaluation (2013) + Β5*Volunteer Hours Dummy (2013) + ε. (3.17) Research Question 4. The researcher examined the correlation between student achievement and volunteer management, parent engagement, student poverty, and leadership experience in multiple analyses. Figure 3.5 represents the corresponding part of the study’s conceptual framework model addressing this research question. Based on the preliminary results of the ordinary least squares regression models in research questions 2 and 3, the researcher excluded volunteer hours from this research question’s analyses. Thus, the sample size increased from 43 to 61 allowing for greater degrees of freedom. As you can see in Figure 3.6, volunteer variables are grayed out in the conceptual framework. 70 Figure 3.6 Research Question 4 Conceptual Framework Model Model 18 – Reading achievement and strategic volunteer talent management, parent engagement, student poverty, and leadership experience. The researcher tested for a correlation between current year’s student reading achievement (dependent variable (Y1)) and total volunteer management composite, total parent engagement composite, school-level FARMS rate and leadership experience, controlling for prior year’s average reading scores (Y0) and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y1[Current Year’s Reading Achievement (2013)] = β0 + γ*Y0[Prior Year’s Reading Achievement (2012)] + β1*Total Volunteer Management (2013) + β2*Total Parent Engagement (2013) + β3*FARMS percentage (2012 – 2013) + β4*Leadership (2013) + β5*Volunteer Hours Dummy (2013) + ε. (3.18) STRATEGIC VOLUNTEER TALENT MANAGEMENT STUDENT ACHIEVEMENT SCHOOL VARIABLES VOLUNTEER VARIABLES ADMINISTRATOR VARIABLES CLIMATE VARIABLES 71 Model 19 – Mathematics achievement and strategic volunteer talent management, parent engagement, student poverty, and leadership experience. The researcher tested for a correlation between current year’s student math achievement (dependent variable (Y1)) and total volunteer management composite, total parent engagement composite, school-level FARMS rate, and leadership experience, controlling for prior year’s average math scores (Y0) and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y1[Current Year’s Math Achievement (2013)] = β0 + γ*Y0[Prior Year’s Math Achievement (2012)] + β1*Total Volunteer Management (2013) + β2*Total Parent Engagement (2013) + β3*FARMS percentage (2012 – 2013) + β4*Leadership (2013) + β5*Volunteer Hours Dummy (2013) + ε. (3.19) Model 20 – Reading achievement and strategic volunteer talent management. The researcher tested for a correlation between current year’s student reading achievement (dependent variable (Y1)) and volunteer management planning, volunteer program management, volunteer management alignment, and volunteer management evaluation, controlling for prior year’s average reading scores (Y0) and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y1[Current Year’s Reading Achievement (2013)] = β0 + γ*Y0[Prior Year’s Reading Achievement (2012)] + β1*Planning (2013) + β2*Program Management (2013) + β3*Alignment (2013) + β4*Evaluation (2013) + β5*Volunteer Hours Dummy (2013) + ε. (3.20) 72 Model 21 – Mathematics achievement and strategic volunteer talent management. The researcher tested for a correlation between the current year’s student math achievement (dependent variable (Y1)) and volunteer management planning, volunteer program management, volunteer management alignment, and volunteer management evaluation, controlling for prior year’s average math scores (Y0) and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y1[Current Year’s Math Achievement (2013)] = β0 + γ*Y0[Prior Year’s Math Achievement (2012)] + β1*Planning (2013) + β2*Program Management (2013) + β3*Alignment (2013) + β4*Evaluation (2013) + β5*Volunteer Hours Dummy (2013) + ε. (3.21) Model 22 – Reading achievement and parent engagement. The researcher tested for a correlation between current year’s student reading achievement (dependent variable (Y1)) and two-way communication, respectful climate, and overall satisfaction, controlling for prior year’s average reading scores (Y0) and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y1[Current Year’s Reading Achievement (2013)] = β0 + γ*Y0[Prior Year’s Reading Achievement (2012)] + β1*Parent Engagement: Two-way Communication (2013) + β2*Parent Engagement: Respectful Climate (2013) + β3*Parent Engagement: Overall Satisfaction (2013) + β4*Volunteer Hours Dummy (2013) + ε. (3.22) Model 23 – Mathematics achievement and parent engagement. The researcher tested for a correlation between the current year’s student math achievement (dependent variable (Y1)) and two-way communication, respectful climate, and 73 overall satisfaction, controlling for prior year’s average math scores (Y0) and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y1[Current Year’s Math Achievement (2013)] = β0 + γ*Y0[Prior Year’s Math Achievement (2012)] + β1*Parent Engagement: Two-way Communication (2013) + β2*Parent Engagement: Respectful Climate (2013) + β3*Parent Engagement: Overall Satisfaction (2013) + β4*Volunteer Hours Dummy (2013) + ε. (3.23) Model 24 – Reading achievement and strategic volunteer talent management, overall satisfaction, two-way communication, student poverty, and leadership experience. The researcher tested for a correlation between the current year’s student reading achievement (dependent variable (Y1)) and total strategic volunteer talent management, overall satisfaction, two-way communication, school-level FARMS rate, and leadership experience, controlling for prior year’s average reading scores (Y0) and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y1[Current Year’s Reading Achievement (2013)] = β0 + γ*Y0[Prior Year’s Reading Achievement (2012)] + β1*Total Volunteer Management (2013) + β2* Parent Engagement: Overall Satisfaction (2013) + β3*Parent Engagement: Two-way Communication (2013) + β4*FARMS percentage (2012 – 2013) + β5*Leadership (2013) + β6*Volunteer Hours Dummy (2013) + ε. (3.24) Model 25 – Mathematics achievement and strategic volunteer talent management, overall satisfaction, two-way communication, student poverty, and leadership experience. The researcher tested for a correlation between the current year’s student math achievement (dependent variable (Y1)) and total strategic 74 volunteer talent management, overall satisfaction, two-way communication, school- level FARMS rate, and leadership experience, controlling for prior year’s average math scores (Y0) and adding a dummy variable that was one for cases where the respondent provided a count of volunteer hours using the following regression model: Y1[Current Year’s Math Achievement (2013)] = β0 + γ*Y0[Prior Year’s Math Achievement (2012)] + β1*Total Volunteer Management (2013) + β2* Parent Engagement: Overall Satisfaction (2013) + β3*Parent Engagement: Two-way Communication (2013) + β4*FARMS percentage (2012 – 2013) + β5*Leadership (2013) + β6*Volunteer Hours Dummy (2013) + ε. (3.25) Lastly, the researcher applied a stepwise regression model in which she calculated the estimated coefficients in each model (3.18 – 3.25) once without the previous year’s achievement and once with the previous year’s achievement. A stepwise regression allows the researcher to enter variables in blocks in order to see how certain variables impact the estimated model (Schwab, 2007). Given the strong correlation between current and prior test scores, the stepwise regression helps isolate the effect of the prior test scores. Ethical Considerations This research relied on data provided by human subjects through indirect contact with the researcher. Participants received information about this research study and its background through electronic written communication. All survey data are confidential. The researcher used privacy measures as not to identify schools and individuals and the study does not involve any deception of subjects. Participants have access to a confidential copy of the dissertation research proposal, upon request. Following all guidelines set out by the University’s Institutional Review Board (IRB), 75 the researcher used implied consent as the method of obtaining participant consent. Although the study used implied consent, the researcher developed an informed consent form that acknowledged the rights of the participant (Creswell, 2009). It was included in the initial electronic communication to all participants for their records. Both the University’s IRB and OLPS accountability office reviewed and approved this study. Summary The study utilized quantitative methods to determine how principals manage volunteers within Orange Leaf Public Schools. The data collected and analyzed addressed the proposed research questions from this study. The findings for the study may assist other school systems as they align their volunteer management practices to utilize volunteers more productively. The findings from these analyses are presented in Chapter 4. 76 CHAPTER FOUR: FINDINGS Chapter four provides (a) a descriptive profile of the volunteer management practices implemented by a sampling of school leaders, (b) data on how volunteer management is related to student poverty, volunteer hours, and leadership experience, (c) an analysis of school climate and its correlation to student poverty, volunteer hours, and leadership experience, and (d) an examination of the relationships between student achievement and volunteer management, parent engagement, student poverty, and leadership experience Procedures and Data Collection There were four sources of quantitative data for this study: the researcher- created Orange Leaf Public Schools Volunteer Management Survey (fall 2013), district records on school-level volunteer hours (2012 – 2013), Orange Leaf Public Schools Gallup Parent Engagement Survey (spring 2013), and state assessment data (spring 2012 and spring 2013). The study was limited to the elementary school principals in Orange Leaf Public Schools (N = 132). The researcher distributed the Orange Leaf Public Schools Volunteer Management Survey instrument electronically to the 132 OLPS elementary school principals at the end of October 2013 using Adobe Forms. A cover letter (Appendix G) accompanied the actual surveys. The first question on the electronic survey required the respondent to mark consent in order to continue to open the survey. By the end of November, there were 33 responses (25%). A reminder e-mail led to another 20 responses. Finally, another hard copy of the survey with a cover letter garnered an additional 13 responses. Five principals declined to participate because 77 they were new to the school, they had not made volunteers a “priority,” or their school was not a “traditional model” school. In total, there were 66 completed surveys for a 50% return rate. The researcher obtained publicly available school-level volunteer data for all 132 elementary schools for years 2012 – 2013 from the district’s partnership office. Each school self-reports these data to the district’s partnership office monthly. Of the 66 schools whose principal completed the volunteer management survey, only 43 had reported volunteer data for the 2012 – 2013 school year. This reduced the sample size for some of the quantitative analyses to 43 schools. The researcher secured the publicly available results of the spring 2013 Parent Engagement Survey for all 132 elementary schools from the district’s accountability office. This survey provides OLPS with information about the perception of the school-level learning environment. Schools use these findings to inform practices and help engage more parents, students, and staff. The researcher found that there were three common themes across the engagement questions: (1) two-way communication, (2) respectful climate, and (3) overall satisfaction. Lastly, the researcher obtained publicly available student reading and mathematics achievement data from the state department of education website for spring 2012 and 2013 for all 132 elementary schools. These assessments meet the federal testing requirements of No Child Left Behind Act and measure students’ yearly progress. The assessment, administered annually, measures student achievement in reading and mathematics. The researcher used building-level average achievement data. Four schools did not have achievement data because their student populations 78 do not represent the grades assessed by the state and one school only had data for 2013. Therefore, the data analysis that included achievement data was limited to a sample of 61. Validity and Reliability To ensure accurate survey questions, the researcher validated the Orange Leaf Public Schools Volunteer Management Survey questions through cognitive testing. This testing examined how survey respondents might answer proposed questions. The researcher arranged cognitive interviews with two assistant principals using the active probing strategy. After the assistant principals completed the survey, the researcher asked questions like “Why did you respond that way?” “What does that mean to you?” and “Please tell me what I was asking in your own words?” as probing questions during the interview (Harrison, 2008, p. 5). The assistant principals provided the researcher with feedback on the proposed survey to identify specific problems. The researcher analyzed the data collected from these interviews and made minor adjustments to wording or the type of question that would remain in the survey. The researcher relied on the Gallup Corporation to test the validity of the parent engagement survey and the state department of education office to test the validity of the student reading and mathematics achievement data. Proper Implementation of Data Collection Procedures The researcher implemented procedures and strategies to protect the confidentiality of participants during the study by maintaining all collected data (survey responses and school level data) in a secure location and using locked files 79 and password-protected computers. In addition, none of the participants were asked to reveal any personal information (such as age, home address, telephone numbers, or financial data) or other information (such as political, religious, cultural, family, or health and medical information). Participants completed the survey independently. The only persons with access to the data were the researcher and members of the dissertation committee. No individual persons or schools were identified in dissertation documents and the school district is known as Orange Leaf Public Schools. Within one year of the study’s completion, records of the data, survey responses, and notes will be destroyed. Research Questions The research questions and regression models are presented here with discussion of the findings for each question. Research Question 1. How do principals manage volunteers across Orange Leaf Public Schools? To answer this research question, the researcher relied on data from the Orange Leaf Public Schools Volunteer Management Survey and publicly available school-level FARMS data. The following graphs and tables provide a summary of the data reported by survey respondents. They include general demographics and each strategic volunteer talent management area surveyed. Respondent numbers for each question are noted. General demographics. Figures 4.1 – 4.3 provide general demographics data including school enrollment, leadership experience, and percent and type of school volunteers. The majority of principals have led their school for less than 10 years. 80 Figure 4.1 Enrollment for Schools with Survey Responses (N = 66) 0 5 10 15 20 25 30 35 40 0 - 250 251 - 500 501 - 750 751 - 1000 m = 556.9 Range 308 - 857 81 Figure 4.2 Leadership Experience of Administrators (N = 66) 0 5 10 15 20 25 30 35 40 0 – 5 years 6 – 10 years 11 – 15 years 16 – 20 years >20 years Total Years as an Administrator 0 5 10 15 20 25 30 35 40 0 – 5 years 6 – 10 years 11 – 15 years 16 – 20 years >20 years Years as an Admininstrator at Current School 82 Figure 4.3 Number of Schools by Volunteer Type* (N = 66) *question allowed for multiple responses and stated, “What percent of your volunteers are from each category below?” Volunteer management planning. Table 4.1 presents data on volunteer management planning. These questions highlight what schools do to prepare for and recruit volunteers. The data show 89% of schools report that volunteers are actively recruited and the majority of schools use multiple recruitment techniques. PTAs and school newsletters are the most common recruitment tools used by schools. Other 0 5 10 15 20 25 30 0 - 20% 20 - 40% 40 - 60% 60 - 80% 80 - 100% Parent n = 66 0 10 20 30 40 50 60 0 - 20% 20 - 40% 40 - 60% 60 - 80% 80 - 100% Community Member n = 63 0 10 20 30 40 50 60 0 - 20% 20 - 40% 40 - 60% 60 - 80% 80 - 100% Student n = 65 0 5 10 15 20 25 0 - 20% 20 - 40% 40 - 60% 60 - 80% 80 - 100% Other n = 21 83 tools reported include university partnerships, teacher websites, Family Involvement Committee, VolunteerSpot (an online program), “through a grant,” Twitter, and Facebook. One principal stated, “We really don't” to the question, “How do you recruit volunteers?” Table 4.1 Volunteer Management Planning (N = 66) Percentage of principals responding Never Rarely Sometimes Always Volunteers have to complete an application to volunteer. n = 65 42% 25% 17% 17% My school compiles a list of school needs/tasks that volunteers can support. n = 64 11% 8% 38% 44% My school has a description of what skills are needed to complete the tasks identified. n = 63 30% 19% 30% 21% My school actively recruits volunteers. n = 64 3% 8% 30% 59% Percentage of principals responding How do you recruit volunteers?* n = 66 PTA School newsletter School website 92% 83% 29% Community partnership Room parents Other 45% 61% 36% *question allowed for multiple responses Volunteer program management. Table 4.2 reports data on volunteer program management. The data show that although principals do not often facilitate 84 volunteer training (68%), 52% do attend the trainings sometimes or always. Volunteer recognition occurs at 97% of schools. Table 4.2 Volunteer Program Management (N = 66) Percentage of principals responding Never Rarely Sometimes Always Volunteers are interviewed before being assigned. n = 65 32% 28% 29% 11% Volunteers are required to attend an initial training. n = 66 18% 6% 33% 42% Volunteers receive ongoing training. n = 65 17% 23% 51% 9% I facilitate the volunteer training. n = 66 48% 20% 20% 12% I do not facilitate the training, but I attend. n = 59 32% 15% 44% 8% ALL volunteers are recognized for their work. n = 66 0% 3% 9% 88% Percentage of principals responding Who coordinates your school’s volunteer program?* Principal Assistant principal Staff member Parent Other n = 63 6% 17% 48% 43% 21% *question allowed for multiple responses Volunteer management alignment. Table 4.3 and figure 4.4 provides data on volunteer management alignment. Principals reported that volunteers help their school meet its priorities sometimes or always 86% of the time. Some respondents 85 provided other areas of school priorities. Their responses included (a) student- focused tasks (one-on-one for students with emotional needs or individualized academic support, afterschool clubs, mentoring, technology projects, artist in residence and environmental programs), (b) teacher-focused tasks (workroom support, bulletin boards, copying), and (c) general administrative tasks (translation, office and lunch/recess support, community outreach, health room, fundraising, special evening events and parties). Additionally, principals report that they use information given by volunteers for assigning volunteers to tasks sometimes or always 82% of the time. 86 Table 4.3 Volunteer Management Alignment (N = 66) Percentage of principals responding Never Rarely Sometimes Always Volunteers help my school meet its priorities. n = 65 2% 12% 48% 38% My school’s priorities for placing volunteers are: Additional academic support n = 62 6% 5% 56% 32% Lower class size ratios n = 61 66% 20% 13% 2% Lower adult to student ratios for safety (e.g., Recess/Lunch) n = 62 13% 13% 55% 19% Other areas of the school program n = 54 4% 6% 72% 19% My school uses the information gathered from volunteers when assigning them to tasks. n = 64 11% 6% 48% 34% Volunteers are assigned to a particular student or student group. n = 65 8% 14% 65% 14% Volunteers are assigned to a particular teacher. n = 62 3% 11% 69% 16% Volunteers are assigned to a particular recess or lunch period. n = 65 20% 12% 49% 18% Volunteers meet with assigned student(s) before beginning their assigned task. n = 62 21% 32% 37% 10% 87 Volunteers meet with assigned teacher before beginning their assigned task. n = 65 5% 11% 42% 43% Percentage of principals responding Volunteer Principal Staff member Parent Who assigns volunteers at your school? Choose the answer that best fits. n = 66 21% 8% 65% 6% Percentage of principals responding My school collects the following information from incoming volunteers. * n = 64 Time commitment Days and times Activities (interested) Activities (not interested) Special skills 73% 89% 79% 19% 61% Occupation Language Interpret Language Translate Student grade level Other 9% 41% 34% 53% 5% *question allowed for multiple responses Figure 4.4 Percent of Volunteers Assigned to Each Task Type (N = 66) 0 5 10 15 20 25 30 0 - 20% 20 - 40% 40 - 60% 60 - 80% 80 - 100% General Administrative Tasks n = 66 88 *question allowed for multiple responses and stated, “What percent of volunteers are assigned to each of the following tasks?” Volunteer management evaluation. Table 4.4 presents data on volunteer management evaluation. The data show that although volunteer assignment processes are reviewed, it occurs only once a year. Most (63%) of schools do not offer exit interviews to volunteers. 0 5 10 15 20 25 0 - 20% 20 - 40% 40 - 60% 60 - 80% 80 - 100% Teacher Focused Tasks n = 66 0 2 4 6 8 10 12 14 16 18 0 - 20% 20 - 40% 40 - 60% 60 - 80% 80 - 100% Student Focused Tasks n = 65 89 Table 4.4 Volunteer Management Evaluation (N = 66) Percentage of principals responding Never Rarely Sometimes Always My school reviews the processes used for assigning volunteers. n = 66 9% 14% 52% 26% Volunteers are provided with an exit interview. n = 65 63% 23% 14% 0% Percentage of principals responding Yearly Quarterly Monthly Weekly We review the processes used for assigning volunteers. n = 63 81% 16% 0% 2% Research Question 2. Are there correlations between volunteer management and student poverty, volunteer hours, and leadership experience? To answer this research question, the researcher relied on the principals’ responses from the Orange Leaf Public Schools Volunteer Management Survey for volunteer management and leadership experience data, publicly available school-level FARMS data, and school-level volunteer data reported to the district’s partnership office (2012 – 2013). Strategic volunteer talent management. The researcher developed composite variables manually by adding together selected questions from the strategic volunteer talent management survey’s four management areas (volunteer management planning, volunteer program management, volunteer management alignment, and volunteer management evaluation). To improve reliability, the researcher omitted 90 questions that did not use a four-point Likert scale. Next, the researcher verified that all questions had a positive correlation so no recoding was necessary. Last, the researcher created a total strategic volunteer talent management composite, which was the sum of the four individual composites. These variables are used in the regression models discussed later in the chapter. Table 4.5 provides the descriptive statistics for each strategic volunteer talent management area composite. Table 4.5 Basic Descriptive Statistics for Volunteer Management Survey Composites M SD Min Max Total volunteer management composite (20 Questions) 59.92 9.88 33 76 Volunteer management planning composite (4 Questions) 10.76 3.06 0 16 Volunteer program management composite (6 Questions) 15.48 3.50 7 21 Volunteer management alignment composite (8 Questions) 29.26 4.92 15 39 Volunteer management evaluation composite (2 Questions) 4.42 1.24 2 7 Free and Reduced Meals. Figure 4.5 displays the percentages of students in each school who received free and reduced meals in 2012 – 2013. More than half (56%) of the schools included in the study have less than 50% of students qualifying for FARMS. Across all school sizes and FARMS rates, the majority of volunteers in these schools are parents. 91 Figure 4.5 Number of Schools in each FARMS Quartile (N = 66) Volunteer hours. Table 4.6 provides a summary of volunteer hour data for the 43 schools that reported (from the larger sample of 66). Table 4.6 Number of Volunteers Hours for Schools with Survey Responses 0 – 1,250 1,251 – 2,500 2,501 – 5,000 5,001 – 7,500 # of volunteer hours n = 43 28% 26% 33% 14% m = 2,586 Range: 8 – 7,274 0 5 10 15 20 25 30 0 - 24.9% 25 - 49.9% 50 - 74.9% 75 - 100% 92 Strategic volunteer talent management and student poverty, volunteer hours, and leadership experience. These analyses estimated the following regression models. Regression Model 1: Y[Total Volunteer Management (2013)] = β0 + β1 FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (4.1) Regression Model 2: Y[Planning (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (4.2) Regression Model 3: Y[Program Management (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (4.3) Regression Model 4: Y[Alignment (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (4.4) Regression Model 5: Y[Evaluation (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (4.5) The estimated coefficients presented in Table 4.7 indicate no statistically significant correlation between total strategic volunteer talent management, volunteer management planning, volunteer program management, volunteer management 93 alignment, volunteer management evaluation and the FARMS rate, the number of volunteer hours, and leadership experience. Table 4.7 Least Square Regression Results for Strategic Volunteer Talent Management and Student Poverty, Volunteer Hours, and Leadership Experience Dependent variable→ ↓ Independent variables Total Volunteer Management Composite Planning Program Management Alignment Evaluation Constant 64.08*** (4.36) 12.35*** (1.34) 16.46*** (1.63) 30.36*** (2.25) 4.91*** (0.62) FARMS% -0.02 (0.05) -0.01 (0.02) -0.01 (0.02) -0.00 (0.03) 0.00 (0.01) Volunteer Hours 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) -0.00 (0.00) Leadership Experience -1.09 (1.23) -0.46 (0.38) -0.02 (0.46) -0.44 (0.63) -0.17 (0.17) R Square No. of Observations 0.06 43 0.09 43 0.03 43 0.02 43 0.03 43 Standard errors are reported in parentheses. *, **, *** indicates significance at the 90% (0.10), 95% (0.05), and 99% (0.01) level respectively. Research Question 3. Are there correlations between climate and student poverty, volunteer hours, and leadership experience? Parent engagement. Table 4.8 provides the summary statistics for the total parent engagement composite and each of the three factors (two-way communication, respectful climate, and overall satisfaction). The principal components analysis composites are weighted averages of the Likert scores (0-4), so the range is much smaller than the other composites in this study. 94 Table 4.8 Summary Statistics for Parent Engagement Composites Variable Mean SD Minimum Max Total Engagement Composite (21 Questions) 72.21 2.37 67.42 77.96 Two-way Communication Composite (13 Questions) 3.37 0.12 3.08 3.67 Respectful Climate Composite (4 Questions) 3.54 0.09 3.29 3.79 Overall Satisfaction Composite (4 Questions) 3.41 0.13 3.10 3.74 Parent engagement and student poverty, volunteer hours, and leadership experience. These analyses estimated the following regression models. Regression Model 6: Y[Total Engagement Comp (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (4.6) Regression Model 7: Y[Two-way Communication (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (4.7) Regression Model 8: Y[Respectful Climate (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (4.8) Regression Model 9: Y[Overall Satisfaction (2013)] = β0 + β1*FARMS percentage (2012 – 2013) + β2*Total Number of Volunteer Hours (2012 – 2013) + β3*Leadership (2013) + ε. (4.9) 95 The results presented in Table 4.9 show that there is a positive correlation between overall satisfaction and leadership experience at the 0.10 level. There was a positive correlation between the FARMS rate and the two-way communication composite (0.01 level), total engagement composite (0.05 level), and respectful climate composite (0.10 level). The data show no statistically significant correlations between the total parent engagement composite, two-way communication composite, respectful climate composite, overall satisfaction composite and volunteer hours. Table 4.9 Least Square Regression Results for Parent Engagement and Student Poverty, Volunteer Hours, and Leadership Experience Dependent variable→ ↓ Independent variables Total Engagement Composite Two-way Communication Respectful Climate Overall Satisfaction Constant 69.78*** (0.99) 3.23*** (0.05) 3.47*** (0.04) 3.31*** (0.06) FARMS% 0.03** (0.01) 0.00*** (0.00) 0.00* (0.00) -0.00 (0.00) Volunteer Hours 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) Leadership Experience 0.35 (0.28) 0.02 (0.02) 0.01 (0.01) 0.03* (0.02) R Square No. of Observations 0.20 43 0.25 43 0.12 43 0.10 43 Standard errors are reported in parentheses. *, **, *** indicates significance at the 90% (0.10), 95% (0.05), and 99% (0.01) level respectively. Parent Engagement and Strategic Volunteer Talent Management. To answer this research question, the researcher relied on parent engagement data (2013) and strategic volunteer talent management data (2013). The researcher chose to include analyses using the total climate composite, the three parent engagement factors, the total strategic volunteer talent management composite, and the four individual strategic volunteer talent management composites in order to explore fully 96 the relationship between climate and strategic volunteer talent management. The first four ordinary least squares regression models investigate the correlations between the total climate composite and total strategic volunteer talent management composite and each parent engagement factor and total strategic volunteer talent management composite. The next four ordinary least squares regression models assess the relationship between the total climate composite and each individual strategic volunteer talent management composite and each parent engagement factor and the four individual strategic volunteer talent management composite. Total parent engagement and total strategic volunteer talent management. These analyses estimated the following regression models. Regression Model 10: Y[Total Engagement Comp (2013)] = β0 + β1*Total Volunteer Management (2013) + Β2*Volunteer Hours Dummy (2013) + ε. (4.10) Two-way communication and total strategic volunteer talent management. These analyses estimated the following regression models. Regression Model 11: Y[Two-way Communication (2013)] = β0 + β1*Total Volunteer Management (2013) + Β2*Volunteer Hours Dummy (2013) + ε. (4.11) Respectful climate and total strategic volunteer talent management. These analyses estimated the following regression models. Regression Model 12: Y[Respectful Climate (2013)] = β0 + β1*Total Volunteer Management (2013) + Β2*Volunteer Hours Dummy (2013) + ε. (4.12) 97 Overall satisfaction and total strategic volunteer talent management. These analyses estimated the following regression models. Regression Model 13: Y[Overall Satisfaction (2013)] = β0 + β1*Total Volunteer Management (2013) + Β2*Volunteer Hours Dummy (2013) + ε. (4.13) The estimated coefficients presented in Table 4.10 indicate no statistically significant correlation between the total parent engagement composite, two-way communication composite, respectful climate composite, overall satisfaction composite and the total strategic volunteer talent management composite or the volunteer hours dummy variable. Table 4.10 Least Square Regression Results for Parent Engagement and Total Strategic Volunteer Talent Management Dependent variable→ ↓ Independent variables Total Engagement Composite Two-way Communication Respectful Climate Overall Satisfaction Constant 72.55*** (4.50) 3.40*** (0.10) 3.56*** (0.08) 3.41*** (0.10) Total Volunteer Management Composite -0.00 (0.03) -0.00 (0.00) -0.00 (0.00) -0.00 (0.00) Volunteer Hours Dummy -0.31 (0.67) -0.02 (0.04) -0.02 (0.03) -0.00 (0.04) R Square No. of Observations 0.00 66 0.01 66 0.01 66 0.00 66 Standard errors are reported in parentheses. *, **, *** indicates significance at the 90% (0.10), 95% (0.05), and 99% (0.01) level respectively. 98 Total parent engagement and strategic volunteer talent management. These analyses estimated the following regression models. Regression Model 14: Y[Total Engagement Comp (2013)] = β0 + β1* Planning (2013) + β2*Program Management (2013) + β3*Alignment (2013) + β4*Evaluation (2013) + Β5*Volunteer Hours Dummy (2013) + ε. (4.14) Two-way communication and strategic volunteer talent management. These analyses estimated the following regression models. Regression Model 15: Y[Two-way Communication (2013)] = β0 + β1* Planning (2013) + β2*Program Management (2013) + β3*Alignment (2013) + β4*Evaluation (2013) + Β5*Volunteer Hours Dummy (2013) + ε. (4.15) Respectful climate and strategic volunteer talent management. These analyses estimated the following regression models. Regression Model 16: Y[Respectful Climate (2013)] = β0 + β1* Planning (2013) + β2*Program Management (2013) + β3*Alignment (2013) + β4*Evaluation (2013) + Β5*Volunteer Hours Dummy (2013) + ε. (4.16) Overall satisfaction and strategic volunteer talent management. These analyses estimated the following regression models. Regression Model 17: Y[Overall Satisfaction (2013)] = β0 + β1* Planning (2013) + β2*Program Management (2013) + β3*Alignment (2013) + β4*Evaluation (2013) + Β5*Volunteer Hours Dummy (2013) + ε. (4.17) 99 The results presented in Table 4.11 show that there is a positive correlation between respectful climate and volunteer management evaluation (0.05 level) and volunteer program management (0.10 level). Volunteer program management also correlates to both total engagement and overall satisfaction at the 0.10 level. Two- way communication shows no statistically significant correlations to any of the strategic volunteer management composites. The data show no statistically significant correlations between the various engagement composites and volunteer management planning, volunteer management alignment, or the volunteer hours dummy variable. Table 4.11 Least Square Regression Results for Parent Engagement and Individual Strategic Volunteer Talent Management Dependent variable→ ↓ Independent variables Total Engagement Composite Two-way Communication Respectful Climate Overall Satisfaction Constant 71.05*** (0.99) 3.32*** (0.11) 3.49*** (0.09) 3.36*** (0.11) Planning -0.18 (0.15) -0.01 (0.00) -0.00 (0.00) -0.00 (0.01) Program Management 0.19* (0.11) 0.01 (0.01) 0.01* (0.00) 0.01* (0.01) Alignment 0.05 (0.07) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) Evaluation -0.24 (0.32) -0.00 (0.02) -0.03** (0.01) -0.02 (0.02) Volunteer Hours Dummy -0.40 (0.67) -0.02 (0.04) -0.02 (0.02) -0.01 (0.04) R Square No. of Observations 0.08 66 0.06 66 0.13 66 0.07 66 Standard errors are reported in parentheses. *, **, *** indicates significance at the 90% (0.10), 95% (0.05), and 99% (0.01) level respectively. 100 Research Question 4. Are there correlations between student achievement and volunteer management, parent engagement, student poverty, and leadership experience? To answer this research question, the researcher relied on publicly available student reading and math achievement data (spring 2012 and 2013), strategic volunteer talent management data (2013), school-level volunteer data (2012 - 2013), FARMS school-level data (2012 - 2013), and parent engagement data (2013). These analyses use eight ordinary least squares regression models. Two models investigate the correlation between current year’s student achievement and total strategic volunteer talent management, total parent engagement, FARMS rate, and leadership experience, controlling for prior year’s student achievement and a dummy variable for schools that provided OLPS with a count of volunteer hours (model 4.18 uses reading data and model 4.19 uses math data). Two models assess the correlation between current year’s student achievement and volunteer management planning, volunteer program management, volunteer management alignment, and volunteer management evaluation, controlling for prior year’s student achievement and a dummy variable for schools that provided OLPS (model 4.20 uses reading data and model 4.21 uses math data). Two models investigate the correlation between current year’s student achievement and two-way communication, respectful climate, and overall satisfaction, controlling for prior year’s student achievement and a dummy variable for schools that provided OLPS (model 4.22 uses reading data and model 4.23 uses math data). Two models assess the correlation between the current year’s student achievement and total strategic volunteer talent management, overall 101 satisfaction, two-way communication, school-level FARMS rate, and leadership experience, controlling for prior year’s student achievement and a dummy variable for schools that provided OLPS (model 4.24 uses reading data and model 4.25 uses math data). Student achievement and strategic volunteer talent management, parent engagement, student poverty, and leadership experience. These analyses estimated the following regression models. Regression Model 18: Y1[Current Year’s Reading Achievement (2013)] = β0 + γ*Y0[Prior Year’s Reading Achievement (2012)] + β1*Total Volunteer Management (2013) + β2*Total Parent Engagement (2013) + β3*FARMS percentage (2012 – 2013) + β4*Leadership (2013) + β5*Volunteer Hours Dummy (2013) + ε. (4.18) Regression Model 19: Y1[Current Year’s Math Achievement (2013)] = β0 + γ*Y0[Prior Year’s Math Achievement (2012)] + β1*Total Volunteer Management (2013) + β2*Total Parent Engagement (2013) + β3*FARMS percentage (2012 – 2013) + β4*Leadership (2013) + β5*Volunteer Hours Dummy (2013) + ε. (4.19) The estimated coefficients presented in Table 4.12 show that there is a positive correlation between schools that reported volunteer hours (volunteer hours dummy variable) and math achievement at the 0.05 level. There is a negative correlation between FARMS rate and both math (0.01 level) and reading (0.05 level) achievement. The data show no statistically significant correlations between student achievement and total strategic volunteer talent management, total parent engagement, and leadership experience. Additionally, there is a positive correlation 102 between the current year’s student achievement and prior year’s student achievement at the 0.01 level in both reading and math. Table 4.12 Least Square Regression Results for Student Achievement and Strategic Volunteer Talent Management, Parent Engagement, Student Poverty, and Leadership Experience Dependent variable→ ↓ Independent variables %_Rdg_2013 %_Rdg_2013 %_Math_2013 %_Math_2013 Constant 81.28*** (17.98) 29.63** (12.94) 79.18*** (24.12) 13.32 (19.32) Total Volunteer Management Composite -0.04 (0.06) -0.06 (0.04) -0.04 (0.08) -0.03 (0.06) Total Engagement Composite 0.25 (0.25) -0.22 (0.17) 0.27 (0.34) -0.05 (0.24) FARMS% -0.21*** (0.02) -0.05** (0.02) -0.30*** (0.03) -0.13*** (0.03) Leadership Experience .234 (0.51) -0.19 (0.33) -0.26 (0.68) -0.89* (0.49) Volunteer Hours Dummy 1.79 (1.22) 1.28 (0.79) 2.57 (1.63) 2.54** (1.16) Previous Year Achievement 0.88*** (0.10) 0.92*** (0.12) R Square No. of Observations .68 61 .87 61 .71 61 .86 61 Standard errors are reported in parentheses. *, **, *** indicates significance at the 90% (0.10), 95% (0.05), and 99% (0.01) level respectively. Student achievement and strategic volunteer talent management. These analyses estimated the following regression models. Regression Model 20: Y1[Current Year’s Reading Achievement (2013)] = β0 + γ*Y0[Prior Year’s Reading Achievement (2012)] + β1*Planning (2013) + β2*Program Management (2013) + β3*Alignment (2013) + β4*Evaluation (2013) + β5*Volunteer Hours Dummy (2013) + ε. (4.20) 103 Regression Model 21: Y1[Current Year’s Math Achievement (2013)] = β0 + γ*Y0[Prior Year’s Math Achievement (2012)] + β1*Planning (2013) + β2*Program Management (2013) + β3*Alignment (2013) + β4*Evaluation (2013) + β5*Volunteer Hours Dummy (2013) + ε. (4.21) The data presented in Table 4.13 indicate no statistically significant correlation between student achievement and volunteer management planning, volunteer program management, volunteer management alignment, volunteer management evaluation, or the volunteer hours dummy variable. There is a positive correlation between the current year’s student achievement and prior year’s student achievement at the 0.01 level in both reading and math, but the estimated coefficients for no other variables are statistically significant. 104 Table 4.13 Least Square Regression Results for Student Achievement and Strategic Volunteer Talent Management Dependent variable→ ↓ Independent variables %_Rdg_2013 %_Rdg_2013 %_Math_2013 %_Math_2013 Constant 87.77*** (6.68) -10.50 (6.45) 80.91*** (9.46) -33.70*** (9.16) Planning 0.34 (0.50) -0.32 (0.21) 0.61 (0.70) 0.16 (0.33) Program Management -0.04 (0.35) 0.09 (0.14) 0.09 (0.49) 0.12 (0.23) Alignment -0.07 (0.22) -0.10 (0.09) -0.13 (0.31) -0.22 (0.14) Evaluation -0.27 (1.01) 0.59 (0.41) -0.77 (1.43) 0.24 (0.66) Volunteer Hours Dummy 2.80 (2.13) 0.93 (0.87) 3.71 (3.01) 1.97 (1.40) Previous Year Achievement 1.11*** (0.07) 1.32*** (0.09) R Square No. of Observations .05 61 .85 61 .06 61 .80 61 Standard errors are reported in parentheses. *, **, *** indicates significance at the 90% (0.10), 95% (0.05), and 99% (0.01) level respectively. Student achievement and parent engagement. These analyses estimated the following regression models. Regression Model 22: Y1[Current Year’s Reading Achievement (2013)] = β0 + γ*Y0[Prior Year’s Reading Achievement (2012)] + β1*Parent Engagement: Two-way Communication (2013) + β2*Parent Engagement: Respectful Climate (2013) + β3*Parent Engagement: Overall Satisfaction (2013) + β4*Volunteer Hours Dummy (2013) + ε. (4.22) Regression Model 23: Y1[Current Year’s Math Achievement (2013)] = β0 + γ*Y0[Prior Year’s Math Achievement (2012)] + β1*Parent Engagement: Two-way Communication (2013) + 105 β2*Parent Engagement: Respectful Climate (2013) + β3*Parent Engagement: Overall Satisfaction (2013) + β4*Volunteer Hours Dummy (2013) + ε. (4.23) The results presented in Table 4.14 show that there is a positive correlation between math achievement and overall satisfaction at the 0.01 level and schools that reported volunteer hours (volunteer hours dummy variable) at the 0.10 level. While, there is a negative correlation between math achievement and two-way communication at the 0.01 level and respectful climate at the 0.10 level. Reading achievement correlates negatively to respectful climate at the 0.10 level. Lastly, there is a positive correlation between the current year’s student achievement and prior year’s student achievement at the 0.01 level in both reading and math. Table 4.14 Least Square Regression Results for Student Achievement and Parent Engagement Dependent variable→ ↓ Independent variables %_Rdg_2013 %_Rdg_2013 %_Math_2013 %_Math_2013 Constant 119.30*** (19.08) 35.94** (14.44) 140.93*** (23.68) 41.29* (22.99) Two-way Communication -50.07*** (7.95) -8.91 (6.43) -70.48 (9.89) -30.84*** (9.41) Respectful Climate -15.71* (9.19) -10.56* (5.64) -33.65 (11.41) -16.59* (8.87) Overall Satisfaction 56.84*** (6.81) 9.90 (6.36) 87.76 (8.46) 36.54*** (9.85) Volunteer Hours Dummy 1.64 (1.23) 0.80 (0.76) 2.19 (1.53) 2.08* (1.14) Previous Year Achievement 0.95*** (0.10) 0.89*** (0.13) R Square No. of Observations .62 61 .86 61 .71 61 .84 61 Standard errors are reported in parentheses. *, **, *** indicates significance at the 90% (0.10), 95% (0.05), and 99% (0.01) level respectively. 106 Student achievement and strategic volunteer talent management, overall satisfaction, two-way communication, student poverty, and leadership experience. These analyses estimated the following regression models. Regression Model 24: Y1[Current Year’s Reading Achievement (2013)] = β0 + γ*Y0[Prior Year’s Reading Achievement (2012)] + β1*Total Volunteer Management (2013) + β2*Parent Engagement: Overall Satisfaction (2013) + β3*Parent Engagement: Two-way Communication (2013) + β4*FARMS percentage (2012 – 2013) + β5*Leadership (2013) + β6*Volunteer Hours Dummy (2013) + ε. (4.24) Regression Model 25: Y1[Current Year’s Math Achievement (2013)] = β0 + γ*Y0[Prior Year’s Math Achievement (2012)] + β1*Total Volunteer Management (2013) + β2*Parent Engagement: Overall Satisfaction (2013) + β3*Parent Engagement: Two-way Communication (2013) + β4*FARMS percentage (2012 – 2013) + β5*Leadership (2013) + β6*Volunteer Hours Dummy (2013) + ε. (4.25) The estimated coefficients presented in Table 4.15 indicate that there are statistically significant correlations between both math achievement and overall satisfaction and two-way communication. However, the correlation with overall satisfaction is positive at the 0.10 level and the correlation to two-way communication is negative at the 0.10 level. There is a positive correlation between schools that reported volunteer hours (volunteer hours dummy variable) and math achievement at the 0.05 level. There is a positive correlation between reading achievement and FARMS rates at the 0.05 level while there is a negative correlation between math achievement and FARMS rates at the 0.01 level. There is no 107 statistically significant relationship between the total strategic volunteer talent management composite and either achievement area. Additionally, there is a positive correlation between the current year’s student achievement and prior year’s student achievement at the 0.01 level in both reading and math. Table 4.15 Least Square Regression Results for Student Achievement and Strategic Volunteer Talent Management, Overall Satisfaction, Two-way Communication, Student Poverty, and Leadership Experience Dependent variable→ ↓ Independent variables %_Rdg_2013 %_Rdg_2013 %_Math_2013 %_Math_2013 Constant 83.89*** (14.74) 28.19** (12.74) 79.62*** (18.77) 20.74 (17.94) Total Volunteer Management Composite -0.05 (0.06) -0.6 (0.04) -0.06 (0.07) -0.04 (0.06) Overall Satisfaction 25.54*** (7.91) 2.73 (6.33) 41.86*** (10.06) 17.57* (8.97) Two-way Communication -21.94** (9.19) -6.19 (6.79) -37.70*** (11.70) -17.83* (9.84) FARMS% -0.14*** (0.03) -0.05** (0.02) -0.20*** (0.04) -0.10*** (0.03) Leadership Experience 0.24 (0.47) -0.17 (0.34) -0.25 (0.60) -0.79 (0.48) Volunteer Hours Dummy 1.74 (1.13) 1.28 (0.79) 2.49* (1.43) 2.51** (1.13) Previous Year Achievement 0.85*** (0.11) 0.79*** (0.14) R Square No. of Observations .73 61 .87 61 .79 61 .87 61 Standard errors are reported in parentheses. *, **, *** indicates significance at the 90% (0.10), 95% (0.05), and 99% (0.01) level respectively. Summary This chapter presented the findings associated with this study. The researcher used a quantitative method, ordinary least squares regression, to address the research questions. The data show that 40% of the schools had a FARMS rate higher than 108 50%. School size in this study varies. One third of the schools had between 251 and 500 pupils and a half of the schools had between 501 and 750 pupils. The majority of volunteers are parents and the most common practices that principals use to manage their volunteers are developing a list of school needs, recognizing volunteers for their contribution and work, having volunteers meet with their assigned teacher prior to volunteering, and reviewing the volunteer assignment process. Principals overwhelmingly (86%) feel that volunteers helped their schools meet their priorities. The study produced mixed results. The data indicate no statistically significant correlation between total strategic volunteer talent management, volunteer management planning, volunteer program management, volunteer management alignment, volunteer management evaluation and the FARMS rate, the number of volunteer hours, and leadership experience. When studying climate, correlations emerged between total parent engagement, two-way communication, respectful climate and the FARMS rate. Additionally, there is a positive correlation between overall satisfaction and leadership experience. However, there are no statistically significant correlations between total parent engagement, two-way communication, respectful climate, overall satisfaction and volunteer hours. When analyzing parent engagement and strategic volunteer talent management, the data showed no correlations between the climate variables and total strategic volunteer talent management, but relationships did emerge between the total climate composite, respectful climate, overall satisfaction and volunteer program management. Additionally, respectful climate and volunteer program management correlate at a statistically significant level. 109 When examining the student achievement models, three of the four ordinary least squares regressions (models 19, 23, and 25) found a positive correlation between schools that reported volunteer hours (volunteer hours dummy variable) and math achievement. When studying the student achievement and parent engagement data (models 22 and 23), a positive correlation between math achievement and overall satisfaction emerges. Yet, the correlation between math achievement and two-way communication and respectful climate is negative, as is the correlation between reading achievement and respectful climate. The same is true when examining student achievement and strategic volunteer talent management, overall satisfaction, two-way communication, student poverty, and leadership experience (model 25) the correlation between math achievement and overall satisfaction is positive and the relationship with two-way communication remains negative. When analyzing student achievement and strategic volunteer talent management, parent engagement, student poverty, and leadership experience (models 18 and 19), math and reading achievement have a negative correlation to FARMS rates. A negative correlation is found when examining the relationship between math achievement and strategic volunteer talent management, overall satisfaction, two-way communication, student poverty, and leadership experience (model 25), but the reading achievement regression (model 24) has a positive correlation to FARMS. The data show no statistically significant correlations between student achievement and the total strategic volunteer talent management composite, volunteer management planning, volunteer program management, volunteer management alignment, volunteer management evaluation, the total parent engagement composite, and leadership 110 experience. A number of recommendations for practice and further research draw from these findings and are presented in Chapter 5. The following chapter also presents conclusions from this study. 111 CHAPTER FIVE: CONCLUSIONS AND RECOMMENDATIONS Managing resources in schools is a complex task and how a principal implements volunteer management policies and procedures may have an effect on productivity. School leaders should be adept volunteer managers who have skills to recruit, train, assign, and sustain their volunteer workforce. Thus, we need to understand the practices and procedures of current school leaders so that we can better utilize volunteers in an effort to improve student achievement. The researcher chose to study how these practices and procedures correlate to school characteristics (student poverty, volunteer hours, and leadership experience), school climate, and student achievement. These variables allowed the study a more robust analysis because school characteristics are often not within the control of school leaders, but how the principal manages processes and procedures may influence school climate and student achievement. The purpose of this chapter is to summarize and discuss the results of this study and suggest policy and research recommendations for further analysis. Discussion This study began with an analysis of the volunteer management practices in Orange Leaf Public Schools. The researcher found much variation in volunteer management practices across the four strategic volunteer total management areas that are the framework for this study. This analysis examined if school characteristics, some outside the control of the principal, and leadership experience correlate with how principals managed volunteers. The researcher used ordinary least squares multiple regression analyses to determine if there were statistically significant 112 correlations between: (1) volunteer management and student poverty, volunteer hours, and leadership experience; (2) school climate and student poverty, volunteer hours, and leadership experience; and (3) student achievement and volunteer management, parent engagement, student poverty, and leadership experience. Overall, the research found some areas of statistical significance, but not across all variables or consistently across content areas. While this may be due to the small size of the data set or because of the data quality, the differences in the results are significant enough to warrant further study to understand better why this occurred or if these results would be reproducible. In fact, the non-results may be a wake-up call to school leaders that it is time to better organize and manage the volunteers in their schools. The limited statistical significance of the volunteer management composite variables suggests that school leaders need to collect better data in order to understand how their practice may affect different areas of the school program, including school climate and student achievement. The following sections, organized by research area, will elaborate more specifically on the findings. Strategic Volunteer Talent Management in Orange Leaf Public Schools. The following sections discuss the researcher’s conclusions for the research question 1: How do principals manage volunteers across Orange Leaf Public Schools? Volunteer Management Planning. The study showed that the practice of actively recruiting volunteers is occurring (89%) and schools use a multitude of tools including traditional methods like the school newsletter and PTA and more current methods like VolunteerSpot (an online program), Twitter, and Facebook. Interestingly, 51% of principals sometimes or always pre-plan for identified tasks by 113 compiling a description of what skills volunteers need to possess to complete the tasks, while almost the same number (49%) rarely or never pre-plan. An analysis of the volunteer management planning composite showed that there is significant variation in how principals plan their volunteer programs. The range of scores in the composite variable was from 0 to 16 with a mean of 3.06. This is the only area where a principal scored a zero. The researcher is not sure if this is because these items were not applicable to that principal’s program or if the principal just choose not to answer the question. Principals who scored higher in this area had programs that usually had volunteers complete an application, compiled a list of school needs/tasks that volunteers could support, have descriptions of what skills are needed to complete the tasks identified, and actively recruited volunteers. These planning steps help to frame the school volunteer program and ensure the creation of a climate in which volunteers will be most productive (Fisher & Cole, 1993). Volunteer Program Management. The data showed that few principals in the study actually coordinate the volunteer program in their schools (6%). The majority of schools have a staff member or parent coordinate the school’s volunteer program. Brent (2000b) found similar results. Volunteer coordinators were typically school staff (82%) and spent a little over five hours a week coordinating volunteer activities. He discovered that in the absence of a coordinator, principals assumed this additional responsibility. Those principals spent over 22 hours each year in this coordinating role. The data from this study showed how principals manage volunteers, even though they may not coordinate directly the volunteer program or the work of the volunteers. 114 The role of volunteer manager is much like how principals manage the entirety of the school program, but do not provide direct instruction to students, facilitate food services, or typically have an active role in cleaning the building. With volunteers, principals manage by defining goals for the volunteer program, establishing expectations and outcomes, defining results, and providing resources to the volunteer program as a whole. Johnson, Guinagh, Bell, and Estroff (2001) concluded, “When planning to develop an effective volunteer program, the principal must offer the same effective leadership he or she offers for the entire school. Object for the program must be defined, procedures for accomplishing them must be clearly stated and a monitoring system must be developed” (p. 21). The failure to provide strong leadership may cause attrition of volunteers (Eisner, Grimm, Maynard, & Washburn, 2009). Volunteer coordinators handle the day-to-day running of the volunteer program, provide direct support to the volunteers and staff members working with volunteers, and work to ensure that the program meets the outlined expectations and outcomes. This role is typically an add-on responsibility when assigned to a staff member and is likely not listed in their job description. Much like Brent, Machin, and Paine (2008) found, the actual time spent coordinating volunteers and the volunteer program was greater than expected by those serving in this role. Given the amount of time spent in this role and due to the low number of principals who actively coordinate their volunteer programs, this study missed the opportunity to ask how the volunteer program coordinators provide the principal with information about the volunteer program including how and to what activities are volunteers assigned. 115 Analysis of the volunteer program management composite variable showed that there is variation in how principals manage volunteer programs. Principals who scored higher in this area had programs that almost always interviewed volunteers, required initial training and provided ongoing training; either facilitated or attended volunteer trainings, and ensured that ALL volunteers were recognized. All of which are areas the research supports as necessary for maintaining effective volunteer programs. Volunteer Management Alignment. Principals reported that volunteers help their school meet its priorities 86% of the time and that the information given by volunteers is used for assigning volunteers to tasks 82% of the time. Given that a majority of schools in this study are identifying tasks and reviewing volunteer information, it is likely that principals are aligning their schools’ priorities and tasks with the information gathered from volunteers. What is unknown and may merit further study is how closely these two are aligned and how effective is that alignment. Bartlett (2013) found that volunteer managers need a clear understanding of what volunteers can do and what they cannot do based on their skills and the needs of the program. The failure to understand the volunteers can be detrimental to the program. Eisner, Grimm, Maynard, and Washburn (2009) identified the mismatching of volunteer skills to assignments as one reason why organizations often lose more than one out of three volunteers each year. A follow-up question might be, “Are assignments of volunteer tasks made at the individual level or as a group and how does the principal define ‘coordinate and assign’?” An analysis of the volunteer management alignment composite showed that principals who scored higher in this 116 area had programs that almost always identified school priorities, used the information provided by the volunteers, assigned volunteers to a particular student, and had the volunteer meet with the person he would be working with prior to beginning a task. All of which are areas the research supports as necessary for purposefully aligning volunteer programs. Volunteer Management Evaluation. The data show that although there are processes for evaluating how volunteers are placed within a school, there seems to be inadequate information gathered from the volunteer and the frequency of gathering information is limited. These data show that 52% of principals review their assignment processes, but this is most often done yearly (81%) and without an exit interview provided to volunteers (63% never and 23% rarely). Johnson, Guinagh, Bell, and Estroff (2001) specified, “A well-planned volunteer program utilizing the valuable resources of the community must be a dynamic ongoing process constantly undergoing evaluation” (p. 21). Given these data and the research, it may benefit schools to either increase the frequency of review or gather volunteer-level data to use during this evaluation process to provide a more comprehensive evaluation. Overall, the data from the four strategic volunteer talent management areas confirm that there is variance with how principals manage the talent of volunteers within schools. Therefore, strategic volunteer talent management skills are a potential area of growth for some principals. Machin and Paine (2008), in their study of over 1,350 volunteer programs, also recommended that volunteer managers be fully supported and provided with opportunities to build their own capacity as they lead volunteer programs. Further study of the practices of effective programs may 117 help other principals create programs within their school that continue to meet the school’s priorities. Strategic Volunteer Talent Management and Student Poverty, Volunteer Hours, and Leadership Experience. The following section discusses the researcher’s conclusions for research question 2: Are there correlations between volunteer management and student poverty, volunteer hours, and leadership experience? Volunteer hours. There was a large variation in the volunteer hours data. The mean number of volunteer hours was 2,586 with a standard deviation of 2,000. Brent’s (2000b) also found large variations in volunteer hours across schools. The large variation in hours may be due to the fact that the school’s volunteer coordinator self-reports volunteer hours and numbers monthly. The survey data showed that the volunteer coordination falls to a staff member, parent or other member of the community 90% of the time. Through examination of OLPS processes and procedures, there is not a centralized process or formula for capturing these data accurately. Schools simply report the number volunteer hours. Furthermore, although these data are requested by the district, there is no penalty for not reporting. Volunteer management and student poverty, volunteer hours, and leadership experience. The research showed there is no statistical significance between the total strategic volunteer talent management composite, volunteer management planning, volunteer program management, volunteer management alignment, volunteer management evaluation and the FARMS rate, the number of volunteer hours, and leadership experience. The researcher did find a wide variation in the strategic 118 volunteer talent management composite scores leading to the conclusion that there may not be set OLPS guidelines for managing volunteers or principals are uncertain of what volunteer management literature suggests are best practices. Parent Engagement and Student Poverty, Volunteer Hours, and Leadership Experience. The following section discusses the researcher’s conclusions for research question 3: Are there correlations between climate and student poverty, volunteer hours, and leadership experience? Results were mixed when ordinary least squares multiple regression analyses were used. There was a positive statistically significant correlation between total parent engagement, two-way communication, respectful climate and FARMS rates. These data show that schools with higher rates of student poverty had higher climate scores. The study found a positive correlation between overall satisfaction and leadership experience. This may be because as principals grow and develop professionally, they are presumably more skilled at meeting stakeholders’ needs and addressing issues as they arise. Both of these qualities may influence parental satisfaction positively. Louis et al. (2010) found that it takes approximately five years of leadership continuity to impact climate. Interestingly, the Wisconsin Department of Public Instruction (2014) chose to include a value-added growth measure as one part of principals’ evaluations, but decided to include an adjustment period. This time allows new principals to develop their capacity to impact school programs and climate since this process may take several years. These principals have three evaluation cycles before certain outcome measures, including climate, affect their evaluations. Like with the strategic volunteer talent management 119 composites, there was no correlation between volunteer hours and total parent engagement, two-way communication, respectful climate and overall satisfaction. This may have been due to the small number of schools that did report volunteer hours causing poor data quality. Parent Engagement and Strategic Volunteer Talent Management. Results show that there is a statistically significant relationship between volunteer program management and respectful climate, total engagement, and overall satisfaction. This area of strategic volunteer talent management includes interviewing volunteers, requiring initial training, providing ongoing training and ensuring all volunteers are recognized. Additionally, principals either facilitate or attend volunteer trainings. This action provides volunteers with an opportunity to meet the principal before working in the school building. These management strategies while steeped in volunteer management theory also clearly show an effort to create respectful partnerships between volunteers, the principal, and school, which may lead to overall satisfaction. There was also a correlation between respectful climate and volunteer management evaluation, which again shows mutual respect by eliciting feedback from the volunteers on their experiences in the school. However, no statistically significant correlations occurred between each parent engagement variable and the total strategic volunteer talent management composite. Student Achievement and Strategic Volunteer Talent Management, Parent Engagement, Student Poverty, and Leadership Experience. The following section discusses the researcher’s conclusions for research question 4: Are 120 there correlations between student achievement and volunteer management, parent engagement, student poverty, and leadership experience? Student Achievement and Strategic Volunteer Talent Management, Parent Engagement, Student Poverty, and Leadership Experience. Three of the math achievement models showed a positive correlation between schools that reported volunteer hours and student math achievement. This may be because schools that report data have volunteer management processes and procedures in place that support how volunteers work with students. Research by Lee, Smith and Cronginger (1997) looked solely at how a school’s structure impacted math and science achievement. They chose these achievement data because they were “more precise” in correlating school level structural practices to student achievement than other subjects such as reading and had less correlation with other factors like family background. One such structural practice included in the study was the use of parent volunteers in the school. They found “…that structural practices that schools engage in do influence academic achievement” in math and science (p. 141). In the current study, the researcher used the volunteer hours dummy variable as a volunteer management proxy that emphasizes principals’ expectations for how their volunteer programs operate and demonstrates a well-planned and implemented program. Similarly in another study of volunteers, Castro et al. (2004) found that higher quality classrooms (measured by the Early Childhood Environment Rating Scale) had a statistically significant relationship with the number of volunteers that worked in these rooms. Both data points display how strong leadership and defined expectations can improve student achievement. 121 When looking only at student achievement and parent engagement data, the correlations between math achievement and both two-way communication and respectful climate were negative. The same was true for reading achievement and respectful climate. Williams, Persaud, and Turner (2008) found the opposite in their study of 81 elementary schools in Atlanta. Their data showed that “school climate predicted significantly student reading scores that met and exceed expectation” (p. 7). Additionally, the current study found a positive correlation between math achievement and overall satisfaction for this particular dataset. Similarly, when analyzing student achievement and strategic volunteer talent management, overall satisfaction, two-way communication, student poverty, and leadership experience the correlation between math achievement and overall satisfaction was positive and two- way communication was negative. Although they do not specify math achievement, Cohen et al. (2009) acknowledged that “Compelling empirical research shows that a positive and sustained school climate promotes students' academic achievement and healthy development” (p. 45) Although this study did not find many statistically significant relationships between volunteer management and student achievement, multiple studies on volunteers have found positive statistically significant relationships between these two variables. A number of studies (Bogan, 1997; Jitendra et al., 2013; Starkey & Klein, 2000) found positive relationships between the work of volunteers and math achievement. Several researchers (DeCusati & Johnson, 2004; Invernizzi, Rosemary, Juel, & Richards, 1997; Pullen et al., 2004; Rebok et al., 2011; Worthy & Hoffman, 1999) found positive correlations between the work of volunteers and reading 122 achievement. While others (Austin Partners in Education, 2012; Rothman & Henderson, 2011; Shaver & Walls, 1998) found positive relationships between the work of volunteers and both achievement areas. Those studies looked directly at the work of volunteers, which is different from this study’s focus. Nevertheless, it is clear that without a well-planned volunteer program that implemented many of the volunteer management strategies discussed throughout this study, the work of volunteers would have likely not affected student achievement at the same level if at all. The school level implemented volunteer management strategies set a framework for these successes. As you would expect, this study showed that the most accurate predictor of the current year’s student achievement is the prior year’s student achievement in both reading and math. Conclusions The study produced mixed results. It was a bit unexpected that there was no statistical difference in how administrators managed volunteers and school-level FARMS rates, but not surprising that prior year achievement is the best predictor of current year achievement. The most significant findings were: (1) a positive correlation between parent engagement and volunteer program management; (2) a link between math achievement and schools that reported volunteer hours; and (3) a positive statistically significant correlation between math achievement and overall satisfaction. Given that a majority of schools in this study are identifying tasks and reviewing volunteer information, we can see that principals are aligning their priorities and tasks with the information gathered from volunteers. These data show 123 purposefulness in placing volunteers in tasks. The struggle to make better use of school-level resources is one of the important challenges facing school leaders today (Ball Foundation, 1995). The study’s results demonstrate how school principals develop and implement volunteer policies and programs that support students’ learning. Yet, the study found a lack of statistically significant relationships between volunteer management and student achievement. Previous research indicates that the management of volunteers is a challenging, but a necessary skill set principals must acquire. Michael (1990) summarized: As a result of its examination of school volunteer programs, the committee has concluded that volunteers do make significant contributions to education and that schools have need of and could not otherwise afford many of the services volunteers can provide. The committee believes equally strongly, however, that volunteer activities should be thought-fully planned, organized, and focused. The committee therefore makes two recommendations:  The committee recommends that educators, school boards, community leaders, and state and federal public officials become informed about and support the development of school volunteer programs.  The committee recommends that volunteer programs be designed to complement and support the educational objectives of schools. (p. 101-102) These mixed results and the literature available provide data to support further principal education on the management of volunteers. 124 Although the study found a limited number of statistically significant links between parent engagement and volunteer management, we do know that how parent volunteers engage with the school principal and staff when volunteering may influence climate results. This is especially likely given the large number of parents who are volunteers. This study found that the majority of volunteers were parents, over 40% of the principals stated that parents make up between 80 - 100% of their entire cadre of volunteers. Further volunteer-level analysis may support this claim statistically, but this study’s data on the number of parent volunteers would suggest that the more engaged and valued parents are as volunteers, the higher their individual engagement score may be for some, if not all, of the climate themes included in this study. Recommendations for Practice The results of this study suggest that all principals should actively evaluate their current volunteer management processes and procedures to look for ways to enhance their programs and to manage this workforce more strategically in order to meet the needs of students and schools. The lack of correlation between volunteers and student achievement suggests that principals could better align volunteers to meet the needs of the students to improve student achievement. This conclusion is consistent with the literature supporting the idea that the highest performing organizations manage individuals using methods that support the strategic goals of an organization. For schools, the strategic goal is often improving student achievement (Odden, 2011, p. 9). 125 Based on the literature, principals should follow three key steps: (1) identify and prioritize which student needs remain unmet before they develop volunteer tasks, (2) develop a clear understanding of the talents and experience of each volunteer, and (3) prioritize placing volunteers in school-based tasks that best align with their unique talents. Given the variation in volunteer management survey responses and the positive correlation between schools that reported volunteer data and math student achievement, boards of education may want to approve funding to build the capacity of elementary school principals and future leaders in developing and managing a volunteer workforce that is prepared to help meet the needs of students and schools. The ultimate goal is to identify strategic processes that would match volunteers to the needs of the school seamlessly. Researcher Reflection The researcher began this study with the assumption that volunteer management would look different across schools and that the implementation of strategic volunteer talent management strategies would positively affect climate and potentially student achievement. As the analysis showed, this was not true, statistically, for all areas of this sample. Suggestions for Further Research Suggestion 1. Study how elementary principals manage volunteers in multiple districts. Due to the size of this study, the results may not be generalizable. But studying how elementary school principals manage their volunteers across districts may provide a clearer profile of what processes and procedures principals use and how this management improves school climate and operations. 126 Suggestion 2. Study how all levels of principals manage volunteers. Studying all levels of schools may provide greater variety in processes and procedures or provide a clearer picture of how the work of both the principal and the school volunteer changes based on the grade level of the school being supported. Suggestion 3. Survey volunteers about their experiences and perceptions working in schools. Gathering volunteer feedback may be able to provide principals with feedback on areas of improvement with their processes and procedures, volunteer perceptions and to gauge reaction to certain aspects volunteering, but also as a way to better meet volunteers' needs in the future. Suggestion 4. Study the distribution of volunteers within a district. School district leaders often are unaware of the disparities in nonmonetary resources across their own schools (Darden & Cavendish, 2011). According to Brent (2001b, 2000b), some school districts exhibit an unequal distribution of volunteers across schools, which may compound an already unequal distribution of resources. This study found a large variation in volunteer hours and a lack of reporting across OLPS. Studying volunteer distribution across schools would be important because an unequal distribution of volunteers that favors schools in affluent neighborhoods over those in poorer areas could result in further inequities in resources, productivity, and academic performance. Such disparities could compound the challenges facing schools today, especially those in poorer neighborhoods. Suggestion 5. Cost analysis of the volunteer distribution within a district. To assess equity in regards to volunteer distribution in a district, the researcher could match job descriptions and salaries to the three types of volunteer work performed by 127 volunteers: (a) general-administrative, (b) teacher-focused, and (c) student-focused. This process would allow the researcher to determine the cost benefit of the volunteer workforce in each school across the district. Additionally, by examining the distribution patterns of each school’s added monetary benefit from its volunteers the research may help to further understand the impact of non-purchased resources on schools and determine whether these particular resources create inequities across a district. Final Thoughts This study examined how elementary principals act as volunteer managers in one school district. The purpose was to clarify how principals actively manage their volunteers. The statistically analysis and findings allowed the researcher to draw conclusions and make suggestions based on the data, including, a focus on how to improve the skill set of principals as volunteer managers. The role of a principal is complex and this particular skill set may improve the overall function of a school. 128 Appendix A Institutional Review Board Application Approval Notification 129 Appendix B Orange Leaf Public Schools Application Approval Notification 130 Appendix C Orange Leaf Public Schools Volunteer Management Survey General Characteristics 1. School Name 2. Total Number of Students 3. I have been an administrator for… 0 – 5 years 6 – 10 years 11 – 15 years 16 – 20 years >20 years 4. I have been an administrator at this school for… 0 – 5 years 6 – 10 years 11 – 15 years 16 – 20 years >20 years 5. What percent of your volunteers are from each category below? Parents 0% - 20% 21% - 40% 41 – 60% 61% - 80% 81% -100% Community Volunteers 0% - 20% 21% - 40% 41 – 60% 61% - 80% 81% -100% Middle/High/ College Students 0% - 20% 21% - 40% 41 – 60% 61% - 80% 81% -100% Other 0% - 20% 21% - 40% 41 – 60% 61% - 80% 81% -100% Volunteer Management Planning Choose the answer that best fits the statement. 6. Volunteers have to complete an application to volunteer. Never Rarely Sometimes Always 7. My school compiles a list of school needs/tasks that volunteers can support. Never Rarely Sometimes Always 131 8. My school has a description of what skills are needed to complete the tasks identified. Never Rarely Sometimes Always 9. My school actively recruits volunteers. Never Rarely Sometimes Always 10. How do you recruit volunteers? Mark all that apply. PTA School Newsletter School Website Community Partnership Room Parents Other ___________ Volunteer Program Management 11. Who coordinates your school’s volunteer program? Principal Assistant Principal Staff Member Parent Other ___________ Choose the answer that best fits the statement. 12. Volunteers are interviewed before being assigned. Never Rarely Sometimes Always 13. Volunteers are required to attend an initial training. Never Rarely Sometimes Always 14. Volunteers receive ongoing training. Never Rarely Sometimes Always 15. I facilitate the volunteer training. Never Rarely Sometimes Always 16. I do not facilitate the training, but I attend. Never Rarely Sometimes Always 132 17. ALL volunteers are recognized for their work. Never Rarely Sometimes Always Volunteer Management Alignment 18. My school’s priorities for placing volunteers are: Additional Academic Support Never Rarely Sometimes Always Lower Class Size Ratios Never Rarely Sometimes Always Lower Adult to Student Ratios in Non-Structured Areas for Safety (e.g., Recess/Lunch) Never Rarely Sometimes Always Other Areas of the School Program Never Rarely Sometimes Always 19. Volunteers help my school meet its priorities. Never Rarely Sometimes Always 133 20. What percent of volunteers are assigned to each of the following tasks? General administrative tasks (examples: recess and lunch duty, media center, field trips, and/or administrative offices) 0% - 20% 21% - 40% 41 – 60% 61% - 80% 81% -100% Teacher-focused tasks (examples: prepare teaching materials, photocopy and preparing materials, assist with grading, decorate classroom, and/or creating bulletin boards) 0% - 20% 21% - 40% 41 – 60% 61% - 80% 81% -100% Student-focused tasks (examples: classroom support (includes tutoring) and/or assist students with reading/writing, math, science, and technology activities) 0% - 20% 21% - 40% 41 – 60% 61% - 80% 81% -100% 21. Who assigns volunteers at your school? Choose the answer that best fits. Volunteers choose their own assigned tasks. I place volunteers in tasks at my school. A staff member places volunteers in tasks at my school. A parent places volunteers in tasks at my school. 22. My school collects the following information from incoming volunteers. Mark all that apply. Desired level of time commitment Days and times available Activities that interest the volunteer Activities that the volunteer does not want to do Special skills Occupation Languages that volunteer can interpret Languages that volunteer can translate Other ___________ 23. My school uses the information gathered from volunteers when assigning them to tasks. Never Rarely Sometimes Always 134 24. Volunteers are assigned to a particular student or student group. Never Rarely Sometimes Always 25. Volunteers are assigned to a particular teacher. Never Rarely Sometimes Always 26. Volunteers are assigned to a particular recess or lunch period. Never Rarely Sometimes Always 27. Volunteers meet with assigned student(s) before beginning their assigned task. Never Rarely Sometimes Always 28. Volunteers meet with assigned teacher before beginning their assigned task. Never Rarely Sometimes Always Volunteer Management Evaluation 29. My school reviews the processes used for assigning volunteers. Never Rarely Sometimes Always 30. We review the processes used for assigning volunteers. Yearly Quarterly Monthly Weekly 31. Volunteers are provided with an exit interview. Never Rarely Sometimes Always 135 Appendix D Principal Comment Analysis Results Principal Component Analysis for Gallup Parent Engagement Survey Component 1 2 3 4 ENG_Q17 0.843 0.432 0.089 0.023 ENG_Q9 0.837 0.170 0.355 -0.008 ENG_Q18 0.834 0.183 0.380 0.070 ENG_Q20 0.822 0.262 0.395 0.044 ENG_Q5 0.821 0.402 0.239 0.030 ENG_Q13 0.756 0.531 0.190 0.070 ENG_Q12 0.751 0.520 0.303 0.108 ENG_Q14 0.746 0.442 0.283 0.098 ENG_Q19 0.737 0.435 0.226 0.275 ENG_Q11 0.693 0.498 0.365 0.180 ENG_Q6 0.655 0.379 0.342 0.208 ENG_Q15 0.647 0.112 0.448 0.080 ENG_Q4 0.616 0.548 0.291 0.164 ENG_Q2 0.254 0.817 0.268 -0.160 ENG_Q1 0.353 0.798 0.341 0.055 ENG_Q3 0.420 0.788 0.341 0.017 ENG_Q8 0.473 0.525 0.218 0.449 ENG_Q22 0.235 0.243 0.899 0.045 ENG_Q21 0.329 0.259 0.835 0.073 ENG_Q10 0.275 0.347 0.738 0.132 ENG_Q7 0.480 0.496 0.567 0.230 ENG_Q16 0.263 0.060 0.119 0.829 ENG_Q23 0.538 0.196 -0.023 -0.593 After the analysis was completed, the researcher reviewed the individual questions under each component. Three common themes emerged across the engagement questions: (a) factor 1 – Two-way Communication, (b) factor 2 – Respectful Climate, and (c) factor 3 – Overall Satisfaction. Based on the principal component analysis data, the researcher chose not to have a fourth factor that included questions 16 and 23. 136 Appendix E Parent Engagement Survey Questions by Factor Factor 1: Two-way Communication # Question 4 I am comfortable talking to my child's teachers about my child's education. 5 The school informs me about my child's education in a timely manner. 6 My child's teachers expect my child to do well in school. 9 The school informs me of resources that are available so I can help my child with his/her homework, tests, and projects. 11 The school has a clear process for addressing my needs. 12 The school provides opportunities for me to voice my needs about my child's education. 13 The school welcomes my input on how my child's educational experience can be improved. 14 There is an adult at the school who will advocate for my child's needs. 15 I am informed in a timely manner about events and activities occurring at my child's school. 17 The school has a clear process for me to provide feedback about my child's education. 18 The school provides information about resources in the school and community that are available to my child and family. 19 The school considers me a partner in my child's education. 20 The school informs me of educational opportunities that are available to my child. Factor 2: Respectful Climate 1 I feel welcomed at my child's school. 2 When I visit my child's school, I am promptly and courteously received. 3 The school respects my family. 8 I am comfortable being an advocate for my child. Factor 3: Overall Satisfaction 7 School staff members are responsive to my concerns about my child. 10 I believe my child is safe at school. 21 I would recommend this school to others. 22 What grade would you give your child's school? Factor 4: Questions Not Included 16 I believe I play an important role in my child's education. 23 What grade would you give the public schools in OLPS? 137 Appendix F Bilateral Correlation Table F A R M S % V o lu n te er H o u rs V o lu n te er H o u rs D u m m y L ea d er sh ip E x p er ie n ce T o ta l V o lu n te er M an ag em en t C o m p o si te P la n n in g P ro g ra m M an ag em en t A li g n m en t E v al u at io n T o ta l E n g ag em en t C o m p o si te FARMS% 1 Volunteer Hours -.188 1 Volunteer Hours Dummy -.097 N/A 1 Leadership Experience -.001 .223 .115 1 Total Volunteer Management Composite -.103 .183 .351 * .015 1 Planning -.175 .212 .295* .015 .847* 1 Program Management -.066 .143 .373* .088 .710* .580* 1 Alignment -.053 .111 .180 -.031 .799* .500* .251* 1 Evaluation .009 .055 .301* -.039 .699* .656* .405* .455* 1 Total Engagement Composite .433 * -.028 -.066 -.005 -.032 -.127 .087 -.011 -.144 1 Two-way Communication .515* -.047 -.072 .008 -.038 -.135 .069 -.016 -.101 .986* Respectful Climate .308* -.061 -.072 -.041 -.030 -.110 .091 .008 -.257* .872* Overall Satisfaction -.043 .147 -.012 .022 -.005 -.062 .126 -.025 -.147 .798* %_Rdg_2013 -.812* .261 .208 .053 .107 .141 .109 .032 .076 -.270* %_Rdg_2012 -.777* .335* .157 .093 .150 .200 .092 .096 .045 -.139 %_Math_2013 -.836* .311 .210 -.008 .126 .167 .156 .025 .063 -.295* %_Math_2012 -.768* .328* .102 .109 .091 .103 .065 .070 -.005 -.211 * indicates significance at the 95% (0.05) level 138 Continued - 2 T w o -w ay C o m m u n ic at io n R es p ec tf u l C li m at e O v er al l S at is fa ct io n % _ R d g _ 2 0 1 3 % _ R d g _ 2 0 1 2 % _ M at h _ 2 0 1 3 % _ M at h _ 2 0 1 2 FARMS% Volunteer Hours Volunteer Hours Dummy Leadership Experience Total Volunteer Management Composite Planning Program Management Alignment Evaluation Total Engagement Composite Two-way Communication 1 Respectful Climate .798* 1 Overall Satisfaction .722* .700* 1 %_Rdg_2013 -.347* -.226 .207 1 %_Rdg_2012 -.232 -.074 .340* .911* 1 %_Math_2013 -.368* -.275* .216 .926* .864* 1 %_Math_2012 -.284* -.191 .282* .864* .889* .883* 1 * indicates significance at the 95% (0.05) level 139 Appendix G Study Cover Letter 140 Bibliography Addonizio, M. 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