This study examined supports that facilitate teacher data use in schools. The purpose of this work was to extend the base of knowledge of general supports for teacher data use, leadership supports for teacher data use, and technology supports for teacher data use. Three research questions guided the study to determine those supports necessary for teachers to be successful in data use: (a) What general data supports exist for teacher data use in schools, (b) what leadership supports exist for teacher data use in schools, and (c) what technology supports exist for teacher data use in schools? A qualitative and quantitative data collection process with a single-case study approach included individual interviews, focus groups, and a survey instrument. The data from these components were coded, analyzed, and organized into themes and implications by implementing the 6-step constant-comparative model. This mixed methods process provided a thorough evaluation of findings to answer the research questions. Two implications were found during the study. First, structures and systems for data use must be intentional in order to support teacher data use in schools. Contributing to the intentionality is time for collaboration; professional development to build teacher capacity; and clearly aligned district vision, mission, and goals. Second, technology support in the classroom is integral to effective data use by teachers. This support manifests in hardware support and personnel support. Hardware includes having the appropriate system that maintains the students, timely access to data and a user-friendly format. Personnel support refers to the integration of technology into teaching and learning, teacher-to-teacher support, and an alleviation of distrust through positive interaction with data. Further analysis revealed implications for practice, including the importance of creating structures and developing a plan for data use. / text

Thesis advisor: Martin Scanlan / This qualitative case study examined leaders’ shared data use, a process of translating data into action (Bernhardt, 2013). Understanding data use is considered conceptually by attending to the assistance relationships shared between central office leaders and principals in the context of turnaround. Such relationships are marked by occasions during which members share expertise by modeling practices; the modeling informs how systems, structures and subsequent practices are introduced and even reinforced for newer members. I focused my analysis on four manifestations of data use: data’s influence on adjusting leadership practice, data’s ability to inform instruction, data use’s benefits from technological advancement, and the intentional promotion of resilience. Data collection included document review as well as interviews with central office leaders and principals. Findings evidenced the nature of both central office leaders’ and principals’ data use as well as revealed a remarkable degree of commonality in the language and practices these leaders shared. The results of this study indicated that assistance relationships are a functioning element of leadership in the turnaround context. This study supported the research that leaders’ shared practice of data use benefits student growth and achievement in line with state-determined assessment and accountability targets. Recommendations include additional research into Lawrence Public Schools’ data use to further inform a blueprint for comprehensive district-wide reform as well as the development of exit criteria from receivership. / Thesis (EdD) — Boston College, 2018. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Leadership and Higher Education.

Magister Commercii - MCom (IM) (Information Management) / In an ideal public health arena, scientific evidence should be incorporated in the health information practices of making management decisions, developing policies, and implementing programs. However, much effort has been spent in developing health information practices focusing mainly on data collection, data quality and processing, with relatively little development on the utilization side of the information spectrum. Although the South Africa Health National Indicator Dataset of 2013 routinely collects and reports on more than two hundred elements, the degree to which this information is being used is not empirically known. The overall aim of the study was to explore the dynamics of routine primary healthcare information utilization in the West Coast district while identifying specific interventions that could ultimately lead to the improved use of data to better inform decision making. The ultimate goal being to enable managers to better utilize their routine health information for effective decision making.

This study applies an empirical research method determine whether Texas public school principals’ leadership styles, coupled with their use of real time data in a data warehouse, influenced their leadership ability as measured by student achievement. In today’s world of data rich environments that require campuses and districts to make data-driven decisions, principals find themselves having to organize and categorize data to help their school boards, campuses, and citizenry make informed decisions. Most school principals in Texas have access to data in multiple forms including national and state resources and a multitude of other data reports. A random sample of principals was selected to take the Multi Factor Leadership Questionnaire (MLQ5x) and the Principals Data Use Survey. The MLQ5x measured principals’ leadership styles as transformational, transactional, or passive avoidant. The Principals Data Use Survey measured how principals use data to inform campus decisions on student achievement, shaping the vision of the campus, and designing professional development. Data obtained from the survey were correlated to determine the relationship between principals’ use of data warehouses and their leadership styles on student achievement as measured by the Texas Assessment of Knowledge and Skills. The results yielded significant relationships between student achievement, principals’ leadership styles, and the principals’ data use with a data warehouse. Student achievement scores were highly correlated with the campuses that participated in the study and provided limited differences between those with data warehouses and those without data warehouses.

Thesis advisor: Henry I. Braun / Data-based instructional programs, including interim assessments, are a common tool for improving teaching and learning. However, few studies have rigorously examined whether they achieve those ends and contributors to their effectiveness. This study conducts a secondary analysis of data from a matched-pair school-randomized evaluation of the Achievement Network (ANet). Year-two teacher surveys (n=616) and interviews from a subset of ANet school leaders and teachers (n=40) are used to examine the impact of ANet on teachers’ data-based instructional practices and the mediating roles of instructional leadership, professional and achievement cultures, and teacher attitudes and confidence. Survey results showed an impact of ANet on the frequency with which teachers’ reviewed and used data, but not their instructional planning or differentiation. Consistent with the program model, ANet had a modest impact on school-mean teacher ratings of their leaders’ instructional leadership abilities and school culture, but no impact on individual teachers’ attitudes toward assessment or confidence with data-based instructional practices. Therefore, it was not surprising that these school and teacher characteristics only partially accounted for ANet’s impact on teachers’ data practices. Interview findings were consistent. Teachers described numerous opportunities to review students’ ANet assessment results and examples of how they used these data (e.g., to pinpoint skills on which their students struggled). However, there were fewer examples of strategies such as differentiated instruction. Interview findings also suggested some ways leadership, culture, and teacher characteristics influenced ANet teachers’ practices. Leaders’ roles seemed as much about holding teachers accountable for implementation as offering instructional support and, while teachers had opportunities to collaborate, a few schools’ implementation efforts were likely hampered by poor collegial trust. Teacher confidence and attitudes varied, but improved over the two years; the latter following from a perceived connection between ANet practices and better student performance. However, some teachers were concerned with the assessments being too difficult for their students or poorly aligned with the curriculum, resulting in data that were not always instructionally useful. / Thesis (PhD) — Boston College, 2016. / Submitted to: Boston College. Lynch School of Education. / Discipline: Educational Research, Measurement and Evaluation.

This research is focused on the intersection of secondary teachers’ data-use to inform instructional decisions and their teaching of STEM in STEM-focused high schools. Teaching STEM requires presenting more than just the content knowledge of the STEM domains. The methods of inquiry (e.g., scientific inquiry, engineering design) are skills that should be taught as part of STEM activities (e.g., science labs). However, under the data- and standards-based accountability focus of education, it is unclear how data from STEM activities is used in instructional decision-making. While teachers give tremendous weight to the data they collect directly from their observations of their classrooms, it is data from standardized testing that strongly influences practices through accountability mandates. STEM education alters this scenario because, while there is a growing focus on teaching STEM, important aspects of STEM education are not readily standardized. This mixed-methods study will examine the perspectives of 9th through 12th grade science and mathematics teachers, in STEM-focused schools, on data-use and STEM teaching. We developed a framework, adapted from existing frameworks of data-use, to categorize these perspectives and outline contexts influencing them. Through a concurrent triangulation design we will combine quantitative and qualitative data for a comprehensive synthesis of these perspectives.

Previous research indicates that pre- and in-service teachers are not receiving adequate training to implement data-informed instructional decision making. This is problematic given the promise this decision making process holds for improving instruction and student learning. At the same time, many educators do not see the value of different types of assessment data (e.g. accountability data), and lack the knowledge, skills, and confidence to use available data to guide instructional decisions. The purpose of this study was to conduct a formative evaluation of an online training designed to improve Iowa pre- and in-service teachers’ perceptions about data, data knowledge, skills and confidence working with data. The training along with a data literacy test was administered online to 29 pre-service teachers from two Iowa universities. A pre-post design was used to assess changes in these data constructs. Results indicated that participants’ perceptions about external accountability data improved significantly after completing the training, as did their confidence working with data. However, most participants’ data performance were relatively stable pre-post training. A content analysis of responses pre-post revealed qualitative changes in some participants’ thinking about data. Participants rated the value, effectiveness and quality of the training and complementary materials. Ratings were mostly positive, with participants signifying the training and materials as valuable and effective for enhancing their understanding of data as well as their confidence working with data. Participants also identified opportunities for improving the training. The author concludes with a discussion of the results, implications for future research, and how the study adds to the existing literature and informs practice.

Diese Dissertation untersucht die Verwendung von Performance-Informationen („Kennzahlen“) durch Führungskräfte in der öffentlichen Verwaltung. Unter „Verwendung“ wird dabei die zweckorientierte Nutzung der Daten verstanden, um zu steuern, zu lernen und öffentliche Leistungen zu verbessern. Die zentrale Frage der Arbeit lautet: Wie können Unterschiede bei der Verwendung von Performance-Informationen erklärt werden? Um diese Frage zu beantworten, wird die bereits existierende Literatur strukturiert ausgewertet. Forschungslücken werden aufgezeigt und eigene Ansätze vorgestellt, wie diese geschlossen werden können. Der erste Teil der Dissertation untersucht den Einfluss von Manager-bezogenen Faktoren auf die Nutzung von Performance-Daten, die bislang in der Forschung noch keine Berücksichtigung gefunden haben. Der zweite Abschnitt testet ein modifiziertes Modell aus der Psychologie, das auf der Annahme basiert, dass die Verwendung von Performance-Informationen ein bewusstes und durchdachtes Verhalten darstellt. Der dritte Teil untersucht, inwieweit sich die Erklärungen für die Nutzung von Performance-Informationen unterscheiden, wenn wir diese nicht nur als Kennzahlen definieren, sondern ebenfalls andere Quellen von „unsystematischem“ Feedback berücksichtigen. Die empirischen Ergebnisse der Arbeit basieren auf einer Umfrage aus dem Jahr 2011. Im Rahmen dieses Surveys habe ich die mittleren Manager (Amtsleiter und Fachbereichsleiter) aus acht ausgewählten Bereichen aller kreisfreien Städte in Deutschland befragt (n=954). Zur Auswertung der Daten wurden die Verfahren Faktorenanalyse, Multiple Regressionsanalyse und Strukturgleichungsmodellierung eingesetzt. Meine Forschung förderte unter anderem vier Erkenntnisse zu Tage, die durch ähnliche Befunde der verschiedenen Teile der Dissertation abgesichert sind: 1) Die Verwendung von Performance-Daten kann als bewusstes Verhalten von Führungskräften modelliert werden, das durch deren Einstellung sowie durch die Einstellung ihres sozialen Umfeldes bestimmt wird. 2) Häufige Nutzer von Performance-Informationen zeigen überraschenderweise keine generelle Präferenz für das abstrakt-analytische Verarbeiten von Informationen. Stattdessen bevorzugen sie, Informationen durch persönliche Interaktionen aufzunehmen. 3) Manager, die sich früh im Rahmen der Ermittlung von Performance-Informationen engagieren, nutzen diese später auch häufiger, um Entscheidungen zu treffen. 4) Performance-Berichte sind nur eine Informationsquelle unter vielen. Verwaltungsmanager präferieren verbales Feedback von Insidern sowie das Feedback von wichtigen externen Stakeholdern gegenüber systematischen Performance-Daten. Die Dissertation erklärt diese Befunde theoretisch und verdeutlicht deren Implikationen für Theorie und Praxis. / The dissertation examines the use of performance information by public managers. “Use” is conceptualized as purposeful utilization in order to steer, learn, and improve public services. The main research question is: Why do public managers use performance information? To answer this question, I systematically review the existing literature, identify research gaps and introduce the approach of my dissertation. The first part deals with manager-related variables that might affect performance information use but which have thus far been disregarded. The second part models performance data use by applying a theory from social psychology which is based on the assumption that this management behavior is conscious and reasoned. The third part examines the extent to which explanations of performance information use vary if we include others sources of “unsystematic” feedback in our analysis. The empirical results are based on survey data from 2011. I surveyed middle managers from eight selected divisions of all German cities with county status (n=954). To analyze the data, I used factor analysis, multiple regression analysis, and structural equation modeling. My research resulted in four major findings: 1) The use of performance information can be modeled as a reasoned behavior which is determined by the attitude of the managers and of their immediate peers. 2) Regular users of performance data surprisingly are not generally inclined to analyze abstract data but rather prefer gathering information through personal interaction. 3) Managers who take on ownership of performance information at an early stage in the measurement process are also more likely to use this data when it is reported to them. 4) Performance reports are only one source of information among many. Public managers prefer verbal feedback from insiders and feedback from external stakeholders over systematic performance reports. The dissertation explains these findings using a deductive approach and discusses their implications for theory and practice.

Nationwide reform efforts strive to improve schooling through a range of approaches including improving the quality of campus leadership, restructuring organizational design, and revamping instruction. National and state education policies reflect the reforms addressed in educational research literature and drive state, district, and campus based improvement initiatives. For example, the more recent influence of the No Child Left Behind Act (NCLB) and the Adequate Yearly Progress (AYP) accountability system has led to a significant increase in the use of data to drive instructional decision-making. Campus leadership is key to both the successful implementation of data initiatives (Wayman and Stringfield, 2006) as well as comprehensive reform efforts (Leithwood & Jantzi, 2005). The literature provides a wide array of leadership theories that offer promise in understanding more effective approaches to leading school improvement efforts; however, much of this literature remains conceptual and vague (Leithwood, Harris, & Hopkins 2008). Data use has gained increasing attention in the literature as well, but the research lacks a strong conceptual framework for leadership. The purpose of this paper is to view data use through the lens of Leithwood’s model of Transformational Leadership in order to explore the linkages between the leadership theory and data use practices and to offer a framework that situates data use as a tool to increase all students’ academic performance and build a democratic and socially just learning organization. The linkages between Transformational Leadership and data use are presented as both bodies of literature are reviewed. The study was guided by the following questions: 1) What are the levels of Transformational Leadership Behaviors exhibited at each campus? 2) What are the data use practices being implemented on each campus? 3) What is the relationship between Transformational Leadership and data use? Two schools served as the sites for the research which drew on both quantitative and qualitative data sources to address the research questions. Results and findings show evidence of Transformational Leadership Behaviors that linked closely with the data use practices. The final discussion offers a preliminary conceptual framework delineating the intersection between the theory of Transformational Leadership and data use in schools. / text

Educators are increasingly being asked to interact with data to facilitate students’ learning in the classroom. However, as an educational measurement community, we have little understanding of the factors and/or contexts that facilitate educators’ successful use of data. Educators’ use of score reports and the relationship to the intended use is integral to the concept of validity. A conceptual model, “Data Habit of Mind,” is proposed to study educators’ understanding, interpretation and potential applications of results from large-scale assessments. The metaphor, “Habit of Mind,” was originally coined by Robert Sternberg and Dan Keating, and has been applied in the education sector to describe educators’ habits of inquiry when interacting with assessments. Based on an extensive review of the literature, Data Habit of Mind is defined as a combination of statistical literacy and score report interpretation. Statistical literacy is the extent to which an individual is able to describe, organize and reduce, represent, and analyze and interpret data. Score report interpretation is the extent to which an individual is able to describe, summarize, question, and propose an application for a given set of elements on a score report. The combination of these two makes up an individual’s Data Habit of Mind. Twenty educators were interviewed to assess their level of statistical literacy and their score report interpretation skills. A cognitive interview approach was used to capture the educators’ cognitive processes as they solved performance-based tasks, and protocol analysis procedures were used to encode the responses into the conceptual model. Descriptions of educators’ Data Habit of Mind were then generated through qualitative matrix analysis. Four groups of educators were identified based on the patterns of relationship between their statistical literacy and score report interpretation scores. Demographic factors, including teaching experience, gender and educational background were not meaningful predictors of educators’ Data Habit of Mind. These results add to our understanding of how educators interpret and use test results and have implications for test validation processes.