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Kim Schildkamp - One of the best experts on this subject based on the ideXlab platform.
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A Conceptual Model for Effective Quality Management of Online and Blended Learning
Electronic Journal of e-Learning, 2020Co-Authors: Yves Blieck, Kim Schildkamp, Cindy Louise Poortman, Chang Zhu, Katrien Struyven, Bram Pynoo, Koen DepryckAbstract:Institutions considering online and blended learning (OBL) face the challenge of strategically adopting OBL to develop, implement, monitor, assess and improve the quality of programmes and courses. The principles of continuous quality improvement (CQI) allow this challenge to be addressed. Effective CQI management implies that quality assurance and quality improvement follow and inform each other as part of a continuous cycle. Scholars report however, that quality management of OBL usually focuses on assurance. The purpose of this paper is to provide a state of the art approach for effective CQI management which allows practitioners to achieve coherence between quality assurance and improvement of OBL. In this conceptual paper we link and integrate work across fields to address the challenge of achieving coherence between quality assurance and improvement. We discuss research in the context of CQI that uncovers features of OBL that prevent practitioners from achieving coherence. The conceptual model for effective CQI of OBL integrates data based Decision‑Making. The conceptual model provides a foundation for research on the effectiveness of this CQI management approach in the context of OBL. The quality management approach supports practitioners during the entire CQI‑cycle to foster dialogue and consultation between all stakeholders in the institution in order to strategically develop assess and improve the quality of OBL programmes and courses. The originality of the model lies in Making explicit data‑based Decision Making as a driver for effective CQI management in the context of OBL.
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Data-Based Decision-Making for school improvement: Research insights and gaps
Educational Research, 2019Co-Authors: Kim SchildkampAbstract:Background: Data-Based Decision-Making in education often focuses on the use of summative assessment data in order to bring about improvements in student achievement. However, many other sources of...
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Data-Based Decision Making for teacher and student learning: a psychological perspective on the role of the teacher
Educational Psychology, 2018Co-Authors: Rilana Prenger, Kim SchildkampAbstract:AbstractData-Based Decision-Making has the potential to increase student achievement results. Data-Based Decision-Making can be defined as teachers’ systematic analysis of data sources in order to ...
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Factors promoting and hindering Data-Based Decision Making in schools
School Effectiveness and School Improvement, 2016Co-Authors: Kim Schildkamp, Cindy Louise Poortman, Hans Luyten, Johanna EbbelerAbstract:Although Data-Based Decision Making can lead to improved student achievement, data are often not used effectively in schools. This paper therefore focuses on conditions for effective data use. We studied the extent to which school organizational characteristics, data characteristics, user characteristics, and collaboration influenced data use for (1) accountability, (2) school development, and (3) instruction. The results of our hierarchical linear modeling (HLM) analysis from this large-scale quantitative study (N = 1073) show that, on average, teachers appear to score relatively high on data use for accountability and school development. Regarding instruction, however, several data sources are used only on a yearly basis. Among the factors investigated, school organizational characteristics and collaboration have the greatest influence on teachers’ data use in schools.
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Data-Based Decision Making in teams : Enablers and barriers
Educational Research and Evaluation, 2016Co-Authors: Erik Bolhuis, Kim Schildkamp, Joke VoogtAbstract:Data use is becoming more important in higher education. In this case study, a team of teachers from a teacher education college was supported in Data-Based Decision Making by means of the data team procedure. This data team studied the reasons why students drop out. A team's success depends in part on whether the team is able to develop and apply new knowledge based on data. To investigate this, we focused on the depth of inquiry within the data team's conversations, because successful teams discuss data in depth. We observed the data team for 2 years, investigating factors that affected the depth of the conversations in the data team. The results show that depth was influenced by factors related to data and data systems (such as access to relevant data), individual factors (such as belief in data use), and organisational factors (guidance from the data coach).
Adrie J Visscher - One of the best experts on this subject based on the ideXlab platform.
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On the value of Data-Based Decision Making in education: The evidence from six intervention studies
Studies in Educational Evaluation, 2020Co-Authors: Adrie J VisscherAbstract:Abstract Although some studies have investigated the impact of Data-Based Decision Making (DBDM) on student achievement, the overall findings are not straightforward, because of the studies’ methodological flaws and their mixed results. This article first presents a breakdown of the DBDM concept as applied in the Dutch context. Next, it explains the theoretical foundations of DBDM in feedback and goal-setting theory and then discusses various factors influencing DBDM effectiveness. The results of six Dutch DBDM interventions with an explicit focus on student achievement effects of DBDM and with strong research designs are then presented. Significant positive effects on student performance as measured by means of standardized tests are reported for four interventions. The interpretation of student progress data from student monitoring systems does not seem to be problematic for teachers, if they are deliberately trained for it, but teachers do find it difficult to translate student progress data into tailor-made instruction.
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effects of a data based Decision Making intervention for teachers on students mathematical achievement
Journal of Teacher Education, 2018Co-Authors: Emmelien A Van Der Scheer, Adrie J VisscherAbstract:Data-Based Decision Making (DBDM) is an important element of educational policy in many countries, as it is assumed that student achievement will improve if teachers worked in a Data-Based way. However, studies that evaluate rigorously the effects of DBDM on student achievement are scarce. In this study, the effects of an intensive DBDM-intervention for Grade 4 teachers on students’ mathematical achievement were investigated in a randomized controlled trial. Multilevel analyses showed that although no main effect on students’ mathematical achievements was found, students who received “extended instruction” benefited significantly from the intervention. Based on the results, recommendations for the design of new DBDM-interventions and for their evaluation are presented.
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Differentiated instruction in a Data-Based Decision-Making context
School Effectiveness and School Improvement, 2017Co-Authors: Janke M. Faber, Cees A. W. Glas, Adrie J VisscherAbstract:In this study, the relationship between differentiated instruction, as an element of Data-Based Decision Making, and student achievement was examined. Classroom observations (n = 144) were used to measure teachers’ differentiated instruction practices and to predict the mathematical achievement of 2nd- and 5th-grade students (n = 953). The analysis of classroom observation data was based on a combination of generalizability theory and item response theory, and student achievement effects were determined by means of multilevel analysis. No significant positive effects were found for differentiated instruction practices. Furthermore, findings showed that students in low-ability groups profited less from differentiated instruction than students in average or high-ability groups. Nevertheless, the findings, data collection, and data-analysis procedures of this study contribute to the study of classroom observation and the measurement of differentiated instruction.
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Changes in educators' data literacy during a Data-Based Decision Making intervention
Teaching and Teacher Education, 2017Co-Authors: Marieke Van Geel, Adrie J Visscher, Trynke Keuning, Jean-paul FoxAbstract:Data literacy is assumed to be a precondition for the effective implementation of Data-Based Decision Making in schools. This study was aimed at investigating changes in 1182 educators' data literacy with regard to student monitoring system data, during a 2-year intervention, which was assessed by using a pretest and posttest. A multivariate multi-level IRT analysis was conducted. The multivariate approach enabled the identification of differences in initial data literacy and development, based on educators' characteristics. Findings showed significant improvements in educators' data literacy. Furthermore, the ‘knowledge gap’ between educators with a master's degree versus higher education was closed, just as the gap between teachers and school leaders.
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Effects of an intensive Data-Based Decision Making intervention on teacher efficacy
Teaching and Teacher Education, 2016Co-Authors: Emmelien A Van Der Scheer, Adrie J VisscherAbstract:Research into the effects of interventions on teacher efficacy is scarce. In this study, the long-term effects of an intensive Data-Based Decision Making intervention on teacher efficacy of mainly grade 4 teachers were investigated by means of a delayed treatment control group design (62 teachers). The findings showed significant strong intervention effects on teachers' efficacy for instructional strategies, and student engagement in both treatment groups. No significant effects were found for teacher efficacy regarding classroom management. Improved teacher efficacy in the first treatment group persisted throughout the second school year. Suggestions for future research are presented
Arend J. Visscher - One of the best experts on this subject based on the ideXlab platform.
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School characteristics influencing the implementation of a Data-Based Decision Making intervention
School Effectiveness and School Improvement, 2017Co-Authors: Marieke Van Geel, Arend J. Visscher, B. TeunisAbstract:There is an increasing global emphasis on using data for Decision Making, with a growing body of research on interventions aimed at implementing and sustaining Data-Based Decision Making (DBDM) in ...
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Why a Data-Based Decision-Making Intervention Works in Some Schools and Not in Others
Learning Disabilities Research & Practice, 2017Co-Authors: Trynke Keuning, Marieke Van Geel, Arend J. VisscherAbstract:The use of data for adaptive, tailor-made education can be beneficial for students with learning difficulties. While evaluating the effects of a Data-Based Decision-Making (DBDM) intervention on student outcomes, considerable variation between intervention effects, ranging from high-intervention effects to small or even negative intervention effects, across schools was found. The main purpose of this study was to investigate whether educator and school organizational characteristics are related to the effects of a DBDM intervention on student achievement growth by comparing 10 primary schools with strong intervention effects with 10 primary schools with no intervention effects on student achievement. Supportive and hindering factors were studied by means of surveys and interviews with school management teams, and by examining school reports from the project trainers. Results indicate that schools with strong intervention effects differed from schools with no intervention effects with regard to their teachers’ teaching quality, staff's attitude toward DBDM, and the school data culture
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Effects of a Data-Based Decision Making intervention on student achievement
Studies in Educational Evaluation, 2017Co-Authors: Laura Staman, Anneke Timmermans, Arend J. VisscherAbstract:Data-Based Decision Making (DBDM) is becoming important for teachers due to increasing amounts of digital feedback on student performance. In the quasi-experimental study reported here, teachers, principals, and academic coaches from 42 schools were trained for two years in using the results of half-year interim assessments for providing students with tailor-made instruction. Our results did not show any main effects of this DBDM training trajectory on student achievement but did indicate interaction effects with students’ low prior achievement levels and socioeconomic status. Teachers experience difficulties in translating student progress data into adaptive instruction in the classroom. Implications of our findings for teacher professionalization are discussed
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Changes in teachers’ instructional skills during an intensive Data-Based Decision Making intervention
Teaching and Teacher Education, 2017Co-Authors: Emmelien A Van Der Scheer, Cornelis A.w. Glas, Arend J. VisscherAbstract:This study evaluates changes in teachers' instructional skills after participating in an intensive Data-Based Decision Making (DBDM) intervention for grade 4 teachers. Teachers were recorded three times prior to the intervention, and three times after the intervention, and all recordings were rated by four raters. The data was analyzed by means of advanced item response theory (IRT) techniques, combined with a generalizability model. Teachers significantly improved their DBDM related skills. Teachers’ initial basic teaching skills did not seem to matter for the extent to which teachers developed their DBDM related instructional skills. Suggestions for future research are presented.
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The Transformation of Schools' Social Networks during a Data-Based Decision Making Reform.
Teachers College Record, 2016Co-Authors: Trynke Keuning, Marieke Van Geel, Arend J. Visscher, Gerardus J.a. Fox, Nienke M. MoolenaarAbstract:Context: Collaboration within school teams is considered to be important to build the capacity school teams need to work in a Data-Based way. In a school characterized by a strong collaborative culture, teachers may have more access to the knowledge and skills for analyzing data, teachers have more opportunity to discuss the performance goals to be set, and they also can share effective teaching strategies to achieve those goals. Although many studies on Data-Based Decision Making (DBDM) foreground the importance of teacher collaboration, our knowledge of what such collaboration looks like and how such collaboration may change during a DBDM reform remains limited. Objective: The current study uses a social network perspective to explore how collaboration in 32 elementary schools in the Netherlands takes shape in the interactions among teachers as they engage in a DBDM reform project. Research Design: Schools’ social networks were examined at the start of the intervention and after having participated 1 year in the DBDM reform. Social networks regarding three DBDM topics are examined: (1) discussing student achievement; (2) discussing achievement goals; (3) and discussing instructional strategies. The density, reciprocity, and centralization of these networks were calculated, and multivariate multiple regression analysis was used to analyze changes over time. Conclusion: Findings suggest that teachers’ DBDM related networks transform during the intervention, especially regarding the discussion of student achievement data: although the number of relationships remains stable, more reciprocal relationships are formed, and this network becomes less centralized around one or a few influential staff members
Marieke Van Geel - One of the best experts on this subject based on the ideXlab platform.
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School characteristics influencing the implementation of a Data-Based Decision Making intervention
School Effectiveness and School Improvement, 2017Co-Authors: Marieke Van Geel, Arend J. Visscher, B. TeunisAbstract:There is an increasing global emphasis on using data for Decision Making, with a growing body of research on interventions aimed at implementing and sustaining Data-Based Decision Making (DBDM) in ...
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Why a Data-Based Decision-Making Intervention Works in Some Schools and Not in Others
Learning Disabilities Research & Practice, 2017Co-Authors: Trynke Keuning, Marieke Van Geel, Arend J. VisscherAbstract:The use of data for adaptive, tailor-made education can be beneficial for students with learning difficulties. While evaluating the effects of a Data-Based Decision-Making (DBDM) intervention on student outcomes, considerable variation between intervention effects, ranging from high-intervention effects to small or even negative intervention effects, across schools was found. The main purpose of this study was to investigate whether educator and school organizational characteristics are related to the effects of a DBDM intervention on student achievement growth by comparing 10 primary schools with strong intervention effects with 10 primary schools with no intervention effects on student achievement. Supportive and hindering factors were studied by means of surveys and interviews with school management teams, and by examining school reports from the project trainers. Results indicate that schools with strong intervention effects differed from schools with no intervention effects with regard to their teachers’ teaching quality, staff's attitude toward DBDM, and the school data culture
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Changes in educators' data literacy during a Data-Based Decision Making intervention
Teaching and Teacher Education, 2017Co-Authors: Marieke Van Geel, Adrie J Visscher, Trynke Keuning, Jean-paul FoxAbstract:Data literacy is assumed to be a precondition for the effective implementation of Data-Based Decision Making in schools. This study was aimed at investigating changes in 1182 educators' data literacy with regard to student monitoring system data, during a 2-year intervention, which was assessed by using a pretest and posttest. A multivariate multi-level IRT analysis was conducted. The multivariate approach enabled the identification of differences in initial data literacy and development, based on educators' characteristics. Findings showed significant improvements in educators' data literacy. Furthermore, the ‘knowledge gap’ between educators with a master's degree versus higher education was closed, just as the gap between teachers and school leaders.
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The Transformation of Schools' Social Networks during a Data-Based Decision Making Reform.
Teachers College Record, 2016Co-Authors: Trynke Keuning, Marieke Van Geel, Arend J. Visscher, Gerardus J.a. Fox, Nienke M. MoolenaarAbstract:Context: Collaboration within school teams is considered to be important to build the capacity school teams need to work in a Data-Based way. In a school characterized by a strong collaborative culture, teachers may have more access to the knowledge and skills for analyzing data, teachers have more opportunity to discuss the performance goals to be set, and they also can share effective teaching strategies to achieve those goals. Although many studies on Data-Based Decision Making (DBDM) foreground the importance of teacher collaboration, our knowledge of what such collaboration looks like and how such collaboration may change during a DBDM reform remains limited. Objective: The current study uses a social network perspective to explore how collaboration in 32 elementary schools in the Netherlands takes shape in the interactions among teachers as they engage in a DBDM reform project. Research Design: Schools’ social networks were examined at the start of the intervention and after having participated 1 year in the DBDM reform. Social networks regarding three DBDM topics are examined: (1) discussing student achievement; (2) discussing achievement goals; (3) and discussing instructional strategies. The density, reciprocity, and centralization of these networks were calculated, and multivariate multiple regression analysis was used to analyze changes over time. Conclusion: Findings suggest that teachers’ DBDM related networks transform during the intervention, especially regarding the discussion of student achievement data: although the number of relationships remains stable, more reciprocal relationships are formed, and this network becomes less centralized around one or a few influential staff members
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Assessing the Effects of a School-Wide Data-Based Decision-Making Intervention on Student Achievement Growth in Primary Schools.
American Educational Research Journal, 2016Co-Authors: Marieke Van Geel, Adrie J Visscher, Trynke Keuning, Jean-paul FoxAbstract:Despite growing international interest in the use of data to improve education, few studies examining the effects on student achievement are yet available. In the present study, the effects of a two-year Data-Based Decision-Making intervention on student achievement growth were investigated. Fifty-three primary schools participated in the project, and student achievement data were collected over the two years before and two years during the intervention. Linear mixed models were used to analyze the differential effect of data use on student achievement. A positive mean intervention effect was estimated, with an average effect of approximately one extra month of schooling. Furthermore, the results suggest that the intervention especially significantly improved the performances of students in low socioeconomic status schools
Jean-paul Fox - One of the best experts on this subject based on the ideXlab platform.
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Changes in educators' data literacy during a Data-Based Decision Making intervention
Teaching and Teacher Education, 2017Co-Authors: Marieke Van Geel, Adrie J Visscher, Trynke Keuning, Jean-paul FoxAbstract:Data literacy is assumed to be a precondition for the effective implementation of Data-Based Decision Making in schools. This study was aimed at investigating changes in 1182 educators' data literacy with regard to student monitoring system data, during a 2-year intervention, which was assessed by using a pretest and posttest. A multivariate multi-level IRT analysis was conducted. The multivariate approach enabled the identification of differences in initial data literacy and development, based on educators' characteristics. Findings showed significant improvements in educators' data literacy. Furthermore, the ‘knowledge gap’ between educators with a master's degree versus higher education was closed, just as the gap between teachers and school leaders.
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Assessing the Effects of a School-Wide Data-Based Decision-Making Intervention on Student Achievement Growth in Primary Schools.
American Educational Research Journal, 2016Co-Authors: Marieke Van Geel, Adrie J Visscher, Trynke Keuning, Jean-paul FoxAbstract:Despite growing international interest in the use of data to improve education, few studies examining the effects on student achievement are yet available. In the present study, the effects of a two-year Data-Based Decision-Making intervention on student achievement growth were investigated. Fifty-three primary schools participated in the project, and student achievement data were collected over the two years before and two years during the intervention. Linear mixed models were used to analyze the differential effect of data use on student achievement. A positive mean intervention effect was estimated, with an average effect of approximately one extra month of schooling. Furthermore, the results suggest that the intervention especially significantly improved the performances of students in low socioeconomic status schools
