Search

Assessment for learning (AfL) can facilitate students' development of metacognition. However, teachers often struggle with the implementation of AfL in their classroom. The dynamic approach can help teachers develop professionally in the complex competency that is AfL. The dynamic approach is based on four principles: (a) addressing the professional needs of teachers, (b) integrating skills, (c) explaining underlying mechanisms, and (d) implementing support and feedback. In this experimental study, we investigated the effect on students' metacognition of an AfL teacher professional development program for secondary mathematics teachers based on the dynamic approach (n[subscript teachers] = 47, n[subscript students] = 803). We found a statistically significant positive effect on students' ability to predict (d = 0.24) and evaluate (d = 0.22), but not on students' ability to plan.

Purpose: Schools struggle with sustaining their educational innovations (Cohen and Mehta, 2017; Askell-Williams and Koh, 2020) and may benefit from concrete and practical guidance (Askell-Williams and Koh, 2020). A dialogue between staff within schools can be a way to promote self-evaluation regarding the innovation. Therefore, a self-evaluation tool for educators was developed: The Sustainability Meter (TSM). The purpose of the tool is to gain insight into the different perspectives and experiences of stakeholders within the school organization regarding the innovation, as a basis for improvement-directed actions to promote sustainable educational innovation. Design/methodology/approach: In this small-scale study, the authors explored conceptual and instrumental use of the Sustainability Meter in two phases, and also examined user satisfaction. In phase 1, the tool was used under the guidance of the researcher (first author), who supported the chairs in taking steps before the group dialogue took place, and who then guided the dialogue itself as a moderator. In phase 2, work with TSM was organized independently by the schools themselves, supported by the manual. Data were collected in the form of observations of the dialogue, group interviews and documents generated by the participants. Findings: In terms of conceptual use, in general, participants gained better understanding of each other's perspectives and backgrounds with regard to the (sustainability of the) innovation. The dialogue also led to insights into challenges for growth toward sustainable innovation. For instrumental use, the results of the analysis were incorporated in a plan of action in the majority of the participants' schools. In terms of user satisfaction, participants in all groups perceived TSM as an enjoyable support for high-quality dialogue. This research provides some indications that the tool might lead to sustainable educational innovations. Originality/value: Next to developing an action plan based on the results of the school, the tool also appeared to help breaking up the process in smaller, clearer and more feasible improvement-directed actions. The results of this study further show that the authors could distinguish between three types of instrumental use. The improvement-directed actions in this research often were a combination of this three types: initial solutions, short-term and longer-term measures. This research provides some indications that the tool might lead to sustainable educational innovations.

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.

Background: The continual improvement of teaching and learning is vital for schools in order to meet the rapid changes in the world around us. Lesson study is considered a valuable professional development approach in that regard. It is focused on teachers collaboratively studying live classroom lessons. Sustaining lesson study, by making its core components part of the school's organisational routines, can help schools continually and systematically to improve student learning and teaching. However, despite the value of this approach, sustaining lesson study turns out to be complex. Leadership seems to play a crucial role therein, but the question is: how? Purpose: The study aimed to gain in-depth insight into what leadership looks like in schools that sustained lesson study. Method: A case study design was used to investigate leadership in two secondary schools. We conducted over 300 hours of observations through immersion within practice, collected school policy documents, and interviewed the school leadership. Data were analysed qualitatively. Findings: The analysis identified that both schools carried out various leadership practices for sustained lesson study. For leadership at schools that aim for sustained lesson study, it seems important to schedule lesson study, to be available, to have knowledge about lesson study and to appoint a lesson study coordinator. Whether and how leadership practices were carried out seemed to depend on the school's context -- for instance, by the policy reasons for working with lesson study. As such, it is important to examine the school and its leadership in context when considering sustainability. Conclusion: Through immersion within practice, specific and real-life examples of leadership were identified. This study's insights could help school leadership to sustain lesson study in their schools.

Because learning from failures is just as important as learning from successes, we used qualitative case study data gathered in the Netherlands and the United States to examine instances in which data teams struggle to contribute to school improvement. Similar factors in both the Dutch and U.S. case hindered the work of the data teams, such as data use focused on accountability instead of improvement. Some hindering factors were more context-specific. Learning why, how, and when data use efforts do not go smoothly provides an important contribution to research and practice.

Background: Professional Learning Networks (PLNs) of educators represent a promising approach to achieving continuous school improvement. At the same time, a range of studies in this area, including several systematic reviews and meta-analyses, report multiple conceptual and methodological challenges, or, at best, mixed results. Purpose and sources: The aim of this theoretical discussion paper, therefore, is to seek, first, to synthesise and connect to previous studies focused on professional learning communities and networks by combining and reflecting on their findings and recommendations. Second, we aim to contribute to the methodological development of the field in order to propose research that can link what happens in PLNs to changes in outcomes for students. For the latter, we will also make use of new insights from the field with regard to the use of big data in education. Main argument: We propose a conceptual model of what defines PLNs, enactment process variables, and influencing factors, presenting our theory-of-action for how PLNs can be effective. Second, we discuss challenges and recommendations in studying PLN impact regarding research approach, research design and measurement. This discussion includes consideration of the use of big data to help to make the analysis of patterns in, and relations between, different types of PLN research data more efficient and reliable. Conclusion: We need to define and study the processes and effects of PLNs more efficiently and effectively, to support PLNs in fulfilling the promise of increased teacher learning, improved outcomes for students, and, ultimately, sustainable school improvement at scale.

Background: To enable all students to reach their full potential, teachers have to adapt their instruction to students' varying needs. In order to do this, teachers need to engage in activities associated with formative assessment, as well as those associated with differentiation. However, both of these types of activities are, in themselves, difficult for teachers to carry out. Furthermore, as both fields tend to use their own terminology, frameworks, and cycles of teacher activities, it can be even more difficult for teachers to navigate both. Although the notion of the strong relationship between formative assessment and differentiation is not new, we argue that a better understanding of the close relationship between the two is needed in the context of teacher education. Purpose: Our aim was to develop a conceptual framework which offers teachers and teacher educators a coherent set of teacher activities in which both formative assessment and differentiation are represented. Sources of evidence: International literature in the fields of formative assessment and differentiation was reviewed. Through this process, we sought to identify, describe and compare teacher activities regarded as crucial for formative assessment and for differentiation. The review was based on extant review studies and frameworks used in both fields and handbooks on both topics. Main argument: Our analysis demonstrated that both approaches have much in common, but differ substantially in terms of the emphasis placed on different activities and the depth of elaboration. As such, we argue that the approaches complement each other well and that it is feasible to present teachers with one coherent set of teacher activities in which both approaches are unified. We propose a conceptual framework for Assessment-Informed Differentiation (AID), which involves a continual cycle of in-depth activities related to preparing and providing differentiated instruction based on assessment data. Conclusion: Formative assessment and differentiation approaches need to be treated as an integrated set of activities in order to realise the full potential of all students. Further research should focus on the usability and effectiveness of the proposed cycle. The conceptual framework we propose could ultimately be used in many different teacher education settings internationally, forming a starting point for much-needed teacher professional development in this area.

Assessment for Learning (AfL) is complex requiring teacher competences for collecting, analysing and interpreting evidence of student progress, and for adapting instruction and learning accordingly. In this study, the four-component instructional design (4C/ID) model for complex learning was used to design a teacher professional development (TPD) programme for developing teachers' AfL competences. The evaluation of the implementation of the program showed that teachers were positive about the relevance and usability of the program, and about the AfL knowledge, skills and attitudes gained. This study yields important lessons about how to support teachers in learning to apply AfL in their classrooms. The study shows that the 4C/ID model can provide the learning-psychological basis for the design of TPD programmes for the acquisition of complex teacher skills, that require the integration of skills, knowledge and attitudes. [ABSTRACT FROM AUTHOR]

Data-informed decision making is considered important for school improvement. Working in data teams is a promising strategy for implementing data use in schools. Data teams consist of teachers and school leaders, who collaboratively analyze data to solve educational problems at their school. Studies show that school leaders can enable and hinder data use in such teams. This study aims at exploring what types of leadership behaviors are applied to support data use in data teams. The results of this study point to five key building blocks for school leaders wanting to build effective data teams in their school: (1) establishing a vision, norms, and goals (e.g., discussing vision, norms, and goals with teachers); (2) providing individualized support (e.g., providing emotional support); (3) intellectual stimulation (e.g., sharing knowledge and providing autonomy); (4) creating a climate for data use (e.g., creating a safe climate focused on improvement rather than accountability, and engaging in data discussions with teachers); and (5) networking to connect different parts of the school organization (e.g., brokering knowledge and creating a network that is committed to data use). Not only formal school leaders, but also teachers, can display these types of behavior. Finally, it is important to stress here that all these building blocks are needed to create sustainable data use practices. These building blocks can be used in a new wave of data-informed decision making in schools, in which teachers and school leaders collaboratively use a multitude of different data sources to improve education.

This study examines the way teachers make sense of data in the context of high-stakes decision making, such as decisions related to student placement in educational tracks. Different types of data, data collected rationally and intuitively, may be used in this sensemaking process, and the same data may be interpreted in different ways by different teachers. Results show that teachers base their decisions on rational processes only to a limited extent. Teachers collect a great amount of data intuitively, and they sometimes interpret data collected rationally by personal criteria and triangulate data to a very limited extent. Since fair educational decisions are informed by a rational collection and a transparent interpretation of data, implications for theory and practice are provided.

Schools need support in the use of data. To provide this support, a data team intervention was developed. A prior study conducted in the Netherlands showed that several factors can enable or hinder the work of data teams. The current replication study focuses on the factors influencing data use in data teams and the perceived effects of the data teams' work, but looking at data teams in Sweden. The results of this qualitative study show that the data teams' work is influenced by the same factors as in the Netherlands: Data characteristics (e.g., relevance of the data), team characteristics (e.g., heterogeneity of the team), and school organizational characteristics (e.g., school leader support).

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 evidence are available across a wide range of indicators. There is potential for school leaders, teachers and students to use these diverse sources more fully to support their work on a range of school improvement goals. Purpose and sources of evidence: To explore data-based decision-making for school improvement, this theoretical paper discusses recent research and literature from different areas of data use in education. These areas include the use of formative assessment data, educational research study findings and 'big data'. In particular, the discussion focuses on how school leaders and teachers can use different sources of data to improve the quality of education. Main argument: Based on the literature reviewed, an iterative model of data use for school improvement is described, consisting of defining goals for data use, collecting different types of data or evidence (e.g. formal data, informal data, research evidence and 'big data'), sense-making, taking improvement actions and evaluation. Drawing on the literature, research insights are discussed for each of these components, as well as identification of the research gaps that still exist. It is noted that the process of data use does not happen in isolation: data use is influenced by system, organisation and team/individual level factors. Conclusions: When it comes to using data to improve the quality of teaching and learning, it is evident that some of the most important enablers and barriers include data literacy and leadership. However, what is less well understood is how we can promote the enablers and remove the barriers to unlock, more fully, the potential of data use. Only then can data use lead to sustainable school improvement.

The way in which school leaders implement professional learning communities (PLCs) is important for realizing sustainable school improvement. The assumption is that school leaders act based on their interpretation of the PLC, which is based on their underlying educational beliefs. In this study, we explored these latter aspects by interviewing six formal and informal school leaders, discussing the sustainability of PLCs in two secondary schools that had each worked with PLCs for seven years. The results of this in-depth qualitative study show that the schools differed in the degree of sustainability they achieved: one still used the PLC as intended; the other now omitted one step of the original format. This can be explained by the leaders' interpretations of the PLC and their educational beliefs. Furthermore, we found that student- and collaboration-oriented beliefs are critical for continuing the work of a PLC. Finally, we found that the organizational context mediateswhether leaders act upon their beliefs. Tensions between leaders' beliefs and the organizational context, such as fear of colleagues' resistance, appeared to influence their choice to act or not concerning specific aspects of the PLC. These findings can give school leaders insights into conditions for sustainable school improvement with PLCs. [ABSTRACT FROM AUTHOR]

The data team intervention was designed to support Dutch secondary schools in using data while developing a solution to an educational problem. A data team can build school-wide capacity for data use through knowledge sharing among data team members, and knowledge brokerage between the team and other colleagues. The goal of this mixed-methods study is to understand how knowledge sharing and brokerage regarding data use and an educational problem changed over time. Social network data were collected twice at eight schools. These data were used to analyse (1) how well team members were connected with each other (density), (2) whether team members' relationships were mutual (reciprocity) and (3) whether all team members were equally important for the data team network (centralisation). Moreover, different types of knowledge brokering (inward, outward and forward) were examined to further understand knowledge exchange between data team members and their colleagues. Qualitative data were analysed to triangulate these findings for four particular cases. Among other things, findings illustrated that while knowledge sharing and knowledge brokerage both changed over time, there were considerable differences between teams in the extent and direction of change. It appeared that the dissemination of knowledge within the organisation requires more explicit attention.

Data-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 study and adapt their educational practices for the purpose of maximizing learning results. Teachers must apply the findings from their data use to their personal teaching activities. Therefore, data-based decision-making may be influenced by individual teachers' psychological characteristics. The present study aimed to explore which psychological factors contribute to teachers' data use in a Dutch primary school context. A questionnaire-based quantitative methodology was employed. We included the following psychological constructs: affective and instrumental attitudes, perceived control, social norms, self-efficacy, collective efficacy, and intentions regarding data use. Results of the path analysis showed that perceived control, instrumental attitude, and intention regarding data use all significantly influenced data use. Additionally, intention was found to be a mediator of the relation between affective attitude and data use. Interventions aimed at data-based decision-making should take these psychological factors into account to increase teachers' implementation of data-based decision-making for instruction and, consequently, educational quality.

Most professional development activities focus on individual teachers, such as mentoring or the use of portfolios. However, new developments in higher education require teachers to work together in teams more often. Due to these changes, there is a growing need for professional development activities focusing on teams. Therefore, this review study was conducted to provide an overview of what is known about professional development in teams in the context of higher education. A total of 18 articles were reviewed that describe the effects of professional development in teams on teacher attitudes and teacher learning. Furthermore, several factors that can either hinder or support professional development in teams are identified at the individual teacher level, at the team level, and also at the organizational level.

Schools in many different countries are increasingly expected to use data for school improvement. However, schools struggle with the implementation of data use, because building human capacity around data use in education has not received enough attention. Educators urgently need to develop data literacy skills for being able to use data. For supporting schools with the endeavor of developing data literacy skills, we developed and implemented a data use intervention in secondary schools based in the Netherlands. This study therefore focuses on the effects of this intervention on educator satisfaction with the intervention and their data literacy skills and attitude toward data use. This study uses a quasi-experimental research design and employs a mixed-methods approach with a data use questionnaire filled in by data team schools (N = 9) and comparison schools (N = 42), a satisfaction questionnaire filled in by data team participants (N = 55), pre- and posttest knowledge tests filled in by data team participants (N = 36), and interview data (N = 11) from three case study schools. The results show that the participants were, for example, very satisfied with the support received during the intervention. Also, respondents developed new data literacy skills and showed a more positive attitude toward data use. The results show how teachers can be supported systematically in data use in their educational practice. In the conclusions, we discuss some important implications for practice regarding the intensity and duration of support and implications for further research.

Background: Data-based decision-making (DBDM) and research-informed teaching practice (RITP) are key to teacher and school improvement. Currently, however, DBDM and RITP represent two distinct approaches to developing evidence-informed practice (EIP) and do not correspond to the all-encompassing notion of EIP envisaged by many academics and commentators. Purpose: DBDM and RITP are usually employed independently of each other. Each is associated with its own theoretical perspectives and research base, and each has its own pitfalls and strengths. Yet the approaches employed appear to be complementary, suggesting that there might be value in combining DBDM and RITP into one overarching process for achieving EIP. This paper presents the conceptual analysis and arguments for this proposal. Sources of evidence: Drawing from literature and previous research in the fields of DBDM, RITP and EIP, we describe both DBDM and RITP, before comparing and contrasting the integral aspects of each. Main argument: Our analysis leads us to suggest that not only is there overlap between these two approaches, but the strengths of each appear to mirror and compensate for the weaknesses of the other. As such, we argue that it is important that decisions in education are based on a combination of personal judgement, research evidence and local school data. This is because such a combination is likely to lead to equitable, effective and efficient decisions that are informed by values and preferences, grounded in context and steeped in practices that have been shown to be effective elsewhere. Conclusions: We suggest that an effective strategy for EIP might be to achieve "the best of two worlds" by integrating DBDM and RITP. In line with evidence-informed practices in medicine and management, this means EIP in education can finally be engaged in as a holistic approach to educational decision-making that critically appraises different forms of evidence before key improvement decisions are made. Our proposed approach, "Evidence Informed School and Teacher Improvement," is thus designed with the aim of enhancing the quality of educational provision by employing these evidence types as part of a systematic cycle of inquiry, focused on continuously improving the quality of learning in schools.

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.