In this study, student teachers explored four data collection methods for data feedback to improve their teaching skills in Science and Technology [S&T]. The aim was to verify whether these methods were suitable for collecting data concerning their teaching skills during S&T activities in their internships. They analysed the collected data…

Educational improvement projects are increasingly focused upon the significant role of data in determining student performance, teachers' learning, and schools' ability to initiate local reforms. Thus, schools are moving toward a new approach to learning, progressing from the routine to the non-routine through inquiry-based working. In addition,…

Purpose: The purpose of this paper is to answer the question, what progress student teachers make during one academic year, while being trained in a professional learning community, using objective classroom observation, using lesson preparation templates that match their developmental stage and stage-focused mentor feedback.…

Inquiry-based science education (IBSE) has been promoted as an inspiring way of learning science by engaging pupils in designing and conducting their own scientific investigations. For primary school teachers, the open nature of IBSE poses challenges as they often lack experience in supporting their pupils during the different phases of an open…

School leaders are assumed to be important for the implementation of data-based decision making (DBDM), but little is known about changes in leadership during this implementation. Educational leadership was measured before, during, and after a two-year, school-wide DBDM intervention in 96 primary schools. Advanced analysis techniques were applied:…

In peer nomination research, individuals who do not provide nominations (nonparticipants) are often included on rosters as potential nominees. This can present ethical questions regarding informed consent, but psychometric consequences of excluding nonparticipants from rosters are unknown. In this investigation, Study 1 simulated both random and…

This article studies the relationship between teachers' perceptions of distributive leadership and inquiry-based work in primary schools and the resulting impact on those teachers' capacity to contribute to educational change. The path analysis that tests the proposed model relies on questionnaire data collected from 787 teachers in 65 primary…

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 schools. Yet, little is known about the school features that facilitate or hinder the implementation of DBDM. Based on a literature review, the authors…

This study's aim was to examine the prevalence, development and domain specificity of fifth- and sixth-grade elementary school students' achievement goal profiles. Achievement goals were measured for language and mathematics among 722 pupils at three points in time. These data were analysed through latent profile analysis and latent transition…

Despite the emphasis on data-based decision making (DBDM) in educational policy in several countries, evidence regarding the intended effect of improved student achievement is still scarce. The purpose of this study is to examine the effects of a DBDM intervention on teacher efficacy. This study incorporates an experimental longitudinal research…

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…

With the advent of computers in education, and the ample availability of online learning and practice environments, enormous amounts of data on learning become available. The purpose of this paper is to present a decade of experience with analyzing and improving an online practice environment for math, which has thus far recorded over a billion…

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…

A first application of multilevel latent class analysis (MLCA) to educational large-scale assessment data is demonstrated. This statistical technique addresses several of the challenges that assessment data offers. Importantly, MLCA allows modeling of the often ignored teacher effects and of the joint influence of teacher and student variables.…

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,…