Teacher self-efficacy (TSE) is supposed to positively affect teachers’ well-being, instructional quality and students’ motivation. However, the extent to which secondary school teachers’ TSE is shaped by their social teaching environment—particularly the different classes they teach—remains largely unexplored. This pre-registered study exploratorily investigated to what extent TSE can be considered a context-specific construct that varies within teachers across classes. Intraclass correlations indicated substantial within-teacher variation for TSE related to student engagement (ICC = 0.40) and classroom management (ICC = 0.37), while TSE for instructional strategies appeared relatively stable (ICC = 0.61). Multilevel regression models, considering the data from 1,326 students in 74 classes taught by 26 teachers, revealed negative relations between class misbehavior and TSE beliefs across all domains of TSE. All other class characteristics (i.e., students’ emotional and behavioral engagement, percentage of boys in class, mean grade) were less consistent or not significantly related to TSE. These exploratory findings call for larger replications to further understand whether conventional approaches to measuring and promoting teacher self-efficacy should be challenged.

Although internal school evaluation (IE) is widely recognized as a key tool for data-based school development, there is limited understanding of what makes it effective. Conducting a narrative literature review, we examined the methods used in IE and IE research, the effectiveness of IE, and factors that influence its outcomes and processes. Based on a systematic literature search and coding process, 19 empirical studies were included in the analyses. The effectiveness of IE seems to depend on the interplay of contextual factors (e.g., schools’ IE capacity), characteristics of the evaluation such as its systematic, research-based design, strong stakeholder involvement, shared leadership, and long-term implementation, and finally, human factors, most prominently, self-efficacy beliefs and the staff’s attitudes toward evaluation. The review highlights the need for more research using diverse methods that also considers classroom-level variables and explores theories of change rather than focusing on IE as a general treatment.

This study, conducted as a registered report, investigates how expectancy beliefs and task values predict diagnostic performance in simulation-based learning environments for prospective teachers and physicians. Using a meta-analytic approach, we analyzed individual participant data from 16 studies (N = 1,492) conducted within a single research unit. Despite the homogeneity in measures and methodologies, measurement invariance analyses revealed two clusters of studies (Cluster 1: nine studies, Cluster 2: five studies) with differing patterns. For expectancies for success and diagnostic accuracy, the aggregated Fisher's z correlation was .07 (p = .03, 95% CI [.01, .13]) in Cluster 1 and -.04 (p = .63, 95% CI [-.18, .11]) in Cluster 2. For utility value and diagnostic accuracy, the correlations were .14 (p < .05; 95% CI [.02, .26]) and .08 (p = .10; 95% CI [-.01, .18]), respectively. The interaction between expectancy beliefs and utility value showed weak, inconsistent, and nonsignificant relations with diagnostic accuracy in both clusters. Findings also varied depending on whether motivational variables were assessed at a task-specific or more general level. No differences emerged between teacher and medical education contexts. These findings highlight the context-dependency of motivational processes and suggest that variations may stem from the situated nature of learning environments and how constructs are operationalized. The results also emphasize the need to tailor interventions to specific learning contexts and caution against generalizing from single studies. Overall, our study underscores the situated nature of expectancy-value frameworks and the importance of multistudy syntheses in understanding their role in professional education.

Students with and without migration backgrounds differ in terms of their achievement. One approach to reducing the gap between the two groups may be through equal participation in classroom discourse. Here, supportive teaching behavior can be particularly important for promoting student participation. Especially teacher support after a student has made a mistake, the so-called error culture in the classroom, could pave the way for students to become active participants. In this study, we analyzed whether error culture as a facet of teacher support could be a promising key to engaging students with and without migration backgrounds. To investigate the generalizability of the process across different subjects, we examined video data from 20 eighth-grade classrooms of academic-track secondary schools in both German Language Arts and Mathematics (N = 387 students). The results from nested hierarchical linear models indicate that error culture is related to student participation in German Language Arts but not in Mathematics. Interestingly, students with and without migration backgrounds did not differ in terms of their participation in classroom discourse. Furthermore, teachers’ positive error culture supported students’ participation irrespective of their migration background. Therefore, we encourage teachers to continue to pay attention to their error culture as this seems relevant for all students in the classroom.

As digitalization progresses and technologies advance rapidly, digital simulations offer great potential for learning professional practices in contexts such as medical or teacher higher education. The technological advancements increasingly facilitate the personalization of learning support to meet the individual needs of learners, whose diverse prerequisites influence their learning processes, activities, and outcomes. However, systematic approaches to combining technologies with educational theories and evidence are scarce. In this article, we propose to use data on relevant learning prerequisites and learning processes as a basis for personalizing feedback and scaffolding to facilitate learning with simulated practice representations. We connect theoretical concepts with methodological and technical approaches (e.g., using artificial intelligence) for modeling important learner variables as a basis for personalized learning support. The interplay between the learner and the simulation environment is outlined in a conceptual framework which may guide systematic research on personalized learning support in digital simulations. Educational relevance statement This paper introduces a conceptual framework, which aims to advance personalized simulation-based learning in higher education. Digital simulations can provide tailored learning experiences that adapt to students' individual differences and needs, using artificial intelligence and other technological advances. This approach might have the potential to transform learning in higher education by increasing student engagement and the effectiveness of learning professional knowledge and skills. The framework is discussed along five central questions of personalized learning, which may guide systematic research on how simulations can accommodate learners' diverse prerequisites and processes. In doing so, the framework provides a starting point for interdisciplinary research collaborations aimed at developing design principles for personalized simulation-based learning in higher

Teacher-student relationships (TSRs) play a vital role in establishing a positive school climate and promoting positive student outcomes. Several meta-analyses have suggested significant associations between TSRs and, for example, academic achievement, a lack of disruptive behavior, school engagement, peer relationships, motivation, executive functions, and general well-being. However, these meta-analyses have differed substantially in TSR-outcome relationships, moderators, and quality, thus complicating the interpretation of these findings. In this preregistered systematic review of meta-analyses plus original second-order meta-analyses (SOMAs), we aimed to (a) synthesize the meta-analytic evidence on relationships between TSRs and student outcomes, (b) map influential moderators of these relationships, and (c) assess the methodological quality of the meta-analyses. We synthesized over 70 years of educational research in 24 meta-analyses encompassing a total of 116 effect sizes based on more than 2 million prekindergarten and K-12 students. We conducted several three-level SOMAs and found that TSRs had similar strong significant relationships with eight clusters of outcomes: academic achievement, academic emotions, appropriate student behavior, behavior problems, executive functions and self-control, motivation, school belonging and engagement, and student well-being. Age, gender, and informant (student-, peer-, or teacher-assessments) were the most frequently examined moderators in prior research, and our moderator analyses suggested student grade level and social minority status as moderators. We further found large differences in quality between the meta-analyses, and these differences were not associated with the TSR-outcome relationships. These results map the field of TSR research; present their relationships, moderators, and meta-analytic quality; and show how TSRs can contribute to improving outcomes in students via relationship building. Future research should follow meta-analytic open science procedures to improve quality and reproducibility.

Student outcomes are of central importance in teaching effectiveness research (TER) because they serve as the criterion for inferences on teaching. This paper, using a systematic literature review, examines how carefully researchers conceptualize and operationalize student outcomes in the field of TER by analysing (a) the choice of outcomes, (b) the development of outcome measures, and (c) the existing evidence for the quality of outcome measures (reliability and validity) in TER studies. The results indicate a lack of explications of the theoretical grounding and a lack of validity evidence in many TER publications. This questions the interpretability of prior findings on the effects of teaching on learning. Approaches to addressing these issues in future studies are mapped out.

: Emotional intelligence (EI) training is increasingly relevant for students as a vulnerable group prone to stress, anxiety, and depression. The diversity of models upon which the trainings are based, the content of the featured units, and the broad spectrum of existing measures call for systematization and providing a landscape of existing training. We conducted a research synthesis in databases such as Web of Science, Scopus, ERIC, Educational Source, and APA PsychArticles and included 49 (quasi-) experimental studies in the systematic review and 39 in the meta-analysis. The findings indicate the need for more theoretically grounded EI training programs for university students, the scarcity of ability-based measures, and the need for better alignment between models, content, and measures. Future research could move in the direction of setting quality benchmarks for EI training and investigating which kinds of models and content are more appropriate for specific population groups.

Digital media-related teacher professionalization is critical in integrating digital technologies into 21st century classrooms. However, in this rapidly growing area of research, teacher educators, policy administrators, and researchers find it challenging to identify and apply evidence to solve educational problems and to discern research gaps. To provide a systematic review of the current state of research, we mapped and categorized existing research syntheses on digital media in teacher professional development (PD). We systematically searched, screened, and extracted data from 38 research syntheses published in academic peer-reviewed journals between 2004 and 2024. We found a variety of characteristics of PD, with nine research syntheses investigating digital media as content, 25 as format, and four as content and format. Methodologically, the research syntheses were quite similar, as they mostly qualitatively analyzed and identified categories to cluster the primary studies. Meta-analyses that assessed the effectiveness were found to be mostly lacking.

Social media has become an integral part of the lives of young people, who, despite being regarded as digital natives, lack essential skills in terms of the reflective use of data, thus underscoring the potential of computing education to empower their data literacy. To this end, this paper presents InstaClone, an innovative educational tool for classrooms that allows students to engage with social media platforms within a secure learning environment. With an appearance and functionality resembling Instagram, InstaClone offers a lifelike learning environment in which students can generate data, which are then processed and visualized on integrated data analytics dashboards, facilitating the development of individual data literacy. A case study with year 9 and year 10 students in a K-12 computer science class demonstrated that InstaClone convincingly emulates the real platform and that students benefit from using the tool by developing a deeper understanding of the data collected by social media platforms and the underlying algorithms.

Contrary to theoretical assumptions, only weak relationships have emerged between feedback and reading literacy in non-experimental settings. Our study contributes to a better understanding of those weak relationships by shedding light on generalizability across specific student groups (different competence levels, multilingual learners) and contexts (countries). Using a meta-analytic approach, we analyzed the PISA 2018 dataset with data from 505,906 students from 75 countries. Our results indicate a weak overall relationship between feedback and reading literacy, an uneven distribution of feedback across competence levels, and heterogeneity across countries. In contrast, multilingual learners do not profit differently from feedback compared to their monolingual peers. Future research should focus on the mechanisms behind these differences.

A high level of teacher self-efficacy is considered to be important for a successful and healthy teaching career. This preregistered meta-analysis focuses on whether and to what degree interventions can promote teacher self-efficacy. We included 115 studies representing 11,284 pre-service and in-service teachers in our meta-analysis. Interventions had a significant, positive effect on the promotion of teachers' self-efficacy (g = 0.47, RVE SE = 0.04, 95% CI = [0.40, 0.54]) with no significant differences between pre- and in-service teachers. A fine-grained coding and systematic review of the targeted sources of self-efficacy according to Bandura's sociocognitive theory revealed that overall interventions including mastery experiences did not significantly differ from those without. However, interventions targeting only mastery experiences were the most successful for pre-service teachers (g = 0.62, RVE SE = 0.11, CI = [0.35, 0.88]). Based on further moderator analyses, we recommend interventions to integrate reflective elements. Finally, future research should apply stricter study designs and more detailed intervention descriptions.

Twitter has evolved from its initial purpose as a microblogging social network to a pivotal platform for science communication. Equally, it has gained significant popularity among teachers who utilize communities like the German #twitterlehrerzimmer (TWLZ; Twitter teachers’ lounge) as a digital professional learning network. (1) Background: To date, no studies examine how science communication is conducted on Twitter specifically tailored to teachers’ needs and whether this facilitates evidence-based teaching. (2) Methods: Answering the three research questions involved a comprehensive mixed methods approach comprising an online teacher survey, utility analysis using Analytical Hierarchy Process (AHP) models, and machine learning-assisted tweet analyses. (3) Results: Teachers implement research findings from the TWLZ in their teaching about twice a month. They prefer interactive tweets with specific content-related, communicative, and interactive tweet features. Science communication in the TWLZ differs from everyday communication but notably emphasizes the relevance of transfer events for educational practice. (4) Conclusions: Findings highlight that dialogue is essential for successful science communication. Practical implications arise from new guidelines on how research findings should be communicated and encourage teachers to reflect on their Twitter usage and attitude toward evidence-based teaching. Recommendations for further research in this emerging field are also discussed.

This meta-analysis builds on and extends Chernikova, Heitzmann, Stadler, et al.'s (2020) meta-analysis on simulation-based learning in higher education by summarizing the findings of 214 empirical studies. The main focus of the current meta-analysis was to investigate the role of prior knowledge and design features, namely (1) the authenticity of simulated scenarios (as both functional correspondence with a real task and a physical resemblance of the environment) and (2) the salience of relevant information in moderating the effects of simulation-based learning on facilitating complex skills in higher education. The analysis identified that the salience of relevant information contributes significantly to explaining the variation in the effectiveness of simulation-based learning environments. We conclude that authenticity and salience can be assessed independently of each other, and both can be considered important design features in creating effective simulation-based learning environments to meet the needs of learners with different levels of prior knowledge.

Simulation-based learning is being increasingly implemented across different domains of higher education to facilitate essential skills and competences (e.g. diagnostic skills, problem-solving, etc.). However, the lack of research that assesses and compares simulations used in different contexts (e.g., from design perspective) makes it challenging to effectively transfer good practices or establish guidelines for effective simulations across different domains. This study suggests some initial steps to address this issue by investigating the relations between learners' experience in simulation-based learning environments and learners' diagnostic accuracy across several different domains and types of simulations, with the goal of facilitating cross-domain research and generalizability. The findings demonstrate that used learners' experience ratings are correlated with objective performance measures, and can be used for meaningful comparisons across different domains. Measures of perceived extraneous cognitive load were found to be specific to the simulation and situation, while perceived involvement and authenticity were not. Further, the negative correlation between perceived extraneous cognitive load and perceived authenticity was more pronounced in interaction-based simulations. These results provide supporting evidence for theoretical models that highlight the connection between learners' experience in simulated learning environments and their performance. Overall, this research contributes to the understanding of the relationship between learners’ experience in simulation-based learning environments and their diagnostic accuracy, paving the way for the dissemination of best practices across different domains within higher education.

The term evidence-based practice has gained importance in teacher education as well as in everyday school life. Calls from policymakers, academics, and society have become increasingly apparent that teachers’ professional actions should not exclusively be based on subjective experiential knowledge but also on empirical evidence from research studies. However, the use of evidence comes along with several challenges for teachers such as often lacking applicability of available sources or limited time resources. This case study explores how teachers (n = 12) at secondary schools think about the relevance and usage of evidence-based information in practice as well as the barriers associated with it. As we see a particular need for evidence-based teaching in STEM disciplines, we focus on these subjects. A thematic analysis of the data indicates that the teachers generally rate relevance highly, for instance seeing opportunities for support and guidance. However, the actual use of evidence-based information in the classroom is rather low. The teachers most frequently mentioned the feasibility of implementation in class as a quality indicator of evidence-based information. Based on the data, we discuss possible conclusions to promote evidence-based practice at schools. Furthermore, the study opens up directions for further research studies with representative teacher samples in various disciplines.