Publikationen

A second-order meta-analysis of interventions and their effectiveness in STEMM education: Effects on motivational, affective, and attitudinal outcomes

Abstract
Background: The STEMM sector is increasingly vital, with a growing demand for skilled professionals. Beyond cognitive skills, non-cognitive factors such as motivation, affect, and attitudes have a significant influence on STEMM performance and aspirations. To gain an overview of the field of research, a second-order meta-analysis was conducted on the effectiveness of interventions on non-cognitive outcomes in STEMM education. A systematic search (2000–2023) identified 6664 review studies, from which 42 meta-analyses containing 64 meta-analytic effect sizes were included. These encompassed 1903 primary studies, covering both K-12 and higher education contexts. The interventions were categorized by the targeted outcome, intervention method, and targeted STEMM discipline.

Results: Mathematics was the most frequently studied subject, and common interventions included applications of educational technology and student-centered instruction. The most studied outcomes were attitudes towards STEMM and affective factors, such as mathematics anxiety and satisfaction. Overall, interventions showed a significant positive effect on non-cognitive outcomes (d = 0.42, 95% CI [0.35, 0.50], p < .001), indicating improved motivation, attitudes, or reduced anxiety toward STEMM. Effectiveness did not differ significantly across outcome types or intervention methods, although mathematics and general STEM studies showed slightly smaller effects. We also found substantial variability in the meta-analytic effects. Notably, gaps in the literature were identified. Affective states such as boredom and enjoyment were rarely addressed, and out-of-school contexts were underrepresented.

Conclusion: This highlights the need for more comprehensive and diverse meta-analyses. Nonetheless, student-centered teaching, games, and technology-based methods appear promising for enhancing non-cognitive outcomes in STEMM education.

Heller, F., Popp, C., Ziegler, A., & Stoeger, H. (2026). A second-order meta-analysis of interventions and their effectiveness in STEMM education: Effects on motivational, affective, and attitudinal outcomes. International Journal of STEM Education, 13, 26. https://doi.org/10.1186/s40594-026-00619-w

Designing Resilient STEM Trajectories: An Ecological Framework for Sustained Participation 

Abstract
STEM learning unfolds over many years. It is shaped by changing contexts, transitions, and occasional breaks. However, much of the existing work still focuses on single stages or isolated factors. This article introduces the E3 Framework. Its purpose is to provide a language for examining why some STEM trajectories endure, why others fade, and what kinds of ecological alignment allow learning to remain viable in the flow of real life. Based on a systemic approach, we aim to explain how STEM participation is preserved over time. This framework describes stability as the result of interactions among three ecological domains: resources, regulation, and time. We identify five key functions—robustness, regulatory re-alignment, renewal, informational persistence, and environmental fit. These functions show how engagement holds steady or recovers as circumstances shift. The E3 Framework offers a way to analyze how supports, feedback loops, and time-related structures either come together or fall apart. We provide simple design guidelines and matrices to show how educators and policymakers can better support STEM trajectories. 

Ziegler, A., & Stoeger, H. (2026). Designing Resilient STEM Trajectoris: An Ecological Framework for Sustained Participation. Education Sciences, 16(5), 790. https://doi.org/10.3390/educsci16050790 

From RAMSing to Rigor: Improving Moderator Analysis in STEM Education Meta-Research

Abstract
Moderators are intended to clarify when, where, and for whom interventions work, yet null moderator results are often omitted from the published record. We term this practice “reporting after moderators are significant” (RAMSing) and examine its scope and consequences in STEM education meta-research. Drawing on an umbrella review of 89 meta-analyses comprising 1,786 moderator effect sizes, we found a substantial visibility gap: non-significant moderator effect sizes showed markedly lower relative visibility than the most strongly selected results (ω ~ 0.40). To address this bias, we combined structural mapping with two bias-robust Bayesian frameworks, RoBMA-PSMA and RoBMA-Regression, to estimate bias-adjusted moderator effects, derive field-specific benchmarks, and estimate realistic evidential requirements for moderator testing. The overall bias-adjusted mean moderator effect was g = 0.27 (95% CrI [0.20, 0.34]) with substantial heterogeneity (τ = 0.48). Modeling a five-level moderator-theme classification substantially improved fit (BFInc = 350) and slightly reduced residual heterogeneity (τ = 0.44). RAMSing-adjusted benchmarks placed the 25th, 50th, and 75th percentiles of |g| at 0.18, 0.38, and 0.64, respectively, all below both Cohen’s conventional heuristics and the raw empirical quartiles. Prospective power analyses further indicated that, under the assumptions examined here (g = 0.38, τ = 0.24, α = 0.05), approximately 14 independent effect sizes per moderator level are needed to detect a typical moderator effect. These findings indicate that RAMSing is likely an important source of distortion in moderator-based inference within this corpus. The workflow and openly available toolkit introduced here provide a practical framework for detecting and bias-adjusting RAMSing, and for supporting practices designed to reduce it in STEM education and other fields that rely on meta-analytic moderator evidence.  

Bicakci, M., Heller, F., Stoeger, H., & Ziegler, A. (2026). From RAMSing to Rigor: Improving Moderator Analysis in STEM Education Meta-Research. Educational Psychology Review, 38, Article 75. https://doi.org/10.1007/s10648-026-10172-1 

Mapping Collaborations in STEM Education: A Scoping Review and Typology of In-School–Out-of-School Partnerships 

Abstract
In-school–out-of-school collaborations are increasingly recognized as a key mechanism for enriching STEM education. Guided by conceptual frameworks on boundary crossing and STEM learning ecologies, this scoping review maps and synthesizes findings from 470 studies and 469 programs published between 2014 and 2024, focusing on how such partnerships are reported, structured, and distributed across educational contexts. Approximately 73% of the programs reported some form of collaboration, although often in general terms. The most common forms included shared infrastructure, recruitment coordination, and personnel involvement. More pedagogically grounded forms, such as curricular alignment and co-development of instruction, were rarely described. Collaboration patterns varied across program types, durations, subject areas, and participant target groups. A typology of seven collaboration categories was developed to organize the findings. Notable gaps include the near-total absence of collaboration in medicine-related programs and the underrepresentation of research from low- and middle-income countries. Although collaboration is frequently mentioned, it is seldom described in enough detail to support systematic analysis or theoretical insight. The review recommends more precise definitions, stronger reporting practices, and enhanced theoretical engagement with collaboration as a pedagogical and systemic component of STEM education. The proposed typology provides a foundation for more coherent future research and comparative studies.

Ziegler, A., Shiani, M., Wengler, D., & Stoeger, H. (2025). Mapping Collaborations in STEM Education: A Scoping Review and Typology of In-School–Out-of-School Partnerships. Education Sciences, 15(11), 1513. https://doi.org/10.3390/educsci15111513 

Robust and semi-robust findings from giftedness and talent research: Results of a secondary-order scoping review on meta-analyses

Abstract
In this second-order scoping review—that is, a broad overview of research on a particular topic, identifying key concepts and evidence gaps—we (a) provide an overview of robust (and semi-robust) findings in giftedness and talent research and (b) identify areas where giftedness and talent research has not yet produced robust (and semi-robust) findings. Of the 23 meta-analyses published between 2000 and 2023 that were identified using our search terms, 17 were categorized as robust and six as semi-robust. The most frequently considered outcome variables were achievement, cognitive processing, socioemotional factors, traits, and identification. Further topics included interventions’ effects and group differences, particularly regarding groups underrepresented in gifted education. The findings are summarized in a condensed list. The lack of standard definitions and operationalizations of crucial terms is particularly critical. We suggest that further meta-research should be used to identify robust findings on giftedness.

Popp, C., Stoeger, H., & Ziegler, A. (2025). Robust and semi-robust findings from giftedness and talent research: Results of a secondary-order scoping review on meta-analyses. Journal for the Education of the Gifted, 01623532251372590. https://doi.org/10.1177/01623532251372590

Attracting and developing STEMM talent toward excellence and innovation

Abstract
This article provides an overview of science, technology, engineering, mathematics, and medical sciences (STEMM) talent development from first exposure to a STEMM domain to achieving eminence and innovation. To this end, a resource-oriented model of STEMM talent development is proposed as a framework. It includes a three-stage phase model based on Bloom (1985), with the main focus on interest development in the first stage, skill acquisition toward expertise and excellence in the second stage, and style formation toward eminence and innovation in the final stage. A literature review shows that from an educational perspective, each phase is mainly characterized by the focus that Bloom postulated. However, it is important that all three stages (i.e., interest development, skill acquisition, and style formation) occur in a stage-typical manner. To explain how these primary objectives of STEMM development can be supported through STEMM talent education, Ziegler and Stoeger's (2011) educational and learning capital framework is used in the proposed resource-based model. A literature review shows that consistent provisioning of the resources specified in the model is necessary for individuals to complete a learning pathway to STEMM eminence and innovation.

Stoeger, H., Luo, L., & Ziegler, A. (2024). Attracting and developing STEMM talent toward excellence and innovation. Annals of the New York Academy of Sciences, 1533(1), 89-98. https://doi.org/10.1111/nyas.15108

Talent denied: Equity and excellence gaps in STEMM

Abstract
In principle, there could be STEMM talent everywhere if there were sufficient and adequate opportunities and learning resources everywhere. The reality, however, is that the likelihood of developing one’s talent in STEMM is tied to membership in social groups. In this contribution, we explore the implications of this statement with multiple examples for different social groups and for different stages of talent development. We propose an educational framework model for analyzing equity gaps in STEMM talent development that identifies and systematizes the unequal and inequitable distribution of resources and opportunities as the proximal cause of the emergence of such equity gaps. Furthermore, we discuss important aspects for closing equity gaps in STEMM talent development. We argue that — similar to public health approaches — the focus in establishing equity in STEMM talent development should be on prevention rather than intervention. We discuss the importance of the cooperation of societal subsystems and argue for the use of adequate methods of disparity detection for creating equal opportunities. We also outline why preventive strategies are crucial for the creation of ressource parity and explain why outcome standards should be considered obligatory.

Ziegler, A., & Stoeger, H. (2023). Talent denied: Equity and excellence gaps in STEMM. Annals of the New York Academy of Sciences, 1530(1), 32-45. https://doi.org/10.1111/nyas.15083