Report on the Scoping Workshop on AI in Science Education Research 2025
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arXiv
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| Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866914189880066048 |
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| author | Kubsch, Marcus Kastaun, Marit Wulff, Peter Graulich, Nicole Ariely, Moriah Bergmann-Gering, Alexander Gombert, Sebastian Gregorcic, Bor Härtig, Hendrik Heuckmann, Benedikt Horbach, Andrea Krist, Christina Kortemeyer, Gerd Münch, Ben Pazicni, Samuel Rosenberg, Joshua M. Schanze, Sascha Sbeglia, Gena Skogvoll, Vidar Speroni, Christophe Thyssen, Christoph Thoms, Lars-Jochen Yik, Brandon J. Zhai, Xiaoming |
| author_facet | Kubsch, Marcus Kastaun, Marit Wulff, Peter Graulich, Nicole Ariely, Moriah Bergmann-Gering, Alexander Gombert, Sebastian Gregorcic, Bor Härtig, Hendrik Heuckmann, Benedikt Horbach, Andrea Krist, Christina Kortemeyer, Gerd Münch, Ben Pazicni, Samuel Rosenberg, Joshua M. Schanze, Sascha Sbeglia, Gena Skogvoll, Vidar Speroni, Christophe Thyssen, Christoph Thoms, Lars-Jochen Yik, Brandon J. Zhai, Xiaoming |
| contents | This report summarizes the outcomes of a two-day international scoping workshop on the role of artificial intelligence (AI) in science education research. As AI rapidly reshapes scientific practice, classroom learning, and research methods, the field faces both new opportunities and significant challenges. The report clarifies key AI concepts to reduce ambiguity and reviews evidence of how AI influences scientific work, teaching practices, and disciplinary learning. It identifies how AI intersects with major areas of science education research, including curriculum development, assessment, epistemic cognition, inclusion, and teacher professional development, highlighting cases where AI can support human reasoning and cases where it may introduce risks to equity or validity. The report also examines how AI is transforming methodological approaches across quantitative, qualitative, ethnographic, and design-based traditions, giving rise to hybrid forms of analysis that combine human and computational strengths. To guide responsible integration, a systems-thinking heuristic is introduced that helps researchers consider stakeholder needs, potential risks, and ethical constraints. The report concludes with actionable recommendations for training, infrastructure, and standards, along with guidance for funders, policymakers, professional organizations, and academic departments. The goal is to support principled and methodologically sound use of AI in science education research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_14318 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Report on the Scoping Workshop on AI in Science Education Research 2025 Kubsch, Marcus Kastaun, Marit Wulff, Peter Graulich, Nicole Ariely, Moriah Bergmann-Gering, Alexander Gombert, Sebastian Gregorcic, Bor Härtig, Hendrik Heuckmann, Benedikt Horbach, Andrea Krist, Christina Kortemeyer, Gerd Münch, Ben Pazicni, Samuel Rosenberg, Joshua M. Schanze, Sascha Sbeglia, Gena Skogvoll, Vidar Speroni, Christophe Thyssen, Christoph Thoms, Lars-Jochen Yik, Brandon J. Zhai, Xiaoming Physics Education Computers and Society This report summarizes the outcomes of a two-day international scoping workshop on the role of artificial intelligence (AI) in science education research. As AI rapidly reshapes scientific practice, classroom learning, and research methods, the field faces both new opportunities and significant challenges. The report clarifies key AI concepts to reduce ambiguity and reviews evidence of how AI influences scientific work, teaching practices, and disciplinary learning. It identifies how AI intersects with major areas of science education research, including curriculum development, assessment, epistemic cognition, inclusion, and teacher professional development, highlighting cases where AI can support human reasoning and cases where it may introduce risks to equity or validity. The report also examines how AI is transforming methodological approaches across quantitative, qualitative, ethnographic, and design-based traditions, giving rise to hybrid forms of analysis that combine human and computational strengths. To guide responsible integration, a systems-thinking heuristic is introduced that helps researchers consider stakeholder needs, potential risks, and ethical constraints. The report concludes with actionable recommendations for training, infrastructure, and standards, along with guidance for funders, policymakers, professional organizations, and academic departments. The goal is to support principled and methodologically sound use of AI in science education research. |
| title | Report on the Scoping Workshop on AI in Science Education Research 2025 |
| topic | Physics Education Computers and Society |
| url | https://arxiv.org/abs/2511.14318 |