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Artificial Intelligence in Physics Learning and Assessment (AIPLA)
AIPLA investigates how generative AI can be meaningfully integrated into upper secondary physics education, both in teaching and assessment.
The project focuses on how AI can support students’ learning processes and teachers’ didactic practices, while incorporating the specific demands of physics, including conceptual understanding, mathematical problem-solving, and working with multiple forms of representation.
The project develops and tests teaching activities and tasks in which AI cannot simply “do everything”, but can support students in their work with, for example, exam questions, experiments, conceptual exploration, and presentations. AIPLA is conducted in close collaboration with Danish physics teachers and Danish Science High Schools (Danske Science Gymnasier). The aim is both to contribute to research and to develop practice-oriented resources that can be used widely in upper secondary education. The project is supported by the Novo Nordisk Foundation.
This project investigates how generative AI (GAI) can be integrated into upper secondary physics education, with a focus on both teaching and assessment. The aim is to explore how GAI can serve as a supportive tool for students’ learning processes and teachers’ teaching practices. The project thus seeks to identify productive ways of working with GAI that take into account the specific demands of physics as a subject.
In both Danish and international contexts, very few publications have reported on the integration of GAI in the physics classroom. Through close contact with physics teachers, the project leader has found that many teachers are hesitant and, at times, even reluctant to use GAI in their teaching. With this project, we aim to explore new perspectives by investigating how and when appropriate use of GAI can support teachers and students in the teaching and learning of physics.
Although studies have investigated what generative AI can and cannot do when solving physics problems, there is limited knowledge about how these technologies can be integrated into teaching practices in ways that support student learning, promote engagement, and enable both formative and summative assessment. This project addresses these opportunities and challenges by pursuing the following objectives:
- Explore the types of physics tasks that GAI cannot fully solve but can assist students in answering.
- Investigate how such tasks can be implemented in physics teaching, learning, and assessment practices.
- Investigate how students’ skills in and attitudes towards physics develop when they work with GAI-supported tasks.
- Collaborate with teachers to implement GAI-supported teaching and learning activities, as well as assessment practices, in the physics classroom.
We argue that these four aspects are central to developing sound pedagogical practices for the use of GAI in physics education and, to the best of our knowledge, this has not previously been done systematically.
AIPLA will use the ADDIE development model (Analysis, Design, Development, Implementation, and Evaluation) to help ensure that the project’s outcomes have a meaningful impact on practitioners/physics teachers and other relevant stakeholders.
- Analysis: At the beginning of the project, upper secondary physics teachers will be recruited to share their experiences of using GAI in their teaching. Their insights will be gathered to inform the design of GAI-integrated teaching and learning activities.
- Design: Data from the analysis phase will be reviewed and used to design physics tasks and assessments that integrate AI. This will involve ongoing dialogue with teachers.
- Development: We will develop physics tasks, activities, experiments, and teaching strategies that integrate AI. The materials will be designed to incorporate GAI as a meaningful contributor to the learning experience.
- Implementation and Evaluation: These stages will form an iterative process, providing a comprehensive approach to ensuring that the integration of GAI leads to positive outcomes for physics education. They also aim to strengthen collaboration among physics teachers in order to increase the project’s impact.
Supported by
AIPLA has received three-year funding from the Novo Nordisk Foundation.
Project: Artificial Intelligence in Physics Learning and Assessment
Period: 2026 to 2028
Contact
Researchers/group members
Internal
| Name | Title | Job responsibilities | |
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| Search in Name | Search in Title | Search in Job responsibilities | |
| Jesper Bruun | Associate Professor |
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| Mark Peter Edmondson | Research Assistant |
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| Muhammad Aswin Rangkuti | Postdoc |
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| Sofie Christine Poulsen | Student |
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