Pure Question-Based Learning (pQBL) with AI-generated learning objectives and activities
The project involves fusing pQBL, an efficient and effective learning technique, together with emerging generative AI capabilities to further reduce time and effort on the teachers, whilst increasing the quality of learning for students.
Project context
Question-Based Learning (QBL) promotes active learning and has been shown to be six times more effective than reading or watching videos. The major drawback is that developing this type of effective interactive learning material is resource-intensive. At EECS, we have further developed this methodology into pure Question-Based Learning (pQBL), which offers several major advantages – one of which is that we can use generative AI to support the creation of learning materials.
Whilst generative AI has been shown to be very capable of producing questions on demand via a given chat interface, it lacks the integration with our learning management systems, such as Canvas Quizzes. Teachers could manually copy and paste questions into these systems, but this is not a sustainable solution.
Thus, the first challenge is to help manage the bulk creation of questions that align well with learning objectives and course material, allow the teachers ample opportunity to review them, then automatically deploy them into a quiz system.
The second challenge is the difficulty for teachers to pre-screen questions for accuracy, quality, and suitability: teachers would need finer degrees of control in terms of difficulty and of how well the learning material meets their quality expectations.
Purpose (outcome)
The project purpose is to:
- relieve teachers while students gain access to more effective learning resources. The target effect is to reduce teachers' least appreciated teaching tasks while improving student learning. This could potentially lead to less time required (scheduled and general) for all involved.
- provide the school with an improved and system-supported method for improving course quality (learning analytics).
Project results (output)
- System and method for generating and distributing learning material in the form of pure Question-Based Learning in Torus for five courses, along with evaluations of teachers’ and students’ experiences with the material.
- Method and system interface for integrating data from learning analyses (how effective questions are) and teachers' individual perspectives (how difficult questions are).
Time plan
Start date: 2024-05-15
End date: 2026-06-30
Project documentation
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- Poster: Poster_FrU25_2415-EECS_pBQL_250520.pdf
- Project initiation document: Projektdirektiv_FrU25_2415-EECS_pQBL_250510.pdf (Swedish)