Cognitive Activation in Adaptive Teaching with AI-based Teaching and Learning Systems

• Applicant: Dr. Daniel Then
• Subject Area: General and Domain-Specific Teaching and Learning
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 579379340

Cognitive activation is a key quality dimension in mathematics teaching: cognitive activation processes are considered essential for encouraging students to engage in deeper learning. For this, it is important to address students’ individual learning needs and to design teaching processes in an adaptive manner. However, adaptive lesson design poses challenges for teachers. To address this, AI-based systems are considered highly important. Intelligent Tutoring Systems (ITS) are considered particularly promising as ITS may provide students with adaptive feedback during the learning process. At the same time, it has been proven that working with ITS does not necessarily initiate learning processes. The way the systems are integrated into the classroom is crucial instead. Therefore, special attention must be paid to the interactions between the teacher and the students in the classroom where cognitive activation processes can take place in. However, it is still unclear what such cognitive activation processes look like, especially in teaching with ITS. This is where the present project comes in. The aim is to identify processes for the individual cognitive activation of students in adaptive, ITS-based mathematics teaching in primary school. The focus is on processes for cognitive activation in a lesson on fraction calculation, as the acquisition of competencies for the appropriate use of fractions leads to mathematical insights that are fundamental to the further mathematical development of students. The project is exploratory in nature and uses a qualitative research design. For this, a mathematics lesson in the fourth grade of primary school is videotaped, in which the students (n=ca. 20) work individually with an ITS (bettermarks) and the teacher (n=1) accompanies this process. The focus is on cognitive activation processes that can be identified in the interactions between the teacher and the students while working with the ITS. Purposive sampling is used for the project. The sample is therefore selected in a way that specific cases are represented. Accordingly, it is intended to videotape the lesson of a teacher with expertise in cognitively activating lesson design (“best practice”). This should maximize the probability of observing a lesson that is truly cognitively activating. On this basis, it should be possible to identify how the specifics of ITS-based teaching are reflected in processes of cognitive activation. The aim is to derive insights into the way an ITS-based mathematics lesson can be arranged in a cognitively activating manner. For this, the data will be analyzed using qualitative content analysis methods. The project aims to provide insights into cognitively activating processes in a mathematics lesson with an adaptive, AI-based system (ITS). On this basis, it should be possible to derive implications for cognitively activating lesson design in lessons with ITS.

• DFG Programme: Fellowship
• International Connection: Switzerland
• Host: Professorin Dr. Anna-Katharina Praetorius