Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor EACEA can be held responsible for them. Project number: 2023-1-NL01-KA220-HED-000155675. system, expanding its capabilities to include additional and wearable cameras and conducting real-time testing in classroom settings. Case Study 2: Student action recognition for improving teacher feedback during tele-education General information Dimitriadou, E., & Lanitis, A. (2024). Student action recognition for improving teacher feedback during tele-education. IEEE Transactions on Learning Technologies, 17, 569–584. https://doi.org/10.1109/tlt.2023.3301094 The aim of the research was to develop and evaluate a student action recognition system, reviewing students' behaviour participation and disaffection, intended to support teacher feedback during distance education. This system was designed to monitor student actions in online courses while protecting student privacy and providing real-time feedback to educators about student engagement without direct visual contact. Description of case An AI system was developed to recognise specific student actions using deep neural network architectures like GoogleNet, Inception-v3, and Faster R-CNN. The system used videos of student actions, processed locally on student devices, to train these networks. The effectiveness of the system was assessed through a comprehensive user evaluation involving students, parents, and educators, who provided feedback via online questionnaires and interviews. Lessons learned The results indicated that the system was effective in recognising student actions and was well-received by all stakeholders. Educators, in particular, found it useful for improving interaction and engagement in online settings. The system was well accepted due to the personal data protection measures applied. Implications for practice The AI system could enhance the effectiveness of online learning and distance education by providing insights into student behaviour, thus facilitating better educational outcomes.
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