Welcome to FLoRA
About FLoRA
FLoRA is a research project aimed at facilitating self-regulation in learning. "Learning to learn" – the ability to monitor and adapt one's learning process productively – is a key competence formulated by the European Parliament (2006) and increasingly a central focus of education. Prior research has shown that self-regulated learning (SRL) leads to better learning performance.
This research collaboration aims to enhance the support provided to students by: i) improving unobtrusive trace data collection and machine learning techniques to gain a better understanding and measurement of SRL processes, and ii) using these new insights to facilitate students' SRL by providing personalized support empowered by large language models (LLMs) such as ChatGPT.
FLoRA has been applied to many learning settings, including reflective writing tasks, academic writing studies, and role-play scenarios using LLMs to support apprenticeship training.
This research collaboration aims to enhance the support provided to students by: i) improving unobtrusive trace data collection and machine learning techniques to gain a better understanding and measurement of SRL processes, and ii) using these new insights to facilitate students' SRL by providing personalized support empowered by large language models (LLMs) such as ChatGPT.
FLoRA has been applied to many learning settings, including reflective writing tasks, academic writing studies, and role-play scenarios using LLMs to support apprenticeship training.
If you would like to gain hands-on experience with the FLoRA platform, please contact us.
About CELLA
In 2022, the Jacobs Foundation has granted CHF 2 million to Professors Sanna Järvelä and Inge Molenaar to establish the Center for Learning and Living with AI (CELLA) at the University of Oulu, Finland, and Radboud University, Netherlands. CELLA aims to prepare young learners for the AI age by collaborating with secondary schools and EdTech entrepreneurs worldwide to develop intelligent learning technologies, such as adaptive systems and VR/AR-based game learning. The center will also work with the University of California Irvine's CERES research facility to promote evidence-based technology use in education.
Recent Publications
Fan, Y., Rakovic, M., van Der Graaf, J., Lim, L., Singh, S., Moore, J., Molenaar, I., Bannert, M. & Gašević, D. (2023). Towards a fuller picture: Triangulation and integration of the measurement of self‐regulated learning based on trace and think aloud data. Journal of Computer Assisted Learning. https://doi.org/10.1111/jcal.12801
Li, T., Fan, Y., Srivastava, N., Zeng, Z., Li, X., Khosravi, H., ... & Gašević, D. (2024, March). Analytics of Planning Behaviours in Self-Regulated Learning: Links with Strategy Use and Prior Knowledge. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 438-449). https://doi.org/10.1145/3636555.3636900
Li, T., Fan, Y., Tan, Y., Wang, Y., Singh, S., Li, X., Raković, M., Lim, L., Yang, B., Molenaar, I., Bannert, M., Moore, J., Swiecki, Z., Tsai, Y., Shaffer, D. W., & Gašević, D. (2023). Analytics of self-regulated learning scaffolding: Effects on learning processes. Frontiers in Psychology, 14, 1206696. DOI:10.3389/fpsyg.2023.1206696
Lim, L., Bannert, M., van der Graaf, J., Singh, S., Fan, Y., Surendrannair, S., Raković, M., Molenaar, I., Moore, J. , Gašević, D. (2023). Effects of real-time analytics-based personalized scaffolds on students’ self-regulated learning. Computers in Human Behavior, 139, 107547. doi:10.1016/j.chb.2022.107547
Saint, J., Fan, Y., & Gasevic, D. (2024, March). Analytics of scaffold compliance for self-regulated learning. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 326-337). https://doi.org/10.1145/3636555.3636887
van der Graaf, J., Taub, M. & Fan, Y. Introduction to special issue on facilitating self-regulated learning with scaffolds: Recent advances and future directions. Metacognition Learning (2023). https://doi.org/10.1007/s11409-023-09364-9
van der Graaf, J., Raković, M., Fan, Y., Lim, L., Singh, S., Bannert, M., Gašević, D., & Molenaar, I. (2023). How to design and evaluate personalized scaffolds for self-regulated learning. Metacognition and Learning. DOI:10.1007/s11409-023-09361-y
Li, T., Fan, Y., Srivastava, N., Zeng, Z., Li, X., Khosravi, H., ... & Gašević, D. (2024, March). Analytics of Planning Behaviours in Self-Regulated Learning: Links with Strategy Use and Prior Knowledge. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 438-449). https://doi.org/10.1145/3636555.3636900
Li, T., Fan, Y., Tan, Y., Wang, Y., Singh, S., Li, X., Raković, M., Lim, L., Yang, B., Molenaar, I., Bannert, M., Moore, J., Swiecki, Z., Tsai, Y., Shaffer, D. W., & Gašević, D. (2023). Analytics of self-regulated learning scaffolding: Effects on learning processes. Frontiers in Psychology, 14, 1206696. DOI:10.3389/fpsyg.2023.1206696
Lim, L., Bannert, M., van der Graaf, J., Singh, S., Fan, Y., Surendrannair, S., Raković, M., Molenaar, I., Moore, J. , Gašević, D. (2023). Effects of real-time analytics-based personalized scaffolds on students’ self-regulated learning. Computers in Human Behavior, 139, 107547. doi:10.1016/j.chb.2022.107547
Saint, J., Fan, Y., & Gasevic, D. (2024, March). Analytics of scaffold compliance for self-regulated learning. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 326-337). https://doi.org/10.1145/3636555.3636887
van der Graaf, J., Taub, M. & Fan, Y. Introduction to special issue on facilitating self-regulated learning with scaffolds: Recent advances and future directions. Metacognition Learning (2023). https://doi.org/10.1007/s11409-023-09364-9
van der Graaf, J., Raković, M., Fan, Y., Lim, L., Singh, S., Bannert, M., Gašević, D., & Molenaar, I. (2023). How to design and evaluate personalized scaffolds for self-regulated learning. Metacognition and Learning. DOI:10.1007/s11409-023-09361-y
Click here to review the full publication list.
Recent Keynotes
