Background and Objective

While current online learning management systems often focus on cognitive skills, there is a lack of data-driven approaches for tracking learning processes and providing feedback on learning tasks that are distributed across physical and virtual spaces. This workshop brings together members of a joint international project funded by JSPS in Japan to discuss and explore innovative integration of AI and socially assistive robotics in a technical infrastructure to support learning and enhance learners’ critical reflection in the psychomotor and cognitive aspects of learning. This international collaboration proposes the miXai^learn workshop to network with researchers and practitioners participating in AIED 2025 to bridge the physical-virtual divide by integrating technologies such as socially assistive robots in the physical space and AI-driven agents in the virtual space, model learning processes, and provide feedback for reflection, both by teachers and learners. The interdisciplinary discussion would focus on the core scientific research question: How can multimodal interactions and data-informed technologies support reflective physical and virtual learning? 

Workshop timeline

Time Activity

14:00-14:10 Introduction

14:10-14:50 Keynote talk: Prof. Ivica Boticki.
Title: The Evolution of AI Use in EdTech: From Conversational Tools to the Physical World of Learning 

14:50 - 15:30 Session 1, Group activity with LA-ReflecT platform

Break

16:00 - 16:30 Session 2, Lightning Presentations (5 x 5 mins)

16:30 - 17:30 Session 3, Group activity to ideate and refine themes

17:30 - 17:50 Discussion and Synthesis

17:50 - 18:00 Wrap up

Venue: 

c/o Dipartimento di Ingegneria, Università degli Studi di Palermo, Viale delle Scienze, Edificio 8 – 90128 Palermo (PA).

Lat/Lon: 38.105247, 13.347289

Timeline leading to workshop

Submission of Participation form: May 16. Collected presenters and participants' research context and its alignment to the theme of the workshop.  

Notifications of Participation: June 16. Notification of acceptance.

Sharing themes for discussion: July 11. The program committee peer-reviewed and curated the participation form content and shared the submitted research context information in an open-access workshop website as a first step and shared topics of discussion to call different perspectives during the workshop.

Workshop Organizers

Rwitajit MAJUMDAR, Kumamoto University, Japan

Huiyong LI, Kyushu University, Japan

Brendan FLANAGAN, Kyoto University, Japan 

Shin-Ichiro KUBOTA, Kumamoto University, Japan 

Soumyadeep BHATTACHARYA, Microsoft Research

Aditi KOTHIYAL, IIT Gandhinagar, India

Prajakt PANDE, SMU Texas, USA

Olga C. SANTOS, UNED, Spain 

Irene-Angelica CHOUNTA, University of Duisburg-Essen, Germany

The co-organizers are collaborators on the miXai project.

Acknowledgments 

This workshop is partially supported by JSPS Grant-in-Aid for Joint International Research B (24KK0051).

Reference

1. Majumdar, R., Prasad, P., Kadam, K., Gatare, K., & Warriem, J. M. (2023). LA-ReflecT: A Platform Facilitating Micro-learning and Its Multimodal Learning Analytics. In European Conference on Technology Enhanced Learning (pp. 731-735). Cham: Springer Nature Switzerland.

2. Majumdar, R., Gatare, K., & Warriem, J. K. (2023b). LA-ReflecT: Multimodal Learning Analytics of Micro-learning. T4E 2023 workshop.

3. Majumdar, R., Li, H., Yang, Y., & Ogata, H. (2024). GOAL - A data-rich environment to foster self-direction skills across learning and physical contexts. Educational Technology & Society, 27(3), 61-82. https://doi.org/10.30191/ETS.202407_27(3).RP04

4. Majumdar, R., Prasad, P., & Sane, A. (2024a). Mining Epistemic Actions of Programming Problem Solving with Chat-GPT. In Educational Data Mining Conference 2024.

5. Majumdar, R., Singh, D., Chen, M.R.A. (2024b) Designing Structured Reflections for Guiding Learners' Interactions with Generative AI. In CELDA 2024.

6. Majumdar, R., Singh D., Rajendran R., Narayanan S. & Gatare, K. (2024c). LA-ReflecT platform's affordances for distributed multimodal learning analytics. In CollabTech 2024.

7. Majumdar, R., Ocheja, P., Li, H., Warriem, J.M. (2024d) LA-ReflecT Dashboard: Scaffolding Reflection on Learning with Teacher Prompts & LLM Interactions. T4E 2024 Tools track.

8. Malinverni, L., & Pares, N. (2014). Learning of abstract concepts through full-body interaction: A systematic review. Educational Technology & Society, 17, 100–116.

9. Menary, R. (2010). The extended mind. MIT Press.

10. Mishra, S., Majumdar, R., Kothiyal, A., Pande, P., & Warriem, J. M. (2021, June). Tracing embodied narratives of critical thinking. In International Conference on Artificial Intelligence in Education (pp. 267-272). Cham: Springer International Publishing.

11. Newen, A., De Bruin, L., & Gallagher, S. (Eds.). (2018). The Oxford handbook of 4E cognition. Oxford University Press.

12. Ogata, H., Majumdar, R., & Flanagan, B. (2023). Learning and evidence analytics framework bridges research and practice for educational data science. Communications of the ACM, 66(7), 72-74.

13. Olga C. Santos. 2016. Training the Body: The Potential of AIED to Support Personalized Motor Skills Learning. International Journal of Artificial Intelligence in Education 26, 2 (2016), 730–755. https://doi.org/10.1007/s40593-016-0103-2

14. Portaz, M., Garcia, P., Majumdar, R., & Santos, O. C. (2024, June). Mastering Mind and Movement. ACM UMAP 2024 Tutorial on Modeling Intelligent Psychomotor Systems (M3@ ACM UMAP 2024). In Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (pp. 9-12).

15. Skulmowski, A., & Rey, G. D. (2018). Embodied learning: introducing a taxonomy based on bodily engagement and task integration. Cognitive research: principles and implications, 3, 1-10.

16. Abou-Khalil, V., Vargo, A., Majumdar, R., Magno, M., & Kapur, M. (2023, June). Automated Assessment and Guidance of Project Work. In International Conference on Artificial Intelligence in Education (pp. 69-73). Cham: Springer Nature Switzerland.

17. Santos, O.C., Portaz, M., Casas-Ortiz, A., Echeverria, J., Perez-Villegas, L.F. (2023). Designing, Building and Evaluating Intelligent Psychomotor AIED Systems (IPAIEDS@AIED2023). In: Wang, N., Rebolledo-Mendez, G., Dimitrova, V., Matsuda, N., Santos, O.C. (eds) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky. AIED 2023. Communications in Computer and Information Science, vol 1831. Springer, Cham. https://doi.org/10.1007/978-3-031-36336-8_14.