Debarshi Nath

About Me

I am a doctoral research scholar in the Joint PhD programme at IIT Bombay-Monash Research Academy. I am affiliated to the Centre for Educational Technology at Indian Institute of Technology Bombay, India and Centre for Learning Analytics at Monash (CoLAM) under Department of Human-Centred Computing at Monash University, Australia. My supervisors are Ramkumar Rajendran and Dragan Gasevic.

My research interests are in Learning Analytics, Self-Regulated Learning, Multimodal Analytics, Eye-tracking analytics and Machine Learning.

Publications

From PhD (2021- )

Nath, D., Gasevic, D., Fan, Y., & Rajendran, R. (2025, July). How do Learners Read the Content in a Multi-Source Reading-to-Write Task? – A Multimodal Study. In 26th International Conference on Artificial Intelligence in Education (AIED 2025), July 22-26, 2025.
Li, T., Nath, D., Cheng, Y., Fan, Y., Li, X., Raković, M., Khosravi, H., Swiecki, Z., Tsai, Y.S. and Gašević, D. (2025, March). Turning real-time analytics into adaptive scaffolds for self-regulated learning using generative artificial intelligence. In Proceedings of the 15th International Learning Analytics and Knowledge Conference (pp. 667-679).
Aldino, A. A., Tsai, Y. S., Gupte, S., Henderson, M., Nath, D., Gasevic, D., & Chen, G. (2025). A case study on learner-centered feedback: Differences and implications in higher education. Computers & Education, 105360.
Nath, D., Gasevic, D., Fan, Y., & Rajendran, R. (2024, March). CTAM4SRL: A Consolidated Temporal Analytic Method for Analysis of Self-Regulated Learning. In Proceedings of the 14th Learning Analytics and Knowledge Conference (pp. 645-655).
Nath, D., Gasevic, D., & Rajendran, R. (2023, January). A Trace-Based Generalized Multimodal SRL Framework for Reading-Writing Tasks. In Educational Data Mining.
Satavlekar, S., Nath, D., Priyadarshini, R., Prasad, P., Singh, D. K., & Rajendran, R. (2021, July). Unraveling Learner Interaction Strategies in VeriSIM for Software Design Diagrams. In 2021 International Conference on Advanced Learning Technologies (ICALT) (pp. 308-310). IEEE.

From Masters (2018-2020)

Nath, D., Anubhav, Singh, M., Sethia, D., Kalra, D., & Indu, S. (2020, March). A comparative study of subject-dependent and subject-independent strategies for EEG-based emotion recognition using LSTM network. In Proceedings of the 2020 4th International Conference on Compute and Data Analysis (pp. 142-147).
Anubhav, Nath, D., Singh, M., Sethia, D., Kalra, D., & Indu, S. (2020, February). An Efficient Approach to EEG-based Emotion Recognition using LSTM Network. In 2020 16th IEEE International Colloquium on Signal Processing & its Applications (CSPA) (pp. 88-92). IEEE.