The research program aims at translating theories in cognitive psychology, human-computer interaction and machine learning to design information technologies that support complex cognitive processes (such as decision-making and learning) for adults across the lifespan.
Designing instructional conversational agents for older adults
- Current students: Smit Desai
Designing persuasive conversational agents for health behavior nudging
- Current student: Smit Desai
AI-assisted agents in informal/self-regulated learning
- Current students: Smit Desai, Tre Tomaszewski
Combing learning theories and machine-learning to design interactive learning interfaces
- Current Student: Tre Tomaszewski
Desai, S. & Chin, J. (2020). An explorative analysis of the feasibility of implementing metacognitive strategies in self-regulated learning with the conversational agents. In Proceedings of the 64th International Annual Meeting of the Human Factors and Ergonomics Society.
Designing adaptive interface to support web information search for older adults
Chin, J. & Fu, W-T. (2012). Age differences in exploratory learning from a health information website. In Proceedings of the 30th ACM Conference on Human Factors in Computing Systems CHI’12 (pp. 3031-3040). Austin, TX: ACM Press. DOI:10.1145/2207676.2208715
Chin, J. & Fu, W-T. (2010). Interactive effects of age and interface differences on search strategies and performance. In Proceedings of the 28th ACM Conference on Human Factors in Computing Systems CHI’10 (pp.403-412). Atlanta, GA: ACM Press. DOI: 10.1145/1753326.1753387
Chin, J., Fu, W-T. & Kannampallil, T. (2009). Adaptive information search: Age-dependent interactions between cognitive profiles and strategies. In Proceedings of the 27th ACM Conference on Human Factors in Computing Systems CHI’09 (pp.1683-1692). Boston, MA: ACM Press. DOI: 10.1145/1518701.1518961