Kenneth Y. T. Lim operates at the intersection of neuroergonomics, the learning sciences, and cognitive psychology. Most recently, his early work on the affordances for learning of the paradigm of spatial computing advanced by the Apple Vision Pro was recognised when he was featured on national broadcast television, and subsequently at the Geography Education Research Collective of the UK Commission on Geographical Education of the International Geographical Union, and at the 16th International Conference on Applied Human Factors and Ergonomics in the track on Human Factors and Wearable Technologies.

Highlights from work co-authored with his students in 2024 include Beyond the Geography Discipline: Applying the Powerful Geography Approach in a College-Level Data Science Curriculum in Singapore - in response to an invitation from the Co-Director of the National Center for Research in Geography Education, USA - and a paper read at Interdisciplinary Perspectives: Bridging Sociological Studies in the Digital Age, hosted by the Department of Digital Humanities, King’s College London. Kenneth is therefore recognised as a thought leader in the affordances for learning of Artificial Intelligence and Data Science.

As further examples in 2024, he was invited to UNESCO's flagship event Digital Learning Week in Paris in September, and to 'AI Policy and Education Futures' at the University of Sydney in July. Kenneth was one of only six members invited to the expert panel at 'Empowering Minds: A Round Table on Generative AI and Education in Asia-Pacific' organized by the UNESCO Multisectoral Regional Office in Bangkok (UNESCO Bangkok), in collaboration with The Southeast Asian Ministers of Education Organization (SEAMEO), November 2023.

At ICOLSEI 2025, Kenneth will deliver a talk titled "In situ physiological responses when interacting with Large Language Models: a neuroergonomic perspective". In this talk, he will share an investigation in to the cognitive and emotional states of adolescents while learning from an LLM. The investigation sought to address a relative dearth in empirical evidence which might otherwise facilitate informed decisions being made by curriculum designers, school leaders and policy makers regarding the use of Generative AI, amidst the wider discourse about the effectiveness of AI in teaching and learning. In this paper, Kenneth’s students analysed electrodermal activity (EDA) in the context of their peers’ scholastic engagement using LLMs in comparison to curated texts. In their 27-minute-long experiment, they recorded the EDA of participants learning from both learning methods, for eight minutes each. A quiz was also conducted to assess the effectiveness of the learning method. They collected 23 samples of EDA from the experiment, and 42 samples of quiz results. They have found that learning with an LLM results in greater Skin Conductance Response (p = 0.09), which is linked to more positive emotional valence, and lower Skin Conductance Level (p = 0.09), which is linked to lower cognitive load, compared to curated texts. They also discovered that learning with an LLM correlates to a higher quiz result (p = 0.02). While this suggests that learning and absorbing information with an LLM could be more effective than curated texts, results from self-reported data indicates that there are little perceived differences between the effectiveness of LLM and curated texts. This study revealed empirical insights between LLM usage and learning effectiveness in situ via physiological indicators, in contrast to much prior work which has adopted post hoc frames over the medium- to long-term.