I-Learn: Empowering Engineering Learners Using Visualizations In Mixed Reality And Machine Learning

This research explores learning with technologies involving the influence of individual cognitive function (perceptual, attentional, and cognitive skills). There remains a gap in knowledge on how or why learners arrive at different results in the learning process. This research project bridges that divide by considering the learner’s individual characteristics as they execute problem-solving tasks while interacting with the advanced technology-enabled environments – a machine-learning (ML) and mixed-reality (MX) technology. By focusing on components of learning cognition (e.g., working memory and sustained attention) as well as mental simulation and situational awareness, this project (1) uses ML predictive modelling to explore the effects of individual differences on learners’ performance in problem-solving tasks modelling, (2) studies learners’ moments of impasse in problem-solving tasks that demand spatial and cognitive ability, and (3) develops and assesses the effectiveness of an interactive and adaptive MX platform for learning when used by students with different cognitive and attentional abilities. Research outcomes will inform the design of adaptive learning technologies and the customization of instruction in engineering education.