Development and commercialization of data-driven e-learning platform with personalized recommendation system (iSTEM AI Lab)

Abstract

This thesis introduces an online-learning tool, iSTEM AI Lab (Figure 5), based on a data-driven assessment approach that helps teachers prepare teaching materials and assess students’ learning performance in active learning activities. It is an e-learning platform that supports STEM-related (Science, Technology, Engineering, Mathematics) subjects. In computer-assisted learning, learners can be easily distracted due to the attraction of different interesting internet content. If learners feel negative emotions during computer-assisted learning, they may discontinue their learning. Thus, finding ways to keep learners feeling positive is an important task. Past studies [1] also revealed the difficulty of evaluating student achievement. It usually takes days for teachers to manually evaluate student learning performance; consequently, the students cannot receive timely feedback from the teachers, which not only affects their learning schedules but also significantly influences the students’ learning achievements. In this thesis, a computer-based alternative learning strategy with real-time assessment and feedback is proposed in order to cope with the problems mentioned above. An evaluation of learning performance which gives real-time feedback to the students will be provided immediately. iSTEM (Figure 5) is an Education technology startup (EdTech) which deploys artificial intelligence, virtual reality and gamification to enhance student engagement and predict and personalize the best solutions for learning efficiency. Education is our future. Our mission is to apply technology to achieve better educational opportunities for every student. This thesis lies at the crossroads of human-computer interaction computing, psychology, and entrepreneurship.

Date of Award	2019
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology