School of Engineering Department of Computer Science and Engineering 113 Predicting Student Performance on an E-learning Platform Supervisor: MA, Xiaojuan / CSE Student: KIM, Justin Juho / MAEC Course: UROP2100, Fall In recent years, the growing demand for distance education has resulted in an influx of Massive Open Online Courses (MOOCs). However, learner engagement and educational success remain among the most critical discourses for educators and developers of these platforms. Although many types of engagement are perceptible, little is known about their contribution to learning outcomes. This paper aims to bridge this knowledge gap by examining how each form of behavioral engagement affects a learner’s performance outcome (grade) when other forms of behavioral engagement are assumed to be constant. An exploratory observational approach was used to analyse the HarvardX Person-Course De-Identified dataset. It was found that spacing learning over a longer period and coverage of course material had a statistically significant impact on learner outcomes (α = 0.05). However, watching MOOC lecture videos and participating in forum discussions alone does not have a statistically significant impact on learning outcomes. These observations are consistent across our analyses of various subjects and academic disciplines. Based on the findings and analyses, the researchers suggest that instructional designers (i) encourage learners to pace their learning, (ii) develop interventions to better capture learners’ attention in lecture videos, and (iii) adjust the design of courses to integrate discussion forums as a major component of the course, ultimately encouraging peer learning. Hence, this paper has an important impact on the learning, HCI, and MOOC community because it provides a motivation for encouraging learners to pace their learning and reveals that watching lecture videos and participating in course forums alone is not sufficient to guide a learner towards achieving course intended learning outcomes. Assess User Experience to Design Effective Visual Representation and Interaction in Virtual Reality Supervisor: MA, Xiaojuan / CSE Student: DOU, Peihao / COSC Course: UROP2100, Fall During this semester, I continued my Urop2100 study with the project title ‘Assess user experience to design effective visual representation and interaction in virtual reality’. I continued to explore VR and began to learn AR. In the past summer, I had tried a VR application with hand interface. To study more about hand interface, I made an application based on the hand tracking SDK to achieve bones detection and gesture (pinch) recognition. Besides, after reading papers about real-time augmented speech, I made my first AR application. The motivation of making this project is to achieve adding some simple visual elements with user interface using AR, which is a foundation of all AR applications. This report summarizes my studies and work during this semester.
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