Abstracts Category : Other

Statistical analysis for building a personalized onlinelearning system

by Liu Shuang ;

Use of computers and new technologies have become acrucial part of teaching and learning at all levels. Online coursesare widely available and the number is growing exponentially. Oneadvantage of most online learning courses is that studentsperformance can be made tangible and measurable. We analyzedatabases from two e-learning platforms developed for twoindependent courses at The University of Hong Kong, namely SCNC1111(Scientific Method and Reasoning offered by Faculty of Science) andNURS1516 (Introduction to Statistics offered by School of Nursing),that record traces of students online activities on the platform.Item Response Theory models are applied to the two databases toestimate students ability based on their performance on solvingquestions online. It is found that active participants showedimprovement in the mathematical capacity in both courses. Moreover,significant differences in students online behaviour are detectedprobably due to the differences in the settings of the two courses.The results of the analyses based on the two datasets will besummarized and compared in this thesis. The direction to thedevelopment of a personalized e-learning system will be discussedbased on the results of the analysis. published_or_final_version Statistics and Actuarial Science Master Master of Philosophy