Abstract

An adaptive learning system allows for personalised instruction depending on the needs, capability, progress and preference of the student.

This study outlines the process, observations and outcomes of implementing an adaptive learning framework to a large Statistics service class (~900 students) for Computing and Engineering students. The class is taught in a blended learning mode.

Each week, students are assigned to watch pre-recorded lecture videos and complete formative quizzes hosted on a learning platform before coming in for a “live” class. As they progress through materials, the platform automatically directs them to the most appropriate content for their current level of understanding. In short, students can skip pass materials where they exhibit a proficient level of understanding and move on to the next topic in a “Learning map”.

To assess the effectiveness of this adaptive-learning framework, a “standardized test” was conducted to compare the performance of these students versus a prior cohort of students who did not undergo this adaptive learning framework. The results looks very promising.