CourseNavigator: interactive learning path exploration

Abstract

Course selection decision making is an extremely tedious task that needs to consider course prerequisites, degree requirements, class schedules, as well as the student's preferences and constraints. As a result, students often make short term decisions based on imprecise information without deep understanding of the longer-term impact on their education goal and in most cases without good understanding of the alternative options. In this paper, we introduce CourseNavigator, a new course exploration service that attempts to address the course exploration challenge. Our service identifies all possible course selection options for a given academic period, referred to as learning paths, that can meet the student's customized goals and constraints. CourseNavigator offers a suite of learning path generation algorithms designed to meet a range of course exploration end-goals such as learning paths for a given period and desired degree as well as the highest ranked paths based on user-defined ranking functions. Our techniques rely on a graph-search algorithm for enumerating candidate learning paths and employ a number of strategies (i.e., early detection of dead-end paths, limiting the exploration to strategic course selections) for improving the exploration efficiency.