CourseNavigator:交互式学习路径探索

Zhan Li, Olga Papaemmanouil, G. Koutrika
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引用次数: 9

摘要

选课决策是一项极其繁琐的工作,需要考虑课程先决条件、学位要求、课程安排以及学生的喜好和限制。因此,学生经常根据不精确的信息做出短期决定,而没有深入了解对他们的教育目标的长期影响,在大多数情况下,没有很好地了解其他选择。在本文中,我们介绍了一种新的课程探索服务coursennavigator,它试图解决课程探索的挑战。我们的服务确定了给定学术期间所有可能的课程选择选项,称为学习路径,可以满足学生定制的目标和限制。CourseNavigator提供了一套学习路径生成算法,旨在满足一系列课程探索的最终目标,例如给定时间段和期望学位的学习路径,以及基于用户自定义排名功能的最高排名路径。我们的技术依赖于图搜索算法来枚举候选学习路径,并采用许多策略(即,早期发现死胡同,将探索限制在战略课程选择上)来提高探索效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CourseNavigator: interactive learning path exploration
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.
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