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Off the Beaten Path: The Impact of Adaptive Content Sequencing on Student Navigation in an Open Social Student Modeling Interface

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Artificial Intelligence in Education, volume 9112 of Lecture Notes in Computer Science, Springer International Publishing, (2015)
DOI: 10.1007/978-3-319-19773-9_77

Abstract

One of the original goals of intelligent educational systems is to guide every student to the most appropriate educational content. Exploring both knowledge-based and social guidance approaches in past work, we learned that each of these approaches has weak sides. In this paper we follow the idea of combining social guidance with more traditional knowledge-based guidance to support more optimal content navigation. We proposed a greedy sequencing approach that maximizes student's level of knowledge and tested it in a classroom. Results indicated that this approach positively impacts students' navigation.

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