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AuCM: Course Map Data Analytics for Australian IT Programs in Higher Education

conference contribution
posted on 2023-02-22, 05:45 authored by J Xia, Y Tang, T Zhao, Jianxin LiJianxin Li
Concept maps have emerged as an essential tool for illustrating the mutual relationships between knowledge in the domain. It provides guidance and suggestions in many educational applications such as optimal study order generating, curriculum design and course evaluation. However, there are no consistent datasets for concept map research. In this work, we aim to build a comprehensive dataset for learning concept maps. Specifically, we collect 1292 undergraduate courses in Information Technology (IT) and Computer Science (CS) from 14 Australian universities including course ID, category and prerequisite requirements. Besides, we analyze the semantic properties based on the concepts retrieved from the course description and visualize them to illustrate how our dataset could be used. To the best of our knowledge, this is the first dataset containing course information from Australian universities.

History

Volume

13725 LNAI

Pagination

158-172

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783031220630

Title of proceedings

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Publisher

Springer Nature Switzerland

Series

Lecture Notes in Computer Science

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