An artificial intelligence approach to identifying skill relationship
Author(s)
Poon, Chung Keung
Xie, Haoran
Wang, Philips Fu Lee
Wong, Tak Lam
Author(s)
Yu, Y. T.
Tang, C. M.
Date Issued
2017
Publisher
Asia-Pacific Society for Computers in Education
Related Publication(s)
Proceedings of the 25th International Conference on Computers in Education (ICCE 2017)
Start page
86
End page
91
Abstract
Designing a good curriculum or an appropriate learning path for learners is challenging because it requires a very good and clear understanding of the subjects concerned as well as many other factors. One common objective of educational data mining and learning analytics is to assist learners to enhance their learning via the discovery of interesting and useful patterns from learning data. We have recently developed a technique called skill2vec, which utilizes an artificial neural network to automatically identify the relationship between skills from learning data. The outcome of skill2vec can help instructors, course planners and learners to have a more objective and data-informed decision making. Skill2vec transforms a skill to a vector in a new vector space by considering the contextual skills. Such a transformation, called embedding, allows the discovery of relevant skills that may be implicit. We conducted experiments on two real-world datasets collected from an online intelligent tutoring system. The results show that the outcome of skill2vec is consistent and reliable.
SFU Affiliated Publication
Yes
Availability at SFU Library
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