An artificial intelligence approach to identifying skill relationship

Tak Lam WONG, Yuen Tak YU, Chung Keung POON, Haoran XIE, Fu Lee WANG, Chung Man TANG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of the 25th International Conference on Computers in Education, ICCE 2017 - Main Conference Proceedings
EditorsAhmad Fauzi MOHD AYUB, Antonija MITROVIC, Jie-Chi YANG, Su Luan WONG, Wenli CHEN
PublisherAsia-Pacific Society for Computers in Education
Pages86-91
Number of pages6
ISBN (Print)9789869401265
Publication statusPublished - 2017
Externally publishedYes
Event25th International Conference on Computers in Education - Rydges Latimer Hotel, Christchurch, New Zealand
Duration: 4 Dec 20178 Dec 2017
https://apsce.net/icce/icce2017/140.115.135.84/icce/icce2017/index.html

Conference

Conference25th International Conference on Computers in Education
Abbreviated titleICCE 2017
Country/TerritoryNew Zealand
CityChristchurch
Period4/12/178/12/17
Internet address

Funding

The work described in this paper is fully supported by the grant from Research Grants Council of the HKSAR (Ref.: UGC/FDS11/E02/15).

Keywords

  • Artificial intelligence
  • Learning analytics
  • Neural network
  • Skill relationship

Fingerprint

Dive into the research topics of 'An artificial intelligence approach to identifying skill relationship'. Together they form a unique fingerprint.

Cite this