LCREC: Learning content recommendation (wiki-based skill book)

Chalothon Chootong, Timothy K. Shih, Ankhtuya Ochirbat, Worapot Sommool, W. K.T.M. Gunarathne, Carl K. Chang

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Knowledge skills in the ICT-industry always evolve. With the vast variety of jobs available, it is unlikely to educate students with skills to fit every job-requirement. This issue inspired us to develop the Learning Content Recommender (LCRec) for students to find appropriate learning contents based on required job-skills. In order to bridge the required skill for industry and academia, we have to work on IT job-skills and the Computer Science Curriculum 2013 (CS2013). Skills from 48 publicly available job searching websites are used to investigate what the industry needs. We carried out experiments among professionals, academics, and students to test the usefulness of LCRec, and evaluated the feedbacks. LCRec successfully used Knowledge Units from CS2013, Wikipedia, and essential skills from job hunting websites, to benefit entry-level job seekers for finding necessary learning contents to study. It is also convenient for academics to look at the skills needed in industries, and to consider enhancing the curriculum with new skills. The study result demonstrated that it is possible to bridge the gap (what learning contents are lacking) between the academia and the industry.

Original languageEnglish
Pages (from-to)1753-1766
Number of pages14
JournalJournal of Internet Technology
Volume20
Issue number6
DOIs
StatePublished - 2019

Keywords

  • Auto generated contents
  • Computer science curriculum 2013
  • Knowledge management
  • Learning content recommendation
  • Wikipedia

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