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Digital Knowledge Engineering Learning Model for Undergraduates in Thai Educational Institutions

Thamasan Suwanroj and Orawan Saeung

Abstract—Efficient learning management is the learning that can reflect students' identities through creating work following desirable competencies. It can develop students by providing opportunities to practice thinking about, using, and applying knowledge to real-life situations under the learning management in the digital age. The objectives of this research were to study and analyze the factors of the Digital Knowledge Engineering Learning Model: DKELM discussed by the group of experts who are all teachers from the government educational institutions in Thailand covering all undergraduate programs. The research instrument was a five-point Likert scale questionnaire about DKELM factors for undergraduates. Data were collected from 1,126 questionnaires from the sample group of 1,126 experts. The researchers used IBM SPSS Statistics 14.0 for descriptive statistical analysis and LISREL 8.72 for the second-order confirmatory factor analysis (CFA). Each aspect's content validity and reliability were .95 - .97, and each factor's content validity and reliability were .93 - .98. The research was employed by the Nakhon Si Thammarat Rajabhat University students, Nakhon Si Thammarat Province, Thailand, in 2019-2020. The discovery of the research was DKELM consisting of six knowledge-related processes gained from 18 variables: 1) Creation, 2) Storing, 3) Acquisition, 4) Access, 5) Sharing, and 6) Application. The findings are important and valuable because they can improve DKELM to develop digital and logical thinking skills for undergraduates in Thai educational institutions in the following research phase. Also, they can be used as a model to manage the learning in the digital age to emphasize and reflect the identities of each student through practical experience.

Index Terms—Digital knowledge engineering, confirmatory factor analysis, educational institutions.

Thamasan Suwanroj and Orawan Saeung are with Nakhon Si Thammarat Rajabhat University, Thailand (e-mail: thamasan_suw@nstru.ac.th, orawan_ray@nstru.ac.th).


Copyright © 2022 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Executive Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (CiteScore 2021: 1.3), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Electronic Journals Library, Google Scholar, Crossref, etc.
  • E-mail: ijiet@ejournal.net

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