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The Application of Information Processing Theory to Design Digital Content in Learning Message Design Course

I Komang Sudarma, Dewa Gede Agus Putra Prabawa, and I Kadek Suartama

Abstract—The development research being carried out has the aim of producing digital content developed based on information processing theory for the message design course in Educational Technology Study Program in Education Science Faculty of Universitas Pendidikan Ganesha. This is a development research in which the Hannafin & Peck model is used. The developed digital content is evaluated using formative evaluation techniques, including 1) expert validation, 2) one-to-one evaluation, and 3) small group evaluation. The subjects involved in this study were 2 experts, namely media experts and instructional design experts, 3 students in one-to-one evaluation, and 9 students in small group evaluation. The methods and instruments used to collect data in this study were observation and questionnaires. Based on the expert’s judgment, the design aspect is in the good category, the media aspect is in the very good category. Students’ responses at the one-to-one and small group evaluation stages are in the good categories. Thus, it can be concluded that the attractiveness of digital content is in the good category.

Index Terms—Information processing theory, digital content, message design.

I Komang Sudarma, Dewa Gede Agus Putra Prabawa, and I Kadek Suartama are with Universitas Pendidikan Ganesha, Bali, Indonesia (e-mail: ik-sudarma@undiksha.ac.id, dgap-prabawa@undiksha.ac.id, ik-suartama@undiksha.ac.id).

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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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