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IJIET 2017 Vol.7(8): 575-580 ISSN: 2010-3689
doi: 10.18178/ijiet.2017.7.8.934

Promote Technology Self-efficacy via a SCORM-Based e-Learning Approach

Xin Bai

Abstract—The purpose of this study is to explore the relationship between undergraduate students’ perceptions of their basic computer literacy skills (self-efficacy) and their attitudes toward the hybrid learning experiences after completing a 15-week SCORM-based hybrid-learning course. Two hundred and forty-six students from a historically black senior college participated in the study. Students completed an anonymous self-assessment survey at the end of the semester. The results show that students with higher self-efficacy beliefs are more likely to report positive learning experiences, including learning pace control, time management, and content understanding. However, students with lower self-efficacy beliefs are more likely to respond that the topics are difficult to follow and time online is hard to control, and they prefer a face-to-face rather than online session. Implications of these findings and the strengths and limitations of such an elearning framework are discussed to inform future research on identifying effective hybrid-learning tools and pedagogies in order to increase self-efficacy for improved motivation and academic performance.

Index Terms—SCORM, elearning, efficacy, instructional design, motivation, hybrid learning, cognition.

Xin Bai is with York College of the City Univ. of New York, 94-20 Guy Brewer Blvd., Jamaica, NY, 11451, USA (e-mail: xbai@york.cuny.edu).

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Cite: Xin Bai, "Promote Technology Self-efficacy via a SCORM-Based e-Learning Approach," International Journal of Information and Education Technology vol. 7, no. 8, pp. 575-580, 2017.

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Jon-Chao Hong
  • Managing Editor: Ms. Nancy Y. Liu
  • E-mail: editor@ijiet.org
  • Abstracting/ Indexing: Scopus (CiteScore 2023: 2.8), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Google Scholar
  • Article Processing Charge: 800 USD

 

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