Predictors of blended learning adoption in higher education institutions in Oman: theory of planned behavior

Faten Hamad*, Ahmed Shehata, Noura Al Hosni

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The shift toward electronic learning due to the COVID-19 pandemic has created many opportunities to shape Oman’s learning styles. This study explores the factors that affect students’ acceptance of blended learning (BL) in higher education institutions in developing countries, focusing on Oman. The study examines the impact of demographic and social factors, attitude, subjective norms, perceived behavioral control, self-efficacy, beliefs, behavioral intention, and actual use of BL among students. The Theory of Planned Behavior (TPB) was used as a theoretical framework to understand the decision-making processes surrounding BL adoption. Hypotheses are formulated and tested using statistical analysis of survey results. The questionnaire was distributed to students from Sultan Qaboos University in Oman. The data collected were analyzed using inferential predictive modeling methods such as multiple regression analysis and Pearson correlation. The findings indicate that students have a positive attitude toward BL and are likely to choose it in the future. The study also reveals that demographic characteristics and various dimensions, such as attitude, subjective norms, perceived behavioral control, self-efficacy, beliefs, behavioral intention, and actual usage, influence students’ acceptance and utilization of BL. The results contribute to the existing literature and provide insights into the factors that affect BL adoption in developing countries.

Original languageEnglish
Article number13
JournalInternational Journal of Educational Technology in Higher Education
Volume21
Issue number1
DOIs
Publication statusPublished - Jan 2024

Keywords

  • Blended learning
  • e-Learning
  • Oman
  • Theory of Planned Behavior (TPB)

ASJC Scopus subject areas

  • Education
  • Computer Science Applications

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