Improving Academic Performance Through Blended Learning: The Case of Afghan Higher Education

Hamidullah Sokout, Tsuyoshi Usagawa

Abstract


The last two decades have witnessed a global revolution in educational information that has led to the development and promotion of e-learning. Blended Learning (BL) is an increasingly growing e-learning model with a background in pedagogical and psychological theory that combines both online and traditional activities. In recent years, it has been an emerging trend and has impacted the growth, revenue, learner retention, and academic accreditation in higher education. With current improvements, extensive research, and successful implementation of blended and fully online learning, little research has been done to report the success of transitioning from face-to-face to blended learning or evaluations of e-learning data regarding learners from developing nations, particularly Afghanistan. This study aims to investigate and analyze the effectiveness of educational types (blended vs. traditional) regarding learners’ academic performance, in-class engagement, and satisfaction from the data in six BL courses and four traditional learning (TL) courses. To measure the success, this study used descriptive statistics. Additionally, Welch’s t-test was used to compare BL with TL courses and assess the differences between success and failure levels for both courses. Likewise, the Pearson correlation coefficient, along with an ordinary least square regression, was used to indicate the relationship between the final score and the BL and TL activities, respectively. The study outcome will be used for reporting and feedback for educational parties to value the quality of teaching and learning, enhance learners’ performances, and for the institutionalization of BL in the country.

Keywords


E-learning; Blended Learning; Descriptive Statistics; Teaching; Learning

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Copyright (c) 2021 Hamidullah Sokout, Tsuyoshi Usagawa


International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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