Meta-Analysis: Comparison of the Effectiveness of Hybrid and Traditional Learning Models At college Levels In 7 Countries
Abstract
Purpose of the study: The Covid-19 pandemic's shift to hybrid learning presents a future educational solution. Though new, hybrid models are widely adopted at universities globally. This study examines hybrid learning effectiveness compared to traditional methods across various countries.
Methodology: This meta-analysis study utilizes Google Scholar database (2020-2024) through Publish or Perish application. Research stages include: 1) Article metadata search, 2) Filtering, 3) Data analysis, and 4) Interpretation and visualization of results. Article analysis employs random effects model using JASP application to examine Effect Size across various articles.
Main Findings: The results of the study obtained 7 articles from various countries that discussed the effectiveness of hybrid and traditional learning models that have varying Effect Size values. The results of the analysis showed that 41.7% of this learning model was effectively used in learning at the university level in 7 countries such as Hongkong, Morocco, China, the Philippines, UAE, Switzerland, and Malaysia.
Novelty/Originality of this study: This study contributes novel understanding of hybrid learning effectiveness in higher education post-pandemic. It demonstrates improved student outcomes and participation while emphasizing efficient, adaptive, data-driven institutional policies. The study proposes integrating collaborative, project-based learning with artificial intelligence support for inclusive, sustainable, responsive education addressing digital era challenges.
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