Knowledge acquisition through online learning environments: A structural equation modeling analysis with gender as a moderator

Abstract

This study aims to investigate the effects of online learning on learners, focusing on various psychological, behavioral, and academic outcomes, with gender as a moderating factor. The research employs Structural Equation Modeling (SEM) to analyze the factors influencing knowledge acquisition in online learning environments. The study uses a mixed-methods approach, combining quantitative surveys and qualitative interviews to gather comprehensive data. The findings reveal that online learning platforms offer significant advantages such as flexibility and accessibility, but also present challenges that impact learners' satisfaction. Key determinants of successful knowledge acquisition include mode of learning, instructor support, digital literacy, and cognitive load. Gender differences play a moderating role in these relationships. The study concludes that while online learning environments provide valuable educational opportunities, it is crucial to address the diverse needs of learners to enhance satisfaction and learning outcomes. Gender-specific strategies can help create more inclusive and effective online learning experiences. Educators and policymakers can use the insights from this research to develop targeted interventions that improve online learning environments. By focusing on key factors such as instructor support and digital literacy, and considering gender differences, they can promote equitable educational opportunities for all learners.