Blended learning effectiveness: the relationship between student characteristics, design features and outcomes

By Mugenyi Justice Kintu, Chang Zhu, Edmond Kagambe. International Journal of Educational Technology in Higher Education, 2017

701 citations recorded by the source corpus.

This paper investigates the effectiveness of a blended learning environment through analyzing the relationship between student characteristics/background, design features and learning outcomes. It is aimed at determining the significant predictors of blended learning effectiveness taking student characteristics/background and design features as independent variables and learning outcomes as dependent variables. A survey was administered to 238 respondents to gather data on student characteristics/background, design features and learning outcomes. The final semester evaluation results were used as a measure for performance as an outcome. We applied the online self regulatory learning questionnaire for data on learner self regulation, the intrinsic motivation inventory for data on intrinsic motivation and other self-developed instruments for measuring the other constructs. Multiple regression analysis results showed that blended learning design features (technology quality, online tools and face-to-face support) and student characteristics (attitudes and self-regulation) predicted student satisfaction as an outcome. The results indicate that some of the student characteristics/backgrounds and design features are significant predictors for student learning outcomes in blended learning.

Subfields: Communication, Developmental and Educational Psychology, Education

View Paper: https://www.semanticscholar.org/paper/f0be2ee3cedc079e86d30c6ee342fca765a7ee3b

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1. Perpetua Lynne Nielson
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Citations in the corpus

• Blended Learning Compared to Traditional Learning in Medical Education: Systematic Review and Meta-Analysis (2020, background): “…blended learning is complex and dependent on how well the evaluation fits, since it occurs before the implementation of any innovation as well as allowing planners to determine the needs, considering participant characteristics, analyzing contextual matters, and gathering baseline information [81].”
• The Effect of Blended Learning on Student's Learning Achievement and Science Process Skills in Plant Tissue Culture Course (2019, background): “The usage of blended learning in learning and teaching has become a popular approach in higher education, Kintu et al. (2017) stated that the introduction of blended learning initiatives is part of these innovations but its uptake, especially in the developing world faces challenges for it to be an…”
• ESL Teachers’ Challenges in Implementing E-learning during COVID-19 (2021, background): “Various studies have been conducted to evaluate how e-learning impacted its users (Mahlangu, 2018; Kintu et al., 2017).”
• THE IMPACT OF A FLIPPED CLASSROOM MODEL OF LEARNING ON A LARGE UNDERGRADUATE STATISTICS CLASS (2018, background): “Kintu et al. (2017) showed that self-regulation was a significant predictor of learner satisfaction and learner knowledge construction.”