Blended Learning and Learning Autonomy in College Students

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DOI: https://doi.org/10.63345/ijre.v14.i8.3

Dr Kamal Kumar Gola

COER University

Roorkee, Uttarakhand, India

kkgolaa1503@gmail.com

Abstract
Blended learning has evolved into a transformative pedagogical approach that synergizes traditional face‑to‑face instruction with digital learning environments. By combining the strengths of in‑person engagement—such as immediate feedback, social interaction, and structured guidance—with the flexibility, scalability, and resource richness of online modalities, blended learning offers unique affordances for fostering autonomous learning behaviors among college students. Learning autonomy—the capacity of learners to take responsibility for goal setting, strategic planning, self‑monitoring, and self‑reflection—is widely recognized as a critical 21st‑century competency that underpins lifelong learning and professional adaptability. Despite its promise, the specific mechanisms through which blended learning scaffolds autonomy remain underexplored, particularly at the undergraduate level across diverse disciplines.

This study investigates the relationship between key design elements of blended courses and the development of learning autonomy among undergraduates. Employing a descriptive correlational design, we administered a comprehensive survey to 235 students enrolled in blended courses at a large public university. The survey included the Blended Learning Perception Scale (BLPS), measuring clarity of instructional design, interactivity, feedback quality, and flexibility, alongside the Learning Autonomy Inventory (LAI), assessing goal setting, self‑monitoring, and reflective practice. We employed rigorous scale validation procedures, including confirmatory factor analysis and reliability testing, to ensure psychometric robustness.

Our findings reveal a strong positive correlation between overall perceptions of blended learning effectiveness and learners’ autonomous behaviors (r = .58, p < .001). Hierarchical regression analyses indicate that feedback quality (β = .28, p < .001) and flexibility of access (β = .24, p = .002) are the most salient predictors of autonomy, followed by interactive features such as discussion forums and multimedia activities (β = .19, p = .010). Discipline emerged as a significant moderator, with engineering students exhibiting slightly lower autonomy scores compared to peers in humanities and social sciences. These results underscore the importance of designing blended environments that not only provide choice and self‑paced pathways but also integrate frequent, constructive feedback loops and scaffolding tools that guide self‑regulated processes.

Implications for practice include recommendations for faculty development programs emphasizing metacognitive prompts, the integration of analytics dashboards for real‑time progress tracking, and the incorporation of reflective assignments that encourage strategic planning. Institutional policy implications involve investing in learning management systems that support adaptive release of materials and facilitate peer collaboration. Future research directions include longitudinal studies tracking autonomy development over multiple semesters and experimental interventions isolating the effects of specific blended components.

Keywords

Blended Learning, Learning Autonomy, Self‑Regulation, College Students, Online Education

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