Comparative Analysis of Online vs. Blended Learning in Computer Education

Thesis Abstract

This study investigates the comparative effectiveness of online versus blended learning modalities in computer education, addressing persistent concerns about student engagement, achievement, and skill transfer in rapidly evolving digital curricula. The problem centers on insufficient empirical evidence linking modality choice to practical competencies in programming, software development, and computational thinking among tertiary students. The aim is to determine whether blended learning yields superior outcomes relative to fully online delivery, and to identify contextual factors that modulate these effects. Specific objectives are to compare academic achievement, practical coding proficiency, cognitive load, and student satisfaction across modalities; to examine the moderating roles of prior digital literacy, access to resources, and instructional design quality; and to develop evidence-based recommendations for optimizing computer education in higher?education settings. The study is guided by the Community of Inquiry (CoI) framework and the Technology Acceptance Model (TAM), with supplementary insights from Cognitive Load Theory to interpret instructional design impacts. A mixed-methods design is employed, combining a quasi-experimental comparative approach with sequential explanatory data collection. The population comprises first- to third-year undergraduate computer science and information technology students enrolled at three public universities in a metropolitan region. A purposive stratified sample of 420 students is drawn across three cohorts online-only, blended, and traditional on-campus as a control, ensuring balanced representation of gender, prior GPA, and year of study. Data collection instruments include (i) validated achievement examinations encompassing theoretical knowledge and practical coding tasks, (ii) a performance-based assessment rubric for laboratory projects, (iii) standardized surveys measuring cognitive load (NASA-TLX adapted for education), perceived usefulness and ease of use (TAM scales), and student satisfaction, (iv) a semi-structured interview protocol for a subset of 60 students and 12 instructors to explore instructional design features and engagement strategies. Data collection occurs over a 14-week semester, with two follow-up assessments at three months to gauge knowledge retention and skill transfer. Quantitative analyses employ descriptive statistics, multivariate analysis of covariance (MANCOVA) to compare outcomes across modalities while controlling for baseline differences, and hierarchical linear modeling (HLM) to account for nested data (students within courses). Regression analyses identify predictors of coding proficiency and academic achievement, while moderation analyses test the effects of prior digital literacy and resource access. Qualitative data are analyzed using thematic analysis to extract themes related to interaction quality, social presence, cognitive load, and perceived credibility of online versus blended environments. Triangulation integrates quantitative and qualitative findings to provide a comprehensive interpretation of modality effects. Key expected findings include (1) blended learning producing higher practical coding proficiency and immediate exam scores than online-only and on-campus approaches, (2) online learning showing comparable theoretical achievement to blended learning but lower performance on hands-on tasks, (3) lower perceived cognitive load and higher satisfaction in blended settings due to structured synchronous activities and timely feedback, (4) moderation by prior digital literacy such that students with low digital literacy benefit more from blended interventions, and (5) instructional design quality (e.g., alignment, feedback frequency, and collaborative activities) being a critical determinant of success in both modalities. The study anticipates explaining variance in outcomes through the CoI’s social, cognitive, and teaching presence components, the TAM’s perceived usefulness constructs, and cognitive load considerations. Contributions to knowledge include nuanced, context-specific evidence on modality effectiveness for computer education at the undergraduate level, validated by a robust mixed-methods design and a large, diverse sample. The research will inform curriculum designers, educators, and policymakers about optimal modality configurations, resource allocations, and professional development needs to enhance student outcomes in programming, software engineering, and computational thinking. The concluding recommendations will emphasize blended-learning design principles, scalable feedback mechanisms, equitable access to technology, and ongoing assessment of cognitive load to sustain high-quality computer education in higher education.