Framing strategies in digital education content: a content analysis of Coursera’s course metadata to enhance learning engagement

Purpose This study examines how framing strategies are embedded in Coursera course metadata and how their presence is associated with course-rating indicators. It conceptualizes metadata as an interpretive layer through which platforms communicate the value, relevance and intended learning experience of online courses. Design/methodology/approach Content analysis of 131 Coursera course entries based on framing theory, using publicly available course metadata (titles, descriptions and skill summaries) as the unit of analysis. Four frames were classified: results-oriented, ethical, personalized and social framing. Course popularity was utilized as an engagement metric. Findings Personalized framing was the most prevalent, followed by results-oriented framing, indicating a strong emphasis on learner autonomy, flexibility, skill acquisition and career value. Analysis of Variance (ANOVA) results showed no significant differences in mean ratings across ethical, personalized or social framing categories. However, ethical and social framing were significantly associated with high-rating classification, suggesting that their relevance may be reflected in rating distributions rather than increases in mean satisfaction. Practical implications The study contributes to the optimization of online learning content. It is a valuable resource for teachers, instructional designers and edtech developers who want to design more interactive and pedagogically successful learning environments in virtual environments. Originality/value This research extends framing theory to digital education, showing that pedagogical content areas are structured to motivate learners and influence their behavior beyond the simple curriculum. This brings a new perspective to the evaluation of massive open online courses (MOOC) design logic.