Statistical Analysis on Engagement Patterns of Fresh Graduates around Different Online Learning Platforms
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839-861
Digital Object Identifier:
10.58578/ijemt.v3i3.7353
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Authors:Ajao Olutunde Michael1*, Ayenigba Alfred Ayo2, Ojekunle Odegua Elizabeth3
Copyright :Authors retain copyright and grant the journal right of first publication.
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Abstract
In the digital era, online learning platforms have become essential tools for delivering education at a global scale. This study examines user engagement across three major platforms—Coursera, edX, and LinkedIn Learning—with a focus on how engagement metrics correlate with perceived learning outcomes. Utilizing a mixed-methods approach, data were collected from 124 fresh graduates (within 0–3 years post-graduation) through structured questionnaires and analyzed using descriptive statistics, ANOVA, t-tests, and chi-square tests. The results indicate that users primarily engage with these platforms to enhance employability and earn certifications, with Coursera and LinkedIn Learning being the most frequently used. Courses related to career-specific skills and personal development were highly preferred. Engagement frequency was high, with most participants accessing content daily or weekly. Motivating features included video lectures and interactive elements, while time constraints and high subscription costs were identified as major barriers. Regression analysis confirmed a statistically significant relationship between user engagement and perceived learning effectiveness (p ≤ 0.05). Furthermore, the study found significant differences in engagement patterns influenced by platform interactivity, content quality, and the availability of certifications. The study concludes that optimizing platform design by offering accessible, career-relevant content and reducing time and cost barriers is critical to improving learner engagement and educational outcomes.
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