Conception, mise en œuvre et évaluation d'une plateforme éducative adaptative en ligne

Thesis Abstract

The rapid expansion of digital education has underscored the necessity for personalized learning environments that adapt to individual learner needs, particularly in online settings where learner engagement and retention remain challenging. Despite the proliferation of e-learning platforms, many lack adaptability features that address diverse learner profiles, thereby limiting their effectiveness. This study aims to design, implement, and evaluate an online adaptive learning platform tailored to enhance learner engagement, knowledge acquisition, and retention through personalized content delivery. The specific objectives include identifying essential features of adaptive learning systems, developing a pedagogically sound platform integrating user profiling and dynamic content adjustment, and assessing the platform’s usability, effectiveness, and impact on learning outcomes. Employing a mixed-methods research design, the study integrates qualitative design-based research principles with quantitative experimental evaluation. The population comprises undergraduate students enrolled at a major university, with a sample of 200 participants selected through stratified random sampling to ensure representation across disciplines and academic levels. Data collection instruments include a series of structured questionnaires to gauge learner satisfaction, perceived usability, and engagement; system logs to gather objective data on learner interactions; and post-intervention assessments consisting of standardized tests to measure knowledge gains. Validity and reliability of the instruments are established through expert validation and Cronbach’s Alpha coefficients exceeding 0. eighth. Data analysis employs descriptive statistics, paired t-tests to compare pre- and post-intervention learning outcomes, and regression analysis to identify predictors of learner achievement. Thematic analysis is conducted on qualitative feedback to explore user experiences and perceptions. Preliminary hypotheses suggest that learners using the adaptive platform will demonstrate statistically significant improvements in engagement and test scores compared to control groups using non-adaptive systems. It is anticipated that the platform’s user-centered design will positively influence perceived usability and satisfaction. The study expects to find that adaptive features, such as real-time content adjustment and learner modeling, significantly contribute to individualized learning experiences and enhance overall academic performance. The innovative contribution of this research resides in the development of a comprehensive, pedagogically grounded adaptive learning platform, complemented by empirical evidence of its efficacy within higher education contexts. It advances existing models by integrating learner analytics, artificial intelligence components for real-time adaptation, and instructional design principles tailored to diverse learner profiles. The findings are expected to fill notable gaps in the literature concerning scalable, effective online adaptive systems that are both pedagogically sound and technologically feasible. The main conclusions indicate that well-structured adaptive learning environments can substantially improve learner engagement, motivation, and academic achievement when grounded in sound educational theories such as Vygotsky’s Zone of Proximal Development and Keller’s ARCS motivation model. Recommendations include adopting iterative development processes incorporating learner feedback, enhancing system personalization capabilities, and training educators on integrating adaptive platforms into their pedagogical practices. The study further suggests avenues for future research, particularly longitudinal studies to assess long-term retention, and the exploration of adaptive features in collaborative learning settings. Overall, this research provides a significant step forward in the conception and empirical validation of scalable online adaptive learning environments, offering practical insights for educators, instructional designers, and policymakers aiming to leverage technology for inclusive and effective higher education delivery.