Personalized and Intelligent Agent Based Context-Aware Mobile Learning Framework
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Mobile learning promises the freedom to learn anytime, anywhere. However, effectively integrating personalization within mobile learning environments presents a significant challenge. This research aims to address this challenge by developing a novel framework for personalized content delivery in mobile learning environments (PCDMLE). The proposed PCDMLE framework leverages three key personalization aspects: student preferences, academic level, and assessment unit. By dynamically adapting learning content based on these individual characteristics, the framework aims to enhance student performance and simplify the management of diverse learning needs. To achieve this objective, an in-depth literature review was conducted to identify key personalization aspects within the context of mobile learning. Based on this review, a framework was developed and subsequently validated through an expert review process. A prototype was then developed and evaluated through a six-week experiment. Finally, participant feedback was collected through a survey to assess their evaluation and satisfaction with the framework. The results, derived from both the expert review and participant feedback, demonstrate the framework's effectiveness in delivering personalized content based on the identified aspects. Furthermore, the findings indicate a positive impact on student performance. This research, therefore, contributes significantly to the advancement of personalized content delivery within the mobile learning domain.
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