Title of article
LEARNING PREFERENCES ADAPTATION BASED ON THE PERSONALIZED ADAPTIVE GAMIFIED E-LEARNING (PAGE) MODEL
Author/Authors
maher, yara egyptian chinese university - faculty of engineering and technology - department of software engineering and information technology, Cairo, Egypt , moussa, sherin m. ain shams university - faculty of computer and information sciences - department of information systems, Cairo, Egypt , khalifa, m. essam egyptian chinese university - faculty of engineering and technology - department of software engineering and information technology, Cairo, Egypt
From page
32
To page
52
Abstract
Many studies have addressed e-learning, aiming to create a platform for the learning process that completes the traditional classroom work and maximizes the effectiveness of learning outcomes. Gamifying personalized adaptable educational systems have been recently considered to keep the learners motivated and positively progressing in a flow state. However, the current models remain inadequate, providing limited resources for comprehensive learning analytics. In this paper, a theoritical learning preferences adaptation model is proposed based on the Personalized Adaptive Gamified E-learning (PAGE) model. The PAGE model supports blended learning by enforcing the engagement of the traditional learning process’s parties, where effective learning analytics can be sustained to continuously improve the quality of the learning experience. The overall model has been evaluated for its validity through a survey from different perspectives. The overall mean value of the evaluation is 2.77 out of 3. Thus, the evaluation outcomes for the adaptation, gamification, and learning experience of the PAGE model ensure a promising vision for advancements in the learning processes and analytics.
Keywords
educational systems , preferences adaptation , learning preferences , elearning , clustering
Journal title
International Journal of Intelligent Computing and Information Sciences
Journal title
International Journal of Intelligent Computing and Information Sciences
Record number
2748013
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