The integration of AI in education, particularly in adaptive learning, emphasizes the critical
need for automatic detection of individual learning styles. Traditional methods such as tests …

Learning systems, whether traditional or computerized ones, often have a teacher-based
design and use a “one-size-fits-all” approach. This approach ignores learners' differences …

The accessibility and popularity of online learning have aided the spread of modern learning
systems, which provide numerous opportunities for studying the behavior of learners and …

The increasingly widespread online education recently enabled a new form of teaching,
learning, and overall educational outcome. However, the need of personalization is required …

In smart education, adaptive e-learning systems personalize the educational process by
tailoring it to individual learning styles. Traditionally, identifying these styles relies on …

Adaptive e-learning systems (AeLS), which emerged in the late 1990s, offer an alternative to
the'one-size-fits-all'approach by addressing the demand for individualized learning …

Student's learning style was identified and considered a critical factor in personalizing the
learning process to meet student's learning preferences, specifically in intelligent e-learning …

With the advancements in technology and the growing demand for online education, Virtual
Learning Environments (VLEs) have experienced rapid development in recent years. This …

Predicting student performance is crucial for improving students' future academic
achievements. Within student groups, common characteristics can reveal trends in overall …

Different approaches or ways of learning are referred to as learning styles. Learning styles
are identified to help educators understand how students learn and to help students become …