Abstract

Collaborative learning allows students to pool their knowledge, skills, and experiences to better understand and learn from one another. Two of the most fundamental features of collaborative learning are the grouping of students and the gaining of knowledge through social interactions with peers. The term “blended learning” refers to a new approach to education that combines conventional and contemporary learning models, in which students' interaction with and education from their digital devices does not totally replace their interaction and education from their traditional teachers. However, there are a number of obstacles that prevent educators from fully grasping blended learning models and putting them into practice. There have been a number of difficulties in implementing blended learning models due to the varying degrees to which they are accepted and used. In this article, we talked about collaborative learning data analysis since it helps teachers determine if their pedagogical approaches are working and where they may be strengthened. These results have the potential to contribute to a more comprehensive knowledge of (Artificial Intelligence in Education) AIED and its consequences for educational policies, educational AI design, and instructional design geared toward improving (The School Advisory Council) SAC in education.

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