Design and Research of Blended Collaborative Learning Model for Deep Learning | IEEE Conference Publication | IEEE Xplore

Design and Research of Blended Collaborative Learning Model for Deep Learning


Abstract:

Deep learning and collaborative learning are widely favored because they emphasize learners' creativity, critical thinking, problem-solving, and collaborative communicati...Show More

Abstract:

Deep learning and collaborative learning are widely favored because they emphasize learners' creativity, critical thinking, problem-solving, and collaborative communication skills to foster the development of their higher-order thinking. However, in practical teaching applications, the specific teaching mode and implementation are highly dependent on teachers' innovative ability, especially in the cultivation of students' implicit higher-order thinking, which still lacks a good focus. In the context of the current era of rapid development of information technology, the development of information-based education promotes the transformation of education, and various education systems at all levels have put forward new requirements for the cultivation of high-quality talents. Therefore, this study summarizes and analyzes the theoretical research and application status of blended learning and collaborative learning, and integrates the advantages of blended learning and collaborative learning to promote the occurrence of deep learning. The Blended Collaborative Learning for Deep Learning model (DECBL) with the advantages of situationality and innovation. As a new teaching mode, The Blended Collaborative Learning for Deep Learning model (DECBL) can solve the dilemma of teachers in choosing the inherent teaching mode and realize the cultivation of students' higher-order thinking and The improvement of comprehensive ability is also of reference value for how to build a teaching model supported by information technology and make better use of information technology to improve the quality of classroom teaching.
Date of Conference: 16-18 March 2023
Date Added to IEEE Xplore: 28 April 2023
ISBN Information:
Conference Location: Chongqing, China

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