Design And Application Of Online Collaborative Learning For Deep Learning

In the era of information technology,online collaborative learning has become an important way of learning and is widely applied.However,due to the lack of effective learning strategies and methods,online collaborative learning is often only formal and superficial,and learners cannot effectively participate in deep interaction activities,and it is difficult to achieve the deep learning state in online collaboration.As an effective regulation strategy,socially shared regulation can facilitate collaborative learning in various dimensions such as cognition,metacognition,motivation and emotion,which provides a new perspective for solving the problems existing in online collaborative learning and promoting learners’ effective deep learning.Therefore,this study integrates the socially shared regulation theory into the online collaborative learning process,designs online collaborative learning activities based on socially shared regulation and develops corresponding shared regulation learning scaffolds,so as to help learners better participate in collaborative learning and ultimately achieve deep learning effects.Firstly,this study used the literature analysis method to review the the current domestic and international research status of online collaborative learning,deep learning and socially shared regulation theory,analyzed the problems existing in online collaborative learning and effective strategies to promote deep learning and explored the feasibility of integrating socially shared regulation into online collaborative learning activities to promote learners’ deep learning.Secondly,the process of online cooperative learning was analyzed from the perspective of shared regulation,and the model of online cooperative learning based on shared regulation was designed and the corresponding regulatory support was provided.Finally,the activity model was tested and iterated through one round of pre-experiment and two rounds of formal experiments in an online course at a university in East China,during which the learners’ deep learning ability and metacognitive level pre and post-test questionnaires,process interaction data and interview data were collected,and the learners’ deep learning effect was evaluated through social epistemic network signature.The result shows that the online collaborative learning activity model based on socially shared regulation and related shared regulation scaffolds designed in this study can effectively promote learners’ deep learning in the three domains of self,interpersonal and cognitive.Specifically,the self domain can significantly improve learners’ deep learning ability and metacognitive level;the interpersonal domain can effectively promote the overall level of interaction among groups,resulting in closer interaction and more balanced participation among group members;and the cognitive domain can improve learners’ academic performance,improve the quality of group interaction and knowledge construction,and promote the complex and advanced cognitive development of the group.The study brings new perspectives to the design of online collaborative learning activities and deep learning evaluation,expands the research field of socially shared regulation.The designed online collaborative learning activity model and related regulation scaffolds also provide guidance and reference for the organization and implementation of learning activities.