Due to the unprecedented supply of knowledge in the online learning environment, the phenomenon of learning trek and knowledge overload is inevitable, resulting in soaring learning costs and low learning efficiency. According to the connectivism learning theory, knowledge graph theory and heat map theory, the relationship between knowledge nodes is fully explored and the heat map idea is introduced into the knowledge graph. A knowledge graph model with heat features is proposed. The model focuses on the integrity of the knowledge framework and clarifies the connections between knowledge nodes, especially by increasing the popularity information of the learning path and expressing the strength of the association between knowledge nodes. Finally, a personalized online learning system based on WeChat is designed and implemented. The "Data Structure" course is taken as an example to verify that the model helps learners to solve learning trek, reduce learning costs and improve learning efficiency.

CICTP