A Personalized Learning Path Recommendation Method Incorporating Multi-Algorithm

• DOI: 10.3390/app13105946
• Publication Date: 2023-05-12T05:30:29Z
• Authors: Yongjuan Ma; Lei Wang; Jiating Zhang; Fengjuan Liu; Qiaoyong Jiang
• Keywords: Personalized Learning; Proactive learning; Instance-based learning; Adaptability

In this era of intelligence, the learning methods learners have substantially changed. Many choose to learn through online education platforms. Although may enjoy more high-quality educational resources, when they are faced with an abundance resource information, prone become lost in knowledge, among other problems. To solve problem, a multi-algorithm collaborative, personalized, path recommendation model is proposed provide guidance for First, learner constructed from four perspectives: cognitive level, ability, style, and intensity. Second, association rule algorithm employed generate sequence knowledge points plan learners. Last, swarm intelligence utilized ensure that each point matched personalized resources higher degree adaptability so can using targeted approach. The experimental results show research paper can, certain extent, recommend ideal paths target users, effectively improve accuracy recommended thus quality effect users.