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Research on the Application of Curriculum Knowledge Point Recommendation Algorithm Based on Learning Diagnosis Model

机译:基于学习诊断模型的课程知识点推荐算法的应用研究

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Because the degree of mastering knowledge points in courses in traditional cognitive diagnostic models cannot be probabilistic, there are only two situations: mastery and non-mastery. Therefore, for the current research, the recommendations of knowledge points recommended by learners' learning behavior attributes are not fully considered to be insufficient, this paper proposes a curriculum knowledge point recommendation algorithm model based on learning diagnosis, the model comprehensively considers the learner's learning emotions, learner problem test conditions and knowledge point characteristics, and the film and television synthesis in the Chaoxing online teaching service platform the course learning data is tested to verify the effectiveness of the recommendation algorithm. The experimental results show that the effectiveness and accuracy of the recommendation algorithm model proposed in this paper can meet the learning needs of learners.
机译:由于传统认知诊断模型中课程的掌握知识点的程度不可能是概率性的,因此只有两种情况:精通和非精通。因此,对于当前的研究,学习者的学习行为属性所推荐的知识点的推荐还没有完全被认为是不足的,本文提出了一种基于学习诊断的课程知识点推荐算法模型,该模型综合考虑了学习者的学习情绪,学习者问题测试条件和知识点特征,以及在潮兴在线教学服务平台中的影视综合测试课程学习数据,以验证推荐算法的有效性。实验结果表明,本文提出的推荐算法模型的有效性和准确性可以满足学习者的学习需求。

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