Research on Online Learning Behavior Supported by Learning Analysis Technology

Teaching students according to their aptitude and personalized learning are demands of online teaching and learning; and learning analysis methods provide a possible way to achieve this goal. From the perspective of learning, this study adopts the field cognitive style as the basic classification of learners, uses lag sequence analysis to mine learner learning paths and study the relationship between learning paths, learning performance, and the key sequences. The results show that the learners of the two cognitive styles have obvious differences in behavioral sequences, and multiple behavioral sequences have a significant impact on learning performance. Finally, suggestions are put forward to promote personalized development and effective learning behaviors from the aspects of teaching, learning, and platform.