Keywords
Superstar platform
Online learning behavior
Analyzing technical indicators
Research
Submitted : 2024-05-05
Accepted : 2024-05-20
Published : 2024-06-04
Abstract
Objective: To analyze the technical indexes of students’ online learning behavior analysis based on Kirkman’s evaluation model, sort out the basic indexes of online learning behavior, and extract scientific and efficient evaluation indexes of online learning effect through statistical analysis. Methods: The online learning behavior data of Physiology of nursing students from 2021–2023 and the first semester of 22 nursing classes (3 and 4) were collected and analyzed. The preset learning behavior indexes were analyzed by multi-dimensional analysis and a correlation analysis was conducted between the indexes and the final examination scores to screen for the dominant important indexes for online learning effect evaluation. Results: The study found that the demand for online learning of nursing students from 2021–2023 increased and the effect was statistically significant. Compared with the stage assessment results, the online learning effect was statistically significant. Conclusion: The main indicators for evaluating and classifying online learning behaviors were summarized. These two indicators can help teachers predict which part of students need learning intervention, optimize the teaching process, and help students improve their learning behavior and academic performance.
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