Abstract
The interactive mode in e-learning can effectively stimulate students' learning motivation, especially the way of video questioning as the mainstream interactive mode of e-learning video, which is conducive to improve students' enthusiasm to participate in learning and enhance learning thinking. This study constructs a theoretical model of the impact of E-learning behavior on Students' learning effect, and analyzes the impact of video bullet problem as an intermediary variable on E-learning behavior on students' learning effect. The results show that the overall Cronbach of the questionnaire α the coefficient is 0.883 and Kaiser – Meyer – Olkin value is 0.822, indicating that the questionnaire has good reliability and validity. The research results of this study provide reference suggestions for exploring the main influencing factors of learning behavior, improving the effect of students' online learning, revealing the optimization strategy of video bullet problem feedback under the network teaching environment, and the production of bullet problem interactive video.
Highlights
To date, with the rapid rise of online education platforms, online learning and ubiquitous learning have become the mainstream forms of e-learning, favored by students, and strongly supported by teachers
Affected by the global epidemic, major online teaching platforms have strengthened integration with traditional offline classroom teaching through massive open online course (MOOCs) and other forms
Learning effect refers to the qualitative changes in cognition, technology, and skills caused by learners after learning knowledge or completing learning tasks
Summary
With the rapid rise of online education platforms, online learning and ubiquitous learning have become the mainstream forms of e-learning, favored by students, and strongly supported by teachers. More online learning platforms have developed the learning situation analysis function to analyze the relationship between students’ learning behavior and learning effect with the support of information technologies, such as big data and artificial intelligence, and send the analysis results to the school, so as to facilitate the school to formulate more scientific and reasonable plans during online learning. After the online learning is widely used, many students’ learning record data will be produced These data need to be further analyzed and summarized by using information-based teaching methods and fed back to students and teachers. We can obtain the learning preferences of individual learners and the laws of learners’ group learning behavior through the analysis and statistics of these data This process provides a favorable support for the scientific and reasonable management of online learners’ learning behavior and makes online education more scientific and humanized. The interaction in the learning video will enhance learners’ understanding of the learning content
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