Outline

Ingegneria Sismica

Ingegneria Sismica

Research on the Application of Human-Computer Interaction in Student Learning Behavior Analysis and Educational Management under Big Data Context

Author(s): Zhaojin Zhang1
1School of Economics and Management, Weinan Normal University, Weinan 714000, Shaanxi, china
Zhang, Zhaojin . “Research on the Application of Human-Computer Interaction in Student Learning Behavior Analysis and Educational Management under Big Data Context.” Ingegneria Sismica Volume 43 Issue 1: 1-14, doi:10.65102/is2026349.

Abstract

With the rapid development of information technology, informatization has become an inevitable trend in modern education. Nowadays, the application of big data and human-computer interaction has brought new ideas and methods to education. This article aims to study the impact of human-computer interaction technology on student learning behavior and educational management in the big data environment. This article selected first-year undergraduate students as the experimental subjects and conducted research using the Zhihuishu online platform as the experimental scenario. The entire experimental cycle included a complete learning cycle, during which students engage in online learning through the Zhihuishu platform. After the end of the learning cycle, a detailed questionnaire survey was conducted on the learning situation of students to collect feedback on the learning process and effectiveness. Moreover, offline interviews were conducted with teachers and students participating in the course to obtain their subjective opinions and experiences. Afterwards, a comprehensive analysis was conducted based on the collected questionnaire data, interview feedback, and learning data on the Zhihuishu platform. The results showed that the Cronbach’s alpha of the survey questionnaire reached 0.931, which was relatively reliable. Combined with the interview results, the new education model significantly improved students’ learning enthusiasm, self-learning ability, and classroom participation. The vast majority of teachers believed that these technologies helped to understand the learning situation of students and optimize the teaching process. Through data analysis, it can be concluded that students who used online interactive platforms to learn courses performed better than traditional teaching, with a 2% to 5% improvement in their daily and test scores compared to traditional offline teaching. They also showed significant effects in self-directed learning and personalized recommendation learning, with 48.4% of students being able to complete online courses more fully and seriously, and 64.8% of students achieving satisfaction in personalized recommendation learning. It is recommended that online education platforms optimize human-computer interaction design, provide training for teachers, and fully tap into technological potential, improving teaching effectiveness and management level.

Keywords
Big Data; Interactive Learning Environment; Online Courses; Learning Behavior; Higher Educational Management Work

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