Research on the Dissemination and Influencing Factors of Big Data and Artificial Intelligence Related Courses in Colleges and Universities-Taking MOOC as an Example

• Published in: Journal on artificial intelligence Vol. 4; no. 2; pp. 115 - 132
• Main Authors: Junyan, Zhu, Yuguo, Min, Yudi, Li, Xiaoyu, Chen, Yu, Zhou
• Format: Journal Article
• Language: English
• Published: Henderson Tech Science Press 2022
• Subjects: Acceptance; Artificial intelligence; Big Data; CAI; Colleges & universities; Communication; Computer assisted instruction; Construction standards; Curricula; Education; Technology Acceptance Model; Technology utilization
• ISSN: 2579-003X; 2579-0021; 2579-003X
• DOI: 10.32604/jai.2022.030353

The rapid development of information technologies such as artificial intelligence, Internet and big data has promoted the deep integration of technology and education, especially the rise of large-scale online courses, which provides a great opportunity for curriculum teaching reform in colleges and universities. At the same time, artificial intelligence, as a cutting-edge technology, has good development prospects and has become a popular professional course in colleges and universities, artificial intelligence technology has become the focus of subject education in many universities. The combination of online education and AI courses will also greatly enhance the enthusiasm of users and expand the dissemination scope of big data and AI related courses. Based on the grounded theory and technology acceptance model, this paper obtains the users’ perception evaluation of learning MOOC big data and artificial intelligence courses through field interviews, summarizes the core categories, constructs MOOC user acceptance model, collects sample data by questionnaire and makes an empirical study. It is found that perceived usefulness, expectation confirmation and primary communication effect have a significant positive impact on the secondary communication effect, and the content quality and socialization interaction indirectly affect the secondary communication effect of MOOC curriculum by affecting the primary communication effect.