Analysis and Satisfaction Evaluation of Online Learning Based on Artificial Intelligence

Huang Li
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Huang Li: Hunan Mass Media Vocational and Technical College, China

International Journal of Information Systems in the Service Sector (IJISSS), 2022, vol. 14, issue 3, 1-19

Abstract: Innovative technology represented by artificial intelligence drives the change of educational concept and practice, the transformation of learning environment and teaching methods to intelligence, and online learning enters the era of learner sovereignty. In this paper, rough set algorithm is used to build an online learning quality evaluation index system, and online learning quality and satisfaction are evaluated and analyzed based on artificial intelligence. The results show that the accuracy of rough set algorithm is the highest, and the recall rate of rough set algorithm is the highest in different data sets, showing an overall upward trend, the highest recall rate is 93.58%. The weight percentages of the first-level indicators are curriculum environment experience (15%), of curriculum content experience (38%), of curriculum activity experience (26%), curriculum interaction experience (6%) and learning effect experience(15%). The corresponding evaluation scores are reflected accordingly, which can objectively describe the online quality evaluation.

Date: 2022
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