JOURNAL ARTICLE

Optimization measures for students' autonomous learning based on deep learning and human-computer interaction technology.

  • Published In: Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.), 2024, v. 24, n. 4/5. P. 3079 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Chen, Yi; Lin, Xiaopin; Li, Zheng 3 of 3

Abstract

This article focuses on the development and evaluation of a micro-video teaching model based on Human-Computer Interaction (HCI) technology to enhance students' autonomous learning and overall learning outcomes. The model integrates interactive micro-videos with teaching resources, processes, and evaluations, aiming to increase student engagement, motivation, and independent learning abilities. An eight-week experimental study involving two middle school classes demonstrated that the HCI-based micro-video approach significantly improved students' autonomous learning skills, assignment performance, knowledge test scores, satisfaction, and interaction frequency compared to traditional non-interactive micro-videos. The study suggests that incorporating HCI into micro-video teaching can effectively support online education, though further research is needed to optimize the model and assess its applicability across different disciplines.

Additional Information

  • Source:Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.). 2024/09, Vol. 24, Issue 4/5, p3079
  • Document Type:Article
  • Subject Area:Education
  • Publication Date:2024
  • ISSN:1472-7978
  • DOI:10.3233/JCM-247554
  • Accession Number:179090216
  • Copyright Statement:Copyright of Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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