<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The steady growth of online education in Chinese higher education, despite its drawbacks, underscores an increasing interest in digital learning platforms. This study proposes enhancements to the Paragraph Vector, Stacking classifiers, and ZEN semantic coders to construct accurate learner profiles, facilitating personalized online education. By applying these improved models, universities can adapt their online courses more effectively, as demonstrated by case study analyses. Performance data for a sample of college students shows a concentration of scores between 80 and 90, with an average of 84.01, suggesting moderate academic achievement. Engagement metrics, particularly in educational experience richness, scored highest at 3.7854, with all engagement scores averaging above 3, indicating a strong engagement in the learning process.</p>
</abstract>

The steady growth of online education in Chinese higher education, despite its drawbacks, underscores an increasing interest in digital learning platforms. This study proposes enhancements to the Paragraph Vector, Stacking classifiers, and ZEN semantic coders to construct accurate learner profiles, facilitating personalized online education. By applying these improved models, universities can adapt their online courses more effectively, as demonstrated by case study analyses. Performance data for a sample of college students shows a concentration of scores between 80 and 90, with an average of 84.01, suggesting moderate academic achievement. Engagement metrics, particularly in educational experience richness, scored highest at 3.7854, with all engagement scores averaging above 3, indicating a strong engagement in the learning process.

Research on Online Education Teaching Mode of Colleges and Universities Based on Internet Technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

The steady growth of online education in Chinese higher education, despite its drawbacks, underscores an increasing interest in digital learning platforms....

Research on Online Education Teaching Mode of Colleges and Universities Based on Internet Technology

Online veröffentlicht: 03. Mai 2024

Seitenbereich: -

Eingereicht: 11. Apr. 2024

Akzeptiert: 23. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-0995

Schlüsselwörter
Learner profiling, Classifier in Stacking, ZEN semantic coder, Learning engagement, Online education teaching model

© 2024 Jia Chen, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Research on Online Education Teaching Mode of Colleges and Universities Based on Internet Technology

Online veröffentlicht: 03. Mai 2024

Seitenbereich: -

Eingereicht: 11. Apr. 2024

Akzeptiert: 23. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-0995

SchlüsselwörterLearner profiling, Classifier in Stacking, ZEN semantic coder, Learning engagement, Online education teaching model

© 2024 Jia Chen, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Learner profiling, Classifier in Stacking, ZEN semantic coder, Learning engagement, Online education teaching model