The Correlation Between Teachers' Visual Digital Media Design Ability and Effective Teaching

Authors

  • Lin Shao Hebei Vocational University of Technology and Engineering
  • Wendi Zhang Hebei Vocational University of Technology and Engineering
  • Aiping Li Hebei Vocational University of Technology and Engineering
  • Feng Xin Shaanxi University of Science and Technology

DOI:

https://doi.org/10.3991/ijet.v17i01.28717

Keywords:

digital media design, teacher quality, effective teaching, correlation analysis

Abstract


Enhancing teachers' visual digital media design ability is conductive to improving the effectiveness of classroom teaching of art design major. Thoroughly exploring, discussing, and studying the correlation between teachers' visual digital media design ability and effective teaching is a requirement for the professional development of art design teachers, and it is a very meaningful job for cultivating high-quality art design professionals. To this end, this paper aims to study the correlation between teachers’ visual digital media design ability and effective teaching. At first, this paper constructed an Evaluation Index System (EIS) for evaluating teachers’ visual digital media design ability, and gave the calculation methods and steps of the evaluation model based on the entropy weight TOPSIS method; then, the paper employed a Bayesian Convolutional Neural Network (BCNN) and made predictions on the multi-dimensional contribution of teachers' visual digital media design ability to effective teaching through the fusion of evaluation elements. At last, the effectiveness of the constructed EISs and models was verified by experimental results.

Cover ijET Vol. 17 No. 01 (2022)

Downloads

Published

2022-01-20

How to Cite

Shao, L., Zhang, W., Li, A., & Xin, F. (2022). The Correlation Between Teachers’ Visual Digital Media Design Ability and Effective Teaching. International Journal of Emerging Technologies in Learning (iJET), 17(01), pp. 254–269. https://doi.org/10.3991/ijet.v17i01.28717

Issue

Vol. 17 No. 01 (2022)

Section

Papers

License

Copyright (c) 2021 Nan Zhang (Submitter); Lin Shao, Wendi Zhang, Aiping Li, Feng Xin

Creative Commons License

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

The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution Licence (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
By submitting an article the author grants to this journal the non-exclusive right to publish it. The author retains the copyright and the publishing rights for his article without any restrictions.