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Sugden, N., Brunton, R., MacDonald, J., Yeo, M., & Hicks, B. (2021). Evaluating Student Engagement and Deep Learning in Interactive Online Psychology Learning Activities. Australasian Journal of Educational Technology, 37, 45-65.
https://doi.org/10.14742/ajet.6632

has been cited by the following article:

• TITLE: An Empirical Studying: Blended Teaching Design Based on Deep Learning

  AUTHORS: Jin Wang

  KEYWORDS: Deep Learning, Blended Learning, Curriculum Development

  JOURNAL NAME: Creative Education, Vol.14 No.3, March 21, 2023

  ABSTRACT: In this paper, the studying targeted to make a practical application demonstration approach studying based on deep learning elements for the blended teaching and learning within the areas of education. The studying creates a DBTA model of the blended teaching method based on the concept of deeplearning, which enhances the effective consistency of online and offlineteaching activities, and improves the professional competence of students. A questionnaire is designed to verify the feasibility and science of the DBTA model,which obtained valid questionnaires 197 from the education practitioners of high education in G province of mainland China. Through research analysis, the studying gained several practical views, illustrated the applicability of DBTA approach to developingcritical thinking awareness to get high-order thinking and enhance Lifelong-learning ability of students.