Teaching Effect Evaluation of Flipped Classroom in Engineering Management Colleges
A Multivariate Ordered Logit Model
DOI:
https://doi.org/10.3991/ijet.v18i20.43875Keywords:
engineering management colleges, flipped classroom, teaching effect, effect evaluation, multivariate ordered Logit modelAbstract
Adapting traditional classroom teaching methods to students’ personalized learning styles and needs can be challenging, resulting in passive learning, low teaching quality, and insufficient support for students’ learning and development. The flipped classroom teaching model integrates information technology (IT) into education, enriches teaching approaches, and emphasizes a student-oriented concept. The flipped classroom can help students deeply understand the content by building upon shallow learning guided by effective teaching strategies. In turn, it facilitates the development of higher-order thinking skills and promotes students’ physical and mental well-being. In this study, five engineering management colleges in Henan Province, China, were surveyed using a questionnaire distributed during the fall semester of 2022–2023. The factors influencing the teaching effect of the flipped classroom were analyzed using a multivariate ordered logit model. Results demonstrated that the questionnaire had a reliability coefficient of 0.844, a KMO value of 0.788, and a Bartlett sphericity test with a corresponding P value of less than 0.01. Several factors, including gender (P = 0.054), self-study ability (P = 0.064), campus network (P = 0.000), teaching resources (P = 0.085), and classroom interaction (P = 0.036), significantly influence the teaching effect of the flipped classroom. The findings of this study provide valuable insights for enriching the teaching management theory of the flipped classroom, helping teachers enhance their management abilities in implementing the flipped classroom, and facilitating convenient teaching and learning experiences for both teachers and students in information technology.
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Copyright (c) 2023 Jia Jia, Jingjing Yang, Li Xue
This work is licensed under a Creative Commons Attribution 4.0 International License.