Repository logo
Communities & Collections
Research Outputs
Fundings & Projects
People
Statistics
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. KMITL
  3. Publication
  4. The effect of the “Prediction-observation-quiz-explanation” inquiry-based e-learning model on flow experience in green energy learning
Loading...
Thumbnail Image

The effect of the “Prediction-observation-quiz-explanation” inquiry-based e-learning model on flow experience in green energy learning

Author(s)
Hong, Jon Chao
Tsai, Chi Ruei
Hsiao, Hsien Sheng
Chen, Po Hsi
Chu, Kuan Cheng
Gu, Jianjun
Sitthiworachart, Jirarat
Date Issued
May 1, 2019
Type
Article
DOI
10.1016/j.compedu.2019.01.009
Abstract
There are several models of inquiry-based learning, some of which may be practiced in experimental classroom teaching, and some of which may be used in online teaching. This study proposes the “prediction-observation-quiz-explanation” (POQE) model to design a green energy generation learning program (i.e., how solar, wind, and water can produce energy) and to test how participants' cognitive-affective factors affect their interest in using this model. A total of 396 technical high school students participated in this experimental study, and 375 valid data were collected and subjected to confirmatory factor analysis with structural equation modelling. The results indicated that incremental belief of intelligence was negatively related to cognitive load, but positively related to green energy learning self-efficacy (GELSE) in practicing POQE. Cognitive load was negatively related to flow experience, while GELSE was positively related to flow experience. Finally, flow experience was positively related to the intention to continue online learning with the POQE model. The implications of this study are that e-learning designers can use this POQE model to develop more educational content for students to learn various concepts.
Citation
Computers and Education, 133, 127-138, 2019
Subjects

e-learning

energy education

inquiry learning mode...

inquiry-based learnin...

Metrics
Get Involved!
  • Source Code
  • Documentation
  • Slack Channel
Make it your own

DSpace-CRIS can be extensively configured to meet your needs. Decide which information need to be collected and available with fine-grained security. Start updating the theme to match your Institution's web identity.

Need professional help?

The original creators of DSpace-CRIS at 4Science can take your project to the next level, get in touch!

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Accessibility settings
  • Privacy policy
  • End User Agreement
  • Send Feedback