A Mixed Methods Design for Assessing Physics Learning in the Online Learning Environment

Zhidong Zhang


This study explored a Bayesian assessment model for physics students in motion learning. The simulated data was applied in examination of the Bayesian assessment model, The study used a mixed-methods design. The exploratory sequential model was developed based on a motion learning student model, which was a structured data collection template. The combination of the student model and the Bayesian network model provided an assessment tool for assessing physics students’ learning in a dynamic process. The study reported that there were three different patterns for a physics student motion learning: lower performance, middle performance, and higher performance. In each pattern, the students may have different performance combinations of the twelve bottom components. These are shown in Figure 4 and used to collect students’ performance data.

Full Text:


DOI: https://doi.org/10.20849/jed.v6i2.1142


  • There are currently no refbacks.

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

Journal of Education and Development  ISSN 2529-7996 (Print)  ISSN 2591-7250 (Online)

Copyright © July Press

To make sure that you can receive messages from us, please add the 'julypress.com' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.