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

Authors

Zhidong Zhang, The University of Texas Rio Grande Valley

Document Type

Article

Publication Date

5-2022

Abstract

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.

Comments

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

Recommended Citation

Zhang, Z. (2022). A mixed methods design for assessing physics learning in the online learning environment. Journal of Education and Development, 6(2), 1. https://doi.org/10.20849/jed.v6i2.1142

Creative Commons License

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

Publication Title

Journal of Education and Development

DOI

10.20849/jed.v6i2.1142