Document Type
Article
Publication Date
10-11-2022
Abstract
This study explored an alternative assessment model to examine Chemistry learners’ progress. “The Assessment of Problem-Solving in Chemistry Learning” as a model represented students’ mastery of chemistry study. The data were from journaling narratives and analyzed through cognitive task analysis. Based on the analyses, a student model was established, which represents the qualitative information in a structure, and provides a potential framework of the assessment model for the quantitative representation—a Bayesian network assessment model. The student’s performance was assessed via the Bayesian network assessment model, and classified into three categories: low level, middle level, and high level. The mastery level should be at least scored at and above 90.51/100 for Declarative, Procedural, and Strategic Knowledge respectively.
Recommended Citation
Zhang, Z., & Guanzon, A. (2022). A Mixed Assessment for the Science Learning via a Bayesian Network Representation. Journal of Education and Development, 6(5), 1. https://doi.org/10.20849/jed.v6i5.1309
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication Title
Journal of Education and Development
Comments
Copyright for this article is retained by the author(s), with first publication rights granted to the journal.