Semantic Network Analysis of Achievement Standards in Physics of 2022 Revised Curriculum

TL;DR

This study uses semantic network analysis to examine the 2022 physics achievement standards, revealing key insights about content focus, connectivity issues, and curriculum adequacy, suggesting improvements for better subject integration.

Contribution

It applies semantic network analysis to curriculum standards, uncovering structural issues and providing data-driven recommendations for curriculum enhancement.

Findings

Keywords focus on scientific thinking and practices, increasing with grade level.

Lack of connection between achievement standards and physics content.

Achievement standards for 'Integrated Science' are insufficient due to reduced curriculum volume.

Abstract

We investigate semantic networks of achievement standards for physics subjects in the 2022 revised curriculum to derive information embedded in the curriculum. We extract each subject's keywords with node strength and random-walk betweenness, detect communities of physics terms by the optimized greedy algorithm, and find the connectivity of physics subjects using bipartite networks. The network analysis reveals three remarkable results: First, keywords are about scientific thinking and practices, evolving to a higher level as the grades increase. Second, there is a lack of connection to learning content in physics. Lastly, achievement standards for 'Integrated Science' are inadequate to fulfill the intended purpose of the curriculum. This is attributed to the reduced learning volume in the 2022 revised curriculum. Our study implies that the curriculum and achievement standards should be improved for the better connectivity of subjects.