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Title: Utilizing network analysis to explore student qualitative inferential reasoning chains
Over the course of the introductory calculus-based physics course, students are often expected to build conceptual understanding and develop and refine skills in problem solving and qualitative inferential reasoning. Many of the research-based materials developed over the past 30 years by the physics education research community use sequences of scaffolded questions to step students through a qualitative inferential reasoning chain. It is often tacitly assumed that, in addition to building conceptual understanding, such materials improve qualitative reasoning skills. However, clear documentation of the impact of such materials on qualitative reasoning skills is critical. New methodologies are needed to better study reasoning processes and to disentangle, to the extent possible, processes related to physics content from processes general to all human reasoning. As a result, we have employed network analysis methodologies to examine student responses to reasoning-related tasks in order to gain deeper insight into the nature of student reasoning in physics. In this paper, we show that network analysis metrics are both interpretable and valuable when applied to student reasoning data generated from . We also demonstrate that documentation of improvements in the articulation of specific lines of reasoning can be obtained from a network analysis of responses to reasoning chain construction tasks. Published by the American Physical Society2024  more » « less
Award ID(s):
2142276 2142436 2142416 2141975
PAR ID:
10550184
Author(s) / Creator(s):
; ;
Publisher / Repository:
American Physical Society
Date Published:
Journal Name:
Physical Review Physics Education Research
Volume:
20
Issue:
1
ISSN:
2469-9896
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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