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This talk presents a network analysis of group exam data from a two-class introductory physics sequence. In each class, on each of four exams, students took the exam individually and then reworked it with classmates. Students recorded their collaborators before submitting the exam, and these reports are used to build directed networks. The networks are partitioned using positional analysis, which uses similarities in linking behavior to detect blocks of actors in a network. By calculating block structure for each exam and mapping over time, it is possible to see a stabilizing social structure over the two semesters. Some students find a coherent group immediately, while others take longer, but almost all settle into a regular set of collaborators by the second semester. We will discuss this evolving block structure, what it suggests about the social positions available to students in the classes, and how network position connects to exam grades.

AAPT WM 21

Social Positions in Group Exam Networks

group exams

network analysis

introductory physics

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technical paper

We have developed a multiple-choice test for measuring students’ quantitative literacy in the context of physics (Physics Inventory of Quantitative Literacy, PIQL). Items were created based on the framework of conceptual blending in which students’ mathematical reasoning and conceptual physics understanding cannot necessarily be separated. As such, we include several multiple-choice/multiple-response (MCMR) items to which students may select as many answer choices as they think are correct. Common factor analysis techniques for identifying groups of items that share common traits are inappropriate because these methods require MCMR items to be scored dichotomously, which destroys the rich information available in students’ response pattern. As an alternative, we use Modified Module Analysis (MMA) to identify communities based on networks of correlations between answer choices. We present the results from using MMA to analyze networks of correct responses to PIQL items, networks of incorrect responses, and networks of all responses combined.

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Freedom, Innovation, and Makerspaces; creating new campus realities.

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"5-Star" Student Self-Assessment for Online Homework Solutions in General Physics

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Social Positions in Group Exam Networks

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Examining Response Patterns to Multiple-Response Items Using Module Analysis

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