Virtual Tools for Developing SCLAs: An Example of Concentration Analysis

Standardized Conceptual Learning Assessments (SCLAs) measure individuals’ conceptual understanding using distractor-driven multiple-choice items. Concentration analysis (CA), a quantitative technique that evaluates the concentrations of each item’s response distribution allowing researchers to determine how many models are triggered by each item, and can be utilized to help establish the validity of distractor driven items. As part of the development of the Fluids Conceptual Evaluation (FCE), a distractor-driven two-tier multiple-choice evaluation instrument, the authors evaluated the concentration factors of a set of responses from the FCE’s preliminary pilot test results. Results of this analysis show how many different mental models are triggered by each item’s first tier. This paper demonstrates how the use of CA verifies recommended models, and suggests a similar model structure for concentration deviation. Recommendations for future use of concentration analysis will be made accordingly. Supported by NSF Award # 2021059 (AAPT), 2021261 (UNE) and 2021273 (UNH).

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Publication Details

Published
2025-10-28
DOI
https://doi.org/10.1119/perc.2025.pr.mason
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Virtual Tools for Developing SCLAs: An Example of Concentration Analysis

Dawn C. Meredith, Rebecca Lindell, James Vesenka, Allen S. Mason et al.
Scientific Computing and Data Management
article

Virtual Tools for Developing SCLAs: An Example of Concentration Analysis

Dawn C. Meredith, Rebecca Lindell, James Vesenka, Allen S. Mason, Daniel Edward Young, Liam G. E. McDermott, Daniel Wagner, Mayuri Gilhooly
article en

Abstract

Standardized Conceptual Learning Assessments (SCLAs) measure individuals’ conceptual understanding using distractor-driven multiple-choice items. Concentration analysis (CA), a quantitative technique that evaluates the concentrations of each item’s response distribution allowing researchers to determine how many models are triggered by each item, and can be utilized to help establish the validity of distractor driven items. As part of the development of the Fluids Conceptual Evaluation (FCE), a distractor-driven two-tier multiple-choice evaluation instrument, the authors evaluated the concentration factors of a set of responses from the FCE’s preliminary pilot test results. Results of this analysis show how many different mental models are triggered by each item’s first tier. This paper demonstrates how the use of CA verifies recommended models, and suggests a similar model structure for concentration deviation. Recommendations for future use of concentration analysis will be made accordingly. Supported by NSF Award # 2021059 (AAPT), 2021261 (UNE) and 2021273 (UNH).

National Science Foundation
Openalex Percentile: Top 70%
Scientific Computing and Data Management
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