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Evaluating Student Proficiency in Quantitative Reasoning

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Title: Evaluating Student Proficiency in Quantitative Reasoning
Language: English
Authors: Gabriel Chavez, Jennifer Clinkenbeard, Tolga Tezcan, Celine Pinet, Jennifer Duggan, George Beckham, Sumadhur Shakya, Christina Zhang
Source: Numeracy. 2026 19(1).
Availability: National Numeracy Network. 906 West 2nd Avenue, Suite 100, Spokane, WA 99201. Tel: 507-222-5239; Web site: https://digitalcommons.usf.edu/numeracy/
Peer Reviewed: Y
Page Count: 25
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Tests/Questionnaires
Education Level: Higher Education
Postsecondary Education
Descriptors: Thinking Skills, Mathematics Skills, Undergraduate Students, Student Attitudes, Self Concept, Learner Engagement
Geographic Terms: California
ISSN: 1936-4660
Abstract: Quantitative Reasoning (QR) competencies are increasingly vital for academic and professional success across disciplines. This study examines the QR proficiency of over 400 undergraduates through a mixed-methods approach, integrating survey-based self-assessments (n = 469) with direct evaluations of final exams (n = 80). This study took place at a public, primarily undergraduate, four-year state university in Northern California with approximate enrollment of 7,500 students. Although students reported frequent engagement in foundational QR tasks--such as calculation and interpretation--rubric-based scoring revealed inconsistent levels of mastery, particularly on higher-order skills like evaluation and coherence. Regression analyses linked confidence to calculation and data visualization abilities but suggested that interpretation may be underappreciated or conflated with other QR dimensions. Qualitative responses emphasized finance-related applications while overlooking broader contexts for quantitative literacy. Limitations of the study include data collection at a single institution, convenience sampling, and utilizing a single artifact type (final exams) for direct assessment. Overall, the findings highlight a need for more explicit instruction and assessment of complex QR tasks, along with curricular design that foregrounds real-world data analysis and problem solving. These results offer practical insights into reinforcing QR education, ultimately supporting students' ability to apply quantitative knowledge meaningfully across diverse contexts.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1495345
Database: ERIC
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  Data: <searchLink fieldCode="SO" term="%22Numeracy%22"><i>Numeracy</i></searchLink>. 2026 19(1).
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  Data: National Numeracy Network. 906 West 2nd Avenue, Suite 100, Spokane, WA 99201. Tel: 507-222-5239; Web site: https://digitalcommons.usf.edu/numeracy/
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  Data: <searchLink fieldCode="DE" term="%22California%22">California</searchLink>
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  Data: 1936-4660
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  Data: Quantitative Reasoning (QR) competencies are increasingly vital for academic and professional success across disciplines. This study examines the QR proficiency of over 400 undergraduates through a mixed-methods approach, integrating survey-based self-assessments (n = 469) with direct evaluations of final exams (n = 80). This study took place at a public, primarily undergraduate, four-year state university in Northern California with approximate enrollment of 7,500 students. Although students reported frequent engagement in foundational QR tasks--such as calculation and interpretation--rubric-based scoring revealed inconsistent levels of mastery, particularly on higher-order skills like evaluation and coherence. Regression analyses linked confidence to calculation and data visualization abilities but suggested that interpretation may be underappreciated or conflated with other QR dimensions. Qualitative responses emphasized finance-related applications while overlooking broader contexts for quantitative literacy. Limitations of the study include data collection at a single institution, convenience sampling, and utilizing a single artifact type (final exams) for direct assessment. Overall, the findings highlight a need for more explicit instruction and assessment of complex QR tasks, along with curricular design that foregrounds real-world data analysis and problem solving. These results offer practical insights into reinforcing QR education, ultimately supporting students' ability to apply quantitative knowledge meaningfully across diverse contexts.
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  Data: 2026
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      – SubjectFull: Mathematics Skills
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      – SubjectFull: Undergraduate Students
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