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. 2017 Fall;16(3):ar45.
doi: 10.1187/cbe.17-03-0043.

The Math-Biology Values Instrument: Development of a Tool to Measure Life Science Majors' Task Values of Using Math in the Context of Biology

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The Math-Biology Values Instrument: Development of a Tool to Measure Life Science Majors' Task Values of Using Math in the Context of Biology

Sarah E Andrews et al. CBE Life Sci Educ. 2017 Fall.

Abstract

In response to calls to improve the quantitative training of undergraduate biology students, there have been increased efforts to better integrate math into biology curricula. One challenge of such efforts is negative student attitudes toward math, which are thought to be particularly prevalent among biology students. According to theory, students' personal values toward using math in a biological context will influence their achievement and behavioral outcomes, but a validated instrument is needed to determine this empirically. We developed the Math-Biology Values Instrument (MBVI), an 11-item college-level self--report instrument grounded in expectancy-value theory, to measure life science students' interest in using math to understand biology, the perceived usefulness of math to their life science career, and the cost of using math in biology courses. We used a process that integrates multiple forms of validity evidence to show that scores from the MBVI can be used as a valid measure of a student's value of math in the context of biology. The MBVI can be used by instructors and researchers to help identify instructional strategies that influence math-biology values and understand how math-biology values are related to students' achievement and decisions to pursue more advanced quantitative-based courses.

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Figures

FIGURE 1.
FIGURE 1.
Validity evidence framework described by Reeves and Marbach-Ad (2016) and the corresponding approaches used to validate the MBVI as a measure of life science majors’ values of math in the context of biology.
FIGURE 2.
FIGURE 2.
Standardized factor loadings of the CFA on the second, independent sample of students (n = 206). The factor variances were set to 1.00 to identify each model. Abbreviations (e.g., Int2) correspond to the items in Table 3.

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