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Interest in mathematics = interest in mathematics? What general measures of interest reflect when the object of interest changes

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Abstract

Students’ motivational characteristics, e.g., subject-related interest, are considered important predictors for successful learning processes. However, few empirical studies provide evidence for the assumed chain of effects between high interest and high achievement in mathematics. One reason for this result might be that the applied measures of learners’ interest in mathematics are not well aligned with the characteristics of the learning content in the respective educational settings. At the transition from school to university, the character of mathematics shifts from a strongly application oriented school subject to a scientific discipline. When students are asked to rate their interest concerning mathematics learning in general, it is not clear which character of mathematics they refer to (in their ratings). To provide a more differentiated picture of learners’ interest, we developed questionnaires that survey students’ interest concerning the different characters of mathematics explicitly. With a sample of 323 students from academic mathematics programs, we analysed the quality of the developed scales and whether it is possible to differentiate interest facets according to the different characters of mathematics. In this contribution, we present the development of the instruments. The results of exploratory factor analyses and correlation analyses provide support for the quality of the developed instruments. Our results indicate that indeed the character of mathematics addressed in the questionnaire strongly influences students’ self-reports. Finally, we study how the differentiated interest constructs are related to general ratings of interest in mathematics.

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Notes

  1. Also similar self-concept measures were developed, and an additional type of interest scales that use concrete mathematical tasks as stimuli to situate the interest items (cf. Rach et al., accepted).

  2. FIML: Full Information Maximum Likelihood.

  3. Inclusion of prior knowledge on calculus and secondary school qualification grade did not change the results from model 4. Both new predictors did not show a substantial contribution to variance explanation.

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Authors and Affiliations

  1. Department of Mathematics, LMU Munich, Theresienstr. 39, 80333, Munich, Germany

    Stefan Ufer & Timo Kosiol

  2. Institute of Mathematics, University of Paderborn, Warburger Str. 100, 33098, Paderborn, Germany

    Stefanie Rach

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  1. Stefan Ufer
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  2. Stefanie Rach
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  3. Timo Kosiol
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Correspondence to Stefan Ufer.

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Ufer, S., Rach, S. & Kosiol, T. Interest in mathematics = interest in mathematics? What general measures of interest reflect when the object of interest changes. ZDM Mathematics Education 49, 397–409 (2017). https://doi.org/10.1007/s11858-016-0828-2

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