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When do spatial abilities support student comprehension of STEM visualizations?

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Abstract

Spatial visualization abilities are positively related to performance on science, technology, engineering, and math tasks, but this relationship is influenced by task demands and learner strategies. In two studies, we illustrate these interactions by demonstrating situations in which greater spatial ability leads to problematic performance. In Study 1, chemistry students observed and explained sets of simultaneously presented displays depicting chemical phenomena at macroscopic and particulate levels of representation. Prior to viewing, the students were asked to make predictions at the macroscopic level. Eye movement analyses revealed that greater spatial ability was associated with greater focus on the prediction-relevant macroscopic level. Unfortunately, that restricted focus was also associated with lower-quality explanations of the phenomena. In Study 2, we presented the same displays but manipulated whether participants were asked to make predictions prior to viewing. Spatial ability was again associated with restricted focus, but only for students who completed the prediction task. Eliminating the prediction task encouraged attempts to integrate the displays that related positively to performance, especially for participants with high spatial ability. Spatial abilities can be recruited in effective or ineffective ways depending on alignments between the demands of a task and the approaches individuals adopt for completing that task.

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Notes

  1. We found no effects of chemistry knowledge quiz scores on any of the outcome measures of interest. Controlling for scores on the chemistry quiz also did not account for any of the relationships discussed in the results section. Accordingly, we will not be discuss the quiz data further.

  2. There are other potential concerns with this answer, including the fact that the air does not take up all of the empty space in the container. Also, the answer appears to attribute intentionality to the NO2 gas, which is inappropriate. While these issues are important, we were mainly interested in whether participants understood the target concept regarding molecular motion that is largely unrelated to these issues.

  3. If included in the factor analysis, scores on the hidden patterns test loaded on the same factor as the MRT, ROT, and GVVT. However, the factor loading was low (.20), and including hidden patterns scores reduced the fit of the model to account for only 51.53% of the variance. Given these results and the theoretical justification for considering hidden patterns as a separate construct, we excluded it from the spatial abilities factor score.

  4. In Study 2, we observed that spatial visualization ability was related to both the chemistry knowledge quiz, t(79) = 6.48, p < .001, and TOLT scores, r(81) = .42, p < .001. However, these variables did not relate significantly to the outcome variables of interest, and controlling for either of these variables did not account for the relationships between spatial visualization ability and the outcome variables. Accordingly, neither the chemistry knowledge quiz nor TOLT scores will be discussed further in Study 2.

  5. As with Study 1, scores on the hidden patterns test loaded on the same factor as the MRT, ROT, and GVVT. However, the factor loading was low (.19), and including hidden patterns scores reduced the fit of the model to account for only 50.87 % of the variance. Thus, we again excluded it from the spatial abilities factor score.

  6. It is surprising that we did not replicate this pattern. However, the replication of the eye tracking data indicates that the prediction task did direct attention toward the videos. Based on Study 1 and previous research (Williamson and Abraham 1995; Williamson et al. 2012), this processing strategy is not optimal. We also note that spatial visualization ability was not positively related to performance in the prediction condition, in contrast to prior research demonstrating generally positive relationships between spatial abilities and learning from visualizations.

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Acknowledgments

This work was funded by REESE grants #0907780 and #0908130 from the National Science Foundation to PIs Dr. David N. Rapp and Dr. Mary Jane Shultz.

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Authors and Affiliations

  1. Department of Psychology and School of Education & Social Policy, Northwestern University, 2120 Campus Drive, Evanston, IL, 60208, USA

    Scott R. Hinze & David N. Rapp

  2. Department of Chemistry, Texas A&M University, College Station, TX, USA

    Vickie M. Williamson

  3. Department of Chemistry, Tufts University, Medford, TX, USA

    Mary Jane Shultz

  4. Department of Construction Science, Texas A&M University, College Station, TX, USA

    Kenneth C. Williamson

  5. Department of Chemistry, University of New Brunswick, Fredericton, Canada

    Ghislain Deslongchamps

Authors
  1. Scott R. Hinze
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  2. Vickie M. Williamson
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  3. Mary Jane Shultz
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  4. Kenneth C. Williamson
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  5. Ghislain Deslongchamps
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  6. David N. Rapp
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Corresponding author

Correspondence to David N. Rapp.

Additional information

This article is part of the special issue on “Spatial Learning and Reasoning Processes,” guest-edited by Thomas F. Shipley, Dedre Gentner.

Handling editor: Thomas F. Shipley.

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Hinze, S.R., Williamson, V.M., Shultz, M.J. et al. When do spatial abilities support student comprehension of STEM visualizations?. Cogn Process 14, 129–142 (2013). https://doi.org/10.1007/s10339-013-0539-3

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