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Karmol-STEM-Thesis-Revised.pdf (1.19 MB)

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STEM for the Rest of Us: A Fuzzy-Trace Theory-Based Computational Methodology for Textual Comprehension

Karmol, Ann Marie
http://orcid.org/0000-0002-2201-5612
http://rave.ohiolink.edu/etdc/view?acc_num=toledo167084708414288

Abstract Details

2022, Master of Arts, University of Toledo, Psychology - Experimental.
STEM (science, technology, engineering, and mathematics) communication that fosters understanding is as crucial today as it is lacking. More than ever, there is a need for STEM communication that goes beyond 'nudging’ the average layperson toward a target behavior, or simply bombarding them with complex and ill-constructed information. The prevailing ‘nudge-or-bombard' strategies can result in subject knowledge that is at best incomplete and easily forgotten, and at its worst is impoverished, eliciting short-term compliance that can result in distrust of experts and policymakers. Additionally, empirically based communication techniques that go beyond disseminating rote facts to achieving insight are imperative in an oversaturated communication environment wherein laypeople are flooded with more information than they can achieve expertise in, or even comprehend (Scheufele, 2006). The present study aimed to extend existing findings of evidence-based communication grounded in a dual-process model of cognition called Fuzzy-Trace Theory (FTT) into the realm of STEM communication. It also sought to lend further evidence to the use of a new computational textual measurement tool based on FTT that informs the development of effective textual information via assisting individuals in the formation of an overall bottom-line understanding of a text. In the present study, 201 participants were presented with one of two versions of a text on a complex STEM subject matter. Texts were edited systematically using the FTT-based computational methodology to produce either a dense information presentation or one that was manipulated with the goal of increasing understanding by helping participants ‘get the gist’ of the text. Participants then completed two measures that tested their knowledge and comprehension of the text. Additionally, risk perception questionnaires and multiple decision intention tasks were administered that were associated with preparedness for the risks presented in the STEM texts. These additional measures aimed to ascertain whether participants’ relative grasp of the texts affected their concern for the risks involved with the STEM scenarios. Three additional scales were included to assess for possible moderating effects of individual differences, specifically numeracy, cognitive processing style, and consistency of handedness. Results indicated no main effect of text condition on participants’ knowledge of the text, but there was a significant effect of comprehension. All measures of risk perceptions and preparedness intentions were non-significant. Individual difference measures also yielded no significant interaction effects. Interestingly, all results, both significant and descriptive, were opposite of the hypothesized direction wherein the dense informational text yielded higher scores than the ‘gisty’ text that aimed to increase participants’ understanding of the text. Altogether, while the results of the present study were largely non-significant, excepting comprehension, the reversal of all results against the hypothesized direction point to the possibility of an outsized influence of one aspect of the texts—namely Referential Cohesion, a variable associated with semantic and syntactic similarity within a text—that provides a promising avenue for future studies that aim to increase comprehension for complex, technical STEM texts.
JD Jasper (Committee Chair)
86 p.
Experimental Psychology; Psychology; Quantitative Psychology
STEM; science communication; science education; individual differences; numeracy; need for cognition; Fuzzy-trace Theory; computational psychology

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Citations

  • Karmol, A. M. (2022). STEM for the Rest of Us: A Fuzzy-Trace Theory-Based Computational Methodology for Textual Comprehension [Master's thesis, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo167084708414288

    APA Style (7th edition)

  • Karmol, Ann. STEM for the Rest of Us: A Fuzzy-Trace Theory-Based Computational Methodology for Textual Comprehension . 2022. University of Toledo, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo167084708414288.

    MLA Style (8th edition)

  • Karmol, Ann. "STEM for the Rest of Us: A Fuzzy-Trace Theory-Based Computational Methodology for Textual Comprehension ." Master's thesis, University of Toledo, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=toledo167084708414288

    Chicago Manual of Style (17th edition)

toledo167084708414288
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This open access ETD is published by University of Toledo and OhioLINK.