A WEB-BASED TUTORIAL TO PREVENT OBESITY GROUNDED IN FUZZY-TRACE THEORY IMPROVES KNOWLEDGE, GIST COMPREHENSION, AND HEALTHY VALUES

Purpose: GistFit is an Intelligent Tutoring System grounded in Fuzzy-Trace Theory (FTT) designed to increase knowledge, comprehension and values that support healthy lifestyles among women with the long-term goal of reducing obesity and improving health. 

Method: We used Sharable Knowledge Objects to create GistFit, which helps women form "gist mental representations" of healthy eating, exercise, and other health-related information. A two-group repeated measures randomized controlled experiment was conducted to assess the effectiveness of the obesity prevention tutorial. Participants (251 undergraduate women) were randomly assigned to either GistFit or a control. Groups did not differ more than chance on baseline characteristics.  The experimental group was further divided into three levels where participants engaged with the tutorial on either none, some, or all on multiple choice and analytic questions embedded within the tutor. Knowledge was assessed with 22 multiple-choice questions assessing specific content about nutrition, nutrition labels, and exercise (α=0.65); and another 22 multiple-choice questions assessing gist knowledge about nutrition, nutrition label, and exercise (α=0.68). A measure of gist comprehension was constructed to assess understanding of tutorial information about nutrition and exercise (α=0.87).  Gist principles were assessed with 57 general simple healthy values and principles that were organized according to three subscales on lifestyle (α=0.95), nutrition (α=0.92), and exercise (α=0.87).  

Result: GistFit participants scored significantly higher than controls on verbatim and gist knowledge [F (3, 216) = 7.10, p < .001, ηp2 = .09, and F (3, 216) = 3.07, p = .029, η_p² = .04].   Moreover, GistFit participants who produced more correct answers to multiple-choice questions embedded within the tutorial showed even better subsequent performance on gist knowledge [r (32) = .55, p = .001] and gist comprehension [r (32) = .45, p = .01].  Interacting with the tutorial also corresponded to increased endorsement of gist lifestyle principles [r (220) = .14, p = .04]. 

Conclusion: Participants demonstrated increased learning outcomes after engaging with GistFit.  Additionally, the more participants engaged and interacted with the tutorial the better their learning outcomes.  Engaging in tutorial dialogues improved knowledge of obesity prevention and the transfer of that knowledge. Results are explained by FTT mechanisms highlighting the distinction between verbatim recall and gist-based intuition. GistFit encourages productive thinking and helps learners make meaningful inferences that go beyond rote memorization.