Understanding Genetic Breast Cancer Risk: Processing Loci of the BRCA Gist Intelligent Tutoring System.

Journal: Learning And Individual Differences
Published:
Abstract

The BRCA Gist Intelligent Tutoring System helps women understand and make decisions about genetic testing for breast cancer risk. BRCA Gist is guided by Fuzzy-Trace Theory, (FTT) and built using AutoTutor Lite. It responds differently to participants depending on what they say. Seven tutorial dialogues requiring explanation and argumentation are guided by three FTT concepts: forming gist explanations in one's own words, emphasizing decision-relevant information, and deliberating the consequences of decision alternatives. Participants were randomly assigned to BRCA Gist, a control, or impoverished BRCA Gist conditions removing gist explanation dialogues, argumentation dialogues, or FTT images. All BRCA Gist conditions performed significantly better than controls on knowledge, comprehension, and risk assessment. Significant differences in knowledge, comprehension, and fine-grained dialogue analyses demonstrate the efficacy of gist explanation dialogues. FTT images significantly increased knowledge. Providing more elements in arguments against testing correlated with increased knowledge and comprehension.

Authors
Christopher Wolfe, Valerie Reyna, Colin Widmer, Elizabeth Cedillos Whynott, Priscila Brust Renck, Audrey Weil, Xiangen Hu
Relevant Conditions

Breast Cancer