Understanding genetic breast cancer risk: Processing loci of the BRCA Gist Intelligent Tutoring System

作者：Wolfe, Christopher R.^*; Reyna, Valerie F.; Widmer, Colin L.; Cedillos-Whynott, Elizabeth M.; Brust-Renck, Priscila G.; Weil, Audrey M.; Hu, Xiangen

来源：Learning and Individual Differences, 2016, 49: 178-189.

DOI：10.1016/j.lindif.2016.06.009

• Intelligent tutoring system
• Fuzzy-trace theory
• Medical decision-making
• Breast cancer
• Genetic testing

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, (FIT) 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 FIT 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 FIT 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. FIT images significantly increased knowledge. Providing more elements in arguments against testing correlated with increased knowledge and comprehension.

• 出版日期2016-7
• 单位华中师范大学