Effects of Choice Restriction on Accuracy and User Experience in an Internet-Based Geopolitical Forecasting Task.

Large-scale geopolitical forecasting tournaments have emerged in recent years as effective testbeds for conducting research into novel forecasting tools and methods. A challenge of such tournaments involves the distribution of forecasting load across forecasters, since there are often more forecasting questions than an individual forecaster can answer. Intelligent load distribution, or triage, may therefore be helpful in ensuring that all questions have sufficient numbers of forecasts to benefit from crowd-based aggregation and that individual forecasters are matched to the questions for which they are best suited.

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

The Intelligent Tutoring System helps women understand and make decisions about genetic testing for breast cancer risk. is guided by Fuzzy-Trace Theory, (FTT) and built using AutoTutor Lite. It responds differently to participants depending on what they say.

Active engagement in a web-based tutorial to prevent obesity grounded in Fuzzy-Trace Theory predicts higher knowledge and gist comprehension.

We used Sharable Knowledge Objects (SKOs) to create an Intelligent Tutoring System (ITS) grounded in Fuzzy-Trace Theory to teach women about obesity prevention: GistFit, getting the gist of healthy eating and exercise. The theory predicts that reliance on gist mental representations (as opposed to verbatim) is more effective in reducing health risks and improving decision making. Technical information was translated into decision-relevant gist representations and gist principles (i.

The effectiveness of argumentation in tutorial dialogues with an Intelligent Tutoring System for genetic risk of breast cancer.

BRCA Gist is an Intelligent Tutoring System that helps women understand issues related to genetic testing and breast cancer risk. In two laboratory experiments and a field experiment with community and web-based samples, an avatar asked 120 participants to produce arguments for and against genetic testing for breast cancer risk. Two raters assessed the number of argumentation elements (claim, reason, backing, etc.

Tutorial dialogues and gist explanations of genetic breast cancer risk.

The intelligent tutoring system (ITS) BRCA Gist is a Web-based tutor developed using the Shareable Knowledge Objects (SKO) platform that uses latent semantic analysis to engage women in natural-language dialogues to teach about breast cancer risk. BRCA Gist appears to be the first ITS designed to assist patients' health decision making. Two studies provide fine-grained analyses of the verbal interactions between BRCA Gist and women responding to five questions pertaining to breast cancer and genetic risk.

Efficacy of a web-based intelligent tutoring system for communicating genetic risk of breast cancer: a fuzzy-trace theory approach.

Background: . Many healthy women consider genetic testing for breast cancer risk, yet BRCA testing issues are complex.

Objective: .

A signal detection analysis of gist-based discrimination of genetic breast cancer risk.

Pervasive biases in probability judgment render the probability scale a poor response mode for assessing risk judgments. By applying fuzzy trace theory, we used ordinal gist categories as a response mode, coupled with a signal detection model to assess risk judgments. The signal detection model is an extension of the familiar model used in binary choice paradigms.

The development and analysis of tutorial dialogues in AutoTutor Lite.

The goal of intelligent tutoring systems (ITS) that interact in natural language is to emulate the benefits that a well-trained human tutor provides to students, by interpreting student answers and appropriately responding in order to encourage elaboration. BRCA Gist is an ITS developed using AutoTutor Lite, a Web-based version of AutoTutor. Fuzzy-trace theory theoretically motivated the development of BRCA Gist, which engages people in tutorial dialogues to teach them about genetic breast cancer risk.