Publication | Journal of Human-Computer Interaction 2016

Interactive Instruction in Bayesian Inference

Abstract

Interactive Instruction in Bayesian Inference

Azam Khan, Simon Breslav, Kasper Hornbaek

Journal of Human-Computer Interaction 2016

An instructional approach is presented to improve human performance in solving Bayesian inference problems. Starting from the original text of the classic Mammography Problem, the textual expression is modified and visualizations are added according to Mayer’s principles of instruction. These principles concern coherence, personalization, signaling, segmenting, multimedia, spatial contiguity, and pre-training. Principles of self-explanation and interactivity are also applied. Four experiments on the Mammography Problem showed that these principles help participants answer the questions at significantly improved rates. Nonetheless, in novel interactivity conditions, performance was lowered suggesting that more interaction can add more difficulty for participants. Overall, a leap forward in accuracy was found, with more than twice the participant accuracy of previous work. This indicates that an instructional approach to improving human performance in Bayesian inference is a promising direction.

Download publication

Related Resources

Publication

2022

Harnessing Game-Inspired Content Creation for Intuitive Generative Design and Optimization

A multi-scale generative design model that adapts the Wave Function…

Publication

1996

Random Caustics: Natural Textures and Wave Theory Revisited

A technique to synthesizes caustic texture maps is presented…

Publication

2011

Results Of The Enumeration Of Costas Arrays Of Order 29

The results of the enumeration of Costas arrays of order 29 are…

Publication

2011

DesignScript: Origins, Explanation, Illustration

DesignScript, as the name suggests, is positioned at the intersection…

Get in touch

Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.

Contact us