Interactive Instruction in Bayesian Inference

Abstract

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 pretraining. 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.

Additional information

Notes on contributors

Azam Khan

Azam Khan ([email protected], https://www.autodeskresearch.com/people/azam-khan) is a computer scientist with an interest in simulation, human–computer interaction, information visualization, architectural design, sensor networks, and sustainability; he is the Head of the Complex Systems Research at Autodesk Research.

Simon Breslav

Simon Breslav ([email protected], https://www.autodeskresearch.com/people/simon-breslav) is a computer scientist with an interest in information visualization, simulation, psychology, and human–computer interaction; he is a research scientist in the Complex Systems Research group of Autodesk Research.

Kasper Hornbæk

Kasper Hornbæk ([email protected], http://www.kasperhornbaek.dk/) is a computer scientist with an interest in human–computer interaction, usability research, search user interfaces, and information visualization, eye tracking, cultural usability, and reality-based interfaces; he is a professor in the Department of Computer Science of University of Copenhagen.