Stevie Carnell


UX Researcher | Educational technology, virtual reality, and conversational agents


Curriculum vitae


Computer Science


University of Central Florida



Predicting Student Success in Communication Skills Learning Scenarios with Virtual Humans


Conference


Stephanie Carnell, B. Lok, Melva T. James, Jonathan Su
LAK, 2019

Semantic Scholar DBLP DOI
Cite

Cite

APA
Carnell, S., Lok, B., James, M. T., & Su, J. (2019). Predicting Student Success in Communication Skills Learning Scenarios with Virtual Humans. In LAK.

Chicago/Turabian
Carnell, Stephanie, B. Lok, Melva T. James, and Jonathan Su. “Predicting Student Success in Communication Skills Learning Scenarios with Virtual Humans.” In LAK, 2019.

MLA
Carnell, Stephanie, et al. “Predicting Student Success in Communication Skills Learning Scenarios with Virtual Humans.” LAK, 2019.


Abstract

Virtual humans are frequently used to help medical students practice communication skills. Here, we show that communication skills features drawn from the literature on best practices for doctor-patient communication can be used to predict student interviewers' success in a given domain skill. We also demonstrate the viability of Bayesian Rule Lists, an interpretable machine learning model, for this use case. Bayesian Rule Lists' predictive performance is comparable to that of other other commonly used algorithms, including decision trees. This suggests that Bayesian Rule Lists, which produce simple, human-readable trained binary classifiers, may be suitable for providing feedback for educational purposes.