2016 article

Predicting Learning from Student Affective Response to Tutor Questions

INTELLIGENT TUTORING SYSTEMS, ITS 2016, Vol. 9684, pp. 154–164.

By: A. Vail n, J. Grafsgaard n, K. Boyer*, E. Wiebe n & J. Lester n

TL;DR: This work examines student facial expression, electrodermal activity, posture, and gesture immediately following inference questions posed by human tutors and shows that for human-human task-oriented tutorial dialogue, facial expression and skin conductance response following tutor inference questions are highly predictive of student learning gains. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, NC State University Libraries
Added: August 6, 2018

2015 conference paper

The Mars and Venus effect: The influence of user gender on the effectiveness of adaptive task support

User modeling, adaptation and personalization, 9146, 265–276.

By: A. Vail, K. Boyer, E. Wiebe & J. Lester

Source: NC State University Libraries
Added: August 6, 2018

2014 conference paper

Identifying effective moves in tutoring: On the refinement of dialogue act annotation schemes

Intelligent tutoring systems, its 2014, 8474, 199–209.

By: A. Vail & K. Boyer

Source: NC State University Libraries
Added: August 6, 2018

Citation Index includes data from a number of different sources. If you have questions about the sources of data in the Citation Index or need a set of data which is free to re-distribute, please contact us.

Certain data included herein are derived from the Web of Science© and InCites© (2024) of Clarivate Analytics. All rights reserved. You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.