Does Seeing One Another’s Gaze Affect Group Dialogue? A Computational Approach
Keywords:Natural language processing, eye-tracking, learning analytics, computer-supported collaborative learning, CSCL
In a previous study, we found that real-time mutual gaze perception (i.e., being able to see the gaze of your partner in real time on a computer screen while solving a learning task) had a positive effect on students’ collaboration and learning (Schneider & Pea, 2013). The goals of this paper are to: 1) explore a variety of computational techniques for analyzing the transcripts of students’ discussions; 2) examine whether any of those measures sheds new light on our previous results; and 3) test whether those metrics have any predictive power regarding learning outcomes. Using various natural language processing algorithms, we found that linguistic coordination (i.e., the extent to which students mimic each other in terms of their grammatical structure) did not predict the quality of student collaboration or learning gains. However, we found that a simple computational measure of students’ verbal coherence (i.e., the extent to which students build on each others’ ideas) was positively correlated with their learning gains. Additionally, this measure was significantly different across our experimental conditions: students who could see the gaze of their partner in real time were more likely to develop a coherent discussion. Finally, using various language metrics, we were able to roughly predict (i.e., using a median-split) learning gains with a 94.4% accuracy using Support Vector Machine. The accuracy dropped to 75% when we used our model on a validation set. We conclude by discussing the benefits of using computational techniques on educational datasets.
How to Cite
Copyright (c) 2015 Journal of Learning Analytics
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons License, Attribution - NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) license that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).