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Simplifying complexity for assessment automation in computer-supported collaborative learning

Xing, W, Marcinkowski, M and Goggins, S (2015) Simplifying complexity for assessment automation in computer-supported collaborative learning. In: AERA Annual Meeting: Toward Justice - Culture, Language, and Heritage in Education Research and Praxis, 16 - 20 April 2015, Marriott Downtown, Chicago, IL, USA.

Abstract

This study proposes a process-oriented, automatic, and formative assessment model for small group learning through the lens of complex systems theory using a small dataset from a technology-mediated environment. We first conceptualize small group learning as a complex system and explain how group dynamics and interaction can be modeled via theoretically-sound, yet simple rules. These rules are then operationalized to build measures. Further, a Tree-Augmented Naïve Bayes classifier was coded to develop the assessment model which achieves the best accuracy (95.8%) as compared to baseline models. By building the assessment model in this manner, we are able to provide actionable insight for teachers so that they can provide real-time support to students.

Item Type: Conference or Workshop Item (Paper)
Subjects: L Education > L Education (General)
L Education > LB Theory and practice of education
L Education > LC Special aspects of education
Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: College of Liberal Arts
Date Deposited: 06 Dec 2016 14:21
Last Modified: 06 Dec 2016 14:21
URI: http://researchspace.bathspa.ac.uk/id/eprint/8575
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