Investigating transitions in affect and activities for online learning interventions

College

College of Computer Studies

Department/Unit

Software Technology

Document Type

Conference Proceeding

Source Title

Proceedings of the 19th International Conference on Computers in Education, ICCE 2011

First Page

571

Last Page

578

Publication Date

12-1-2011

Abstract

In this paper we investigated student online learning and non-learning related activities. The data collected in the research showed that students felt certain affective states when performing particular activity types and performed particular activity types when they felt certain affective states. These transitions were further investigated by generating transition likelihoods between all pairs of activity types and affective states. The transition likelihoods were used to create a model that could predict possible student behavior when they learn online. Certain transitions wherein students may need interventions were identified, so that feedback can be put in place to prevent them from transitioning to activity types and affective states that do not support learning.

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Disciplines

Computer Sciences

Keywords

Learning; Education—Data processing; Computer-assisted instruction

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