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An intelligent interface for learning content: Combining an open learner model and social comparison to support self-regulated learning and engagement

Guerra, J and Hosseini, R and Somyurek, S and Brusilovsky, P (2016) An intelligent interface for learning content: Combining an open learner model and social comparison to support self-regulated learning and engagement. In: UNSPECIFIED.

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Abstract

© Copyright 2016 ACM. We present the Mastery Grids system, an intelligent interface for online learning content that combines open learner modeling (OLM) and social comparison features. We grounded the design of Mastery Grids in self-regulated learning and learning motivation theories, as well as in our past work in social comparison, OLM, and adaptive navigation support. The force behind the interface is the combination of adaptive navigation functionality with the mastery-oriented aspects of OLM and the performance-oriented aspects of social comparison. We examined different configurations of Mastery Grids in two classroom studies and report the results of analysis of log data and survey responses. The results show how Mastery Grids interacts with different factors, like gender and achievement-goal orientation, and ultimately, its impact on student engagement, performance, and motivation.


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Details

Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Guerra, Jjdg60@pitt.eduJDG60
Hosseini, Rroh38@pitt.eduROH38
Somyurek, S
Brusilovsky, Ppeterb@pitt.eduPETERB0000-0002-1902-1464
Date: 7 March 2016
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: International Conference on Intelligent User Interfaces, Proceedings IUI
Volume: 07-10-
Page Range: 152 - 163
Event Type: Conference
DOI or Unique Handle: 10.1145/2856767.2856784
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Intelligent Systems
School of Information Sciences > Information Science
Refereed: Yes
ISBN: 9781450341370
Date Deposited: 28 Mar 2016 13:37
Last Modified: 08 Dec 2017 14:55
URI: http://d-scholarship.pitt.edu/id/eprint/27358

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