Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Open Social Student Modeling for Personalized Learning

Brusilovsky, P and Somyurek, S and Guerra, J and Hosseini, R and Zadorozhny, V and Durlach, PJ (2016) Open Social Student Modeling for Personalized Learning. IEEE Transactions on Emerging Topics in Computing, 4 (3). 450 - 461.

[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)


Open student modeling (OSM) is an approach to technology-based learning, which makes student models available to the learners for exploration. OSM is known for its ability to increase student engagement, motivation, and knowledge reflection. A recent extension of OSM known as open social student modeling (OSSM) complements cognitive aspects of OSM with social aspects by allowing students to explore models of peer students and/or an aggregated class model. In this paper, we introduce an OSSM interface, MasteryGrids, and report the results of a large-scale classroom study, which explored the impact of the social dimension of OSSM. Students in a database management course accessed nonrequired learning materials (examples and problems) via the MasteryGrids interface using either OSM or OSSM. The results revealed that OSSM-enhanced learning, especially for students with lower prior knowledge, compared with OSM. It also enhanced user attitude and engagement. Amount of student usage, efficiency of student usage, and student attitude varied depending on the combination of interface condition (OSM/OSSM), gender, and student social comparison orientation.


Social Networking:
Share |


Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Brusilovsky, Ppeterb@pitt.eduPETERB0000-0002-1902-1464
Somyurek, S
Guerra, Jjdg60@pitt.eduJDG60
Hosseini, Rroh38@pitt.eduROH38
Zadorozhny, V
Durlach, PJ
Date: 1 January 2016
Date Type: Publication
Journal or Publication Title: IEEE Transactions on Emerging Topics in Computing
Volume: 4
Number: 3
Page Range: 450 - 461
DOI or Unique Handle: 10.1109/tetc.2015.2501243
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
Date Deposited: 30 Jun 2017 13:47
Last Modified: 30 Mar 2021 12:55


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item