Perfect match: facilitating study partner matching

Tam Nguyen Thanh, Matthew Butler, Michael Morgan, Kim Marriott

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

With the massive growth of online learning, there has been a decrease in students' face-to-face interactions, leading to rising feelings of isolation. This in turn contributes to several issues such as motivation loss, increased course attrition rates and poor learning experiences. Strong Online Learning Communities (OLCs) have been suggested as a means to help improve the situation, however the formation of OLCs is strongly influenced by learners' individual characteristics and their preferences regarding how and with whom they would want to form study groups. Taking students as its focus, this research attempts to develop a learning partner recommender system (LPRS) to facilitate finding compatible study peers in order to promote informal learning communities among students. From a synthesis of related literature and using data from a study of the student' preferences, a collection of learners' individual characteristics has been identified as a set of matching criteria in our LPRS model. A proof of concept based on the conceptual model has been developed and evaluated with a small group of target users. Results of the investigation showed positive feedback from participants and good prospects of the recommender system.

Original languageEnglish
Title of host publicationProceedings of the 50th ACM Technical Symposium on Computer Science Education
EditorsSarah Heckman, Jian Zhang
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages1102-1108
Number of pages7
ISBN (Electronic)9781450358903
DOIs
Publication statusPublished - 2019
EventACM Technical Symposium on Computer Science Education 2019 - Minneapolis, United States of America
Duration: 27 Feb 20192 Mar 2019
Conference number: 50th
https://sigcse2019.sigcse.org/

Conference

ConferenceACM Technical Symposium on Computer Science Education 2019
Abbreviated titleSIGCSE 2019
CountryUnited States of America
CityMinneapolis
Period27/02/192/03/19
Internet address

Keywords

  • Learning Partners
  • Online Learning Communities
  • Recommender Systems

Cite this

Nguyen Thanh, T., Butler, M., Morgan, M., & Marriott, K. (2019). Perfect match: facilitating study partner matching. In S. Heckman, & J. Zhang (Eds.), Proceedings of the 50th ACM Technical Symposium on Computer Science Education (pp. 1102-1108). New York NY USA: Association for Computing Machinery (ACM). https://doi.org/10.1145/3287324.3287344
Nguyen Thanh, Tam ; Butler, Matthew ; Morgan, Michael ; Marriott, Kim. / Perfect match : facilitating study partner matching. Proceedings of the 50th ACM Technical Symposium on Computer Science Education. editor / Sarah Heckman ; Jian Zhang. New York NY USA : Association for Computing Machinery (ACM), 2019. pp. 1102-1108
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Nguyen Thanh, T, Butler, M, Morgan, M & Marriott, K 2019, Perfect match: facilitating study partner matching. in S Heckman & J Zhang (eds), Proceedings of the 50th ACM Technical Symposium on Computer Science Education. Association for Computing Machinery (ACM), New York NY USA, pp. 1102-1108, ACM Technical Symposium on Computer Science Education 2019, Minneapolis, United States of America, 27/02/19. https://doi.org/10.1145/3287324.3287344

Perfect match : facilitating study partner matching. / Nguyen Thanh, Tam; Butler, Matthew; Morgan, Michael; Marriott, Kim.

Proceedings of the 50th ACM Technical Symposium on Computer Science Education. ed. / Sarah Heckman; Jian Zhang. New York NY USA : Association for Computing Machinery (ACM), 2019. p. 1102-1108.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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Nguyen Thanh T, Butler M, Morgan M, Marriott K. Perfect match: facilitating study partner matching. In Heckman S, Zhang J, editors, Proceedings of the 50th ACM Technical Symposium on Computer Science Education. New York NY USA: Association for Computing Machinery (ACM). 2019. p. 1102-1108 https://doi.org/10.1145/3287324.3287344