Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/26748
DC FieldValueLanguage
dc.contributor.authorHellas, Artoen_US
dc.contributor.authorIhantola, Petrien_US
dc.contributor.authorPetersen, Andrewen_US
dc.contributor.authorAjanovski, Vangel V.en_US
dc.contributor.authorGutica, Mirelaen_US
dc.contributor.authorHynninen, Timoen_US
dc.contributor.authorKnutas, Anttien_US
dc.contributor.authorLeinonen, Juhoen_US
dc.contributor.authorMessom, Chrisen_US
dc.contributor.authorLiao, Soohyun Namen_US
dc.date.accessioned2023-06-08T14:07:03Z-
dc.date.available2023-06-08T14:07:03Z-
dc.date.issued2018-07-02-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/26748-
dc.description.abstractThe ability to predict student performance in a course or program creates opportunities to improve educational outcomes. With effective performance prediction approaches, instructors can allocate resources and instruction more accurately. Research in this area seeks to identify features that can be used to make predictions, to identify algorithms that can improve predictions, and to quantify aspects of student performance. Moreover, research in predicting student performance seeks to determine interrelated features and to identify the underlying reasons why certain features work better than others. This working group report presents a systematic literature review of work in the area of predicting student performance. Our analysis shows a clearly increasing amount of research in this area, as well as an increasing variety of techniques used. At the same time, the review uncovered a number of issues with research quality that drives a need for the community to provide more detailed reporting of methods and results and to increase efforts to validate and replicate work.en_US
dc.language.isoenen_US
dc.publisherACMen_US
dc.titlePredicting academic performance: a systematic literature reviewen_US
dc.typeProceeding articleen_US
dc.relation.conferenceProceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Educationen_US
dc.identifier.doi10.1145/3293881.3295783-
dc.identifier.urlhttps://dl.acm.org/doi/pdf/10.1145/3293881.3295783-
item.grantfulltextnone-
item.fulltextNo Fulltext-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
Show simple item record

Page view(s)

42
checked on Sep 22, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.