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An exploratory study on student engagement with adaptive notifications in programming courses
Azcona, David; Hsiao, I-Han; Smeaton, Alan F.
This paper presents a study on students’ engagement and personalized weekly performance notifications. Students were offered to voluntarily opt-in to receive customized notifications regarding their predicted course performances and recommended resources. In addition, the predicted at-risk students were also recommended with code solutions from higher performers in the class. Data was collected from Computer Science programming courses. Students’ engagement with the notifications and resources were tracked and have been found to be an indicator of their differential improvement between their exams.
Keyword(s): Artificial intelligence; Machine learning
Publication Date:
2018
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Azcona, David ORCID: 0000-0003-3693-7906 <https://orcid.org/0000-0003-3693-7906>, Hsiao, I-Han ORCID: 0000-0002-1888-3951 <https://orcid.org/0000-0002-1888-3951> and Smeaton, Alan F. ORCID: 0000-0003-1028-8389 <https://orcid.org/0000-0003-1028-8389> (2018) An exploratory study on student engagement with adaptive notifications in programming courses. In: European Conference on Technology Enhanced Learning (EC-TEL’18), 3-6 Sept 2018, Leeds, UK. ISBN 9783319985718
Publisher(s): Springer Verlag
File Format(s): application/pdf
Related Link(s): http://doras.dcu.ie/22955/1/EC-TEL_2018_paper_197.pdf,
http://dx.doi.org/10.1007/978-3-319-98572-5_64
First Indexed: 2019-01-29 06:07:48 Last Updated: 2019-02-09 06:10:58