A contingency table derived method for analyzing course data

Ahadi, A; Hellas, A; Lister, R

A contingency table derived method for analyzing course data

Ahadi, A

Hellas, A Lister, R

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Publication Type:: Journal Article
Citation:: ACM Transactions on Computing Education, 2017, 17 (3)
Issue Date:: 2017-08-01

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Field	Value	Language
dc.contributor.author	Ahadi, A https://orcid.org/0000-0002-2018-3065	en_US
dc.contributor.author	Hellas, A	en_US
dc.contributor.author	Lister, R https://orcid.org/0000-0001-5780-0445	en_US
dc.date.issued	2017-08-01	en_US
dc.identifier.citation	ACM Transactions on Computing Education, 2017, 17 (3)	en_US
dc.identifier.uri	http://hdl.handle.net/10453/80230
dc.description.abstract	© 2017 ACM. We describe a method for analyzing student data from online programming exercises. Our approach uses contingency tables that combine whether or not a student answered an online exercise correctly with the number of attempts that the student made on that exercise. We use this method to explore the relationship between student performance on online exercises done during semester with subsequent performance on questions in a paper-based exam at the end of semester. We found that it is useful to include data about the number of attempts a student makes on an online exercise.	en_US
dc.relation.ispartof	ACM Transactions on Computing Education	en_US
dc.relation.isbasedon	10.1145/3123814	en_US
dc.subject.classification	Education	en_US
dc.title	A contingency table derived method for analyzing course data	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	17	en_US
utslib.for	0899 Other Information and Computing Sciences	en_US
utslib.for	0802 Computation Theory and Mathematics	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	1301 Education Systems	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - HCTD - Human Centred Technology Design
utslib.copyright.status	closed_access
pubs.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	17	en_US

Abstract:

© 2017 ACM. We describe a method for analyzing student data from online programming exercises. Our approach uses contingency tables that combine whether or not a student answered an online exercise correctly with the number of attempts that the student made on that exercise. We use this method to explore the relationship between student performance on online exercises done during semester with subsequent performance on questions in a paper-based exam at the end of semester. We found that it is useful to include data about the number of attempts a student makes on an online exercise.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/80230