Syntax error based quantification of the learning progress of the novice programmer

Ahadi, A; Lister, R; Mathieson, L

Syntax error based quantification of the learning progress of the novice programmer

Ahadi, A

Lister, R

Mathieson, L

Permalink

Publication Type:: Conference Proceeding
Citation:: Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE, 2018, pp. 10 - 14
Issue Date:: 2018-07-02

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Accepted Manuscript VersionAdobe PDF (234.22 kB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Ahadi, A https://orcid.org/0000-0002-2018-3065	en_US
dc.contributor.author	Lister, R https://orcid.org/0000-0001-5780-0445	en_US
dc.contributor.author	Mathieson, L https://orcid.org/0000-0001-6470-2296	en_US
dc.date.available	2018-03-07	en_US
dc.date.issued	2018-07-02	en_US
dc.identifier.citation	Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE, 2018, pp. 10 - 14	en_US
dc.identifier.isbn	9781450357074	en_US
dc.identifier.issn	1942-647X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/128636
dc.description.abstract	© 2018 Association for Computing Machinery. Recent data-driven research has produced metrics for quantifying a novice programmer’s error profile, such as Jadud’s error quotient. However, these metrics tend to be context dependent and contain free parameters. This paper reviews the caveats of such metrics and proposes a more general approach to developing a metric. The online implementation of the proposed metric is publicly available at http://online-analysis-demo.herokuapp.com/.	en_US
dc.relation.ispartof	Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE	en_US
dc.relation.isbasedon	10.1145/3197091.3197121	en_US
dc.title	Syntax error based quantification of the learning progress of the novice programmer	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	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	open_access
pubs.publication-status	Published	en_US

Abstract:

© 2018 Association for Computing Machinery. Recent data-driven research has produced metrics for quantifying a novice programmer’s error profile, such as Jadud’s error quotient. However, these metrics tend to be context dependent and contain free parameters. This paper reviews the caveats of such metrics and proposes a more general approach to developing a metric. The online implementation of the proposed metric is publicly available at http://online-analysis-demo.herokuapp.com/.

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

http://hdl.handle.net/10453/128636