Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/107845
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Type: Conference paper
Title: Increasing the effectiveness of automated assessment by increasing marking granularity and feedback units
Author: Falkner, N.
Vivian, R.
Piper, D.
Falkner, K.
Citation: Proceedings of the 45th ACM Technical Symposium on Computer Science Education, 2014 / pp.9-14
Publisher: ACM New York
Issue Date: 2014
ISBN: 978-1-4503-2605-6
Conference Name: 45th ACM Technical Symposium on Computer Science Education (SIGCSE '14) (05 Mar 2014 - 08 Mar 2014 : Atlanta, Georgia)
Statement of
Responsibility: 
Nickolas Falkner, Rebecca Vivian, David Piper and Katrina Falkner
Abstract: Computer-based assessment is a useful tool for handling large-scale classes and is extensively used in the automated assessment of student programming assignments in Computer Science. The forms that this assessment takes, however, can vary widely from simple acknowledgement to a detailed analysis of output, structure and code. This study focusses on output analysis of submitted student assignment code and the degree to which changes in automated feedback influence student marks and persistence in submission. Data was collected over a four year period, over 22 courses but we focus on one course for this paper. Assignments were grouped by the number of different units of automated feedback that were delivered per assignment to investigate if students changed their submission behaviour or performance as the possible set of marks, that a student could achieve, changed. We discovered that pre-deadline results improved as the number of feedback units increase and that post-deadline activity was also improved as more feedback units were available.
Keywords: Automated assessment, feedback, student performance
Rights: Copyright is held by the author(s). Publication rights licensed to ACM. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org.
RMID: 0030007494
DOI: 10.1145/2538862.2538896
Appears in Collections:Computer Science publications

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