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Automatically detectable indicators of programming assignment difficulty

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publicationSIGITE 2014 - Proceedings of the 15th Annual Conference on Information Technology Education
PublisherAssociation for Computing Machinery, Inc
Pages33-38
Number of pages6
ISBN (Electronic)9781450326865
DOIs
Publication statusPublished - 14 Oct 2014
Publication typeA4 Article in a conference publication
Event15th Annual Conference on Information Technology Education, SIGITE 2014 - Atlanta, United States
Duration: 15 Oct 201418 Oct 2014

Conference

Conference15th Annual Conference on Information Technology Education, SIGITE 2014
CountryUnited States
CityAtlanta
Period15/10/1418/10/14

Abstract

The difficulty of learning tasks is a major factor in learning, as is the feedback given to students. Even automatic feedback should ideally be influenced by student-dependent factors such as task difficulty. We report on a preliminary exploration of such indicators of programming assignment difficulty that can be automatically detected for each student from source code snapshots of the student's evolving code. Using a combination of different metrics emerged as a promising approach. In the future, our results may help provide students with personalized automatic feedback.

Keywords

  • Assignment difficulty, Automated assessment, Personalized feedback, Programming assignments