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Author Vihavainen, Arto ♦ Ihantola, Petri ♦ Sorva, Juha
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
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.
Description Affiliation: Aalto University (Ihantola, Petri; Sorva, Juha) || University of Helsinki (Vihavainen, Arto)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2008-01-01
Publisher Place New York
Journal ACM SIGITE Newsletter (SITE)
Volume Number 10
Issue Number 2
Page Count 1
Starting Page 10
Ending Page 10


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Source: ACM Digital Library