Automatically detectable indicators of programming assignment difficulty

Petri Ihantola; Juha Sorva; Arto Vihavainen

doi:10.1145/2656450.2656476

Automatically detectable indicators of programming assignment difficulty

Petri Ihantola, Juha Sorva, Arto Vihavainen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

20 Citations (Scopus)

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.

Original language	English
Title of host publication	SIGITE 2014 - Proceedings of the 15th Annual Conference on Information Technology Education
Publisher	ACM
Pages	33-38
Number of pages	6
ISBN (Electronic)	9781450326865
DOIs	https://doi.org/10.1145/2656450.2656476
Publication status	Published - 14 Oct 2014
Publication type	A4 Article in conference proceedings
Event	15th Annual Conference on Information Technology Education, SIGITE 2014 - Atlanta, United States Duration: 15 Oct 2014 → 18 Oct 2014

Conference

Conference	15th Annual Conference on Information Technology Education, SIGITE 2014
Country/Territory	United States
City	Atlanta
Period	15/10/14 → 18/10/14

Keywords

Assignment difficulty
Automated assessment
Personalized feedback
Programming assignments

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems
Education

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10.1145/2656450.2656476

Cite this

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title = "Automatically detectable indicators of programming assignment difficulty",

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",

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doi = "10.1145/2656450.2656476",

language = "English",

pages = "33--38",

booktitle = "SIGITE 2014 - Proceedings of the 15th Annual Conference on Information Technology Education",

publisher = "ACM",

address = "United States",

note = "15th Annual Conference on Information Technology Education, SIGITE 2014 ; Conference date: 15-10-2014 Through 18-10-2014",

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Ihantola, P, Sorva, J & Vihavainen, A 2014, Automatically detectable indicators of programming assignment difficulty. in SIGITE 2014 - Proceedings of the 15th Annual Conference on Information Technology Education. ACM, pp. 33-38, 15th Annual Conference on Information Technology Education, SIGITE 2014, Atlanta, United States, 15/10/14. https://doi.org/10.1145/2656450.2656476

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AU - Ihantola, Petri

AU - Sorva, Juha

AU - Vihavainen, Arto

PY - 2014/10/14

Y1 - 2014/10/14

N2 - 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.

AB - 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.

KW - Assignment difficulty

KW - Automated assessment

KW - Personalized feedback

KW - Programming assignments

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U2 - 10.1145/2656450.2656476

DO - 10.1145/2656450.2656476

M3 - Conference contribution

AN - SCOPUS:84910019801

SP - 33

EP - 38

BT - SIGITE 2014 - Proceedings of the 15th Annual Conference on Information Technology Education

PB - ACM

T2 - 15th Annual Conference on Information Technology Education, SIGITE 2014

Y2 - 15 October 2014 through 18 October 2014

ER -

Automatically detectable indicators of programming assignment difficulty

Abstract

Conference

Keywords

ASJC Scopus subject areas

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