Automated Assessment of Learning Objectives in Programming Assignments

Arthur Rump; Ansgar Fehnker; Angelika Mader

doi:10.1007/978-3-030-80421-3_33

Automated Assessment of Learning Objectives in Programming Assignments

Arthur Rump
, Ansgar Fehnker^*
, Angelika Mader

^*Corresponding author for this work

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

11 Citations (Scopus)

202 Downloads (Pure)

Abstract

Individual feedback is a core ingredient of a personalised learning path. However, it also is time-intensive and, as a teaching form, it is not easily scalable. In order to make individual feedback realisable for larger groups of students, we develop tool support for teaching assistants to use in the process of giving feedback. In this paper, we introduce Apollo, a tool that automatically analyses code uploaded by students with respect to their progression towards the learning objectives of the course. First, typical learning objectives in Computer Science courses are analysed on their suitability for automated assessment. A set of learning objectives is analysed further to get an understanding of what achievement of these objectives looks like in code. Finally, this is implemented in Apollo, a tool that assesses the achievement of learning objectives in Processing projects. Early results suggest an agreement in assessment between Apollo and teaching assistants.

Original language	English
Title of host publication	Intelligent Tutoring Systems
Subtitle of host publication	17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings
Editors	Alexandra I. Cristea, Christos Troussas
Place of Publication	Cham
Publisher	Springer
Pages	299-309
Number of pages	11
ISBN (Electronic)	978-3-030-80421-3
ISBN (Print)	978-3-030-80420-6
DOIs	https://doi.org/10.1007/978-3-030-80421-3_33
Publication status	Published - 9 Jul 2021
Event	17th International Conference on Intelligent Tutoring Systems, ITS 2021 - Virtual, Online Duration: 7 Jun 2021 → 11 Jun 2021 Conference number: 17

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	12677
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th International Conference on Intelligent Tutoring Systems, ITS 2021
Abbreviated title	ITS 2021
City	Virtual, Online
Period	7/06/21 → 11/06/21

Keywords

2022 OA procedure
Automated feedback
Programming education
Automated assessment

Access to Document

10.1007/978-3-030-80421-3_33

Rump-2021-Automated-assessment-of-learning-obFinal published version, 847 KBLicence: Taverne

Cite this

Rump, A., Fehnker, A., & Mader, A. (2021). Automated Assessment of Learning Objectives in Programming Assignments. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (pp. 299-309). (Lecture Notes in Computer Science; Vol. 12677). Springer. https://doi.org/10.1007/978-3-030-80421-3_33

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title = "Automated Assessment of Learning Objectives in Programming Assignments",

abstract = "Individual feedback is a core ingredient of a personalised learning path. However, it also is time-intensive and, as a teaching form, it is not easily scalable. In order to make individual feedback realisable for larger groups of students, we develop tool support for teaching assistants to use in the process of giving feedback. In this paper, we introduce Apollo, a tool that automatically analyses code uploaded by students with respect to their progression towards the learning objectives of the course. First, typical learning objectives in Computer Science courses are analysed on their suitability for automated assessment. A set of learning objectives is analysed further to get an understanding of what achievement of these objectives looks like in code. Finally, this is implemented in Apollo, a tool that assesses the achievement of learning objectives in Processing projects. Early results suggest an agreement in assessment between Apollo and teaching assistants.",

keywords = "2022 OA procedure, Automated feedback, Programming education, Automated assessment",

author = "Arthur Rump and Ansgar Fehnker and Angelika Mader",

note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 17th International Conference on Intelligent Tutoring Systems, ITS 2021, ITS 2021 ; Conference date: 07-06-2021 Through 11-06-2021",

year = "2021",

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doi = "10.1007/978-3-030-80421-3\_33",

language = "English",

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editor = "Cristea, \{Alexandra I.\} and Christos Troussas",

booktitle = "Intelligent Tutoring Systems",

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Rump, A, Fehnker, A & Mader, A 2021, Automated Assessment of Learning Objectives in Programming Assignments. in AI Cristea & C Troussas (eds), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings. Lecture Notes in Computer Science, vol. 12677, Springer, Cham, pp. 299-309, 17th International Conference on Intelligent Tutoring Systems, ITS 2021, Virtual, Online, 7/06/21. https://doi.org/10.1007/978-3-030-80421-3_33

Automated Assessment of Learning Objectives in Programming Assignments. / Rump, Arthur; Fehnker, Ansgar; Mader, Angelika.
Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings. ed. / Alexandra I. Cristea; Christos Troussas. Cham: Springer, 2021. p. 299-309 (Lecture Notes in Computer Science; Vol. 12677).

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

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T1 - Automated Assessment of Learning Objectives in Programming Assignments

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AU - Fehnker, Ansgar

AU - Mader, Angelika

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N2 - Individual feedback is a core ingredient of a personalised learning path. However, it also is time-intensive and, as a teaching form, it is not easily scalable. In order to make individual feedback realisable for larger groups of students, we develop tool support for teaching assistants to use in the process of giving feedback. In this paper, we introduce Apollo, a tool that automatically analyses code uploaded by students with respect to their progression towards the learning objectives of the course. First, typical learning objectives in Computer Science courses are analysed on their suitability for automated assessment. A set of learning objectives is analysed further to get an understanding of what achievement of these objectives looks like in code. Finally, this is implemented in Apollo, a tool that assesses the achievement of learning objectives in Processing projects. Early results suggest an agreement in assessment between Apollo and teaching assistants.

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KW - 2022 OA procedure

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KW - Programming education

KW - Automated assessment

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M3 - Conference contribution

AN - SCOPUS:85112248847

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ER -

Automated Assessment of Learning Objectives in Programming Assignments

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