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

8 Citations (Scopus)

126 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

Automated assessment
Automated feedback
Programming education

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

@inproceedings{a1337db584524ba8adf543b2cdd2d868,

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 = "Automated assessment, Automated feedback, Programming education",

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",

month = jul,

day = "9",

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

language = "English",

isbn = "978-3-030-80420-6",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "299--309",

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

booktitle = "Intelligent Tutoring Systems",

address = "Germany",

}

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

TY - GEN

T1 - Automated Assessment of Learning Objectives in Programming Assignments

AU - Rump, Arthur

AU - Fehnker, Ansgar

AU - Mader, Angelika

N1 - Conference code: 17

PY - 2021/7/9

Y1 - 2021/7/9

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.

AB - 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.

KW - Automated assessment

KW - Automated feedback

KW - Programming education

UR - http://www.scopus.com/inward/record.url?scp=85112248847&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-80421-3_33

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

M3 - Conference contribution

AN - SCOPUS:85112248847

SN - 978-3-030-80420-6

T3 - Lecture Notes in Computer Science

SP - 299

EP - 309

BT - Intelligent Tutoring Systems

A2 - Cristea, Alexandra I.

A2 - Troussas, Christos

PB - Springer

CY - Cham

T2 - 17th International Conference on Intelligent Tutoring Systems, ITS 2021

Y2 - 7 June 2021 through 11 June 2021

ER -

Automated Assessment of Learning Objectives in Programming Assignments

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this