Applying Test-Driven Development for Improved Feedback and Automation of Grading in Academic Courses on Software Development

Dragos Truscan; Tanwir Ahmad; Cuong Tran

doi:10.1007/978-3-030-57663-9_20

Applying Test-Driven Development for Improved Feedback and Automation of Grading in Academic Courses on Software Development

Dragos Truscan, Tanwir Ahmad, Cuong Tran

Information Technology

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

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Abstract

Grading student assignments and projects in software development courses is a time-consuming task. The lecturer has to download individually each assignment, compile it and manually check that the implementation satisfies the requirements. In addition, the students would like to get early feedback on their solutions, not only as guidelines on whether their solution meets the expectations of the lecturers, but also a way to estimate the current number of points their solution deserves. In this work, we propose the use of the test-driven development process as an approach to both guide the students during the implementation of their projects and as a way to speed up and make the grading process more scalable. Furthermore, we show how we take advantage of community-based software development tools such as GitHub to support our approach. We evaluate the proposed approach by applying it to an academic course for developing web applications. The results show that the approach reduces the grading effort by 60{%} and that the early feedback it provides was appreciated by students.

Original language	English
Title of host publication	Frontiers in Software Engineering Education - 1st International Workshop, FISEE 2019, Invited Papers
Editors	Jean-Michel Bruel, Alfredo Capozucca, Manuel Mazzara, Alexandr Naumchev, Andrey Sadovykh, Bertrand Meyer
Publisher	Springer
Pages	310–323
ISBN (Electronic)	978-3-030-57663-9
ISBN (Print)	978-3-030-57662-2
DOIs	https://doi.org/10.1007/978-3-030-57663-9_20
Publication status	Published - 2020
MoE publication type	A4 Article in a conference publication
Event	International Workshop on Frontiers in Software Engineering Education - First International Workshop on Frontiers in Software Engineering Education, FISEE 2019 Duration: 11 Nov 2019 → 13 Nov 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12271 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Workshop on Frontiers in Software Engineering Education
Period	11/11/19 → 13/11/19

Keywords

Software Development
Test-Driven Development
self-evaluation

Access to Document

10.1007/978-3-030-57663-9_20

paper_13 (1).pdfAccepted author manuscript, 471 KBLicence: Publisher rights policy

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MegaM@Rt2: MegaModelling at Runtime
Truscan, D., Ahmad, T., Iqbal, J., Porres Paltor, I., Siavashi, F. & Ashraf, A.
European Commission
01/04/17 → 31/03/20
Project: EU

Cite this

Truscan, D., Ahmad, T., & Tran, C. (2020). Applying Test-Driven Development for Improved Feedback and Automation of Grading in Academic Courses on Software Development. In J.-M. Bruel, A. Capozucca, M. Mazzara, A. Naumchev, A. Sadovykh, & B. Meyer (Eds.), Frontiers in Software Engineering Education - 1st International Workshop, FISEE 2019, Invited Papers (pp. 310–323). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12271 LNCS). Springer. https://doi.org/10.1007/978-3-030-57663-9_20

Truscan, Dragos ; Ahmad, Tanwir ; Tran, Cuong. / Applying Test-Driven Development for Improved Feedback and Automation of Grading in Academic Courses on Software Development. Frontiers in Software Engineering Education - 1st International Workshop, FISEE 2019, Invited Papers. editor / Jean-Michel Bruel ; Alfredo Capozucca ; Manuel Mazzara ; Alexandr Naumchev ; Andrey Sadovykh ; Bertrand Meyer. Springer, 2020. pp. 310–323 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{89fedb9d01b447a082290cc79630c165,

title = "Applying Test-Driven Development for Improved Feedback and Automation of Grading in Academic Courses on Software Development",

abstract = "Grading student assignments and projects in software development courses is a time-consuming task. The lecturer has to download individually each assignment, compile it and manually check that the implementation satisfies the requirements. In addition, the students would like to get early feedback on their solutions, not only as guidelines on whether their solution meets the expectations of the lecturers, but also a way to estimate the current number of points their solution deserves. In this work, we propose the use of the test-driven development process as an approach to both guide the students during the implementation of their projects and as a way to speed up and make the grading process more scalable. Furthermore, we show how we take advantage of community-based software development tools such as GitHub to support our approach. We evaluate the proposed approach by applying it to an academic course for developing web applications. The results show that the approach reduces the grading effort by 60{%} and that the early feedback it provides was appreciated by students.",

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Truscan, D , Ahmad, T & Tran, C 2020, Applying Test-Driven Development for Improved Feedback and Automation of Grading in Academic Courses on Software Development. in J-M Bruel, A Capozucca, M Mazzara, A Naumchev, A Sadovykh & B Meyer (eds), Frontiers in Software Engineering Education - 1st International Workshop, FISEE 2019, Invited Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12271 LNCS, Springer, pp. 310–323, International Workshop on Frontiers in Software Engineering Education, 11/11/19. https://doi.org/10.1007/978-3-030-57663-9_20

Applying Test-Driven Development for Improved Feedback and Automation of Grading in Academic Courses on Software Development. / Truscan, Dragos ; Ahmad, Tanwir; Tran, Cuong.
Frontiers in Software Engineering Education - 1st International Workshop, FISEE 2019, Invited Papers. ed. / Jean-Michel Bruel; Alfredo Capozucca; Manuel Mazzara; Alexandr Naumchev; Andrey Sadovykh; Bertrand Meyer. Springer, 2020. p. 310–323 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12271 LNCS).

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

TY - GEN

T1 - Applying Test-Driven Development for Improved Feedback and Automation of Grading in Academic Courses on Software Development

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Y1 - 2020

N2 - Grading student assignments and projects in software development courses is a time-consuming task. The lecturer has to download individually each assignment, compile it and manually check that the implementation satisfies the requirements. In addition, the students would like to get early feedback on their solutions, not only as guidelines on whether their solution meets the expectations of the lecturers, but also a way to estimate the current number of points their solution deserves. In this work, we propose the use of the test-driven development process as an approach to both guide the students during the implementation of their projects and as a way to speed up and make the grading process more scalable. Furthermore, we show how we take advantage of community-based software development tools such as GitHub to support our approach. We evaluate the proposed approach by applying it to an academic course for developing web applications. The results show that the approach reduces the grading effort by 60{%} and that the early feedback it provides was appreciated by students.

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ER -

Truscan D , Ahmad T, Tran C. Applying Test-Driven Development for Improved Feedback and Automation of Grading in Academic Courses on Software Development. In Bruel JM, Capozucca A, Mazzara M, Naumchev A, Sadovykh A, Meyer B, editors, Frontiers in Software Engineering Education - 1st International Workshop, FISEE 2019, Invited Papers. Springer. 2020. p. 310–323. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-57663-9_20

Applying Test-Driven Development for Improved Feedback and Automation of Grading in Academic Courses on Software Development

Abstract

Publication series

Conference

Keywords

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MegaM@Rt2: MegaModelling at Runtime

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