Preventing Cheating in Hands-on Lab Assignments

D 2022

Preventing Cheating in Hands-on Lab Assignments

VYKOPAL, Jan, Valdemar ŠVÁBENSKÝ, Pavel ŠEDA a Pavel ČELEDA

Základní údaje

Originální název

Preventing Cheating in Hands-on Lab Assignments

Autoři

VYKOPAL, Jan (203 Česká republika, garant, domácí), Valdemar ŠVÁBENSKÝ (703 Slovensko, domácí), Pavel ŠEDA (203 Česká republika, domácí) a Pavel ČELEDA (203 Česká republika, domácí)

Vydání

New York, NY, USA, Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (SIGCSE '22), od s. 78-84, 7 s. 2022

Nakladatel

ACM

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

Preprint on ArXiv.org

Kód RIV

RIV/00216224:14610/22:00125129

Organizační jednotka

Ústav výpočetní techniky

ISBN

978-1-4503-9070-5

DOI

http://dx.doi.org/10.1145/3478431.3499420

UT WoS

000884263800012

Klíčová slova anglicky

summative assessment; automatic problem generation; networking; operating systems; cybersecurity; exercise; homework; case study

Štítky

core_A, firank_A, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 26. 1. 2023 16:14, RNDr. Valdemar Švábenský, Ph.D.

Anotace

V originále

Networking, operating systems, and cybersecurity skills are exercised best in an authentic environment. Students work with real systems and tools in a lab environment and complete assigned tasks. Since all students typically receive the same assignment, they can consult their approach and progress with an instructor, a tutoring system, or their peers. They may also search for information on the Internet. Having the same assignment for all students in class is standard practice efficient for learning and developing skills. However, it is prone to cheating when used in a summative assessment such as graded homework, a mid-term test, or a final exam. Students can easily share and submit correct answers without completing the assignment. In this paper, we discuss methods for automatic problem generation for hands-on tasks completed in a computer lab environment. Using this approach, each student receives personalized tasks. We developed software for generating and submitting these personalized tasks and conducted a case study. The software was used for creating and grading a homework assignment in an introductory security course enrolled by 207 students. The software revealed seven cases of suspicious submissions, which may constitute cheating. In addition, students and instructors welcomed the personalized assignments. Instructors commented that this approach scales well for large classes. Students rarely encountered issues while running their personalized lab environment. Finally, we have released the open-source software to enable other educators to use it in their courses and learning environments.

Návaznosti

EF16_019/0000822, projekt VaV

Název: Centrum excelence pro kyberkriminalitu, kyberbezpečnost a ochranu kritických informačních infrastruktur

MUNI/A/1520/2021, interní kód MU

Název: Aplikovaný výzkum na FI: Bezpečnost počítačových systémů, softwarových architektur kritických infrastruktur a zpracování rozsáhlých senzorových dat

Investor: Masarykova univerzita, Aplikovaný výzkum na FI: Bezpečnost počítačových systémů, softwarových architektur kritických infrastruktur a zpracování rozsáhlých senzorových dat

Přiložené soubory

2022-SIGCSE-preventing-cheating-hands-on-lab-assignments-paper.pdf

Vyhledat podobné dokumenty

2022-SIGCSE-preventing-cheating-hands-on-lab-assignments-presentation.pdf

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Citovat

VYKOPAL, Jan, Valdemar ŠVÁBENSKÝ, Pavel ŠEDA a Pavel ČELEDA. Preventing Cheating in Hands-on Lab Assignments. Online. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (SIGCSE '22). New York, NY, USA: ACM, 2022, s. 78-84. ISBN 978-1-4503-9070-5. Dostupné z: https://dx.doi.org/10.1145/3478431.3499420.

@inproceedings{1816366,
   author = {Vykopal, Jan and Švábenský, Valdemar and Šeda, Pavel and Čeleda, Pavel},
   address = {New York, NY, USA},
   booktitle = {Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (SIGCSE '22)},
   doi = {http://dx.doi.org/10.1145/3478431.3499420},
   keywords = {summative assessment; automatic problem generation; networking; operating systems; cybersecurity; exercise; homework; case study},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {New York, NY, USA},
   isbn = {978-1-4503-9070-5},
   pages = {78-84},
   publisher = {ACM},
   title = {Preventing Cheating in Hands-on Lab Assignments},
   url = {https://arxiv.org/abs/2201.01154},
   year = {2022}
}

TY  - JOUR
ID  - 1816366
AU  - Vykopal, Jan - Švábenský, Valdemar - Šeda, Pavel - Čeleda, Pavel
PY  - 2022
TI  - Preventing Cheating in Hands-on Lab Assignments
PB  - ACM
CY  - New York, NY, USA
SN  - 9781450390705
KW  - summative assessment
KW  - automatic problem generation
KW  - networking
KW  - operating systems
KW  - cybersecurity
KW  - exercise
KW  - homework
KW  - case study
UR  - https://arxiv.org/abs/2201.01154
N2  - Networking, operating systems, and cybersecurity skills are exercised best in an authentic environment. Students work with real systems and tools in a lab environment and complete assigned tasks. Since all students typically receive the same assignment, they can consult their approach and progress with an instructor, a tutoring system, or their peers. They may also search for information on the Internet. Having the same assignment for all students in class is standard practice efficient for learning and developing skills. However, it is prone to cheating when used in a summative assessment such as graded homework, a mid-term test, or a final exam. Students can easily share and submit correct answers without completing the assignment. In this paper, we discuss methods for automatic problem generation for hands-on tasks completed in a computer lab environment. Using this approach, each student receives personalized tasks. We developed software for generating and submitting these personalized tasks and conducted a case study. The software was used for creating and grading a homework assignment in an introductory security course enrolled by 207 students. The software revealed seven cases of suspicious submissions, which may constitute cheating. In addition, students and instructors welcomed the personalized assignments. Instructors commented that this approach scales well for large classes. Students rarely encountered issues while running their personalized lab environment. Finally, we have released the open-source software to enable other educators to use it in their courses and learning environments.
ER  -

VYKOPAL, Jan, Valdemar ŠVÁBENSKÝ, Pavel ŠEDA a Pavel ČELEDA. Preventing Cheating in Hands-on Lab Assignments. Online. In \textit{Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (SIGCSE '22)}. New York, NY, USA: ACM, 2022, s.~78-84. ISBN~978-1-4503-9070-5. Dostupné z: https://dx.doi.org/10.1145/3478431.3499420.

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