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Exploring the Impact: How Online Exam Proctoring Reduces Cheating and Enhances Course Legitimacy

2024· article· en· W4402034355 on OpenAlexvenueno aff
Daniel Woldeab, Thomas Brothen

Bibliographic record

VenueInternational journal of e-learning & distance education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAcademic integrity and plagiarism
Canadian institutionsnot available
Fundersnot available
KeywordsCheatingLegitimacyLignePsychologyMedical educationHumanitiesSocial psychologyMedicinePolitical science

Abstract

fetched live from OpenAlex

In this study, we analyze undergraduate student responses in 1,364 surveys to better understand student reactions to online proctoring. We present findings regarding two aspects of student reactions to online proctoring: First, we assess whether students believe that the act of cheating in online exams diminishes the legitimacy of their courses; and second, whether students think online proctoring reduces cheating and enhances the perceived legitimacy of their course performance in the eyes of graduate schools or employers. Additionally, we explore how anxiety interacts with these student perceptions. The data collected in this study support the contention that cheating reduces perceived course legitimacy, and online proctoring minimizes cheating and increases perceived course legitimacy. Finally, the data shows that when asked if they would prefer to take their examinations in the classroom or with online proctoring, students who participated in this study said they would pick online proctored exams. Keywords: online proctoring, cheating, legitimacy, anxiety Exploration de l'impact de la surveillance des examens en ligne : réduction de la tricherie et renforcement de la légitimité des cours Résumé : Dans cette étude, nous analysons les réponses d'étudiants de premier cycle dans 1 364 enquêtes afin de mieux comprendre les réactions des étudiants à la surveillance en ligne. Nous présentons les résultats concernant deux aspects des réactions des étudiants à la surveillance en ligne : d'une part, nous évaluons si les étudiants pensent que la tricherie dans les examens en ligne diminue la légitimité de leurs cours et, d'autre part, si les étudiants pensent que la surveillance en ligne réduit la tricherie et améliore la légitimité perçue de leurs résultats dans les cours aux yeux des établissements d’enseignement supérieur ou des employeurs. En outre, nous étudions l'interaction entre l'anxiété et ces perceptions des étudiants. Les données recueillies dans le cadre de cette étude confirment que la tricherie réduit la légitimité perçue des cours et que le contrôle en ligne minimise la tricherie et augmente la légitimité perçue des cours. Enfin, les données montrent que lorsqu'on leur a demandé s'ils préféraient passer leurs examens en classe ou avec un système de surveillance en ligne, les étudiants qui ont participé à cette étude ont déclaré qu'ils choisiraient les examens surveillés en ligne. Mots clés : surveillance en ligne, tricherie, légitimité, anxiété

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.674

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.055
GPT teacher head0.390
Teacher spread0.335 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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