Engineering Integrity: Using text-matching software in a graduate level engineering course
Notice bibliographique
Résumé
Academic misconduct is an unfortunate reality for many post-secondary level educators across disciplines; however, there is currently a paucity of Canadian research on Academic Integrity (Eaton, 2018). This study describes an inter-disciplinary project to investigate the potential for text-matching software to prevent and avoid plagiarism by graduate level engineering students. Conceptual/Theoretical Framework: Our study was informed by the potential for text-matching software to help students understand and avoid plagiarism (Zaza & McKenzie, 2018) and faculty identify instances of plagiarism in an engineering course (Cooper & Bullard, 2014). Although text-matching software has been commercially available since the 1990s, its acceptance within academic contexts is uneven. Reasons for this are manifold, but the most commonly expressed concerns are about a) the punitive nature of the software use; b) the potential for it to be used as a tool for cheating students to “beat the system”, and c) privacy concerns (Savage, 2004). Methodology / Approach: In this project, approved by the institutional REB, assignments submitted in a graduate-level engineering communication course were analyzed using text-matching software, Ithenticate. The first phase of the study involved collecting baseline data from students enrolled in a graduate-level Engineering course (N=132). As per REB protocol, individual results were not shared with the professor or teaching assistants and sharing of aggregated results is not permitted until after February 15, 2019. In our presentation, we share baseline results, as well as outcomes of the second phase of the research, in which the research associate revealed the deception, explained the study, and solicited consent from students to have their next assignment harvested and analyzed. The research associate also introduced the software and provided a workshop on academic integrity including strategies for avoiding plagiarism, such as paraphrasing. Subsequent to these workshops, assignments written by consenting participants were analyzed with Ithenticate to determine whether a reduction in textual similarity occurred. Results / Findings: The results of this study indicate that text-matching software can be useful to students and educators to prevent and identify academic misconduct. This study will add to the growing body of empirical research about academic integrity in Canada and in particular, in engineering contexts.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».