University Student and Faculty Opinions on Academic Integrity Are Informed by Social Practices or Personal Values
Notice bibliographique
Résumé
A Review of: Randall, Ken, Denise G. Bender and Diane M. Montgomery. “Determining the Opinions of Health Sciences Students and Faculty Regarding Academic Integrity.” International Journal for Educational Integrity 3.2 (2007): 27-40. Objective – To understand the opinions of students and faculty in physical therapy (PT) and occupational therapy (OT) regarding issues of academic integrity such as plagiarism and cheating. Design – Q method (a mixed method of qualitative data collection with application of quantitative methods to facilitate grouping and interpretation). Setting – An urban university-affiliated health sciences facility in the mid-western United States. Subjects – Thirty-three students and five faculty members of ages 21 to 61 years, 30 associated with the physical therapy program and 8 with occupational therapy, including 6 males and 32 females. Methods –Initially, 300 opinion statements for, against, or neutral on the subject of academic integrity were gathered from journal articles, editorials and commentaries, Internet sites, and personal web logs, 36 of which were selected to represent a full spectrum of perspectives on the topic. Participants in the study performed a “Q-sort” in which they ranked the 36 statements as more-like or less-like their own values. A correlation matrix was developed based on the participants' rankings to create “factors” or groups of individuals with similar views. Two such groups were found and interpreted qualitatively to meaningfully describe the differing views of each group. Three participants could not be sorted into either group, being split between the factors. Main Results – Analysis of the two groups, using software specific to the Q method, revealed a good deal of consensus, particularly in being “most unlike” those statements in support of academic dishonesty. The two groups differed primarily in the motivation for academic honesty. Factor one, with 21 individuals, was labeled “Collective Integrity,” (CI) being represented by socially oriented statements such as “I believe in being honest, true, virtuous, and in doing good to all people,” or “My goal is to help create a world where all people are treated with fairness, decency, and respect.” Factor two, with 14 individuals, was described as “Personal Integrity,” (PI), and focused on an internal sense of values and self-modulation, identifying with statements like “Honour means having the courage to make difficult choices and accepting responsibility for actions and their consequences, even at personal cost.” There were also some demographic patterns in the results. Twenty of the 31 students, 20 of the 29 females, and 17 of the 25 participants aged 30 and under were in the CI group, while 3 of the 4 faculty were in PI. Males, occupational therapists, physical therapists, and those over the age of 30 did not belong clearly to one or the other group, having close to equal numbers in both. Conclusion – Given the two factors, CI and PI, this sample of OT and PT students and faculty can be seen to make academic decisions based on either what they believe society deems correct or what their own internal values tell them. The discovery that more females, students, and those 30 and under were associated with CI resonates with the some key claims in the literature, such as that younger individuals tend to have a more social outlook on academic integrity, or that women's ethic of care is often focused on connections among people. Most importantly, students and faculty appear to share a notable degree of common ground as it relates to their opinions on academic integrity. Additional exploration and the continued use and development of policies promoting academic integrity is called for.
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 | 0,007 |
| 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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,150 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 ».