Supporting Academic Integrity: Approaches and Resources for Higher Education
Notice bibliographique
Résumé
This guide is for the higher education community as a whole . Readers might be lecturers, educational developers, student services managers or academic conduct officers who would like a better feel for the current issues relating to student plagiarism and associated concerns . It is designed to provide ‘a bird’s-eye view’: to pull together key institutional approaches and resources that have been developed since 2000 . Case studies and perspectives from a number of higher education institutions (HEIs) highlight practice at the institution, programme and course level . The intention is to make them accessible and easy to follow up, whatever your link to academic integrity issues . The notion of academic integrity has been defined as adherence to the values of “honesty, trust, fairness, respect, and responsibility” (Center for Academic Integrity, 1999, p4) . The Center for Academic Integrity, a consortium of over 360 institutions including member institutions from Australia, Canada and the US, provides expertise The Higher Education Academy – 2010 3on practice and policies that can help to foster a ‘culture’ of integrity1 . Established guidance, developed from a UK perspective, has also emphasised how HEIs need to consider issues of academic integrity and associated values when reviewing policy and practice on plagiarism within their institution (JISC, 2005) . On a more practical note, it is important to think about the principles and values that might inform the development of institutional policies, where, for example, statements on the importance of academic honesty are included in policy documents (Carroll, 2009; Morris, 2010) . The focus of this guide is on student plagiarism, but it illustrates how strategies and methods employed at a range of levels within an institution can enable students to develop an understanding of and the necessary skills for good academic practice . It is clear that HEIs in the UK have done much in recent years to address and manage student plagiarism . Initiatives, working groups and projects have been set up, and have worked to improve policies, introduce preventive measures through assessment practices, make effective use of plagiarism detection tools and develop online resources for students: the intention being to ensure that students fully grasp the concept of plagiarism and the skills they need to follow good academic practice . There is a wealth of resources available in this area and this guide is designed to provide a valuable up-to-date selection of these . It is vital that we share these resources and examples of good practice . The Academic Integrity Service was set up by the Higher Education Academy and JISC in 2008 . This initiative was charged with raising awareness of issues relating to academic integrity in UK higher education and encouraging the sharing of best practice in this area . One priority was to build on expertise by consulting with the Higher Education Academy subject centres to identify generic and subject-specific issues, and existing resources relating to academic integrity (e .g . assessment strategies, students’ skills development, plagiarism, disciplinary perspectives, examples of good practice, support resources for staff and relevant guidance for students) . This information gathering exercise informed the development of this guide.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,017 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,008 | 0,009 |
| Communication savante | 0,028 | 0,035 |
| Science ouverte | 0,005 | 0,023 |
| Intégrité de la recherche | 0,011 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,070 | 0,049 |
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 source (Gemma direct ou Codex distillé), 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 ».