Le développement professionnel lié à l’intégration pédagogique du numérique dans l'enseignement supérieur québécois : un survol des pratiques en place dans les cégeps
Notice bibliographique
Résumé
CEGEP teachers are one of a kind. Although their primary training lies within their disciplinary expertise, their primary professional function is the teaching of students, even though they are not required to undergo any form of pedagogical training. They possess a wide-ranging academic and pedagogical freedom, participate in the administration of their departments, programs and schools, and even are afforded opportunities to conduct research. These faculties also possesses varied levels of pedagogical training. This specific context calls for deep reflections on the training needs of these collegiate teachers, whose needs are numerous: content area knowledge, classroom management, up-to-date pedagogical practices, and, increasingly, digital technology. Recent initiatives from the Quebec ministries of Education and Higher Education, such as the Digital Action Plan in Education and Higher Education (2018), the Framework of Digital competency (2019a) and the Action Plan for Achievement in Higher Education (2021a), have made the classroom use of digital technology a priority for all levels within the province. Within the Quebec education system, the college network thus offers unique opportunities for research as a distinct educational niche. Many experts claim that teacher professional development is a tool that can greatly help overcome the lack of pedagogical training of CEGEP teachers. However, at this level, the data on this topic are quite scarce. Many frameworks describe the process of professional development, including those of Borko (2004), or of Uwamariya and Mukamurera (2005); the concept can be interpreted through the developmental or professional perspective. It is thus paramount to understand how and why professional development can be integrated to one’s teaching practice. Therefore, it appears important to investigate how CEGEP teacher professional development is carried out, to determine its impacts on the rollout of digital technology in the classroom. As indicated above, the Quebec government has established digital technology use and integration in the classroom as a focal point of the education system through its recent five-year Digital Action Plan in Education and Higher Education, which lasted from 2018 to 2023 (Ministère de l’Éducation et de l’Enseignement supérieur, 2018a). This plan establishes thirty-three unique objectives which address, amongst other topics, equipment use and acquisition, required resources and teacher support and training. The interest of the current project involves the integration of digital technology to the daily classroom practices of CEGEP teachers. It therefore appears logical to examine current teacher uses to then better examine and understand the training needed to support such practices. The results of this project are presented as three research articles, the first of which offers an overall view of CEGEP teacher professional development across multiple colleges in the province. Using a mixed method research survey, the data presented within this paper show that professional development practices vary greatly between colleges and are largely decentralized. Within the studied programs, most appear to focus on the development of teaching skills, a stated desired outcome of many studied programs. The second presented article describes the uses CEGEP teachers make of digital technology in their daily practices. One outcome of this portion of the project was the ability to catalogue the various hardware and software tools employed by teachers in a Montreal-area college, within the context of a single mixed method case study using a mixed survey and semi-directed interviews. In addition to these results, frameworks for digital technology use (Russell et al., 2003), and for the roles of digital technology in the learning process (McKnight et al., 2016), were both used to analyze the habits of the studies CEGEP teachers. Overall, the collected data support both frameworks at the collegiate level and allow for their preliminary validation at this educational level. The third article presented exposes another aspect of the results obtained in the previously described case study, and pertain to the professional development of CEGEP teachers. To properly contextualize these results, it was important to consult an administrator at the college to establish an in-depth understanding of the professional development program on offer at the college, which includes pedagogical days, a teaching lab, discretionary funds, a partnership with the PERFORMA program and independently led teacher activities. Furthermore, analysis of teacher perceptions demonstrate that they do not find this program particularly useful, namely due to its lack of relevance to their daily practice. However, certain positive perceptions were also documented, which include the flexibility of the program and the opportunities to interact with other faculty and college community members. This research project manages to expose the complexity that belies the professional development of CEGEP teachers and their uses of digital technology. As well, the documented results allowed for the preliminary validation, at the collegiate level, of conceptual frameworks related to the uses (Russell et al., 2003) and roles (McKnight et al., 2016) of digital technology in collegiate classrooms. Furthermore, the collected data support a proposed expansion of the CEGEP professional development framework proposed by Lauzon ( 2002a), while also proving important and interesting paths for future research. To conclude, a proposal for the implementation of a collegiate teaching professional framework and a national professional development program are presented to standardize the professional development opportunities presented to CEGEP teachers and help support larger ministerial projects, such as the widespread adoption and integration of digital technology in the province’s classrooms and student achievement in higher education.
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 | 0,004 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,004 |
| Études des sciences et des technologies | 0,010 | 0,007 |
| Communication savante | 0,008 | 0,006 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 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 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 ».