Preferences for Micro-credentials Offered by Canadian Colleges and Universities
Notice bibliographique
Résumé
Micro-credentials are certifications earned for acquiring specific skills or knowledge. They may be useful to earners for their relevance and immediacy in addressing learning needs. When offered by post-secondary institutions, micro-credentials can provide learners with flexible and focused learning pathways to employment or further education. . Noticeably absent from scholarly and public discourse on micro-credentials offered by traditional post-secondary institutions is empirical evidence about the factors potential learners of these new credentials find appealing and important. This dissertation in practice investigates the attributes that potential learners find appealing in micro-credential programs offered by accredited post-secondary institutions in Canada. Using a discrete choice experiment (DCE), the study surveyed 1,005 Canadian respondents aged 24 to 64 to understand their preferences and willingness to pay for various program attributes. These attributes included the format of instruction, total hours to complete, time commitment, provider reputation, connections to employers and other programs, availability of reimbursement, and program cost.The analysis used conjoint, latent class, and market simulation methods to explore aggregate, individual, and subgroup preferences. Subgroups were formed based on similar decision profiles and stated preferences rather than socio-demographic data. Results indicated that enrollment preferences are influenced by program cost, provider reputation, employer connections, and instructional format. Reimbursement availability, total completion hours, and time commitment were also factors, but to a lesser extent. Four latent class segments were identified, showing significant variations in preferences, particularly regarding employer connections and in-person versus online learning. Practical implications of potential learners’ preferences were demonstrated through market simulations, predicting different enrollment rates and willingness to pay among the four subgroups. This study is the first to apply DCE methodology to investigate micro-credential program preferences, providing insights into adult learner preferences and discussing their implications for program design. By quantifying preferences for various program attributes, this research establishes a national empirical baseline that informs post-secondary institutions on how to tailor micro-credential offerings to meet the diverse preferences of adult learners and serves as a foundation for future empirical research in this field.
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) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».