Creating Continuing Professional Online Learning Communities
Notice bibliographique
Résumé
With continuing professional education increasingly offered through distance and distributed learning technologies, adult educators need to creatively interweave and traditional face-to-face delivery strategies to craft successful continuing professional learning opportunities and communities that extend beyond typically time-limited opportunities. While some professionals choose continuing education programs that utilize computer-mediated conferencing (CMC) because of convenience, cost-effectiveness and the unique learning environment offered online, others may experience difficulty becoming active participants within online classrooms. As a result, they may lose the professional networking potential and subsequent ongoing learning opportunities and professional development that formal courses can launch (Houle, 1980). Here, we describe how one graduate program provided working professionals with an initial formal professional development opportunity that evolved into a continuing learning community. The community was brought about through careful program planning and skillful facilitation in an atmosphere of trust and respect. The University of Calgary graduate program in workplace learning was taught mostly to working professionals across Canada using a program design strategy that combined both face-to-face and delivery Background of the Program The two-year Master of Continuing Education (MCE) program begins with a three-week, summer face-to-face institute held on the University of Calgary campus. The subsequent fall and winter terms offer core and elective courses delivered by computer-mediated conferencing (CMC). The second year repeats the first-year format and students also start a final integrative project by CMC under the direction of a faculty supervisor. The oral defense at the end of the program is conducted either in person or via audio-conference, depending on the geographic location and preference of the student. The program designers chose FirstClass course delivery software for its discussion-based format, ease of use and availability to students and faculty. A key design feature of the program is the placing of students into small, 24-member cohorts that study together for both of the institutes and all core CMC courses before taking their elective CMC courses with the larger community of MCE students. The cohort model promotes learning during the course of the program and fosters continuing professional development of the participants. One Example of Trust and Respect in Online CPE One course in the program, Facilitating Learning, was designed for students seeking instruction on how to become skillful, facilitators. Among the FirstClass software facilities available for students in the course were: Rogues Gallery for student biographies; Web Hot-Spot for additional resource material; Ask the Professor and Ask the Learner for questions about course issues; and Team Presentation for the students' use in building small group presentations on topics that were eventually shared with the entire class. Many of the best practices in delivery (for example Palloff & Pratt, 1999; Wiesenberg & Hutton, 1996) were incorporated into the course. For example, the program invited learners to share their personal stories and biographies with others as a way to develop a personal identity and shared rapport with one another online; they established their own communication guidelines and codes of netiquette that demonstrated respect for others and guided their future interactions in an community. Feedback from students about their learning experiences in this course emphasized the flexibility of course access and discussions, the ease of interaction with colleagues and faculty and the abundance of opportunities to question and dialogue about all aspects of the course as it unfolded--all aspects of the program that promoted the development of an learning community. …
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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 | 0,009 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,002 |
| Communication savante | 0,007 | 0,008 |
| Science ouverte | 0,003 | 0,014 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,023 | 0,006 |
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 ».