Notice bibliographique
Résumé
AbstractThe challenges that massive open online courses (MOOCs) bring to learning arena spur adult educators to improve delivery. A framework for a new type of MOOC is presented to address some of challenges presented by earlier models. This new MOOC, called a mesoMOOC, can bridge several challenges that hinder current effective delivery of MOOCs and utilize proven strategies in online learning to better implement MOOCs. The framework for mesoMOOC calls for MOOC designers to address orientation process, embed a connectivist synchronous component to classroom, provide online formative and summative assessment, and develop subsections within classes.IntroductionIn spite of development of massive open online courses (MOOCs) as a form of adult learning, adult educators as a whole have not been at forefront of ensuring that effective pedagogical and andragogical principles have been embedded in process. Thus, not all forward movement has been characterized as progress. Linda Morris (2013), President of American Association for Adult and Continuing Education (AAACE), acknowledges that MOOCs are gaining ground as a means of reaching adult learners. She encourages educators of adults to enter discussion that is already taking place and challenges us to address ineffective practices of MOOCs.McAuley, Stewart, Siemens, and Cormier (2010) explain that a MOOC integrates connectivity of social networking, facilitation of an acknowledged expert in a field of study, and a collection of freely accessible online resources (p. 4). If one were to stop there, this definition might fit current definition of a MOOC. However, McAuley et al. continue on to say that perhaps most importantly, a MOOC builds on active engagement of several hundred to several thousand 'students' who self-organize their participation according to learning goals, prior knowledge and skill, and common interests (p. 4).The research on MOOCs is minimal yet growing. The research shows a clear delineation in what a MOOC of 2008 and what a MOOC of 2013 represent.In 2008, Siemens' theory of Connectivism became basis for development of CCK08, which is now referred to as first MOOC and was delivered through University of Manitoba (Mackness, Mak, & Williams, 2010). This MOOC was designed with the notion that large numbers of participants (thousands) might gain significant benefits from participating in a course (O'Toole, 2013, p. 2).cMOOCsConnectivist MOOCs (cMOOCs) follow connectivist principles, where large numbers of participants self-assemble collections of knowledge, learning activities and curriculum from openly available sources across publicly open platforms (O'Toole, 2013, p. 1). The idea behind cMOOCs is that they focus on collaborative education through knowledge creation as opposed to duplication of knowledge already known (Siemens, 2012, para. 3). The assumption then is that with collaboration greatest benefit occurs when more people put in more effort and thus work more intelligently (O'Toole, 2013, p. 1).The Challenges of cMOOCsAlthough cMOOCs embed and practice many effective techniques for reaching participants, there are a number of challenges that cMOOC design and implementation should address. Kop (2011) noted that:The motivational factors in a traditional adult education classroom are very important in learners.... If confidence levels are low, it is not likely that a person will take up connectivist learning. The technology itself or activity learner is taking on could form a barrier, (p. 22)Another challenge of cMOOC lies in inability to effectively reach a massive audience. Stewart (2013) points out that with cMOOC the network effect of peer-oriented communications and connections and process-focused knowledge generation may thus be difficult to contain entirely, particularly at scale (p. …
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 | 0,000 | 0,001 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».