MOOCs as LIS Professional Development Platforms: Evaluating and Refining SJSU's First Not-for-Credit MOOC
Notice bibliographique
Résumé
IntroductionPundits and mass media have argued that massive open online courses (MOOCs) can transform education in the 21st century, presenting an opportunity for global, open learning. Many have greeted MOOCs with enthusiastic acclaim and described them with such words as storming (Clarke, 2013, p. 403), unprecedented (Schwartz, 2013, p. 1), and revolutionar' (Morrison, 2013, p. 1). Understanding this new, evolving landscape and its potential to make learning more accessible and affordable should be a priority for educators, and is already being scrutinized by faculty, administrators, and librarians.Beyond for-credit offerings, some schools are exploring MOOCs as a means to promote lifelong learning and professional development. In their MOOCs, LIS schools have offered timely content and learning opportunities for practitioners far and wide. Either on the sideline or on the frontline, LIS administrators and faculty are beginning to address the potential and pitfalls of MOOCs in a spirit of risk-taking and environmental scanning of future opportunities, especially in the broad area of online education.In this paper, we begin to empirically address if MOOCs can, for LIS programs, fill a role and serve new populations of learners within large-scale learning environments. To do so, we use a MOOC we designed, built, and instructed as a test bed.In Fall 2013, the SJSU School of Library and Information Science (SLIS) offered its first large-scale, open online course, the Hyperlinked Library (HL) MOOC. The MOOC was intended to serve as a professional development opportunity for students working in LIS environments. Unlike SJSU's partnership with Udacity, the SLIS's HL MOOC was offered free of charge, not for academic credit, and was taught in a bespoke learning environment.For this paper, the following research questions frame our inquiry:* Is there potential for LIS programs to serve new populations of learners using MOOC environments?* Can this MOOC model help LIS practitioners develop professionally?This paper begins with a brief review of the literature on MOOCs and large-scale professional development, before providing background about the HL MOOC. Next, we detail the findings of our analysis of preand post-course online survey responses about expectations and motivations for enrolling in the MOOC, opinions regarding the course design, course content, and perceptions regarding the course's value as a professional development venue. The paper finishes with a discussion regarding our takeaways for refining the platform and course design, as well as insights regarding the use of large-scale learning environments for professional development in LIS.Literature ReviewA Brief History of MOOCsMOOC-what the acronym describes is open to interpretation. While the M in MOOC stands for massive, there exists no hard-and-fast rule that defines what size a course needs to be to fit the name (Fasimpaur, 2013, p. 13). While openness is the primary means of differentiating MOOCs from other online courses (Fasimpaur, 2013), varying interpretations of how open a course needs to be, also confuse the issue. MOOCs are most often free and open to anyone, but some courses may restrict class enrollment on a first-come firstserved basis. Some may also require fees. The second O in MOOC is a given-the course must be offered online. Even then, however, many students have taken it upon themselves to meet in-person with others taking the same MOOC, as evinced by the nearly 30,000 people who have signed up to join one of the Coursera communities on Meetup.com, a site dedicated to helping groups with similar interests meet face-to-face (Meetup.com, 2013).The term MOOC was first used in 2008, by George Siemens and Stephen Downes, to describe a free, online course of 2,300 students taught at the University of Manitoba (Educause, 2011). Since then, largescale learning opportunities have multiplied, including varying forms and sizes of for-profit and for-credit MOOCs along with strategic partnerships with organizations like Coursera and Instructure. …
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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 | 0,004 | 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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».