Certifying TEACHERS as Distance Learning SPECIALISTS
Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
AS the viability of using distance learning (DL) to reach students increases for school districts, there is a need for sound methodology on how to teach using the medium. How can instructors transition from relating to a warm body to relating to the camera? Are there established certification standards for instructors to teach over the information highway? What skills do instructors need to effectively teach using remote learning technologies? This article grew from a formative evaluation of the Direct Technical Assistance Model for Assisting Classroom Teachers in the Use of Technology to Improve Teaching and project in eastern North Carolina conducted by SERVE, Inc. A goal of this project was to identify and improve the skills teachers need to teach over the North Carolina Information Highway (NCIH) and provide certification standards for teachers to teach via the medium of telecommunications technologies. Certifying Teachers to Teach over the Information Highway Funded through the Technology Literacy Challenge Fund Sub-Grant Program, the project called for teachers and administrators in eastern North Carolina to participate in a series of workshops to prepare them to teach on the NCIH. As a beginning step in establishing standards for the state of North Carolina, the evaluator was tasked with determining what other states were doing regarding certification of teachers by: * Making inquiries on a distance education listserv, the Distance Education Online Symposium(1); * Reviewing relevant Web sites, including the US Distance Learning Association at www.usdla.org and the Distance Education and Training Council at www.detc.org; and * Searching for related literature on the ERIC online database (http://ericir.syr.edu) and in several distance education journals, including The American Journal of Distance Education (www.cde.psu.edu/acsde/jour.html), Distance Education: An International Journal (www.usq.edu.au/dec/decjournal/demain.html), From Now On: The Educational Technology Journal (www.fno.org), Syllabus: New Directions in Educational Technology (www.syllabus.com), and T.H.E. Journal (www.thejournal.com). Web and journal searches, though extensive, yielded little useful information. Numerous leads, provided by the members of the Distance Education Online Symposium (DEOS), led to information about a variety of short courses and degree programs designed to prepare teachers to teach via DL technology. The following examples illustrate the range of training options available to teachers: * A five-day Distance Education Certification Program offered through the Center for Distance Learning Research at Texas A&M University (www.cdlr.tamu.edu). The program includes 40 hours of competency-based training conducted on the campus of Texas A&M. To receive the Distance Education Professional Certificate, participants must attend all training modules, complete a group presentation, and perform a short assignment or Competency Transfer Activity. * California State University-Hayward offers an online program in online teaching and learning (www.online.csuhayward.edu/) for teachers, trainers, administrators, and instructional designers. The Certificate in Online Teaching and Learning consists of four 4.5-unit courses including Introduction to Online Teaching and Learning, Models for Online Instruction, Technology Tools for Online Instruction, and Designing Curriculum for Online Instruction. This program is not a state-sponsored credential program for K-12 teachers. * Athabasca University in Alberta, Canada offers a Masters Degree in Distance Education (www.athabascau.ca/html/depts/mde/mde broch.htm). The program was designed to cover key competencies in distance education, including systems concepts, instructional systems design, individualized instruction, developing an instructional product, and planning and management of distance education programs. …
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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 | 0,002 | 0,000 |
| 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 | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 découle