Notice bibliographique
Résumé
Gary J. Anglin is Program Coordinator of the Instructional Systems Design Program at the University of Kentucky, where he teaches graduate courses in instructional design, instructional theory, and foundations of instructional technology. His current research interests include e-Learning, in particular the adaptations students, instructional designers, and instructors will have to make in an e-learning environment. In particular, his instructional design research interests include the role of metacognition and cognitive load theory for the design of Web-based instruction.Mary Beth Bianco is a doctoral candidate at Penn State University in the Instructional Systems Department. She is currently employed as an education consultant with the BLaST, Itermediate Unit 17 in Williamsport, PA, after eight years as an elementary educator. Bianco recently finished her doctoral coursework and is in the process of completing her dissertation.Barbara Bichelmeyer is an assistant professor of instructional systems technology, Indiana University. Her primary interests in teaching, research and service activities are related to learners’ engagement, ownership and control of the learning process. Bichelmeyer is also interested in understanding the role that emotion plays in intelligence, learning and instruction. Currently, Bichelmeyer is engaged in research concerned with the relationships between learner emotions and learner engagement in Web-based learning environments.Wellesley R. (Rob) Foshay is the chief instructional architect of the PLATO Learning System. He has 25 years of experience doing instructional design in university and private sector environments. He is active in the International Society for Performance Improvement and the Association for Educational Communications and Technology, and serves on the editorial boards of two research journals. He has published over 50 major papers and book chapters on ID methodology, problem solving, e-Learning, and evaluation.Doug Harvey is currently director of the graduate program in Instructional Technology at the Richard Stockton College of New Jersey. His research focus is on the use of hypertext and online learning. He holds a doctoral degree from Penn State University in Instructional Systems.Tiffany Koszalka is an assistant professor of education and director of assessment and research for the Kids as Airborne Mission Scientist project at the Pennsylvania State University. She spent over a decade as an instructional designer creating and implementing a variety of paper-, classroom-, and technology-based training for adults in the corporate world. She then turned her attention to investigating teacher and student uses of Web-based information and human resources in K-12 science classrooms. She currently teaches instructional design and educational technology integration courses both in the classroom and through distance education. Her recent research in distance education has included computer-mediated communication, social interactions, and the design of distance education to support synchronous and asynchronous learning.Jung Lee is an assistant professor of Instructional Technology at the Richard Stockton College of New Jersey. She received a Ph.D. degree in Adult Learning and Technology from the University of Wyoming. Her research interests include visual design and human factors in hypermedia/multimedia design.Melanie Misanchuk is a doctoral student in Instructional Systems Technology at Indiana University. Her research interests include online learning communities, communities of practice, distance education, and language instruction.Richard Schwier is a professor of educational communications and technology at the University of Saskatchewan, where he teaches graduate courses in educational technology theory, instructional design, and multimedia design. Recent research interests include the use of virtual learning communities in distance education, usability research, and visual design for instructional multimedia.
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 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 | 0,002 | 0,019 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,536 | 0,313 |
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 ».