Open Educational Practices: Equity, Achievement, and Pedagogical Innovation
Notice bibliographique
Résumé
Open Education practices (OEP) have emerged as a transformational force in higher education. Whereas, higher education promises to be an instrument for economic and social mobility, in reality our institutions reinforce existing inequalities: Achievement, engagement, and persistence are closely tied to affordability. Our claim to be student-centered is likewise hypocritical as faculty pressures, accreditation requirements, and budgetary constraints influence or dictate the structure and content of learning experiences. \n \nOpen Educational practices support teaching, learning, and publication in an increasingly diverse faculty and student body. OEP encompass the creation, adaptation, and adoption of open educational resources, open course development, and even the design of renewable, real-world assignments where students are empowered as co-creators of knowledge. These practices leverage learning beyond socio-economic disparities and put engaged, active student (and faculty) learning at the center. These practices champion academic freedom, pedagogical innovation, applied approaches, and innovation. OEP represents learner-centered and learning-together approaches to education that radically enhance both agency and access. \n \nThis presentation draws on a diverse set of examples to make a case for why the shift away from traditional (closed) practices is not only desirable but also inevitable, and how OEP support the modern university’s mission by serving academic achievement, faculty and student engagement, diversity & inclusion, pedagogical innovation, and the university’s Land-grant mission. \n \nThis event was part of Virginia Tech’s Open Education Week 2018 Symposium. \n \nPresenter: Dr. Rajiv Jhangiani <a href="https://thatpsychprof.com/about">https://thatpsychprof.com/about</a> \n \nRajiv Jhangiani is Special Advisor to the Provost and a faculty member in the Psychology Department at Kwantlen Polytechnic University, British Columbia. He earned his Ph.D. in Social & Personality Psychology in 2009 from the University of British Columbia and has published articles and chapters in political psychology, the scholarship of teaching & learning, and open educational practices. The most recent of his two books is Open: The philosophy and practices that are revolutionizing education and science published in 2017. He is also the author of two open textbooks and editor of a third in psychology. \n \nDr. Jhangiani also serves as an Ambassador for the Center for Open Science in Charlottesville, VA, Senior Open Education Research & Advocacy Fellow with BCcampus, British Columbia, and is an Associate Editor of Psychology Learning and Teaching. He previously served as an OER Research Fellow with the Open Education Group, a Faculty Fellow with the BC Open Textbook Project, a Faculty Workshop Facilitator with the Open Textbook Network, and the Associate Editor of NOBA Psychology. \n \nHe is a well known and highly regarded expert, dynamic speaker, consultant and strong advocate of diversity and inclusion in academics, open educational practices, and the scholarship of teaching and learning across Canada and the United States.
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 | 0,015 | 0,017 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,008 | 0,054 |
| Communication savante | 0,028 | 0,020 |
| Science ouverte | 0,002 | 0,030 |
| Intégrité de la recherche | 0,004 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».