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Enregistrement W3137516511

Knowledge Network for Applied Education Research (KNAER) FINAL REPORT

2014· article· en· W3137516511 sur OpenAlexaboutno aff
Carol Campbell, Katina Pollock, Shasta Carr-Harris, Patricia Briscoe

Notice bibliographique

RevueScholarship@Western (Western University) · 2014
Typearticle
Langueen
DomaineComputer Science
ThématiqueOnline Learning and Analytics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésComputer science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Category 2: Building or Extending Networks (6 Projects) KMb Strategies.All projects exhibited similar KMb efforts: creating new or extending existing networks, developing a need-based or gap assessment, and producing appropriate products and dissemination processes based on the results gathered.New or existing partnerships were used to further develop networks.The projects generated numerous products connected to a KMb plan for networking for a particular purpose.Challenges.The major challenge was time.Innovative approaches to developing products required more time than anticipated and projects also encountered a range of practical challenges concerning time for ethics approvals, participants' workload and schedules, gaining access to stakeholders, and time required to develop trusting partnerships and to move forward to implementation.Successes.The overarching success theme was access and connection to other people.Projects reported the use of learning communities and engaging with stakeholders. Category 3: Strengthening Research Brokering (19 Projects)KMb Strategies.Most projects within this category exhibited similar KMb strategies, they organized steering committees to guide their work and gathered information via a literature review or by collecting information from stakeholders.Once a gap in practice was identified, the projects served as research brokers by collecting and mobilizing relevant knowledge to inform practice.Challenges.Operational challenges encountered included coming to consensus across different partners about what knowledge was to be shared, balancing partners' time and workload to achieve project goals, and difficulties if the participants involved had a lack of project topic knowledge.Successes.Successes involved building lasting networks with different stakeholders for continued knowledge brokering.Success stories generally focused on the effective use of intermediaries to connect research to practice. Category 4: Visiting World Experts (6 Projects)KMb strategies.The KMb plan for these projects included hosting visiting scholars.Projects either established partnerships with recognized networks or forged new networks, including universities and schools.Projects utilized partners' social media and communication processes to mobilize KMb products.Challenges.Maximizing the benefits of short visits was a common challenge.Successes.These projects built on and advanced already established KMb efforts. Collaboration through Partnerships and NetworkingThere were 140 different partners of varying types involved in the projects.Over half (26 of 44) of the projects created new partnerships.All regions of Ontario had some degree of connection to a KNAER network and some networks extended nationally and/or internationally.v Relationship BuildingPIs indicated the importance of developing intentional relationships with individuals or organizations with similar interests and/or to provide intended access.Substantial time and effort needed to be invested to make face-to-face opportunities happen. Network CreationFor PIs who created new networks, having a strategic implementation plan regarding how to build a specific network was essential. Network ExpansionPIs expanding existing networks indicated the importance of developing trusting relationships.Establishing collaborative teams with common goals and engaging in joint conversations was crucial.Recommendation 3: While highly successful overall, there remain recurring themes that require consideration upfront in the future work of a possible "KNAER Phase II" including attention to a clear, agreed-upon vision between members, as well as attention to the various roles and responsibilities of each partner. Identify and Approve Applied Education Research and Knowledge Mobilization Projects in Support of Enhancing Practice Recommendation 4:To learn from the experiences of the KNAER projects to inform future approaches to KMb, applied education research, and improved impact for enhancing practice.To consider, for example: the benefits of using professional learning communities to develop research-to-practice connections, the importance of actionable products such as professional resources for use by educators, and the need for training and guides to KMb for researchers.Recommendation 5: To act on the future opportunities proposed in the external evaluation to: focus on development of quality KMb activities, provide sector-wide training on KMb, and leverage existing knowledge and resources from the KNAER. Ensure Collaboration between Leading Provincial, National, and International Researchers Recommendation 6:Include attention to the provision of guidance and supports for effective partnership working into future models and plans.Recommendation 7: There is a need for provincial support for networking across projects and beyond and developing an overall Ministry-university partnership(s) to function as a "hub" or "knowledge broker" to connect individuals, organizations, and activities around shared priority interests and areas of evidence.Recommendation 10: For the Ontario Ministry of Education (and Government) to engage in and support partnerships to advance an evidence-informed education system. Recommendation 11:Analyze the current status of an evidence-informed system for education in Ontario.Recommendation 12: Clarify the purpose of KNAER Phase II and conceptualize the intended function.Recommendation 13: Develop a specific focus and linked goals. Recommendation 14: Provincial functions for KNAER Phase II include

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,042
score de la tête « metaresearch » (Gemma)0,057
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,306
Score d'incertitude au seuil0,990

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0420,057
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0050,006
Études des sciences et des technologies0,0020,001
Communication savante0,0120,006
Science ouverte0,0030,008
Intégrité de la recherche0,0030,003
Charge utile insuffisante (le modèle a refusé de juger)0,3060,187

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.

Tête enseignante Opus0,171
Tête enseignante GPT0,404
Écart entre enseignants0,233 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2014
Routes d'admission1
Résumé présentoui

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