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Enregistrement W4379883382 · doi:10.21428/f1f23564.0576ee6f

Making Things Together: Collaborating and Mentoring on an OER Project

2023· article· en· W4379883382 sur OpenAlexafffund
Denae Dyck, Andrea Korda, Mary Elizabeth Leighton, Vanessa Warne, Katherine DeCoste, Madison George-Berlet, Maryssa Grayer, Anne Hung, J. Krahn, Natalie LoVetri, Anne Mirejovsky, Ruth Ormiston, Allegra Stevenson-Kaplan, Jamie Zabel

Notice bibliographique

RevueIDEAH · 2023
Typearticle
Langueen
DomaineComputer Science
ThématiqueOpen Education and E-Learning
Établissements canadiensUniversity of ManitobaSimon Fraser UniversityUniversity of AlbertaUniversity of Victoria
Organismes subventionnairesSocial Sciences and Humanities Research Council of Canada
Mots-clésProcess managementEngineering ethicsEngineering

Résumé

récupéré en direct d'OpenAlex

Making Things Together: Collaborating and Mentoring on an OER Project 2In spring 2020, during the early months of the COVID-19 pandemic, articles in the Smithsonian Magazine and the Atlantic reported a resurgence of interest in handicrafts as a means of both finding calm and building community (Grossman; Machemer; Smith).DIY arts and crafts surged in popularity in North America, with "stay-at-home orders [inspiring] those with ample free time to pick up hands-on projects" (Machemer).At the same time, teaching and learning, as well as academic conferences, moved online into hands-off virtual spaces.Connected by a shared interest in both craft and Victorian material culture, a small group of academics piloted two virtual events to enable hands-on learning in a hands-off context: a roundtable on Victorian objects and a workshop on Victorian hair art.Prompted by COVID-19 restrictions on in-person gatherings and fueled by the community support that coalesced around these events, the group launched a year-long series to study old things using new methods of virtual connection: Crafting Communities: A Series of Victorian Object Lessons & Scholarly Exchanges in COVID Times. 1 In its inception, we, the members of this group, imagined Crafting Communities primarily as a series of virtual events hosted over Zoom.But as we sought to secure a legacy for live roundtable and workshop events by developing a digital exhibit, a podcast, and a website, what we had imagined primarily as an event series morphed into a digital humanities (DH) project and an open educational resource (OER).As we assembled a team of collaborators and recruited student research assistants, our hands-on investigation of Victorian material culture became, also, a hands-on crash course in digital making, collaboration, and mentoring.We found ourselves doing what we now think of as "Accidental DH"-that is, learning about DH methods at the same time as we collaborated remotely with a geographically dispersed group of students.As we pursued our research focus on Victorian material culture and hands-on making, we discovered compelling parallels between our crafting of physical objects and the cultivation of digital legacy projects--that is, online resources and archives created to support and inspire further learning.While we had a lot to learn about the digital tools we were employing, our most valuable lessons concerned mentorship, lessons we learned from making things together as a team collaborating remotely across three provinces.This essay argues for the value of making together as a form of mentoring.In it, we explain how our project's focus on experimental crafting prompted us both to see and to appreciate connections between the processes of experimental crafting and digital making, processes which benefit alike from collaboration and peer mentorship.Our hands-on workshops exploring Victorian craft practices-which emphasized the pleasure of making things, the benefits of working together, and the value of failure as part of learning-primed us to imagine our OER project in similar terms and to focus on hands-on experimentation, peer mentorship, and acceptance of uncertainty.Faculty members on the team thus set aside their traditional roles as supervisorexperts, instead learning alongside student team members in skills-based training sessions and facilitating mentorship opportunities that often centred students as experts, inviting students to mentor the project's faculty members as well as one another.The project thus embraced a multi-directional mentoring model in which all team members had opportunities to learn, teach, and mentor.As faculty members made things together, they

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)0,029
score de la tête « metaresearch » (Gemma)0,031
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,029
Score d'incertitude au seuil0,153

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0290,031
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0200,008
Communication savante0,0130,010
Science ouverte0,0040,027
Intégrité de la recherche0,0030,007
Charge utile insuffisante (le modèle a refusé de juger)0,0150,006

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 Opus0,055
Tête enseignante GPT0,357
Écart entre enseignants0,301 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

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
Publié2023
Routes d'admission2
Résumé présentoui

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