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Record W2952799258 · doi:10.22329/celt.v12i0.5382

Multidisciplinary Team-based Model for Faculty Supports in Online Learning

2019· article· en· W2952799258 on OpenAlexvenueno aff
CJ Dalton, Antoinette Thornton, Christina Dinsmore, Wanda Beyer, Keren Akiva, Beverly King

Bibliographic record

VenueCollected Essays on Learning and Teaching · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicAdult and Continuing Education Topics
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyTransformative learningHumanitiesOnline coursePedagogyMathematics educationPhilosophy

Abstract

fetched live from OpenAlex

This study examined the experiences of three new online instructors supported by a multidisciplinary, team-based model of course development and how their experiences may transform their knowledge of teaching and learning. In-depth, individual interviews with instructors during the course development process provided insights into participants’ perspectives. Analysis reveals faculty reflected positively on the overall development process and that they intend to incorporate new understandings in future course design, suggesting that the model provides a solid foundation for online course development and faculty support. Based on a cross-case analysis using Cranton’s (2002) adaptations to transformative learning theory, findings indicated the importance of critical reflection and discourse during the course development process. Lastly, the need for development teams to acknowledge time-management concerns and to consider instructors as novice learners is recognized as an essential requirement to online course development. 
 
 La présente étude se penche sur l’expérience de trois nouveaux instructeurs en ligne utilisant un modèle d’élaboration de cours multidisciplinaire fondé sur le travail d’équipe. Nous nous demandons comment cette expérience est susceptible de transformer leur connaissance de l’enseignement et de l’apprentissage. Des entrevues individuelles approfondies avec les instructeurs pendant l’élaboration des cours nous ont permis d’observer le point de vue des participants. Selon notre analyse, les enseignants ont formulé des réflexions positives au sujet du processus d’élaboration dans son ensemble. Ils ont dit vouloir incorporer leurs nouvelles connaissances dans la conception de leurs cours à l’avenir, ce qui suggère que le modèle constitue une assise solide pour l’élaboration de cours en ligne et pour le soutien des enseignants. Fondés sur une analyse transversale faisant usage des adaptations de Cranton (2002) aux théories de l’apprentissage transformationnel, nos résultats mettent en relief l’importance de la réflexion critique et du discours dans le processus d’élaboration des cours. Enfin, nous prenons acte du fait que l’équipe d’élaboration des cours doit prendre en compte les préoccupations en matière de gestion du temps et doit considérer les instructeurs comme des apprenants débutants. Ce sont là des exigences essentielles pour l’élaboration de cours en ligne.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.835
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.345
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2019
Admission routes1
Has abstractyes

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