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Record W1484411164 · doi:10.19173/irrodl.v14i3.1477

Pedagogical roles and competencies of university teachers practicing in the e-learning environment

2013· article· en· W1484411164 on OpenAlexvenueno aff
Pablo César Muñoz Carril, Mercedes González Sanmamed, Núria Hernández Sellés

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsMedical educationScope (computer science)PsychologyHigher educationFaculty developmentPerceptionPedagogyInstructional designFocus groupMathematics educationComputer scienceProfessional developmentSociologyMedicinePolitical science

Abstract

fetched live from OpenAlex

<p>Identifying the roles and competencies of faculty performing in virtual environments is crucial to higher education institutions in order to build a common frame for teaching and training initiatives. One of the goals of this study is to identify and systematize faculty’s roles through a review of the most representative surveys. There has also been an effort to identify competencies associated to every role, with an emphasis on those of the pedagogical scope, by means of a focus group. Furthermore, a cross-sectional survey with 166 faculty participants has been conducted in order to identify faculty’s level of proficiency on the pedagogical competencies and the interest in training programs. Teacher perceptions on both these aspects constitutes a relevant reference for the design of faculty training programs. Results reveal that content drafting is the aspect in which the subjects declare the highest level of proficiency as opposed to assessment. Faculty also appear to be willing to improve their training, being aware of the changes and requirements entailed by e-learning.</p>

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)0.010
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score0.721

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.136
GPT teacher head0.454
Teacher spread0.317 · 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 designObservational
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

Citations141
Published2013
Admission routes1
Has abstractyes

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