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VIDEO CAMERA ON-OFF DURING SYNCHRONOUS ONLINE GROUP WORK

2022· article· en· W4312818081 on OpenAlexaboutno aff
Bruna Nogueira, Amber Hartwell, Christy Thomas, Barbara Brown

Bibliographic record

VenueInternational journal on innovations in online education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsVideoconferencingOnline learningMultimediaComputer scienceOnline videoFeature (linguistics)Component (thermodynamics)CognitionGroup workWork (physics)PsychologyMathematics educationEngineering

Abstract

fetched live from OpenAlex

Since its introduction several decades ago, online learning has become a component of higher education, with institutions worldwide providing a form of online course delivery. One key feature of online learning is the use of video conferencing software and the use of a video camera feature. Grounded on Vygotsky and Wallon's ideas of how emotion and cognition are interconnected and equally relevant in learning processes, this paper aims to understand how the use of the video camera feature in synchronous online group work affects relationship building in those settings and the students' overall learning experience. Qualitative findings from 22 semistructured interviews completed with 12 students and 10 instructors enrolled in Canadian postsecondary online teacher education courses are shared. Results indicate instructors and students perceive there are consequences for turning the video camera on and off during synchronous sessions and that seeing others on camera helps promote positive affective relationships among students. The findings contribute to the literature related to video camera usage in online learning environments and serve to inform institutions and instructors designing online courses with synchronous group activities.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.362
Teacher spread0.344 · 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.

Study designNot applicable
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

Citations2
Published2022
Admission routes1
Has abstractyes

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