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Record W2148814994 · doi:10.2196/jmir.9.5.e39

Pragmatists, Positive Communicators, and Shy Enthusiasts: Three Viewpoints on Web Conferencing in Health Sciences Education

2007· article· en· W2148814994 on OpenAlexaff
Ruta Valaitis, Noori Akhtar‐Danesh, Kevin W. Eva, Anthony J Levinson, Bruce Wainman

Bibliographic record

VenueJournal of Medical Internet Research · 2007
Typearticle
Languageen
FieldDecision Sciences
TopicQ Methodology Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsViewpointsWhiteboardCurriculumMedical educationVideoconferencingInterpersonal communicationComputer sciencePsychologyMultimediaPedagogyMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Web conferencing is a synchronous technology that allows coordinated online audio and visual interactions with learners logged in to a central server. Recently, its use has grown rapidly in academia, while research on its use has not kept up. Conferencing systems typically facilitate communication and support for multiple presenters in different locations. A paucity of research has evaluated synchronous Web conferencing in health sciences education. OBJECTIVE: McMaster University Faculty of Health Sciences trialed Wimba's Live Classroom Web conferencing technology to support education and curriculum activities with students and faculty. The purpose of this study was to explore faculty, staff, and student perceptions of Web conferencing as a support for teaching and learning in health sciences. The Live Classroom technology provided features including real-time VoIP audio, an interactive whiteboard, text chat, PowerPoint slide sharing, application sharing, and archiving of live conferences to support student education and curriculum activities. METHODS: Q-methodology was used to identify unique and common viewpoints of participants who had exposure to Web conferencing to support educational applications during the trial evaluation period. This methodology is particularly useful for research on human perceptions and interpersonal relationships to identify groups of participants with different perceptions. It mixes qualitative and quantitative methods. In a Q-methodology study, the goal is to uncover different patterns of thought rather than their numerical distribution among the larger population. RESULTS: A total of 36 people participated in the study, including medical residents (14), nursing graduate students (11), health sciences faculty (9), and health sciences staff (2). Three unique viewpoints were identified: pragmatists (factor 1), positive communicators (factor 2A), and shy enthusiasts (factor 2B). These factors explained 28% (factor 1) and 11% (factor 2) of the total variance, respectively. The majority of respondents were pragmatists (n = 26), who endorsed the value of Web conferencing yet identified that technical and ease-of-use problems could jeopardize its use. Positive communicators (N = 4) enjoyed technology and felt that Web conferencing could facilitate communication in a variety of contexts. Shy enthusiasts (N = 4) were also positive and comfortable with the technology but differed in that they preferred communicating from a distance rather than face-to-face. Common viewpoints were held by all groups: they found Web conferencing to be superior to audio conferencing alone, felt more training would be useful, and had no concerns that Web conferencing would hamper their interactivity with remote participants or that students accustomed to face-to-face learning would not enjoy Web conferencing. CONCLUSIONS: Overall, all participants, including pragmatists who were more cautious about the technology, viewed Web conferencing as an enabler, especially when face-to-face meetings were not possible. Adequate technical support and training need to be provided for successful ongoing implementation of Web conferencing.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0100.016
Scholarly communication0.0050.006
Open science0.0010.009
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0020.000

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 head0.391
GPT teacher head0.623
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations36
Published2007
Admission routes1
Has abstractyes

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