MétaCan
Menu
Back to cohort
Record W1604927769 · doi:10.19173/irrodl.v10i3.629

Video-Driven Multimedia, Web-Based Training in the Corporate Sector: Pedagogical Equivalence and Component Effectiveness

2009· article· en· W1604927769 on OpenAlexvenueno aff
Katherine Pang

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsMultimediaComputer scienceWeb applicationComponent (thermodynamics)World Wide Web

Abstract

fetched live from OpenAlex

The purpose of this study was to assess the pedagogical equivalence, as determined by knowledge gains, and the pedagogical effectiveness of certain components in a video-driven multimedia, web-based professional development training program as compared to a traditional, face-to-face program under real-world constraints of time and limited economic resources. The study focused on the use of video-driven multimedia, web-based instruction in the corporate environment to determine if the quality of the learning experience and the knowledge gained from the instruction were the same as with traditional methods. This experimental study assigned business professionals quasi-randomly to either a control group or an experimental group, where they attended either a live-instructed professional development program or a video-driven multimedia, web-based professional development program. Overall, results indicated that the video-driven multimedia, web-based instruction was not only pedagogically equivalent in terms of knowledge gains to the live instruction but that the knowledge gains were slightly higher among the web-based participants. Further, certain components in the web-based environment contributed more than components in the live environment to pedagogical effectiveness.

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)0.015
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 score0.557
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.267
GPT teacher head0.499
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 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

Citations32
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueThe International Review of Research in Open and Distributed LearningSame topicOnline and Blended LearningFrench-language works237,207