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Record W2950876281 · doi:10.19173/irrodl.v20i2.3838

Diversity in Video Lectures

2019· article· en· W2950876281 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2019
Typearticle
Languageen
FieldPsychology
TopicVisual and Cognitive Learning Processes
Canadian institutionsnot available
Fundersnot available
KeywordsDiversity (politics)Affect (linguistics)PsychologyCognitionMathematics educationMultimediaComputer scienceSociologyCommunication

Abstract

fetched live from OpenAlex

Media diversity within video lectures has been shown to have an effect on students who participate in both flipped classes as well as online courses. While some research claims that content delivered through multiple sources leads to more learning, contrasting research makes the claim that too much media hinders cognitive processing. The present study investigated the effects of varying levels of instructional media delivered to students (n=110) within a flipped scientific writing course to investigate the relationship between higher levels of media diversity and student performance. Results showed that more diversity led to lower levels of performance. It was also found that higher levels of media diversity correlated with higher levels of students’ scanning between different forms of media, possibly contributing to the lower levels of performance. The implications of these results provide insight into the optimal level of media diversity, and on student behavior that can affect learning.

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.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 science0.0010.002
Research integrity0.0000.001
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 head0.142
GPT teacher head0.501
Teacher spread0.359 · 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