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Record W2205138048

Effects of synchronous redundancy in multimedia on recognition

2000· article· en· W2205138048 on OpenAlex
Deborah Lynn Ptak

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Atrium (University of Guelph) · 2000
Typearticle
Languageen
FieldHealth Professions
TopicInnovation in Digital Healthcare Systems
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsComputer scienceRedundancy (engineering)MultimediaSpeech recognition
DOInot available

Abstract

fetched live from OpenAlex

This thesis considered whether multimedia learning materials should simultaneously combine continuous text captions, audio, and video. Multiple Resource Theory suggests that interference among media competing for resources may diminish attention and learning. In contrast, redundancy advocates claim that when media present redundant content, learning is not limited by interference and may even be enhanced. These contrasting perspectives were tested by measuring recognition, comprehension, and subjective experience in three groups. One group saw an audio-video (AV) program with redundant text captioning ("in-synch"). A second group saw the same content, but the captions were delayed by 10 seconds. The control group saw only the AV. Results were marginal, but indicated some trends. The "in-synch" group's recognition of audio content was enhanced relative to the control group. They found it easier to pay attention, were more biased to say they recognized audio content-prompts, and tended to be more sensitive (accurate) than the control. In fact, significantly more subjects had a higher sensitivity to audio than video. The group which received "out-of-synch" captions also were more biased, but not more sensitive than the control, and found the captions difficult to follow.

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)0.001
metaresearch head score (Gemma)0.000
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 score0.949
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.032
GPT teacher head0.308
Teacher spread0.276 · 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