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Record W2141187687 · doi:10.4018/ijopcd.2012070103

Speech Cueing on the Web by 'the Little Dude': Multimedia Instruction for Young Children

2012· article· en· W2141187687 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.

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

Bibliographic record

VenueSSRN Electronic Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Tools and Methods
Canadian institutionsBow Valley CollegeMemorial University of Newfoundland
Fundersnot available
KeywordsMultimediaGraphicsComputer sciencePsychologyPicture booksVisual artsArt

Abstract

fetched live from OpenAlex

There is a real need for studies on learning from multimedia with school-age children, even pre-school children. In this research, temporal speech cueing was proposed to help young children as they listened to a speaking pedagogical agent direct their attention to details in on-screen text and graphics. An experiment was conducted with 4th and 5th graders (n = 133) who read on-screen text, and listened to cues presented by a pedagogical agent. Results showed that children in the speech cueing group out-performed those in the on-screen text group in immediate and delayed post-tests. Agent movement had no effect. Implications are discussed for helping young children to learn from the on-screen text presented in contemporary educational multimedia.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.577
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.022
GPT teacher head0.340
Teacher spread0.318 · 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