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Record W3003451124 · doi:10.22215/etd/2019-13787

An Eye Tracking Comparison of Instructional Videos Showing a Monologue Versus a Dialogue: Impacts On Visual Attention, Learning, and Psychological Variables

2019· dissertation· en· W3003451124 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

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicVisual and Cognitive Learning Processes
Canadian institutionsCarleton University
Fundersnot available
KeywordsMindsetEye trackingPsychologyPerceptionTracking (education)CognitionCognitive psychologyCognitive loadMultimediaComputer sciencePedagogyArtificial intelligence

Abstract

fetched live from OpenAlex

The present study aimed to synthesize two disparate domains of instructional video research to investigate what impacts occurred from, on one hand, the visual presence of the speaker(s), and on the other hand, the format of a dialogue. Seventy-seven participants watched either a narrated control video without the instructor visible, a monologue video with the instructor visible, or a dialogue video between an instructor and student, both visible. To compare the conditions, we examined learning outcomes, visual attention, self-efficacy, mindset, cognitive load, social presence, and interest. Despite eye tracking data showing that participants in speaker-visible conditions spent significantly less time attending to the learning content, we found no conditional differences on measures of learning, social presence, cognitive load, selfefficacy, or mindset. These results suggest that neither speaker visual presence nor dialogue format affected learning or participants' perceptions of the videos.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.408
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.450
Teacher spread0.379 · 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

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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