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Record W4391361292 · doi:10.1080/00220973.2024.2306399

Examining Increasing Playback Speed in Recorded Lectures on Memory, Attention, and Experience

2024· article· en· W4391361292 on OpenAlex
Serena Tran, Laura J. Bianchi, Evan F. Risko

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 Journal of Experimental Education · 2024
Typearticle
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPsychologyCognitive psychologyComputer science

Abstract

fetched live from OpenAlex

Recorded lectures represent a popular means of delivering educational content. These lectures afford increasing the playback speed which could be used to reduce time demands and increase the likelihood that a lecture is consumed. In two experiments (N = 320), we examined the impact of increasing the playback speed of lectures across a range of speeds on memory for the lecture material, mind wandering, and the learner’s experience of the lecture. For speeds up until 2x, findings revealed no significant differences in memory for the material, mind wandering, and learner’s subjective experience of the lecture, with the exception that “enjoyment of speed” decreased as speed increased. Beyond a speed of 2x, however, significant impairments in memory for the lecture material and decreases in liking toward both the video lecture and the speed were observed. Moreover, the increase in mind wandering with time on task often observed in recorded lectures was not modulated by lecture playback speed. These results reinforce extant results in the literature on the effects of increasing playback speed on memory for lecture material and add new insights in terms of this strategy’s influence on mind wandering and learner’s subjective experience of the lecture.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.057
GPT teacher head0.342
Teacher spread0.286 · 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