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Asynchronous Lectures, View-Speed Effect

2021· article· en· W4214875055 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

VenueLiteracy Information and Computer Education Journal · 2021
Typearticle
Languageen
FieldComputer Science
TopicQuantum Computing Algorithms and Architecture
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAsynchronous communicationComputer scienceParallel computingMathematics educationMathematicsTelecommunications

Abstract

fetched live from OpenAlex

A study on the effect of speed-watching of recorded lectures in a second, third-, and fourth-year Mechanical Engineering undergraduate courses and one Graduate level course showed that the view speed (i.e. watching lectures with 1.5 or 2 times faster than normal speed) has no significant effect on the average grade performance. While the data might suggest that the supposed benefits of being able to speed up a lecture (preserving a lecture content while decreasing the amount of time spending on it) does not have any significant effect on a student's understanding of the Engineering topics content, there might be some disadvantages in speedwatching. Through, a post survey of the same sample groups, majority (82%) of the speed watcher reported that they feel a bit impatient when they couldn't "speed up" a live conversation. Some reported the feeling of frustration or a lack of attention when they have to attend a live lecture (real-time speed) or inperson lectures.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.999

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 communication0.0020.002
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 head0.003
GPT teacher head0.241
Teacher spread0.238 · 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