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Record W6888363896 · doi:10.20380/gi2016.26

An Investigation of Textbook-Style Highlighting for Video

2016· article· en· W6888363896 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

VenueCanada Human-Computer Communications Society · 2016
Typearticle
Languageen
FieldComputer Science
TopicVideo Analysis and Summarization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInterface (matter)Online videoInteractive videoVideo recordingDigital videoVideo trackingData collectionOnline learning

Abstract

fetched live from OpenAlex

Video is used extensively as an instructional aid within educational contexts such as blended (flipped) courses, self-learning with MOOCs and informal learning through online tutorials. One challenge is providing mechanisms for students to manage their video collection and quickly review or search for content. We provided students with a number of video interface features to establish which they would find most useful for video courses. From this, we designed an interface which uses textbook-style highlighting on a video filmstrip and transcript, both presented adjacent to a video player. This interface was qualitatively evaluated to determine if highlighting works well for saving intervals, and what strategies students use when given both direct video highlighting and the textbased transcript interface. Our participants reported that highlighting is a useful addition to instructional video. The familiar interaction of highlighting text was preferred, with the filmstrip used for intervals with more visual stimuli.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.887
Threshold uncertainty score0.989

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.027
GPT teacher head0.260
Teacher spread0.233 · 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