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Record W3024747827 · doi:10.14434/josotl.v20i1.25093

Powerful learning tool or ‘cool factor’? Instructors’ perceptions of using film and video within teaching and learning

2020· article· en· W3024747827 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of the Scholarship of Teaching and Learning · 2020
Typearticle
Languageen
FieldHealth Professions
TopicFilm in Education and Therapy
Canadian institutionsMcMaster University
Fundersnot available
KeywordsContext (archaeology)Process (computing)PsychologyPerceptionTeaching methodMathematics educationEducational technologyMultimediaPedagogyComputer science

Abstract

fetched live from OpenAlex

This study builds upon previous research that explores the use of film and video in a pedagogical context by explicitly asking instructors about their attitudes towards and motivations for employing such texts in their teaching, as well as the challenges they face in the process. Data were gathered through an anonymous, online survey of instructors across disciplines at seven Ontario universities. Commonalities were found amongst participants in the purposes cited for using film and video as well as in the challenges that accompany use of this pedagogical tool. For example, instructors in four of our six Faculty groupings commonly noted drawing on film and video to engage student attention, and the two most frequently selected challenges in five of our six Faculty groupings were ‘technical difficulties screening films’ and ‘problems finding appropriate materials’. We consider the implications of these findings for teaching and learning and suggest areas for future research.

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)0.007
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.014
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 head0.071
GPT teacher head0.402
Teacher spread0.331 · 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