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Record W3031616814 · doi:10.20429/ijsotl.2020.140109

"A Video of Myself Helps Me Learn": A Scoping Review of the Evidence of Video-Making for Situated Learning

2020· review· en· W3031616814 on OpenAlexafffund
Iris Epstein, Melanie Baljko, Kurt Thumlert, Evadne Kelly, James Andrew Smith, Yelin Su, Justeena Zaki-Azat, Natasha May

Bibliographic record

VenueInternational Journal for the Scholarship of Teaching and Learning · 2020
Typereview
Languageen
FieldArts and Humanities
TopicDiverse Music Education Insights
Canadian institutionsYork University
FundersYork University
KeywordsSituatedToolboxSituated learningPsychologyComputer scienceCurriculumResource (disambiguation)Multidisciplinary approachThe artsMultimediaPedagogySociologyVisual arts

Abstract

fetched live from OpenAlex

Nursing, dance and studio-based arts, engineering, and athletic therapy are viewed as practice-oriented professions in which the teaching and situated learning of practical skills are central. In order to succeed, students must perform a series of performance-based assessments, which seemingly require an "able" body to enact complex tasks in situated and/or simulation-based contexts (for example, "safe nursing practice"). Our interdisciplinary research seeks to intervene within the culture of professional learning by investigating what we know about the use of smartphone video recording for situated, practice-based learning, and for supporting interactive video-based assessment as a means of accommodation and extending access for students, including students with performance anxiety, mature students, ESL learners, students with disabilities, and students in remote communities. In this paper we employ a scoping review methodology to present our findings related to students' and instructors' perspectives on the use of smartphone video to demonstrate and document practical knowledge and practice-oriented competencies across fields in the arts and sciences. We also examine broader research, as well as the ethical and design implications for the development of our technology-based toolbox project -an online resource created to advance pedagogies deploying smartphones as tools for practical skills acquisitionand for accommodation -within multidisciplinary practical learning environments.

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.

How this classification was reachedexpand

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)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.730
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.196
GPT teacher head0.421
Teacher spread0.225 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations20
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal for the Scholarship of Teaching and LearningSame topicDiverse Music Education InsightsFrench-language works237,207