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Record W3177421727

Multiple Perspectives on Digital Literacies Research Methods in Canada.

2020· article· en· W3177421727 on OpenAlexvenueaboutno aff
Michelle Schira Hagerman, Pamela Beach, Megan Cotnam-Kappel, Cristyne Hébert

Bibliographic record

VenueInternational journal of e-learning & distance education · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicLiteracy, Media, and Education
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceSociology
DOInot available

Abstract

fetched live from OpenAlex

Abstract In this article, we call for Canadian digital literacies researchers to invest in designs and research methods that centralise in-the-moment insights, embrace complexity, and that are informed by a deep commitment to authentic, ethical reciprocity that serves the communities in which our work is placed. We present three cases that offer multiple perspectives for how we might operationalise these principles, and we consider implications for the use of data collected with new approaches to digital literacies assessment, with virtual retrospective think alouds, eye-tracking, and spy glasses video. As the first co-authored article by The Digital Literacies Collective, this article contributes our shared position on the methodological priorities that will enable Canadian digital literacies researchers to construct new, contextually-situated frameworks that inform digital literacies policies and practices in Canadian systems of schooling. Keywords: digital literacies; research methods; Canada; think aloud; eye tracking; spy glasses; assessment Résumé Dans cet article, nous appelons les chercheurs canadiens en littératie numérique à investir dans des conceptions et des méthodes de recherche qui centralisent les connaissances instantanées, embrassent la complexité et sont éclairées par un engagement profond envers une réciprocité authentique et éthique au service des communautés dans lesquelles se situe notre travail. Nous présentons trois cas qui offrent de multiples perspectives sur la façon dont nous pourrions opérationnaliser ces principes, et considérons les implications pour l'utilisation des données collectées avec de nouvelles approches d'évaluation des littératies numériques, avec des rétrospectives virtuelles de réflexion à haute voix, des suivis du mouvement des yeux, des vidéos enregistrées par lunettes d'espionnage. En tant que premier article co-écrit par le Collectif des littératies numériques, cet article défend notre position commune concernant les priorités méthodologiques qui permettront aux chercheurs canadiens en littératies numériques de construire de nouveaux cadres contextuels qui éclairent les politiques et les pratiques des littératies numériques dans les systèmes scolaires canadiens. Mots-clés : littératies numériques; méthodes de recherche; Canada; réfléchir à haute voix; suivi de l'oeil; lunettes d'espion; évaluation

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.141
metaresearch head score (Gemma)0.123
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.811

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1410.123
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0180.032
Science and technology studies0.0500.042
Scholarly communication0.0440.012
Open science0.0060.015
Research integrity0.0070.011
Insufficient payload (model declined to judge)0.0100.001

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 head0.067
GPT teacher head0.395
Teacher spread0.327 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
DomainMethods
GenreEmpirical

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

Citations7
Published2020
Admission routes2
Has abstractno

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Same venueInternational journal of e-learning & distance educationSame topicLiteracy, Media, and EducationFrench-language works237,207