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Record W1979350885 · doi:10.4018/jvple.2011070103

Developing New Literacies through Blended Learning

2011· article· en· W1979350885 on OpenAlex
Deborah Kitchener, Janet Murphy, Robert Lebans

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

VenueInternational Journal of Virtual and Personal Learning Environments · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsYork University
Fundersnot available
KeywordsNumeracyLiteracyMathematics educationBlended learningSituatedPedagogyEducational technologyPsychologySociologyComputer science

Abstract

fetched live from OpenAlex

This article reports on the implementation and impact of two blended models of teacher professional learning that promote innovative classroom practice and improved literacy and numeracy in six school districts in Ontario, Canada. The Advanced Broadband Enabled Learning Program (ABEL), situated at York University in Toronto, Ontario, Canada, transforms how teachers learn and teach through a strategic blend of face-to-face interaction, technological tools and resources, online interaction and support. Learning Connections (LC), its sister project, uses the same model to improve literacy and numeracy in school districts. Research into the impact of both programs reveals increased student engagement and achievement, enhanced teacher efficacy, and improved results in literacy and numeracy. This report presents the findings from two participant surveys conducted in one large suburban board just north of Toronto, and one large rural board in Northern Ontario, and demonstrates how the working definition of literacy that teachers use in the classroom is being transformed by their use of technology in the classroom.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.864
Threshold uncertainty score0.770

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.052
GPT teacher head0.325
Teacher spread0.273 · 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