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Record W2787228099 · doi:10.21083/nrsc.v0i11.4016

Flipped Classroom, Flipped Teaching and Flipped Learning in the Foreign/Second Language Post–Secondary Classroom

2018· article· en· W2787228099 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueNouvelle Revue Synergies Canada · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicSecond Language Learning and Teaching
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsFlipped classroomFlipped learningBlended learningTerminologyContext (archaeology)Mathematics educationForeign languageActive learning (machine learning)PedagogyPsychologyEducational technologyComputer scienceLinguisticsArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

The term “flipped classroom”, coined in 2007, represents a pedagogy aligned with long-established principles of student-centered learning. Over the last two decades, the flipped classroom has been adopted by instructors across a range of disciplines, from primary to post-secondary settings. During its development, the characteristics of the flipped classroom have evolved, as have the terminology used to reference it, leading practitioners and researchers to now address it as flipped classroom, flipped teaching or flipped learning. In this article, these terms will be used interchangeably. The article will examine the foundations of flipped learning, discuss its roots in learner-centered pedagogy, trace its development over the last two decades, profile its characteristics, and examine the feedback on its effectiveness and challenges as provided by flipped learning instructors and researchers. An attempt will be made to answer the following four questions. Where does flipped learning fit on the continuum of learner-centered pedagogies? How have educators responded, both positively and negatively, to the flipped learning/teaching approach? How has flipped learning been implemented in the foreign/second language (FL/L2) classroom? What are some considerations and recommendations for FL/L2 instructors contemplating using this approach in the FL/L2 post-secondary context? Finally, some suggestions will be made regarding next steps in research on flipped learning.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.008
GPT teacher head0.204
Teacher spread0.196 · 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