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Record W4389376986 · doi:10.19173/irrodl.v24i4.7005

Integrating Community of Inquiry Framework Principles With Flipped Classroom Pedagogy to Enhance Students’ Perceived Presence Sense, Self-Regulated Learning, and Learning Performance in Preservice Teacher Education

2023· article· en· W4389376986 on OpenAlexvenueno aff
Abbas Taghizade, Esmaeil Azimi, Hassan Mahmoodian, Salman Akhash

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2023
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsSense of communityPsychologyMathematics educationBlended learningFlipped learningExperiential learningEducational technologySelf-regulated learningPedagogyFlipped classroomCommunity of inquirySocial psychologyCognition

Abstract

fetched live from OpenAlex

The purpose of this study was to assess the effectiveness of integrating community of inquiry (COI) framework principles with flipped classroom pedagogy to enhance students’ perceived presence sense, self-regulated learning, and learning performance. A quasi-experimental study was conducted to examine whether integrating COI framework principles with flipped classrooms could enhance college students’ perceived presence sense, self-regulated learning, and learning performance. The participants were 64 third-year male college students in an online course at a teacher education university in Iran in 2021. The study employed the COI Survey, the online self-regulated learning questionnaire (OLSQ), and a teacher-made test to measure learning performance. The results indicated significant between-group differences in perceived presence sense, self-regulated learning, and learning performance (p < 0.001). Integrating COI framework principles with flipped classroom pedagogy was an effective approach to enhancing perceived presence sense, self-regulated learning, and learning performance among teacher education students.

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)0.025
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, 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 score0.037
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.005
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 head0.121
GPT teacher head0.541
Teacher spread0.421 · 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 designObservational
Domainnot available
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

Citations3
Published2023
Admission routes1
Has abstractyes

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