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Record W3120566955 · doi:10.5430/jnep.v11n5p10

Interdisciplinary teaching practices: Reflections from a teaching triangle

2021· article· en· W3120566955 on OpenAlexafffundvenue
Melba Sheila D’Souza, Bala Raju Nikku, Cael Field

Bibliographic record

VenueJournal of Nursing Education and Practice · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsThompson Rivers University
FundersThompson Rivers University
KeywordsClass (philosophy)PedagogyTeaching methodReflective practicePsychologyMathematics educationAction (physics)Computer science

Abstract

fetched live from OpenAlex

Background and aim: There is an increased understanding of and appreciation for teachers' work from other disciplines, primarily for formulating individual plans and enhancing one's teaching based on observations and shared reflections. This article reviews how reflective practice, which is self-initiated and focused, informs the understanding and improvement of teaching practices, demonstrates interaction with students, and guides teaching experiences. This article aims to explore reflective practices that were meaningful for engaging in in-class instructional teaching practices.Methods: A self-study methodology was used to examine the complicated relationship between teaching and learning and knowledge in action of teacher education pedagogy.Results and discussion: As teacher, we understand the importance of problem-solving, establishing connections between relationships, and motivating students to think about missing connections or reconsidering them. Implications: The benefit of the Teaching Triangle was enhancing interdisciplinary relationships, understanding professional teaching relationships, and learning from each other without boundaries.Conclusions: Three aspects of the interdisciplinary reflective practice that emerged were adopting philosophy and purpose-driven goals; facilitating teaching pedagogy and technology; and creating culturally safe and effective student 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)0.006
metaresearch head score (Gemma)0.065
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.780
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.065
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.005
Open science0.0000.000
Research integrity0.0000.001
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 head0.199
GPT teacher head0.585
Teacher spread0.386 · 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 designQualitative
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

Citations5
Published2021
Admission routes3
Has abstractyes

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