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Record W4406287339 · doi:10.1080/07380577.2025.2450712

The Role of Reflective Activities for Occupational Therapy Education: Key Elements from a Student Perspective

2025· article· en· W4406287339 on OpenAlexaffabout
MuhamadIrfanYasin Au, Jenna Knelson, Gayla Grinde, Shu‐Ping Chen

Bibliographic record

VenueOccupational Therapy In Health Care · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPerspective (graphical)Occupational therapyThematic analysisReflective practicePsychologyDescriptive statisticsMedical educationReflective writingExploratory researchQualitative researchPedagogyMedicineSociologyComputer scienceSocial science

Abstract

fetched live from OpenAlex

This exploratory study explored second-year students' experience with reflective activities in a Canadian Master's in Occupation Therapy program. A survey and follow-up interviews were conducted to examine multiple perspectives and the influences of reflective activities on students. Data were analyzed using descriptive statistics, Pearson Chi-Square, and thematic analysis. Findings revealed that reflections on personal or societal perspectives were perceived to be more beneficial than reflections on clinical simulations. Three themes emerged: (1) key elements influencing the reflective experience, (2) diverse experiences of reflective activity, and (3) the perceived outcomes resulting from positive reflective experiences. This study highlights the significance of reflective activities in occupational therapy education and identifies key elements that shape students' experiences with reflective activities.

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)0.013
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.009
Scholarly communication0.0110.004
Open science0.0010.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.056
GPT teacher head0.524
Teacher spread0.468 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2025
Admission routes2
Has abstractyes

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