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Minding the Gap: Comparing Student and Instructor Experiences with Critical Reflection

2021· article· en· W3135160225 on OpenAlexafffund
Bridget D. Arend, Beth Archer‐Kuhn, Kazuko Hiramatsu, Chris Ostrowdun, Janel Seeley, Adrian Jones

Bibliographic record

VenueTeaching & Learning Inquiry The ISSOTL Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicReflective Practices in Education
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsLamentValue (mathematics)Critical reflectionPerceptionPsychologyPedagogyQualitative researchReflection (computer programming)Higher educationMathematics educationSociologyComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Critical reflection (CR) is regarded as essential for learning in higher education. Many instructors want students to reflect deeply and critically, but lament perceived deficiencies in students’ value and understanding of CR. This qualitative study explored four undergraduate courses across disciplines to appraise how instructors' perceptions of CR compared to the perceptions of their students. We uncovered similarities and differences in how instructors and students define, engage, identify, and value CR. Our findings reveal tensions around how to explain CR to students, and around different methods and meanings across disciplines and contexts with implications for practice. The findings suggest that although facilitating CR remains a challenging and often-nebulous endeavor, both instructors and students value the process and the gap may not be as insurmountable as commonly perceived.

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)0.021
metaresearch head score (Gemma)0.096
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 score0.021
Threshold uncertainty score0.109

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.096
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0070.004
Open science0.0020.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.100
GPT teacher head0.469
Teacher spread0.369 · 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".

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Citations3
Published2021
Admission routes2
Has abstractyes

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