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Record W4410891438 · doi:10.20343/teachlearninqu.13.30

Exploring Immediate and Sustained Changes in Teaching Practices Following Midterm Student Feedback

2025· article· en· W4410891438 on OpenAlexaffabout
Rebecca L. Taylor, Kris Knorr, Michelle Ogrodnik, Peter Sinclair

Bibliographic record

VenueTeaching & Learning Inquiry The ISSOTL Journal · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsDouglas CollegeUniversity of WaterlooMcMaster University
Fundersnot available
KeywordsHigher educationPsychologyMathematics educationMedical educationPedagogyMedicineEconomicsEconomic growth

Abstract

fetched live from OpenAlex

Midterm student feedback is increasingly considered to have greater potential for improvement in post-secondary teaching than end-of-term course evaluations. While many benefits have been established, the process for gathering midterm feedback has been studied exclusively with the aim of characterizing short-term effects. At McMaster University, in Hamilton, Ontario, Canada, midterm student feedback is called a “course refinement.” As the final part of a multiphase study investigating instructors’ perceptions of the course refinement process and its impact, this paper examines whether changes made by instructors following the course refinement process are sustained beyond the term. The study involved two phases of data collection: initially, a semi-structured in-person interview or survey completed one to three months following the conclusion of an instructor’s refined course, followed by an additional interview one year after the instructor’s course refinement. Changes to instructors’ teaching practices were evident in both phases. Furthermore, a thorough examination of sustained change revealed two predominant themes: the relationship between sustained change and instructors’ beliefs about teaching, and the impact of sustained change on various levels of higher education. The latter theme is explored via an ecological systems framework, which revealed much broader implications than we ever imagined. Course refinements do, indeed, lead to lasting changes that go beyond the boundaries of a course and have effects departmentally, institutionally, and inter-institutionally—and conceivably even influence post-secondary society and culture more widely.

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)0.043
metaresearch head score (Gemma)0.029
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0430.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.000
Scholarly communication0.0020.003
Open science0.0010.000
Research integrity0.0000.006
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 head0.229
GPT teacher head0.476
Teacher spread0.247 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2025
Admission routes2
Has abstractyes

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