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Record W4403764187 · doi:10.24908/pceea.2023.17078

Instructor Reflections from a Graduate-level Course on STEM Education Research and Practice

2024· article· en· W4403764187 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methods
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCourse (navigation)Medical educationMathematics educationPsychologyPedagogyEngineeringMedicine

Abstract

fetched live from OpenAlex

The University of Guelph has piloted a graduate-level course on STEM Education. The course sought to balance research and practice lenses, including learning outcomes and activities related to learning theories, epistemologies, research methodologies, and an embedded Instructional Skills Workshop. The course was intentionally designed to target affective learning domains, challenging learner beliefs and values about teaching and research. The aim is to share critical reflections from the co-instructors following the first offering of the course, with a focus on philosophical approaches, expectations, student perceptions, threshold concepts, and the negotiation of meaning. Key themes identified in both reflections included: exploration, transformation, climate & community and logistics & operations. These themes illustrate learning as a process, depending on the openness of learners to question pre-existing beliefs, and re-build existing mental models. The resulting transformation is aided by collaboratively learning with others, where different perspectives and values help students uncover their own.

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.

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)0.005
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.817
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.209
GPT teacher head0.459
Teacher spread0.250 · 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