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Record W3002303888 · doi:10.24908/pceea.vi0.13760

REVELATIONS OF A COLLABORATIVE MIDTERM IN AN ENGINEERING TECHNOLOGY MANAGEMENT COURSE

2019· article· en· W3002303888 on OpenAlexafffundvenue
Allan MacKenzie

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2019
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsTest (biology)Test anxietyPsychologyPerspective (graphical)Medical educationWork (physics)Mathematics educationEngineering ethicsEngineeringEngineering managementAnxietyKnowledge managementComputer scienceMedicine

Abstract

fetched live from OpenAlex

Collaborative testing or two-stage testing as it commonly referred, is where students work together to discuss examination questions and arrive at a consensus to test answers. Two-stage testing is an extension of collaborative learning that has been purported to decrease test anxiety and increase critical thinking, communication, and cooperation skills. Concurrently, there has been considerable research and attention focused on the development of these same transferable skills since employers highly value them. This paper explores the outcomes over two academic terms from administrating a two-stage midterm in a mandatory management course for undergraduate students in an engineering technology program. The pedagogical consideration, application to transferable skills, and administration of this type of assessment method are discussed, along with the student perspective regarding the experience and impact on student test performance.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.806

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.002
GPT teacher head0.184
Teacher spread0.182 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2019
Admission routes3
Has abstractyes

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