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Record W4403764066 · doi:10.24908/pceea.2023.17153

The Long and Winding Road: standards- and attribute-based grading in vastly different first-year math courses

2024· article· en· W4403764066 on OpenAlex
Shai Cohen, Camelia Karimian Pour

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.

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2024
Typearticle
Languageen
FieldComputer Science
TopicEducational Technology and Assessment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGrading (engineering)Mathematics educationMathematicsComputer sciencePsychologyEngineeringCivil engineering

Abstract

fetched live from OpenAlex

Standards- and attribute-based marking methods grade students according to specific learning objectives. These methods can be difficult to implement but lead to positive results for both students and instructors. This paper summarizes the experience of and results from two divergent grading systems, one that utilized standards-based grading for a small part of the grade in a very large class and another that used attribute-based grading for the entire experience of a small class. The instructors discuss the challenges in implementing their systems and how the benefits outweighed the accompanying difficulties. The results of the alternative marking led to greater student engagement and to changes in course curriculum. Suggestions for easing the use of these systems are proposed.

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)0.001
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 score0.362
Threshold uncertainty score0.391

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.005
GPT teacher head0.225
Teacher spread0.220 · 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