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Record W4386396810 · doi:10.1287/ited.2023.0020

That’s Incorrect and Let Me Tell You Why: A Scalable Assessment to Evaluate Higher Order Thinking Skills

2023· article· en· W4386396810 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.

Bibliographic record

VenueINFORMS Transactions on Education · 2023
Typearticle
Languageen
FieldComputer Science
TopicOnline Learning and Analytics
Canadian institutionsWestern University
Fundersnot available
KeywordsGrading (engineering)Higher-order thinkingComputer scienceScalabilityCritical thinkingData scienceAnalyticsMathematics educationTeaching methodPsychologyDatabaseEngineering

Abstract

fetched live from OpenAlex

We introduce a novel type of assessment that allows for efficient grading of higher order thinking skills. In this assessment, a student reviews and corrects a technical memo that has errors in its formulation or process. To overcome the grading challenges imposed by essay-type responses in large undergraduate courses, we provide a Visual Basic for Applications Excel tool for instructors, ensuring efficient grading of student submissions. We report our experience using this type of assessment in a multisection introductory business analytics course over several years and present survey-based evidence indicating that students perceive it to be clear and beneficial for learning. Supplemental Material: Data is available at https://www.informs.org/Publications/Subscribe/Access-Restricted-Materials

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.889
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.318
Teacher spread0.302 · 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