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Record W4244747690 · doi:10.18130/v3r06d

Pragmatic Measurement for Education Science: A Method-Substance Synergy of Validation and Motivation

2017· dissertation· en· W4244747690 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

VenueLibra · 2017
Typedissertation
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsYork University
FundersNational Association for Research in Science TeachingJames Madison UniversitySage Foundation
KeywordsPsychologySubstance useData scienceComputer scienceMathematics educationEngineering ethicsEngineeringClinical psychology

Abstract

fetched live from OpenAlex

Education researchers often require quick and efficient assessments of various student characteristics (e.g., motivation) to use in classroom settings. Unfortunately, guidelines for addressing measurement obstacles, such as scale length, are ambiguous at best and non-existent at worst. Many measures lack sufficient evidence that the conclusions they produce are merited, and short measures have received particular criticism from measurement experts. The result is a tension between technical and pragmatic constraints when conducting measurement in field research. This three-paper dissertation is aimed at identifying and addressing these tensions in one area of motivation research. Paper 1 provides the substantive frame for the overall dissertation. The goal was to understand short-term student motivation change in a classroom setting. Paper 2 provides a typical approach to assessing a scale’s quality and viability for use in the field. The goal was to use traditional psychometric approaches to evaluate a brief measure of motivation. Finally, Paper 3 presents a pragmatic approach to determining validity evidence (i.e., pragmatic measurement) by considering the underlying uses and restrictions of collecting data. The goal was to evaluate the pragmatic approach as a framework for measure users to identify the relevant validity evidence needed based on the potential uses and interpretations of a measure. Together, these papers highlight the nature and benefit of advancing methodological goals by pursuing substantive goals. The current research is a methodological-substantive synergy (i.e., work that advances a substantive domain, such as motivation, while developing and utilizing state-of-the-art methodology) aimed alleviating technical and practical tensions.

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)0.009
metaresearch head score (Gemma)0.006
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: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.719

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
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 head0.230
GPT teacher head0.525
Teacher spread0.295 · 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