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Record W2736595548

POSTER: A Validity Argument Approach to Collaborative Development of the Colleges Mathematics Assessment Program

2016· article· en· W2736595548 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueITC 2016 Conference · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsArgument (complex analysis)Test (biology)Mathematics educationComputer sciencePsychology
DOInot available

Abstract

fetched live from OpenAlex

Introduction Ensuring that a test will produce results that are valid for the intended uses, such as the placement of students into community college mathematics courses, begins during test development. When test development is a collaboration among intended users, such as the community colleges within a province, communicating to all collaborators the implications of the many decisions that must be made about content, format, scoring, and reporting is especially important. Objectives This paper describes and illustrates a validity argument approach to support collaborative test development through the example of Ontario’s Colleges Mathematics Assessment Program (CMAP). Design/Methodology For mathematics tests, Schilling and Hill (2007) have proposed a variation on Kane’s (2002, 2013) validity argument approach. The assumptions required to support the proposed use of the test results and corresponding evidence for those assumptions are organized into three categories: (1) Elemental – concerning the performance of specific test items, (2) Structural – concerning the internal structure of the test, and (3) Ecological – concerning the external structure of the test. In this paper, we use Schilling and Hill’s (2007) three categories to relate the assumptions and evidence to decisions made in developing the test. Results The resulting validity argument makes explicit why each test development decision is important and what types of evidence might inform or support each decision. For use with collaborators with minimal test development experience or expertise, the elements of the argument are expressed in non-technical language. Conclusions In one of their critiques of Kane’s validity argument approach, Schilling and Hill (2007) note the scarcity of real-world examples using an interpretive argument approach. This study provides an illustration of this approach, with a particular emphasis on the use of non-technical language to support collaborative test development. References Kane, M. (2002). Validating high-stakes testing programs. Educational Measurement: Issues and Practice, 21 (1), 31-41. Kane, M. (2013). Validating the interpretations and uses of test scores. Journal of Educational Measurement, 50, 1-73. Schilling, S. G., & Hill, H. C. (2007). Assessing measures of mathematical knowledge for teaching: A validity argument approach. Measurement: Interdisciplinary Research & Perspectives, 5 (2/3), 70-80.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.371

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 science0.0010.000
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 head0.081
GPT teacher head0.373
Teacher spread0.293 · 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