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Record W1600384676

Teaching to the Test: What Every Educator and Policy-Maker Should Know.

2004· article· en· W1600384676 on OpenAlexvenueaboutno aff
Louis Volante

Bibliographic record

VenueCanadian Journal of Educational Administration and Policy · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsnot available
Fundersnot available
KeywordsStandardized testMathematics educationTest (biology)CurriculumPsychologyStrengths and weaknessesNorm (philosophy)Medical educationPedagogyMedicineSocial psychologyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

The job of any teacher is first and foremost to promote learning in their students. Student learning should emphasize applied learning and thinking skills, not just declarative knowledge and basic skills (Jones, 2004). Ideally, students are able to develop the skills necessary to take what they have learned and apply this knowledge in a novel situation. In this sense, teachers are promoting authentic learning within their classrooms. In North America, however, high-stakes testing procedures have interfered with these goals, and are increasingly used to measure student knowledge and gauge the effectiveness of instruction. Each spring teachers throughout Canada are required to administer a series of provincially mandated tests to students in their classrooms (Simner, 2000). These standardized tests are often used to make comparisons across students, schools, and boards of education. Individual teachers and schools are often blamed for poor test results, which are typically reported in the press. Standardized tests, when used appropriately, help teachers identify student strengths and weaknesses (McMillan, 2000). A standardized test is one that is administered and scored under uniform and controlled conditions (Payne, 2003). Used most commonly in K-12 schools, standardized tests are intended to measure learning outcomes and skills that are common to the curricula in a vast number of schools and school districts (Chatterji, 2003). Students typically complete norm-referenced tests that compare their performance to a representative sample of students in a norm group (e.g., a group of students at the national, regional, or provincial/state level) (Gronlund, 2003). Other students undertake criterion-referenced tests that compare their performance to a preset standard of acceptable performance in a particular area (Borich & Tombari, 2004). Both norm-referenced and criterion-referenced test results are increasingly used as benchmarks of success in North American schools.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.034
metaresearch head score (Gemma)0.127
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.178

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.127
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.003
Science and technology studies0.0030.009
Scholarly communication0.0090.021
Open science0.0060.005
Research integrity0.0160.015
Insufficient payload (model declined to judge)0.0150.017

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 head0.034
GPT teacher head0.396
Teacher spread0.363 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations125
Published2004
Admission routes2
Has abstractyes

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