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Record W2802248479 · doi:10.7939/r3bg96

Developing and Evaluating Student Score Reports for Cognitive Diagnostic Assessment

2012· article· en· W2802248479 on OpenAlexaboutno aff
Mary Patrice R. Roberts

Bibliographic record

VenueUniversity of Alberta Library · 2012
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionPsychology

Abstract

fetched live from OpenAlex

Score reporting serves a critical function as the interface between the test developer and a diverse audience of test users. The basic requirements for score reporting are clearly identified within the Standards for Educational and Psychological Testing (1999). However, the methods to achieve these standards are not. There lies an implicit assumption that results are reported in a useful manner to educational stakeholders to enable their use for communicating student performance, but there has been a paucity of research in this area to confirm or disconfirm this assumption. Effective reporting of diagnostic results requires a multi-disciplinary effort and input from all target audiences. In this study, a framework was created to structure an approach for developing score reports for cognitive diagnostic assessments. Guidelines for reporting and presenting diagnostic scores were based on a review of current educational test score reporting practices and literature from the area of information design. Then, core members of Alberta Education’s Cognitive Diagnostic Mathematics Assessments team applied the reporting framework to create three score reporting templates in the context of a Grade 3 diagnostic mathematics assessment. The templates were then evaluated by teachers on the dimensions of: (1) content and format, (2) understanding and interpretation, and (3) uses of and preferences for information. Results of this study revealed that all three reporting templates provided the teachers with information consistent with what was expected from a diagnostic assessment. Teachers did not have difficulties understanding and interpreting information within the report. However, suggestions were made to improve visual organization and clarity of wording. Primary uses identified for reported information include communicating learning to parents and students, informing instructional planning, evaluating student learning, and incorporating results in summative reporting. To facilitate use of results, paper-based, classroom-level reports with an accompanying website should be considered. Limitations of the study and recommendations for future research are also discussed.

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)0.182
metaresearch head score (Gemma)0.383
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.182
Threshold uncertainty score0.960

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1820.383
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0160.007
Science and technology studies0.0010.001
Scholarly communication0.0060.005
Open science0.0030.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.002

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 head0.083
GPT teacher head0.393
Teacher spread0.310 · 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 designBench or experimental
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

Citations2
Published2012
Admission routes1
Has abstractyes

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