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Record W7155756298

Assessing Core Competencies in British Columbia

2021· dissertation· en· W7155756298 on OpenAlexaboutno aff
Gerald Fussell

Bibliographic record

VenueKU ScholarWorks (The University of Kansas) · 2021
Typedissertation
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsnot available
Fundersnot available
KeywordsCLARITYCurriculumSocial skillsSkills managementLife skillsCore competencyPlan (archaeology)Academic skills
DOInot available

Abstract

fetched live from OpenAlex

The purpose of this study was to assess whether the use of student self-assessment of non-cognitive skills is accurate and reliable by comparing them to the assessment of student development provided by their teachers of these same skills. For this study non-cognitive skills refer to skills including communication, collaboration, creative thinking, critical thinking, and social emotional skills. Non-cognitive skills are recognized as important for individuals and for communities. There is increased pressure on schools to develop non-cognitive skills in their students. To do this, useful assessments must be used to guide individuals as well as decision makers and policy makers. Assessing non-cognitive skills is particularly challenging. British Columbia recently redesigned its entire K-12 curriculum and placed non-cognitive skills as the foundation of the new curriculum. The plan to measure the development of these skills is to use student self-assessments. Are such assessments useful? This study uses students in grades six through nine from a small British Columbia middle school as the sample and compares self-assessment of non-cognitive skills to the assessments that homeroom teachers provide of the same students to help ascertain the utility of the assessments. This study found that though the relationship between assessments is positive, it is weak. Teacher assessments are most strongly predicted by student fundamental skill development than any other variable. Serious questions are raised about the validity of either assessment which points to the need for clarity of purpose when selecting and using assessment tools, especially for non-cognitive skills.

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 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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.781
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.027
GPT teacher head0.293
Teacher spread0.266 · 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 teacher head, not a consensus.

Study designObservational
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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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