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Record W2975522667

Moderation versus validation: policy and practices in higher education at TAFE

2015· article· en· W2975522667 on OpenAlexaboutno aff
Emmy Pham

Bibliographic record

VenueNational Vocational Education and Training Research Conference · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducation Systems and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsModerationComparabilityVocational educationHigher educationAgency (philosophy)Public relationsConsistency (knowledge bases)Grading (engineering)PsychologyMedical educationPolitical sciencePedagogySociologyEngineeringMedicineSocial psychologyComputer scienceSocial science
DOInot available

Abstract

fetched live from OpenAlex

Current studies conducted by the National Centre for Vocational Education Research (NCVER) and others in a vocational setting suggest that practitioners at TAFE are quite clear about validation, but much more needs to be done to ensure that the concept and practice of moderation is clearly understood and implemented within the sector. This preliminary study further investigates the nature and extent of moderation policies and practices in higher education programs at a TAFE institute. The study firstly explores staff perceptions that underlie their experiences in relation to the moderation policy and practice within a department. The preliminary findings will be used to explore, review and evaluate the consistency, reliability and comparability of assessment judgment from different departments within the institute. The scope will then be extended to a nation-wide basis, surveying Australian TAFE higher education providers members to compare understandings and practices of moderation to seek ways to improve the practice in order to meet the Tertiary Education Quality and Standards Agency (TEQSA) requirements, which demands evidence of 'details of moderation and any other arrangements that will be used to support consistency and reliability of assessment and grading across each subject in the course study, noting any differences in these processes across delivery methods, delivery sites, and/or student cohorts' (TEQSA 2012, page 32). The final stage of the study will be further broadened internationally, comparing New Zealand, UK, Australia, Canada and the United States under similar settings, for international comparison and analysis. The aim of the research is to better understand the issues and challenges in relation to the quality and rigour of assessments within an institute, nationally and internationally.

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)0.752
metaresearch head score (Gemma)0.774
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.752
Threshold uncertainty score0.305

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.7520.774
Meta-epidemiology (narrow)0.0010.003
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0080.009
Science and technology studies0.0310.052
Scholarly communication0.0260.037
Open science0.0090.039
Research integrity0.0130.018
Insufficient payload (model declined to judge)0.0050.001

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 head0.691
GPT teacher head0.607
Teacher spread0.084 · 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.

Study designQualitative
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
Published2015
Admission routes1
Has abstractyes

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