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Record W4405940634 · doi:10.18554/rt.v17i3.7450

CONCEPTIONS OF ASSESSMENT IN HIGHER EDUCATION

2024· article· en· W4405940634 on OpenAlexfundno aff
Eva Lopes Fernandes, María Assunção Flores, Gavin Brown, Clara Pereira Coutinho

Bibliographic record

VenueRevista Triângulo · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicStudent Assessment and Feedback
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaUniversidade do MinhoInternational Council for Canadian Studies
KeywordsMathematics educationPsychologyPedagogyMedical educationMedicine

Abstract

fetched live from OpenAlex

Under Bologna processes, it is important that educators understand and use assessment for formative purposes as well as traditional summative evaluation purposes. This small-scale exploratory study tested the Teachers Conceptions of Assessment (TCoA) inventory in the Portuguese higher education context. A convenience sample of Portuguese academic faculty (n=185) from five public universities and across multiple scientific areas were surveyed. Confirmatory factor analysis rejected the original model and preferred a four-factor model (i.e., improvement, assessment quality, institutional quality, and, reject assessment use) using just 15 of 27 items. Findings from this study indicate that, in line with Bologna intentions, Portuguese faculty seem to be taking a positive and constructive view of assessment as a tool for improved outcomes and have confidence in their evaluative practices. Faculty agreed that assessment was a high-quality process for improved outcomes and rejected its irrelevance. At the same time, they had a much weaker but positive view that assessment evaluated institutional quality. The study indicates that the TCoA inventory needs to be supplemented with different items and factors to capture the quality of Portuguese faculty conceptions of assessment. Keywords: Higher Education; Faculty; Teachers Conceptions of assessment (TCoA)

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.949
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.065
GPT teacher head0.439
Teacher spread0.374 · 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 designTheoretical or conceptual
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

Citations1
Published2024
Admission routes1
Has abstractyes

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