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Record W1637917995

A AVALIAÇÃO DE CURSOS A DISTÂNCIA APLICANDO OS PRESSUPOSTOS DA PESQUISA AVALIATIVA FORMATIVA

2008· article· pt· W1637917995 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2008
Typearticle
Languagept
FieldSocial Sciences
TopicEducation and Public Policy
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyPsychology
DOInot available

Abstract

fetched live from OpenAlex

One of the criteria for the credibility and trustworthiness of scientific research is the methodological procedure adopted and it falls to the researcher to operationalize the theoretical assumptions in order to establish how to collect and analyze research data. In this article there is a description of a method for applying Formative Evaluative Research, a type of research for evaluating processes, be they methods of service, teaching or even proposals for training, as is the case here. The method created is part of a doctorate study, validated through evaluation in a bi-modal course (a course where activities are carried out both locally and at a distance) in teacher training for the integration of technological resources in teaching practice at a Canadian university. Among the results we see that, in addition to the central matter of research, it is essential to prepare guiding questions to be answered at every stage of an evaluative process as they make the researcher concentrate on the central focus of his research. In courses where students have both local and distance activities, the sources of data are rich and the variables that arise during research are manifold, leading the researcher to disperse the focus of his evaluation. A limit to be considered is that the method should be applied during the training process so that the researcher can more easily access the subjects involved in the process. In this way it will always be possible, when deemed necessary, to complement the information that has been collected.

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.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0030.007
Open science0.0070.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0540.000

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 head0.399
GPT teacher head0.598
Teacher spread0.199 · 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