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O real e o imaginário: a literatura de ficção científica para o ensino de questões ambientais entre licenciandos e licenciandas

2023· dissertation· pt· W4376602674 on OpenAlexaff
Raquel Mayne Rodrigues

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsQuest University Canada
Fundersnot available
KeywordsHumanitiesPhilosophyArt

Abstract

fetched live from OpenAlex

The real and the imaginary: science fiction literature for teaching environmental issuesScience fiction literature has been considered as a methodology for science teaching for some time.Thus, the assumption of this research development was to study the science fiction literature as a basis for new methodological perspectives for teaching of environmental sciences in particular, considering that future teachers may reflect on how this literature supports the overcoming of the fragmented way of working environmental issues in school, especially in Science and Biology, so that they develop a professionalism committed to raising awareness about the environmental crisis we live in today, since the teaching and learning of environmental sciences are benefited by the contextualization, awareness and motivation to learn when provided by science fiction narratives.Therefore, the general objective of this research was to analyze how Biological Science undergraduates from a public university in the interior of São Paulo understand the insertion of science fiction literature for teaching environmental issues, evaluating, through participation in a book club, development of didactic sequences and semi-structured interviews, how this understanding of science fiction and its use in teaching is linked to a pedagogical practice for environmental awareness.It was observed that the Learning Community formed by the participating undergraduate students is mostly made up of fiction readers who are at the final level of initial teacher training; they were able to appropriate the understanding of science fiction literature as an effective methodology for teaching science and environmental issues and also to think about the construction of their own teaching practices articulated to particular visions of teaching and detached from the traditional teaching approach, besides being able to think critically about the role they may come to play in Education.

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)0.011
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.010
Science and technology studies0.0160.055
Scholarly communication0.0260.016
Open science0.0020.009
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0080.001

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 head0.054
GPT teacher head0.406
Teacher spread0.352 · 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 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
Published2023
Admission routes1
Has abstractyes

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