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Record W6957163403 · doi:10.60511/zgd.v35i4.216

Fostering Progress in Children's Developing Geoscience Interests

2023· article· en· W6957163403 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGeography Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsSituational ethicsContext (archaeology)Order (exchange)Empirical researchEmpirical evidence

Abstract

fetched live from OpenAlex

Interest is a complex construct, yet is often treated by researchers and other authors as being a non-problematic uni-faceted concept. Negligible research has been undertaken into the geoscience interests of teachers and students, with even less probing of interrelationships between individual, situational and topic interest. Interest research is very weakly-developed in the UK, with many recent publications emanating from several pivotal countries including Canada, Germany, Australia and the USA. In recent years the interest research community has been developing theory, including a four-phase model which provides a framework for analysing the progressive development of learners' interest from "triggered situational interest" to "well-developed individual interest" (Hidi and Renninger, 2006). In order to identify teachers' possible instructional starting points, a questionnaire survey of 652 children aged 11 and 12 years was undertaken to investigate the nature of their individual geoscience interests. Selected data from a second study of 51 serving teachers were also used to compare the geoscience interests of teachers and children and to compare those interests with actual classroom experiences of selected geoscience concepts. Several mismatches between teachers' and children's interests were identified, alongside further mismatches between interest and classroom geoscience experiences. In order to illustrate children's growth towards a 'well-developed individual geoscience interest', comprising both cognitive and affective elements, the four-phase model of interest development was examined in the context of the planning of geoscience learning activities. The implications of this model for geoscience education are examined in relation to the empirical results reported here and in the two previous related papers.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, 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 score0.072
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0000.000
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 head0.431
GPT teacher head0.634
Teacher spread0.203 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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