Fostering Progress in Children's Developing Geoscience Interests
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".