Thunderbolt hunt. Educational Program for Students from 5 to 9 Years Old in the Archaeological Museum of Ioannina
Bibliographic record
Abstract
The present study aims to improve the quality and the effectiveness of Science Education in early grades along withthe goals of UNESCO’s emerging agenda for sustainable development and the 4th goal about quality in education. Itexamines the interaction between formal and non-formal education in designing and organizing complete educationalprograms directly connected with science education curriculum and utilizing innovative tools targeting to anattractive and rich context for science education. According to the second Science Centre World Summit (SCWS,2017), museums promote scientific knowledge which is considered a pure cultural component and as such it isstudied under the prism of cultural historical activity theory. Activity Theory is used in this research as a theoreticalframework for the design and analysis of educational activities, with an emphasis on active and interactive learningprocesses. It is a predominantly socio-cultural theory offering a broad scope of design and implementation forlinking science with culture and society. The educational program developed, “Thunderbolt hunt”, is different fromthe usual educational programs offered because, although it cultivates scientific method skills, it is implemented inthe Archaeological museum of Ioannina which constitutes a non-formal learning environment of general interest.The process of designing such programs is based on a number of principles and on numerous fields: thesocio-cultural theory of activity, the science education and the museum education. The museum thus becomes afacilitator of scientific knowledge while at the same time functions as a dynamic meeting place for students withtheir social, cultural and historical environment. The preliminary results of the study are presented in this paper.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".