Bibliographic record
Abstract
The purpose of this book is to establish a broader context for rethinking science learning and teaching by using cultural historical activity theoretic approach. Activity theory already steps in its third generation and only a few works have been done on its applications to science education, especially in Europe. The context takes into account more recent developments in activity theory applications in US, Canada, Australia and Europe. The chapters articulate new ways of thinking about learning and teaching science i.e., new theoretical perspectives and some case studies of teaching important scientific topics in/for compulsory education. The ultimate purpose of each chapter and the collective book as a whole is to prepare the ground upon which a new pedagogy in science education can be emerged to provide more encompassing theoretical frameworks that allow us to capture the complexity of science learning and teaching as it occurs in and out-of schools. The book captures the dialogic and interactive nature of the transferring the activity theory to both formal and informal science education. It also contributes to the development of innovative curricula, school science textbooks, educational programs and ICT’s materials. As a whole, the book moves theorizing and practicing of science education into new face and uncharted terrain. It is recommended to new scholars and researchers as well as teachers/researchers.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.011 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
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".