Identifying Contradictions in Science Education Activity Using the Change Laboratory Methodology
Bibliographic record
Abstract
The study is based on an implementation of the basic steps of the Change Laboratory methodology (Engeström,Virkkunen, Helle, Pihlaja & Poikela, 1996) at the University of Ioannina. It was derived by a discussion withmaster’s students during a course about science education curricula in pre-school and primary education and theireffectiveness in the current educational system. Students’ engagement in Science Education is a multifaceted andcomplex process. Under a socio-cultural approach it constitutes an activity system which consists of several elementsand as a whole, is interconnected and interacting with more activity systems which interfere in the process. Theelement that connects all the above systems is the shared object which in the case we are studding is theenhancement of teachers’ confidence in teaching science education. The developmental work research methodology(Virkkunen & Newnham, 2013; Engestrom, 2015) was chosen in order the participants to reflect on the currentactivity, to identify the contradictions of the activity and propose solutions forming a new model. Within thisimplementation Engestrom’s triangular model of the Activity system (2001) is deployed and qualitative researchmethods are applied to analyze the content of the CL sessions occurred among participants. The findings of thisstudy attempt to examine the challenges of the participating teachers in teaching science education and how theirconfidence can be enhanced and furthermore, the CL methodology as a tool in professional development.
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 | 0.054 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".