Enacting Critical Thinking in Primary School
Bibliographic record
Abstract
This anthology is a result of the research and innovation project Critical Thinking in Primary School (KriT), funded by the Research Council of Norway (2020( -2023, No. 309873), No. 309873).The KriT-project is an interdisciplinary project aiming at developing Didaktik approaches for critical thinking in primary school, using children's literature and news items.The project has included researchers from Norwegian language arts, English language teaching, natural sciences, social studies, and pedagogy.The content has been the starting point of the KriT-project, and it is also the foundation of all the chapters in the anthology.The chapters are based on different subject traditions and have different theoretical approaches but are unified by the Didaktik approach and dialogic teaching.Chapter 1, Critical Thinking in Primary School-a large-scale design-based research project, by Jegstad, Bjørkvold, and Andersson-Bakken, gives an overview of the project, including theoretical perspectives and methods.Furthermore, it presents the main results from the project in relation to the Didaktik triangle and Didaktik principles for critical thinking in primary school.This chapter is followed by five chapters focusing on students' critical thinking (Chapters 2-6) and four chapters focusing on how the teacher facilitates critical thinking (Chapters 7-10).Chapter 2, the first chapter focusing on students' critical thinking, is titled Children's Agency for Critical Thinking in Early Literacy Education.In this chapter, Svanes, Andersson-Bakken, Bjørkvold, and Sandvik explore how students' agency for critical thinking can be realised in early literacy education framed by the shared reading of picturebooks.In Chapter 3, Emergent Critical Thinking through Picturebook Dialogues, Heggernes, Svanes, Tørnby, and Andersson-Bakken further investigate how picturebook dialogues may be a starting point for critical thinking in young learners through an in-depth analysis of the picturebook Huskereisa (Bjørkli & Horndal, 2009) read in second and fourth grade.In Chapter 4, Critical Writing in Early Schooling, Bjørkvold and Marti study critical writing by analysing student texts written in third grade concerning the Norwegian prime minister breaking rules regarding social regulations.Chapter 5, The Bumblebee Project: Systems Thinking about the Environment, is one of three chapters that starts out with sustainability issues.In this chapter,
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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 | 0.002 | 0.003 |
| 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 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".