Approaches to industrial processes in technology textbooks
Bibliographic record
Abstract
The aim of this study is to explore how technology textbooks can provide students with a basis for expressing knowledge about technical solutions within industrial processes.The base and the delimitation for the study is the formulation of the specific content on industrial processes that must be taught to 13 to 15-year-olds in Swedish schools pursuant to the national syllabus.Textbooks constitute an important foundation for teaching, particularly in the subject of technology, in which teachers may find the breadth of content they are expected to teach challenging.The study analyses the sections concerning industrial processes in four different technology textbooks commonly used for students in the age group 13-15.Analysis involved interpreting content in the form of text, images, assignments etc. related to aspects that are expected to characterise students' descriptions and explanations of technical solutions: understanding of technical solutions purpose and functionality, how components interact as a whole, similarities to other technical solutions and relating them to their own experiences.The results show that these aspects emerge in different ways depending on, among other things, how the area is presented.We found three different ways in which industrial processes are presented in the textbooks: A unique industrial process is described carefully and in detail, Sub-processes and methods are presented systematically and Industrial processes are described as technological systems at a general level.One interpretation is that, as a teacher, you can teach about industrial processes in these different ways and that which one you choose affects to what extent certain aspects of technical solutions are visualised for the students.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".