Reframing From Design Fields: Supporting Pre-Service Teachers in Designerly Thinking
Bibliographic record
Abstract
Guided by contemporary theory and research from design fields, we propose a framework for conceptualizing K-12 educators' stances towards design that focuses on problem framing, information gathering, divergent thinking, and iteration.We use this framework to analyze data drawn from 28 pre-service teachers' conceptualization of design within the context of a design course taken by over 400 pre-service teachers.Our analysis demonstrated that most participants made only moderate progress in refining their thinking about design. Theoretical frameworkInsights from design fields suggest that a designerly stance towards design for K-12 educators focused on supporting second order changes would emphasize four key themes as follows: (a) view of the problem space (e.g., Buchanan, 1992; Norman, 2013;Schön, 1984), (b) approach to stakeholders and inquiry (e.g., Bang & Vossoughi, 2016;Christensen et al., 2016;Krippendorff, 2004), (c) framing and frame creation (e.g., Buchanan, 1992;Dorst, 2011), and (d) conceptualization of the design process (e.g., Norman, 2013; Owen, 2006).These elements overlap and interrelate with one another and share, in many instances, common themes.We developed a detailed rubric based on these four areas that we used to guide this study and data analysis leveraging the structure and ideas that Crismond and Adams (2012) used to in their framework for engineering education.As with Crismond and Adams, we developed pairs of contrasting statements for analyzing pre-service teachers' approaches to design on a scale from beginning to designer to "informed designer" whose "level of competence lies somewhere between that of the novice and expert designer" from the perspective of the design fields (Crismond & Adams, 2012, p. 743).Space precludes including the full rubric here, but we will share the full version at the conference.
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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 | 0.030 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.007 | 0.026 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".