Exploring design discourses and liminality as features of professional learning in an elementary makerspace
Bibliographic record
Abstract
Purpose Using Johansson-Sköldberg et al.’s (2013) descriptions of design discourses, this study aims to analyze teacher interviews, research notes and teacher and student artifacts to determine if engagement in design practices led to changes in the teacher’s thinking. Design/methodology/approach This article presents results from a year-long study that explored how a teacher enacted design discourses to engage in curriculum learning within an elementary school makerspace. The design-based study involved a collaborative partnership where a teacher and researcher co-designed, co-enacted and co-reflected on three cycles of making featuring curriculum studies in science, mathematics and social studies. Findings The authors determined that engagement in all four design discourses led to transformative changes in the teacher’s thinking about herself as a teacher and her students as learners. The evidence suggests the school makerspace can serve as a liminal design space for professional learning, given that implicit in the makerspace is the embodiment of design practices such as problem finding, iteration and reflection. Research limitations/implications Engaging in design discourses in the makerspace can lead teachers to question the frames they hold about teaching and learning. However, teachers need ongoing support in developing discipline knowledge and prioritizing the time required for designing, iterating and reflecting on learning in the makerspace. Practical implications The makerspace provides a liminal space for teachers’ professional learning in that implicit in the makerspace is the embodiment of design practices such as problem finding, iteration and reflection. Originality/value This study is unique, in that it places the importance of teacher learning in the elementary school makerspace on equal footing with student learning, thereby creating a culture of inquiry for all.
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 | 0.019 | 0.037 |
| 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 | 0.033 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".