“This is the biggest place where you can express your imagination”: Information practices of middle school students at a school library makerspace
Bibliographic record
Abstract
This study aims to understand what brought a group of middle students to their school library makerspace, their questions, information practices, and barriers in their participation. Informed by Dervin’s sense-making verbing approach and sociocultural approaches to learning, qualitative data were collected through initial interviews, surveys, follow-up interviews, and weekly field observations over six months. The findings show that the school library makerspace was a social and informal learning environment for the students to have fun, be creative and develop skills in science, technology, engineering, mathematics and arts. Their information practices ranged from tinkering with materials and technologies, and getting help from interpersonal resources. This study highlights the information practices at the library makerspace were social in nature, embodied through materials and tools, and embedded in the formal educational system; this study also sheds light on the affordances and constraints of the materials and computers in the students’ activities at makerspace.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".