Fullness of life as minimal unit: Science, technology, engineering, and mathematics (STEM) learning across the life span
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Challenged by a National Science Foundation–funded conference, 2020 Vision: The Next Generation of STEM Learning Research, in which participants were asked to recognize science, technology, engineering, and mathematics (STEM) learning as lifelong, life‐wide, and life‐deep, we draw upon 20 years of research across the lifespan to propose a new way of thinking about and investigating the topic. We propose Fullness of Life (or Total Life ) as the minimal unit of analysis that allows people generally and researchers specifically to make sense of cognition. This move reverses traditional perspectives: Rather than understanding life from the position of STEM activities, we understand STEM learning from the perspective of life taken as a whole. We propose three attendant concepts that do not focus on stable knowledge content but on (a) the ability to mobilize and augment knowledge (knowledge ability ), (b) the necessity to develop the disposition of the débrouillard/e and bricoleur, and (c) the necessity to conceive knowledge ability as collective property, outcome of collective praxis. We conclude by commenting on five dimensions suggested as need requirements for implementing a 2020 vision for STEM learning research. © 2010 Wiley Periodicals, Inc. Sci Ed 94: 1027–1048, 2010
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it