Bibliographic record
Abstract
There is nothing new about the ideas that learners are unique and have different propensities for understanding and communicating (Gardner, 1983(Gardner, , 2000;;Goldberger, Tarule, Clinchy, & Belenky, 1996).They construct their understanding from previous experiences (Bruner, 1960), personal beliefs and backgrounds (Berger, 1972), and learn best by doing (Dewey, 1916) in meaningful and culturally relevant, inquiry-oriented tasks (Aoki, 1993).Moreover, there is common agreement among educators, artists, and researchers, to name a few, that form mediates understanding (Eisner, 1991;McLuhan, 1964).This suggests that learners should have opportunities to receive information and communicate in a variety of mediums and modalities.There is no better time than now to experience multiple forms of communication and expression, given the current access to sophisticated technology.These basic tenets of knowing/understanding have been documented extensively and discussed and researched by educators for more than a century.Yet, educational practices are slow to catch up on how to integrate these perspectives in ways that will provide the optimal circumstances for engaging, meaningful, inclusive, and differentiated learning in all contexts.Now more than ever it has become imperative for acknowledging and scaffolding (Wood, Bruner, & Ross, 1976) different ways of knowing if educators are to address the ethical, cultural, economic, and social needs of the 21st century.Time is running out as we prepare to enter its third decade.The impetus for this issue, "Understanding Ways of Knowing: Insights and Illustrations," came from the need to address the important dimensions of learning outlined above.We hoped to give both researchers and practitioners the space in which to share innovations and illustrate different ways of constructing understanding.We were not disappointed.It is heartening to know that boundaries are being pushed in exciting ways in classroom practices at all levels of education, in research methodologies, in approaches to curriculum, in self-study/reflective work, and in professional development contexts.The contributions in this issue attest to this.
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 | 0.006 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.015 | 0.016 |
| Insufficient payload (model declined to judge) | 0.035 | 0.025 |
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".