Bibliographic record
Abstract
Observation and documentation are integral to the early childhood classroom. Observation provides the information necessary for adults to build meaningful relationships with individual children. Documentation panels including photographs, teacher's notes, transcriptions, and artifacts, artfully and prominently displayed, serve as a visual archive of children's learning (Helm, Beneke, & Steinheimer, 1998 Helm, J., Beneke, S. and Steinheimer, K. 1998. Windows on learning: Documenting young children's work, New York: Teacher's College Press. [Google Scholar]). Carefully designed panels provide an array of authentic assessment artifacts of children's exploration, while also providing a vehicle for preservice teachers to showcase their understanding of the teaching-learning process. As candidates capture and collect significant moments of learning and reflect on data collected, they develop the practice-teaching inquiry. Inquiry prepares teacher candidates to recognize the value of revisiting previous thinking to help them see relationships between teaching and learning. It is a reflective, intellectually challenging process that is the essence of teacher self-reflection (Hong & Forman, 2000 Hong, S. and Forman, G. 2000. What constitutes a good documentation panel and how to achieve it?. Canadian Children, 25(2): 26–31. [Google Scholar]). The Making Learning Visible project described in this article provides opportunities for teacher candidates to observe children at work and play; formulate questions about what they have seen; advance opinions about meaning; analyze issues; confront biases; and develop ideas for future practice. The project may be used as one of the eight assessment tools required in the National Council for Accreditation of Teacher Education/National Association for the Education of Young Children (NCATE/NAEYC) program accreditation process.
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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.035 | 0.016 |
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".