Towards a Transforming Constructivism: Understanding Learners' Meanings and the Messages of Learning Environments
Bibliographic record
Abstract
This article is based on the ideas and material presented at the invitation to deliver the 17 u, Annual University of Calgary Faculty of Education Annual Distinguished Lecture. This lecture honors the work of a member of Faculty whose research contributions have been judged to contribute significant new insight in the field of Education. The article presents the foundations of research and thinking that have inspired work to deepen knowledge about the value and use of constructivist approaches in research, teaching, and learning. The article deepens the discussion by presenting additional ideas designed to produce a transforming constructivism. A transforming constructivism goes beyond taking into account learner conceptions or ideas in the teaching/learning dialogue. It incorporates thinking about the cultural and social messages presented within the environments of learning that also must be taken into account to build a more complete story of the ways that the learner constructs meaning. illustrative dialogue on children learning about the topic light is presented from my book, What Children Bring to Light: A Constructivist Perspective on Children's Learning in Science, (1994). The article presents findings and further work that has extended and deepened understanding by featuring the messages of science learning environments in the account of learner construction of ideas.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".