Using concept mapping for assessing and promoting relational conceptual change in science
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 In this article, we adopted the relational conceptual change as our theoretical framework to accommodate current views of conceptual change such as ontological beliefs, epistemological commitment, and social/affective contexts commonly mentioned in the literature. We used a specific concept mapping format and process—digraphs and digraphing—as an operational framework for assessing and promoting relational conceptual change. We wanted to find out how concept mapping can be used to account for relational conceptual change. We collected data from a Grade 12 chemistry class using collaborative computerized concept mapping on an ongoing basis during a unit of instruction. Analysis of progressive concept maps and interview transcripts of representative students and the teacher showed that ongoing and collaborative computerized concept mapping is able to account for student conceptual change in ontological, epistemological, and social/affective domains. © 2004 Wiley Periodicals, Inc. Sci Ed 88: 373–396, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/.sce10127
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 | 0.006 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it