Discovery-Based Learning in World Arts: Creativity and Collaboration in the Undergraduate Fine Arts Class
Bibliographic record
Abstract
This workshop will begin to prepare instructors to use discovery-based learning methods in order to foster undergraduate education by deepening student learning and developing studentsâ written and verbal communication of their research experiences. Discovery-based learning is like problem-based learning in so far as students formulate a problem, investigate facts, generate a thesis, and test their theses against the evidence. However, discovery-based learning is more individualized because students do not respond to problems that are provided by the instructor, but rather generate their own questions in response to course material in dialogue with the instructor. These methods are based on theories of creativity that highlight the connections among creativity, meaningful inquiry, and self-expression. This workshop will review key elements of creativity in education and discovery-based learning, outline how they promote relevance and enjoyment of the course material, and consider ways to integrate them into classroom projects and activities. Participants will experience the application of discovery-based learning to group work, share with others their hopes and experiences of this kind of teaching and learning, become more familiar with the theory that supports this approach, and learn where to seek further information and activities.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".