Teaching for the Ambiguous, Creative, and Practical: Daring to be A/R/Tography
Bibliographic record
Abstract
This purpose of this inquiry is to explore how an a/r/tographic model of shared inquiry led to deeper insights about learner-centered pedagogy. Invited to teach and redesign a very large ‘Art & Society: Visual Arts’ course at a large university with a 21st century issues-based focus, together with my commitment as a constructivist, learner-centered teacher, the current phenomenological study was born. The phenomena studied was whether a large, lecture-style class taught from a more non-traditional, non-lecture, art-as-experience, learner-centered epistemology might affect students’ balanced thinking and perceptions about their learning. Students’ perceptions, along with the regulatory role of emotions, are critical factors in motivation and behavior; students’ self-beliefs about learning and their capabilities affect their behavior, resilience, and persistence in the face of challenge.Arts-based methods of inquiry with multiple forms of data, regarding both students’ and researcher’s lived experiences resulted in new artforms and informed praxis. After a student survey was determined the best way to poll perceptions about their learning in a more constructivist environment, the author’s Mixed Parallaxic Praxis method emerged from this study. Key findings indicated students’ increased openness to other perspectives and to cultural and creative experiences, increased engagement and a personal desire/thirst to create art, and a personal confidence to analyze art—despite their lack of former experience with artmaking or art instruction in high school. Qualitative and survey data informed how learner-centered practices enhance students’ self-beliefs about their abilities as creative learners, so important to overall motivation and capacity to learn overall.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".