Interdisciplinary Instruction: Between Art and Literature
Bibliographic record
Abstract
This paper explores the developments and trends in higher education from a pedagogical perspective (specifically, multidisciplinary curricula) and research perspective (the interdisciplinary approach), and traces them from a last resort option to their recognition as a legitimate development with added value. The paper focuses on a case study that integrates two disciplines, art and literature, based on the poem by the Israeli poet Rachel entitled My Book of Poems and the painting The Scream by Norwegian artist Eduard Munch. The interdisciplinary approach opens up possibilities of enriching, expanding horizons, and breaking boundaries, and can grant graduates of the higher education system a cultural perspective suitable for the current generation of students, who typically use multiple interactive media and platforms, often simultaneously. This paper may shed light on teaching and learning of many diverse fields. The case study illustrates the joy of interdisciplinary learning and its academic benefits, despite the fact that for years, higher education institutions have tended to refer to researchers’ specializations in specific academic disciplines. This case study may serve as a model or source of inspiration for multidisciplinary learning involving motifs and topics that traditionally represent specific disciplines.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.007 | 0.029 |
| Scholarly communication | 0.025 | 0.024 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".