Digital technology and the arts: Investigating the integration of digital technologies in the elementary art curriculum
Bibliographic record
Abstract
Art is a wonderful way for students to express their creativity and engage in their learning in a new and interesting way. In today’s modern world, the integration of digital technologies has the capability to enhance lessons and provide unique opportunities for students to experience the curriculum. Through the surveying of my fellow teacher candidates, family, friends and an e-mail interview with a subject matter expert, I asked specific questions about the potential positive and negative effects of the integration of digital technology in the elementary art curriculum. In addition, I explored five added sources to supplement my research. As a result of this investigation, I discovered that a balance of new and old technologies is fundamental to the art experience in the elementary art curriculum. It is imperative that technology is not the sole focus and that other traditional art mediums are included in the curriculum. This research project allowed for the exploration of the positive and negative impact of integrating digital technologies in the arts for my future teaching practice. Ultimately, the potential benefits of the integration of digital technologies far outweigh any of the negatives and the opportunities they present are endless.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".