Exploring young children’s self and others: integrating visual diaries and the digital emotional expression application in art education
Bibliographic record
Abstract
This study explores the integration of technology-based and hands-on art practices in an early childhood art education program tailored to preschoolers in South Korea. The participants of this study included 20 young children aged five or six years old, who engaged in the program for a two-year period. By employing qualitative research methods, the results reveal the young learners’ enhanced expression of their emotion, including feelings, desires, and moods with the aid of visual diaries in conjunction with a digital emotional expression application supported by teacher intervention. Further, the young learners were stimulated to engage in self-discovery, self-awareness, and understanding of others. Ultimately, young children’s visual diaries enhanced educators’ and parents’ comprehension of their emotions. Moreover, showcasing these visual diaries and collaborative artwork promoted numerous opportunities for engagement and resonance with the local community. The fusion of visual diaries and the digital emotional expression application is viewed as a practice of emotional meaning making, wherein art and technology agency is distributed.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".