A Study on the Situations, Problems, and Needs of Teaching and Learning in Higher Education to Enhance Songwriting Skills for Children’s Songs
Bibliographic record
Abstract
This research aimed to explore the situations, problems, and needs of teaching in higher education with the goal of enhancing songwriting skills for children’s songs. A survey research method was employed, with data collection through online questionnaires. The sample of this study consisted of 522 participants, including 19 lecturers and 503 undergraduate students majoring in Early Childhood Education and studying at universities located in the northeast of Thailand. Mean, standard deviation, percentage, and content analysis were employed to analyze the data. This study reveals that most students and educators lack a background in music. Also, teaching how to write children's songs by adapting lyrics of original songs without learning music notes is used the most. The level of problems is moderate, equally for both students and instructors. The level of needs is high, similar to that of both learners and instructors. In addition, the findings of this research provide important information to those who are involved in early childhood education programs at higher education institutions, allowing them to consider appropriate teaching strategies to meet students' and instructors' needs and to find suitable and sustainable solutions.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".