Implementation of Mathematics Learning Through Hydroponic Farming to Improve Mathematics Ability in Early Childhood
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aims to produce and determine the feasibility of early mathematics learning media through hydroponic farming for Early Childhood. The type of research carried out is development research, because in this study an initial mathematics learning media was developed through hydroponic farming for Early Childhood. The research instruments used were media validation sheets and teacher response questionnaires. The data analysis used is descriptive quantitative. The product produced in this study is a medium for early mathematics learning through hydroponic farming for Early Childhood that meets valid and practical criteria. This study took subjects in Early Childhood at Kartika Kindergarten, Peguyangan Kaja Village. The results of this study regarding media validation showed that the initial mathematics learning media through hydroponic farming for Early Childhood had met the valid criteria. Judging from the results of the analysis of the teacher's response to learning media, namely the teacher's response to the use of media, it shows 75.8% in the good category. This shows that the media can be implemented practically by the teacher.
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.
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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it