The Effect of Multiple Intelligence(MI) Programs on Improving Interpersonal and Intrapersonal Intelligence in Young Children
Bibliographic record
Abstract
Personal intelligence in young children has been an important issue in early childhood education for decades, yet there is a dearth of empirical programs to foster personal intelligence in young children. This study describes an educational program to improve personal intelligence, in which 20 young children in Korea were randomly assigned to an experimental group or a control group in the quasi-experimental design. The children`s personal intelligence was assessed using the Multiple Intelligence (MI) Test for the pretest and posttest. The experimental group, which was engaged in a 10-session educational program, demonstrated significant improvement in multiple intelligence scores compared to the control group. The instructional activities of the multiple intelligence program improved both intrapersonal intelligence and interpersonal intelligence because the program was appropriately based on each young child`s intelligence level. Findings suggest that the multiple intelligence program with a focus on instructional activities is an effective educational program to improve interpersonal and intrapersonal intelligence for these young children.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".