The Study on the Development of Accreditation System for Instructional Materials and Equipment in Early Childhood Education
Bibliographic record
Abstract
본 연구의 목적은 국내에서 개발되거나 또는 수입되는 교수-학습용 교재 교구의 인증 시스템 개발 방향과 가능성에 대한 방안을 논의하는데 있다. 유아교육 현장에서 교재 및 교구는 제3의 교사라 할 정도로 그 중요성과 효과성이 크다. 또한 교재의 상업화, 보편화의 추세로 수많은 교재 교구가 개발되고 있어 이러한 교재 교구에 대한 질적 확보 및 판단이 요구되고 있다. 따라서 현장에서 용이하게 사용할 수 있는 우수한 질의 교구를 개발, 유지, 관리하는 전문 인증시스템의 필요성이 대두된다. 본고에서는 현 상황에서의 교재교구 인증 시스템을 살펴보고 이러한 시스템이 가지고 있는 문제점을 파악하여 바람직한 교재 교구 인증 시스템 개발에 대한 방향을 제시하고자 한다. The purpose of this study is to discuss plan for the development of accreditation system for instructional materials and equipment in kindergarten. Instructional materials in early childhood education are enough importance and effectiveness is high. In addition, the commercialization of materials, a number of common trends in the development of instructional materials, and these materials and ensure a qualitative judgment of the teaching and learning are required. So that can be used easily in the field to develop the instructional materials of excellent quality, maintenance, and management of a professional certification system is a demand. In this paper, the current situation in the instructional materials authentication system to examine the books have such a system, to identify the problems, to suggest preferred direction for teaching and leaning materials certification system.
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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 | 0.010 | 0.028 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".