Peningkatan Kompetensi Siswa SMP Perguruan Islam Ar-Risalah dalam rangka Persiapan Menghadapi Olimpiade Sains Nasional (OSN) di Bidang IPA Khususnya Fisika
Bibliographic record
Abstract
The National Science Olympiad (OSN) is a competition event in the field of science for students at elementary, middle and high school levels in Indonesia. Students who take part in OSN are students who have passed district and provincial level selection, so they are the best students from their respective provinces. One indicator of the success of the learning process at school is student success in academic competitions such as OSN. The 2023 OSN will be held in August in the city of Bogor, West Java Province. Before going to OSN, students undergo school level selection (OSN-S) in February, district/city level selection (OSN-K) is held in April, Provincial level selection (OSN-P) is held in June. Considering that this prestigious competency is routinely carried out every year and selection is carried out at the beginning of every year, it is therefore necessary for schools to prepare their best students continuously and sustainably. This OSN is one part of a series of selections to get the best students from all over Indonesia who will be further guided by their respective competition teams and will be included in international level Olympiads. OSN is a never-ending process. Students and all educational stakeholders involved in it take turns carrying out productive work. Starting from selecting prospective OSN participants, imparting knowledge, maintaining and developing mastery of knowledge, to reaping the rewards as a young scientist. For teachers, as direct supervisors at the school level, this OSN competition is clearly a challenge in itself. Although it must be admitted that the weight of the material and the quality of questions at the level of Olympic questions are relatively much more difficult than the material usually taught in schools. It is even said that the majority of resources in schools are not yet able to handle it. Apart from that, the school's references and financial support for its development are not yet available adequately. This is actually the main obstacle for most schools to play an active role in preparing their students to take part in OSN competitions. Based on experience in the field, so far West Sumatra is only represented by a few schools. Therefore, the Adzkia Physics Education Study Program was called upon to overcome this problem by carrying out training to increase the competency of junior high school students at the Ar-Risale Islamic College in Padang in preparing students for OSN in the field of science (physics). This service is carried out by delivering material equipped with modules and discussion of National Science Olympiad questions. This service is expected to produce articles published in journals and print/online media. Keywords: Physics, Training, National Science Olympiad, OSN, Science, SMP/MTs
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.060 | 0.017 |
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".