ANALISIS KESULITAN GURU DALAM IMPLEMENTASI KURIKULUM 2013 DI SDN 216 TALUNGENG KECAMATAN BAREBBO KABUPATEN BONE
Bibliographic record
Abstract
This research is a type of descriptive qualitative research that aims to find out. The subjects in this study were 6 class teachers at SDN 216 Talungeng. Data collection was carried out by interviews, and observations. Data analysis techniques are data reduction, data display, Conclusion Drawing/Verification. The results of this study indicate that in planning and implementing authentic assessments at SDN 216 Talungeng, Barebbo District, Bone Regency, there are still difficulties experienced by teachers in planning and implementing authentic assessments in the affective, cognitive, and psychomotor domains, but there are also several aspects that teachers carry out without any difficulties. . The conclusion of this study is that there are still some difficulties experienced by teachers in planning and implementing authentic assessments. Therefore, special attention is needed in conducting coaching and training for teachers related to authentic assessments in order to be able to assess students optimally.
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.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".