Inquiry-Based Learning Model to Improve Higher Order Thinking Skills
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 present ways of implementing inquiry- learning model with the use of scientific reports to improve teachers’ understanding and ability on teaching biology at secondary level. The quantitative research method is quasi-experiment design with pre-test and post-test control group. The research instrument for collecting data of students’ higher order thinking skills is scoring rubrics for assessing abilities on developing and presenting a scientific report. The instruments for assessing teachers’ skills are teacher observation sheets over inquiry-based learning scientific report using an induction method. The research subjects consist of 4 biology teachers and 80 of grade 10 students from Public Secondary School 3 Samarinda.The teachers are all female; while from 80 students, 53 of them are female and the rest 27 are male. The students’ age ranges from 16 to 18 years old. The research lasted for 1 month.Analysis of data uses t test, that if toutcome is higher than ttable, the inquiry-based learning model using scientific reports does affect students’ higher order thinking skills. Data analysis is composed in tabulation format with several graded categories: inadequate, sufficient, good and excellent. The result of the study is that higher order thinking skills of students are increasing in numbers and more equal compared with classes taught by teachers who did not follow the inquiry-based learning model workshop and presentation. The inquiry-based learning model was applied via preparation and presentations of scientific reports after the students carry out practical activities through the guidance of student activity worksheets.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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