Construction and Application of OBE-based Multiple Formative Assessment System in the “Micro-lecture + PAD Class”
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
To construct a scientific and effective curriculum assessment system of higher education is an effective measure to improve classroom teaching quality, a powerful guarantee to enhance students’ classroom participation and enthusiasm, and an important way to achieve fair learning evaluation. Based on a brief introduction of OBE and a comprehensive review of the current research situation of formative assessment, this paper analyzes the existing problems in the curriculum evaluation of higher education, constructs an OBE-based multiple formative evaluation system, and tries to apply it in the “micro-lecture + PAD class”. Finally, the author carries out a controlled experiment and makes a quantitative analysis of the relevant data obtained in the experiment. The results of the study show that the OBE-based multiple formative assessment system plays a positive role in promoting students’ academic performance, improving their autonomous learning ability, and enhancing their self-confidence.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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