Research and Practice of "1141" Research-Based Teaching Model
Bibliographic record
Abstract
In the process of practical research-based teaching of engineering majors in applied undergraduate universities, there are common problems such as the first-class research-based teaching focuses on form but not substance, research-based teaching is regarded as an "extracurricular activity" outside the daily teaching process, and research-based teaching evaluation focuses on terminal evaluation but not developmental evaluation. This paper takes the Internet of Things Engineering major as an example, innovates and practices the "1141" research-based teaching model, and takes talent training programs, classroom teaching, second classroom, and practical teaching reform as practical approaches to construct a "two-classroom" linkage mechanism and a multi-evaluation mechanism to cultivate students' ability to discover, analyze and solve problems using scientific thinking and methods. Practice shows that this model can effectively improve students' ability level and comprehensive quality, and provide strong support for the certification of engineering education majors.
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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 | 0.055 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.024 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".