On the Importance of Combining the Theoretical Teaching and Practical Teaching of College Sailing Club Courses-Taking Qingdao University of Science and Technology as an Example
Bibliographic record
Abstract
The 18th National Congress of the Communist Party of China put forward the maritime power strategy. College students shoulder the heavy responsibility of building a maritime power, and they can get close to the ocean and appreciate the charm of the sea through participating in sailing. In recent years, with the rapid development of sailing in China, more and more colleges and universities have begun to participate in the sailing. For example, Xiamen University on behalf of China to participate in the World University Sailing Championships, and Qingdao University of Science and Technology on behalf of China to participate in the Russian St. Petersburg University Regatta. More and more sailing teams of universities went abroad to the world. In 2017, the China University Student Sailing Championship attracted more than 30 colleges and universities from all over the country. There are sailing courses in the universities that performance well in sailing races, such as Xiamen University, Qingdao University of Science and Technology, Dalian Maritime University. These courses are loved by many students, and the sport is especially appealing to students who like challenges, brainstorm and enjoy good physical constitution. Sailing is a combination of intelligence and physical strength. Theory and practical teaching are both very important in teaching. If the teacher combines theory and practical teaching in the teaching process, then the students will have a more solid grasp of the learning content in the sailing course, and their learning process will be more secure.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".