Bibliographic record
Abstract
本研究では, グローバル化の進展や産業構造の変化に対して, 大学教育が社会の要請に対応していない問題を意識し, 国際社会に向け, 日本の大学はどのような人材をどのように育成していけばよいのか, 学士課程教育再編の一方策として, キャリア教育の質保証に, ライティング教育がいかに資するか を検討した。先進的取り組みを行っているカナダ・豪州の大学を訪問調査し, その成果を国内外の 学会で発表した。学生の書いた記録はキャリア教育のエビデンスとなるだけでなく, 書く訓練は学 生の思考を鍛えることができる。これら一連の成果をもとにテキストを開発出版した。 Japan has entered the universalization phase of higher education.The decline of university students' writing and thinking abilities has become a big issue.In order to improve students' abilities, faculty need to design the curriculum for not only basic study skills but the disciplines related to comprehensive sequential learning process throughout underguraduate coursewok.For the purpose of enforcement relevance to the need from society in globalization today, quality assurance of university educational reform requires systematic development of writing education and teaching and learning skills.Visiting advanced campuses of the universities in Canada and Australia brought the stimulating and informative different perspectives and systems.Based on the survey findings, the textbook has been published from the University Press of Keio and revised.The title is Developing Critical Thinking to Write Papers".
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".