Think globally, act locally: Case study BSU summer school in Shanghai, China 2018
Bibliographic record
Abstract
Aim: This article focuses on the teaching and learning style, intercultural knowledge, and educational abilities as experienced by both; the Chinese students and faculty. Advancing the idea of world citizenship among college students coupled with the framework of decreasing state and federal funding for public education in the United States, scuffle for students, and strong academic desire for the internationalization of higher education, colleges and universities turned their attention to the world. As a medium-sized public institution, Bridgewater State University (BSU) was among the pioneering institutions to do both; signing partnership and working with a third-party organization in China to recruit students.Method: The analytical discussion analysis is based on a qualitative and quantitative methodology. Theories of interpersonal communication and the development of communication and management highlighted the international educational model KAP: Knowledge, Attitudes, and Practice in this article.Findings: The results show that the BSU summer program in Shanghai seems attractive to students from different parts of China. Student home universities and colleges in the U.S. and Canada have no issue recognizing, accepting, and transferring credits from American institutions such as Bridgewater State University and Canadian university summer programs.Implications/Novel Contribution: The significance of this case is 1) to showcase the innovative approach of BSU to provide academic opportunities for international students to complete a portion of required and elected courses that taught by BSU faculty, and 2) to avoid the cost of building and maintaining international campuses or branches abroad.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".