The multi-disciplinary approach to an interdisciplinary virtual exchange
Bibliographic record
Abstract
New communication technologies are changing the way we work and communicate with people around the world. Given this reality, students in Higher Education (HE) worldwide need to develop knowledge in their area of study as well as attitudes and values that will enable them to be responsible and ethical global citizens in the workforce they will soon enter, regardless of the degree. Different institutional and country-specific requirements are important factors when developing an international Virtual Exchange (VE) program. Digital learning environments such as ProGlobe – Promoting the Global Exchange of Ideas on Sustainable Goals, Practices, and Cultural Diversity – offer a platform for collaborating with diverse students around the world to share and reflect on ideas on sustainable practices. Students work together virtually on a joint interdisciplinary project that aims to create knowledge and foster cultural diversity. This project was successfully integrated into each country’s course syllabus through a common global theme; sustainability. The focus of this paper is to present multi-disciplinary perspectives on the opportunities and challenges in implementing a VE project in HE. Furthermore, it will present the challenges that country coordinators dealt with when planning and implementing their project. Given the disparity found in each course syllabus, project coordinators uniquely handled the project goal, approach, and assessment for their specific course and program. Not only did the students and faculty gain valuable insight into different aspects of collaboration when working in interdisciplinary HE projects, they also reflected on their own impact on the environment and learned to listen to how people in different countries deal with environmental issues. This approach provided students with meaningful intercultural experiences that helped them link ideas and concepts about a global issue through the lens of their own discipline as well as other disciplines worldwide.
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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 | 0.016 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.013 | 0.040 |
| Scholarly communication | 0.025 | 0.015 |
| Open science | 0.004 | 0.034 |
| Research integrity | 0.005 | 0.008 |
| 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".