SUSTAINABLE SOLUTIONS FOR GLOBAL CO-CREATION AND COLLABORATION IN POST-PANDEMIC HIGHER EDUCATION
Bibliographic record
Abstract
This presentation examines models of international collaboration between Hochschule der Medien (Stuttgart, Germany) and The Creative School, Ryerson U (Toronto, Canada), identifying the elements that make it a successful best-practices partnership model that is sustainable in the post-pandemic higher education. This session will highlight the importance of global partnerships in the future workplace and explain how sustainable solutions like the Global Campus Studio model can increase the students’ employability in the future. The presenters will share their journey of fostering this transatlantic partnership and present specific strategies on sustainable transatlantic collaboration that has proven vital in response to COVID-19 global health pandemic and beyond.The global health pandemic has created an opportunity for higher education institutions to reinvision global learning and international collaboration. Institutions are tasked with finding innovative and sustainable solutions to enable students and faculty to access and engage in unique global learning opportunities in response to global changes and challenges in the post-pandemic era. Background: With COVID-19 limiting global mobility, Hochschule der Medien (HdM), working alongside strategic partners such as, The Creative School at Ryerson University, sought to reinvision global experiences, co-creation and collaboration. With access and inclusion as a core priority of their institution’s internationalization strategy, both institutions came together to rethink and enhance international learning opportunities for students and faculty through new sustainable models Virtual International Collaboration and Co-creation through the Global Campus Studio (GCS) model: Piloted in 2018, GCS is a virtual hub for creative international collaboration and co-creation, offering students the opportunity to collaborate with diverse international teams, using the connective affordances of contemporary digital technology. This for-credit course at Ryerson University runs concurrently with select international academic partners including HdM, where students from various interdisciplinary and international backgrounds collaborate on hands-on creative projects, ranging from immersive VR experiences, live events, media challenges, to board games and beyond. Students who complete the course gain valuable skills in creative development, media entrepreneurship, and design thinking, as well as develop cultural understanding, gain global leadership strategies, enhance knowledge of digital technologies and refine strategies for remote collaboration. Each year, over 100 students from around the world co-create and collaborate on a creative output centered around a global theme such as Food Insecurity and Climate Change. This past fall, The Creative School, HdM alongside two other academic partners (University of the Arts in London and Seoul Institute of the Arts) Reimagined the Creative Fields Post COVID-19. HdM and The Creative School worked on a challenge with an external partner from the media industry: Wiley & Sons, a global publisher with subsidiaries in Canada and Germany.Outline:- Re-Envisioning Global Collaboration through a 21st-Century Lense- Ideation to Implementation: Stages of Development- Reflection, Lessons Learned, & Anticipated Obstacles- The Future of Sustainable International Collaboration
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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 | 0.012 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.012 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.002 | 0.038 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.026 | 0.005 |
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".