Call for Proposals - Fall 2023
About the Education and Generative AI Fund
The Education and Generative AI (EDGE-AI) Fund has been established to support program-level, course-level and cross-disciplinary projects that integrate generative AI tools in the formal undergraduate curriculum at HKUST. We welcome projects that aim to:
- Incorporate generative AI and generative models to enrich engagement
- Adopt generative AI technology in teaching activities or tasks
- Foster authentic learning through experiential approaches with generative AI
- Experimenting with new and innovative approaches to assessment design
- Utilize generative AI to measure students’ learning process and provide feedback
- Facilitate innovative active learning through competency-based, challenge-based, and inquiry-based pedagogies with generative AI in academic courses
As part of the application process, applicants are required to indicate how their project deliverables can be adapted for at least two courses within their department. This will help to ensure that the project deliverables are relevant to the teaching courses and can be transferred to other courses within the department and promote appropriate and wider adoption of generative AI tools in teaching and learning. You may consider working with other members of your departments to best deliver this.
If you want to know more about possible uses of generative AI in teaching and learning:
Up to HK$250,000. Clear justifications must be provided for the amount requested. Funding awarded can be used for the purposes such as:
- hiring support staff (for example, project / instructional assistant / teaching associate / research assistant); and
- With the Department Head’s agreement, hiring temporary staff to partially release the project leader from regular commitments to work on the project.
The following expenses are NOT normally covered by the funding:
- equipment and teaching material expenses, which should be covered by the relevant School/Department
- conference attendance, publications in journals, and traveling outside Hong Kong; and
- refreshment for functions/events; and provision of incentives to students (for example, coupons or allowance) for taking part in the study.
Funding for the EDGE-AI is managed by the Center for Education Innovation (CEI), and project applications will be vetted by representatives from the Schools, Academy, and Provost Office.
Eligibility for Application
All full-time faculty members of the University with the responsibility of teaching and learning are eligible for application. You may apply individually or as a pair/group.
Tuesday, 10 October 2023
Friday, 27 October 2023
End of NOV 2023
Early December 2023
Funding will be allocated on the basis of competitive bidding. Only high-quality proposals meeting the evaluation criteria below will be funded.
- Alignment with aim of funding: The proposal should demonstrate a clear connection with the aim of the GAITL and how it aligns with the formal undergraduate curriculum at HKUST.
- Impact: The proposal should have a clear and measurable impact on teaching and learning. It should show how it will improve student engagement, learning outcomes, and assessment practices.
- Sustainability: The proposal should demonstrate how the project's impact can be sustained beyond the funding period. It should include a plan for how the project outcomes can be integrated into the regular curriculum and how the project can be continued beyond the funding period.
- Evidence-based: Provides a clear and systematic evaluation plan to demonstrate evidence of attainment of project objectives, which may include a generic and subject-specific baseline measurements for pre- and post-implementation comparison.
- Wide applicability: Impacts a large number of students, with potential continuation in other courses and programs.
- Relevance and transferability: The extent to which the project outcomes are relevant to additional courses and can be transferred to other courses within the department. This includes the degree to which the project outcomes align with the learning objectives and curriculum of the identified courses, and the potential for the project outcomes to be adapted and implemented in other courses.
- Feasibility: Provides a realistic scope for the deliverables, given the funding resources and time-frame.
- Project Management: Provides a clear and systematic design, development and implementation plan to demonstrate how each of the milestones can be achieved and the final target can be met.
Reporting and Dissemination Requirement
The project team will be required to disseminate the project outcomes (e.g. findings, deliverables, experiences) through School/Department/Division professional development, with the aim of informing colleagues of how the project deliverables can be implemented in other courses. The reporting and dissemination requirements of EDGE projects are as follows:
- An annual progress report will have to be submitted by the project leader to describe and evaluate the progress in implementing the approved projects.
- A final report should be submitted upon the completion of the project. The final report must outline how the project team disseminated the project outcomes and demonstrate how their project outcomes can be successfully adapted and implemented in two identified courses within the department
1 | Download the EDGE-AI Fund Template. It will guide you to complete the proposals with the key information needed.
2 | Preliminary proposal: Email to email@example.com by the specified deadline. Upon receiving your submission, CEI will contact you to discuss your idea and to provide advice to shape up the proposal.
3 | Final proposal: Email to firstname.lastname@example.org by the specified deadline. Please ensure that the proposal is endorsed and signed by relevant parties and mail the endorsed hardcopy to CEI (Room 6401), c/o Dr. Beatrice Chu.
4 | Pitch your ideas: Submit a 3-minute video or 10-slide deck with your final proposal describing the goal of your project and expected impact on teaching and learning. The pitch should cover:
- The problem/opportunity that is being addressed. For example:
- problem: students lack opportunities to engage in authentic problem-solving experiences
- opportunity: generative AI tasks promote engagement, provide instant feedback, and reinforce reflection
- Description of the solution
- Course(s) involved
- Target/size of the beneficiaries (e.g., students / teaching faculty)
- Value of the solution to teaching and learning
- How this project will inform future teaching practices, course and/or curriculum design