AI in Assessment Example: Level 5

Interdisciplinary Project (Graduate-level, Sustainability)

At this level “AI Exploration” of the five-level AI Assessment Scale (Perkins, et al., 2024) Al is used creatively to enhance problem-solving, generate novel insights, or develop innovative solutions to solve problems. In more advanced courses, students and educators may also choose co-design assessments to explore unique Al applications within the field of study.

Course: SUST 601 – Interdisciplinary Approaches to Sustainability

Assignment Title: Developing a Sustainable Solution for a Real-World Environmental Problem

Due Date: [Insert Due Date]

Assignment Overview:
In this assignment, you will develop a sustainable solution for a real-world environmental problem by leveraging AI tools to explore various approaches and strategies. The project requires you to engage in interdisciplinary innovation, where AI will assist in modeling potential solutions, predicting outcomes, and generating creative ideas. Your task is to critically engage with AI as a co-creator, using its capabilities to refine complex solutions that address the environmental issue at hand.

Objectives:

To develop a comprehensive and sustainable solution for a real-world environmental problem using interdisciplinary approaches.
To use AI tools to model solutions, predict outcomes, and generate innovative strategies.
To document and critically reflect on the co-creation process with AI, highlighting the role of AI in shaping your solution.

Instructions:

Problem Selection and Initial Research:
- Identify a real-world environmental problem that requires a sustainable solution. This could range from climate change mitigation, waste management, water resource management, to sustainable urban planning.
- Conduct initial research on the problem, focusing on its interdisciplinary aspects and the challenges it presents. Gather data and background information that will inform your approach.
AI-Assisted Solution Modeling:
- Use AI tools to model potential solutions to the problem. AI can assist in analyzing environmental data, simulating the impacts of different strategies, and predicting long-term outcomes.
- Experiment with AI to generate creative ideas and alternative approaches that may not be immediately apparent through traditional methods. Explore various scenarios and strategies, using AI to assess the viability and sustainability of each option.
Refining the Solution:
- Refine the AI-generated solutions by integrating your interdisciplinary knowledge and expertise. Focus on ensuring that the proposed solution is not only technically feasible but also socially, economically, and environmentally sustainable.
- Collaborate with AI to iterate on the solution, making adjustments based on AI’s predictions and your own analysis. This iterative process should involve a balance between AI-generated insights and human judgment.
Co-Creation Log and Reflective Report:
- Maintain a co-creation log throughout the project, documenting your interactions with AI, the decisions influenced by AI, and the innovative solutions generated through this partnership. The log should include specific examples of how AI shaped your approach and the challenges you encountered.
- Write a reflective report (5-7 pages) that highlights the collaborative process between you and AI. Discuss how AI contributed to the interdisciplinary innovation process, the benefits and limitations of AI in developing sustainable solutions, and how the partnership between human expertise and AI led to the final solution.
Final Submission:
- Submit your final sustainable solution proposal (20-25 pages), including all key components such as problem analysis, proposed strategies, modeled outcomes, and implementation plan.
- Include the co-creation log and the reflective report as appendices to your proposal. Ensure that the entire submission is well-organized, clearly written, and professionally presented.

Evaluation Criteria:

– Innovation and Sustainability of the Solution (35%): Demonstrating a high level of innovation and interdisciplinary thinking in developing a sustainable solution that addresses the environmental problem effectively.

– Integration of AI Tools (25%): Effectively using AI to model solutions, predict outcomes, and generate creative ideas. The co-creation log should reflect a deep engagement with AI tools and a thoughtful integration of AI-generated insights into the final solution.

– Comprehensive and Clear Proposal (25%): Presenting a well-organized and detailed proposal that covers all required components, with clear and compelling arguments supporting the viability and sustainability of the solution.

– Reflective Report (10%): Providing insightful and critical reflections on the co-creation process with AI, including an analysis of the collaborative dynamics and the role of AI in interdisciplinary innovation.

– Writing and Presentation Quality (5%): Producing a professionally written and well-presented proposal, with attention to clarity, formatting, and adherence to academic standards.

Support Resources:

– AI Tools and Software: Access to AI tools such as [specify tools, e.g., TensorFlow, MATLAB, ArcGIS] will be provided through the university’s sustainability lab. Workshops on using these tools for environmental modeling and scenario analysis will be available during the first month of the project.

– Interdisciplinary Collaboration: Participate in interdisciplinary workshops and seminars that bring together students and faculty from different fields (e.g., environmental science, engineering, economics) to discuss the integration of AI in sustainability projects.

– Office Hours: Schedule office hours with your instructor to discuss your project ideas, AI tool use, and strategies for integrating AI insights into your solution.

– Library Resources: The university library offers access to environmental and sustainability databases, including case studies on AI applications in sustainability. Librarians can assist you in finding relevant research and data sources.

– Peer Collaboration: Engage in peer review sessions where you can present your AI-generated solutions and receive feedback on how to refine and enhance your approach.

Academic Integrity:
Your final solution proposal must reflect your original work, with AI tools used as co-creators rather than as sole creators. Misuse of AI to generate unoriginal content or failure to critically engage with AI-generated outputs will be considered a violation of academic integrity. All AI tools and methods used must be properly documented and critically assessed in your co-creation log and reflective report.

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