Moodle
Duration: 15-20 minutes per team + 5 minutes for Q&A
Objective:
Each team will present a functional prototype of their software project, demonstrating how it meets community needs, adheres to software engineering best practices, and incorporates AI-assisted development where applicable.
Presentation Outline & Expectations
1. Introduction (2-3 minutes)
- Project Title & Team Members
- Community Partner / Problem Statement
- Who are the users or stakeholders?
- What problem does the software aim to solve?
2. System Overview & Key Features (4-5 minutes)
- Live Demonstration of the Prototype
- Walk through key features and user workflows.
- Showcase the user interface (UI) and how users interact with the system.
- Explain major functionalities and their purpose.
- Technology Stack & Architecture
- Programming languages, frameworks, and databases used.
- System architecture diagram (e.g., frontend/backend interactions, cloud services, APIs).
3. Software Engineering Process & AI Utilization (4-5 minutes)
- Development Process & Methodologies
- Agile, Scrum, Kanban, or other development approaches.
- Version control and collaboration tools (GitHub, CI/CD pipelines).
- Use of AI in Development (Required Component)
- How AI tools were used in the project, such as:
- Coding Assistance: GitHub Copilot, ChatGPT for debugging or generating code snippets.
- Automated Testing: AI-based test case generation (e.g., Test.ai, DeepCode).
- Data Processing: AI-assisted data analysis, NLP, or image recognition.
- Security Checks: AI-driven vulnerability scanning (e.g., SonarQube, Snyk).
- UI/UX Enhancements: AI-driven usability testing or feedback.
- How AI tools were used in the project, such as:
4. Software Quality & Testing (3-4 minutes)
- Validation & Verification
- How did you ensure the software meets user needs (validation)?
- How did you verify correctness through testing?
- Testing Strategies Used
- Unit, integration, system, or user acceptance testing.
- How AI was used (if applicable) to automate or enhance testing.
5. Impact & Future Development (3-4 minutes)
- Community Impact & User Feedback
- How does the software benefit the target community?
- Any feedback received from stakeholders or test users.
- Future Work & Scalability
- What improvements or features would you add with more time?
- How scalable is the project for broader use?
6. Conclusion & Q&A (Final 5 Minutes)
- Key Takeaways from the Project
- Lessons learned in development and teamwork.
- Any surprises or major challenges encountered.
- Open the floor for audience questions.
Grading Criteria (100 Points Total)
| Category | Points | Description |
|---|---|---|
| Project Overview & Problem Definition | 10 | Clearly explains problem & community need. |
| Prototype Functionality & Demonstration | 20 | Shows working prototype, key features, and UI. |
| Technical Depth & AI Utilization | 20 | Effectively integrates AI in development. |
| Software Quality & Testing | 15 | Demonstrates testing strategies & validation. |
| Impact & Future Considerations | 15 | Explains real-world impact & future scalability. |
| Presentation & Communication | 10 | Clear, engaging, well-structured. |
| Q&A Engagement | 10 | Responds effectively to audience questions. |
Final Notes:
- Teams should prepare slides and a live demo (recorded backup demo in case of technical issues).
- AI must be meaningfully integrated—teams should explain its role in development, testing, or deployment.
- The presentation should be engaging, professional, and well-practiced.