Material Properties Analysis with AI Support

Example developed based on CLOs from: CCE 321 – Materials Science in Civil Engineering.

Purpose

This assignment helps students identify key material properties for construction materials and analyze their importance in real-world applications. This assignment emphasizes the human capacity for critical thinking, collaboration, and the ability to synthesize insights from diverse sources while leveraging AI tools to enhance understanding.

Learning Outcomes

• Identify key material properties of construction materials, including aggregates, asphalt concrete, portland cement concrete, wood, and metals.
• Analyze the significance of these properties for various civil engineering applications.
• Collaboratively explore and share findings to enhance collective understanding.

Instructions

Format (Final Deliverable)

1. Think-Pair-ChatGPT-Pair-Share Activity
   • Think: Individually, list key material properties for aggregates, asphalt concrete, portland cement concrete, wood, and metals.
   • Pair: Pair up with a classmate and discuss your lists, comparing and contrasting identified properties.
   • ChatGPT Exploration:
     • Use an AI generative tool like Microsoft Copilot](m365.cloud.microsoft/chat) or ChatGPT to explore additional insights on material properties. For example, ask, “What are the most critical material properties of wood for structural applications?” or “How does asphalt concrete’s viscosity affect its performance in road construction?”
     • Document AI tool usage with screenshots of outputs and brief descriptions of how the tool supported your exploration.
   • Pair-Share: Share your findings with the class, highlighting the most critical material properties and their implications for specific applications.
2. Reflection
   • Write a brief reflection (250 words) on the activity, addressing:
     • How collaboration and AI tools contributed to your learning.
     • Insights gained from the discussion and AI exploration.

Grading Criteria

• Depth and accuracy of material property analysis (40%)
• Effective use of AI tools and documentation (30%)
• Quality of collaboration and contribution to class discussion (20%)
• Reflection on the learning process (10%)

Resources

• Writing Center consultations for structuring your reflection.
• Microsoft Copilot for refining and organizing your written reflection. – ChatGPT for generating insights and enhancing understanding.