Faculty and Staff AI Resource Repository

Advanced AI Activities

Complex learning activities leveraging AI for deeper understanding and skill development.

AI Repository > First Activities > Advanced Activities

Collaborative Research Analysis

Research
Analysis
Collaboration

Implementation Steps:

  1. Students form research teams
  2. Each team selects a complex topic
  3. AI assists in literature review
  4. Teams analyze and synthesize findings
  5. AI helps identify patterns and gaps
  6. Students present conclusions

AI Prompts:

1. "Analyze these research abstracts and identify common themes..."
2. "Compare methodologies across these studies..."
3. "Generate potential research questions based on gaps in current literature..."

Learning Outcomes:

  • Advanced research skills development
  • Critical analysis abilities
  • Synthesis of complex information
  • Collaborative research techniques

Multi-Stage Writing Development

Writing
Process
Revision

Project Stages:

  1. AI-assisted research and outlining
  2. Collaborative brainstorming
  3. Structured writing process
  4. Peer review with AI support
  5. Revision and refinement
  6. Final analysis and reflection

Research Phase

  • Source evaluation
  • Theme identification
  • Pattern recognition

Writing Phase

  • Structure development
  • Argument construction
  • Evidence integration

Revision Phase

  • Content refinement
  • Style enhancement
  • Coherence check

Multi-Perspective Problem Analysis

Problem-Solving
Critical Thinking
Analysis

Activity Structure:

  1. Present complex scenario
  2. AI generates multiple perspectives
  3. Students analyze viewpoints
  4. Develop solution strategies
  5. Test and refine approaches
  6. Present and defend solutions

Sample Scenarios:

1. "Environmental impact analysis of new technology..."
2. "Ethical implications of AI in healthcare..."
3. "Economic policy effects on diverse populations..."

Real-Time Data Interpretation

Data Analysis
Visualization
Interpretation

Implementation Process:

  1. Data collection setup
  2. AI-assisted analysis
  3. Pattern identification
  4. Visualization creation
  5. Interpretation development
  6. Presentation of findings

Skills Developed:

  • Data literacy
  • Statistical analysis
  • Visual communication
  • Analytical thinking

Process Assessment

  • Documentation quality
  • Tool usage effectiveness
  • Strategy development

Output Assessment

  • Content quality
  • Analysis depth
  • Innovation level

Reflection Assessment

  • Learning insights
  • Process evaluation
  • Future applications