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Module 2.8

Example: AI Research Analysis

Let's walk through the process of creating a detailed analysis report, seeing how different prompt engineering techniques work together to achieve better results.

Initial Setup

AI: What can I help with?  
  You: I need to analyze and summarize 10 research papers about artificial intelligence's impact on healthcare for a literature review. The summary needs to:
  • Identify key findings and methodologies
  • Compare research approaches
  • Highlight contradictions or agreements
  • Extract relevant statistics and data
  • Synthesize conclusions

Please act as a research methodologist with expertise in systematic reviews. Can you confirm this expertise?
AI: I'll assist as a research methodologist with systematic review expertise. To ensure a thorough and well-structured analysis, could you first clarify:
  • Are these papers from a specific timeframe?
  • Do they focus on particular healthcare domains?
  • What level of statistical analysis is needed? This will help us create an appropriate framework for the review.
  

 

Why We Did This:

  • Established clear scope and deliverables upfront
  • Specified multiple analysis requirements
  • Requested relevant expertise
  • Set foundation for systematic approach
  • Created framework for detailed analysis

 

Topic Development

  You: Let's develop our analysis framework. Please create a structured approach that:
  1. Starts with individual paper analysis
  2. Builds to cross-paper comparison
  3. Includes methodology evaluation
  4. Culminates in synthesis
  5. Maintains clear citation tracking

Please outline how we'll organize and connect these elements.
AI: Based on your requirements, here's a structured analytical framework:
  1. Individual Paper Analysis Core Components:
    • Research question/hypothesis
    • Methodology overview
    • Key findings
    • Statistical significance
    • Study limitations Documentation: Citation matrix with key points
  2. Comparative Analysis Framework:
    • Methodological approaches
    • Sample sizes and demographics
    • Outcome measures
    • Statistical methods Documentation: Cross-reference table
  3. Synthesis Development Structure:
    • Common themes
    • Contradictory findings
    • Evidence strength assessment
    • Research gaps Documentation: Synthesis matrix

Would you like me to detail the specific analysis process for any of these components?

  

 

Why We Did This:

  • Provided clear structure for content development
  • Identified specific pieces of information to focus on
  • Explained a specific desired outcome

 

Creating the Structure

  You: The framework looks comprehensive. For the Individual Paper Analysis component, please create a detailed template that:
- Follows systematic review best practices
- Includes clear data extraction points
- Creates consistent documentation
- Enables effective synthesis later
- Maintains source traceability
AI: Here's a structured analysis template:

Paper Analysis Framework
1. Study Overview
   Documentation Points:
   - Full citation (APA format)
   - Research objectives
   - Study timeframe
   - Population details
   
2. Methodology Breakdown
   Key Elements:
   - Research design
   - Data collection methods
   - Analysis approaches
   - Validation techniques

3. Findings Organization
   Capture Points:
   - Primary outcomes
   - Secondary results
   - Statistical significance
   - Practical implications

4. Quality Assessment
   Review Criteria:
   - Methodology robustness
   - Bias considerations
   - Limitation acknowledgment
   - Generalizability

Should we test this template with one paper before applying it to the full set?		  

 

Why We Did This:

  • Created reusable structure
  • Established clear capture points
  • Built in quality assessment
  • Enabled systematic documentation
  • Prepared for synthesis phase

 

Creating Content

  You: Yes, let's test the template with one paper. Additionally, please create:
- A tracking system for cross-paper themes
- A method for noting contradictions
- A format for statistical comparison
- A synthesis preparation guide
AI: Let's implement the template with these additional elements:

Analysis Documentation System:

1. Individual Paper Tracking
   Paper ID: [Citation Key]
   Primary Theme(s): [Categories]
   Key Statistics:
   - Sample size: [N=]
   - Significance levels: [p-values]
   - Effect sizes: [measures]
   
2. Cross-Paper Comparison Matrix
   Theme Tracking:
   - Supporting findings: [Paper IDs]
   - Contradicting findings: [Paper IDs]
   - Inconclusive results: [Paper IDs]
   
3. Statistical Comparison Table
   | Study | Sample Size | Effect Size | P-Value |
   |-------|-------------|-------------|---------|
   | ID1   |             |             |         |
   
4. Synthesis Preparation
   - Theme consolidation points
   - Evidence strength markers
   - Gap identification areas
   - Future research implications

Would you like to proceed with analyzing the first paper using this system?		  

 

Why We Did This:

  • Built comprehensive tracking system
  • Enabled systematic comparison
  • Created clear data organization
  • Prepared for thorough synthesis
  • Maintained methodological rigor

 

The Whole Picture

While this conversation was broken down into individual sections that we could focus on, the whole thread would look be much longer. We added spaces between each of the sections in the thread below so you can see where it was broken down. 

AI: What can I help with?  
  You: I need to analyze and summarize 10 research papers about artificial intelligence's impact on healthcare for a literature review. The summary needs to:
  • Identify key findings and methodologies
  • Compare research approaches
  • Highlight contradictions or agreements
  • Extract relevant statistics and data
  • Synthesize conclusions

Please act as a research methodologist with expertise in systematic reviews. Can you confirm this expertise?
AI: I'll assist as a research methodologist with systematic review expertise. To ensure a thorough and well-structured analysis, could you first clarify:
  • Are these papers from a specific timeframe?
  • Do they focus on particular healthcare domains?
  • What level of statistical analysis is needed? This will help us create an appropriate framework for the review.
  
   
  You: Let's develop our analysis framework. Please create a structured approach that:
  1. Starts with individual paper analysis
  2. Builds to cross-paper comparison
  3. Includes methodology evaluation
  4. Culminates in synthesis
  5. Maintains clear citation tracking

Please outline how we'll organize and connect these elements.
AI: Based on your requirements, here's a structured analytical framework:
  1. Individual Paper Analysis Core Components:
    • Research question/hypothesis
    • Methodology overview
    • Key findings
    • Statistical significance
    • Study limitations Documentation: Citation matrix with key points
  2. Comparative Analysis Framework:
    • Methodological approaches
    • Sample sizes and demographics
    • Outcome measures
    • Statistical methods Documentation: Cross-reference table
  3. Synthesis Development Structure:
    • Common themes
    • Contradictory findings
    • Evidence strength assessment
    • Research gaps Documentation: Synthesis matrix

Would you like me to detail the specific analysis process for any of these components?

  
   
  You: The framework looks comprehensive. For the Individual Paper Analysis component, please create a detailed template that:
- Follows systematic review best practices
- Includes clear data extraction points
- Creates consistent documentation
- Enables effective synthesis later
- Maintains source traceability
AI: Here's a structured analysis template:

Paper Analysis Framework
1. Study Overview
   Documentation Points:
   - Full citation (APA format)
   - Research objectives
   - Study timeframe
   - Population details
   
2. Methodology Breakdown
   Key Elements:
   - Research design
   - Data collection methods
   - Analysis approaches
   - Validation techniques

3. Findings Organization
   Capture Points:
   - Primary outcomes
   - Secondary results
   - Statistical significance
   - Practical implications

4. Quality Assessment
   Review Criteria:
   - Methodology robustness
   - Bias considerations
   - Limitation acknowledgment
   - Generalizability

Should we test this template with one paper before applying it to the full set?		  
   
  You: Yes, let's test the template with one paper. Additionally, please create:
- A tracking system for cross-paper themes
- A method for noting contradictions
- A format for statistical comparison
- A synthesis preparation guide
AI: Let's implement the template with these additional elements:

Analysis Documentation System:

1. Individual Paper Tracking
   Paper ID: [Citation Key]
   Primary Theme(s): [Categories]
   Key Statistics:
   - Sample size: [N=]
   - Significance levels: [p-values]
   - Effect sizes: [measures]
   
2. Cross-Paper Comparison Matrix
   Theme Tracking:
   - Supporting findings: [Paper IDs]
   - Contradicting findings: [Paper IDs]
   - Inconclusive results: [Paper IDs]
   
3. Statistical Comparison Table
   | Study | Sample Size | Effect Size | P-Value |
   |-------|-------------|-------------|---------|
   | ID1   |             |             |         |
   
4. Synthesis Preparation
   - Theme consolidation points
   - Evidence strength markers
   - Gap identification areas
   - Future research implications

Would you like to proceed with analyzing the first paper using this system?		  

 

Key Techniques Used in This Example

Throughout this conversation, we've seen several prompt engineering techniques working together. Like instruments in an orchestra, each technique plays its own part while contributing to a harmonious whole. Let's break down the key techniques and see how they created a successful outcome:

  • Token Management
    • Used clear categorization
    • Created efficient documentation structure
    • Organized information systematically
    • Avoided redundant capture
  • Context Management
    • Maintained clear paper relationships
    • Created theme linkages
    • Established clear reference points
    • Built progressive understanding
  • Response Parameters
    • Provided clear deliverable specifications
    • Set format requirements upfront
    • Included quality benchmarks
    • Specified depth and detail needs
  • Advanced Control Techniques
    • Set clear documentation requirements
    • Established format standards
    • Created structured outputs
    • Enabled quality control

What Makes This Approach Successful

Looking back at our conversation, we can see several key factors that contributed to creating an effective research analysis framework:

Systematic Development

  • Started with clear requirements before jumping into analysis
  • Built frameworks before beginning detailed work
  • Created reusable templates and structures
  • Established quality control points throughout

Progressive Complexity

  • Began with individual paper analysis
  • Built to cross-paper comparisons
  • Moved to thematic analysis
  • Culminated in comprehensive synthesis

Documentation Strength

  • Created clear paper trails
  • Established source traceability
  • Enabled fact-checking
  • Maintained academic rigor

Integration of Tools

  • Combined multiple analysis methods
  • Created complementary tracking systems
  • Built interconnected documentation
  • Enabled comprehensive review

Most importantly, these elements worked together to create a robust analysis system. Each component supported the others, creating a methodology that was both thorough and practical. The approach ensures no critical information is lost while making the synthesis process more manageable.

Try It Yourself!

When conducting research analysis:

  1. Create clear analysis frameworks
  2. Establish systematic documentation
  3. Build clear comparison methods
  4. Maintain rigorous organization
  5. Prepare for synthesis throughout

Putting It All Together

Now that you've completed this practice experience, be sure to check out the next example!

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