7 Ways to Critical Thinking & Problem Solving

Course Modules

Day 1: Foundations of Critical Thinking, Problem-Solving Methods, and AI Integration

Module 1: The Role of Critical Thinking and AI in Problem Solving

Description:
This module introduces critical thinking as a foundation for problem-solving, with an emphasis on how AI can augment these processes. Participants will explore critical thinking fundamentals alongside AI tools that can provide insights, such as AI-powered data analysis platforms.

Learning Objectives:

• Define critical thinking and its role in effective problem-solving
• Recognize the role of AI in enhancing analytical capabilities
• Understand how to use AI tools for deeper insights in problem analysis

Module 2: Method 1 – Root Cause Analysis with AI

Description:
Root Cause Analysis aims to identify the underlying

causes of problems. Participants will learn traditional techniques like the “5 Whys” and Fishbone Diagram, while using AI-driven data analytics to uncover deeper insights and patterns that may not be visible manually.

Learning Objectives:

• Use AI-powered data analysis to identify problem origins
• Apply the “5 Whys” technique with AI support to explore problem layers
• Integrate AI tools to automate and enhance Root Cause Analysis

Module 3: Method 2 – AI-Augmented Brainstorming for Creative Solutions

Description:
Participants will explore AI tools, such as ChatGPT or brainstorming platforms, to enhance traditional brainstorming methods. AI will be used to generate new ideas, inspire creativity, and filter ideas based on criteria for practicality and impact.

Learning Objectives:

• Use AI to generate a wide range of creative solutions
• Apply AI filtering tools to evaluate and prioritize ideas
• Enhance open and judgment-free ideation by leveraging AI creativity tools

Module 4: Method 3 – SWOT Analysis with AI Insights

Description:
SWOT Analysis assesses Strengths, Weaknesses, Opportunities, and Threats. Participants will use AI-powered market analysis tools to gather data on external factors and business intelligence platforms to gain insights into internal strengths and weaknesses.

Learning Objectives:

• Apply AI to perform a data-driven SWOT Analysis
• Use AI tools to analyze external threats and opportunities
• Leverage AI-driven insights to create a more comprehensive SWOT profile

Day 2: Advanced AI-Powered Problem-Solving Techniques and Application

Module 5: Method 4 – The Decision Matrix with AI-Assisted Scoring

Description:
The Decision Matrix is a quantitative approach to compare multiple options objectively. Participants will learn how to use AI to automate the scoring of different options based on predefined criteria, simplifying the decision-making process and increasing objectivity.

Learning Objectives:

• Use AI to automate the Decision Matrix for unbiased evaluations
• Assign weights to criteria and allow AI tools to process comparative data
• Apply AI-driven quantitative analysis to support decision-making

Module 6: Method 5 – Scenario Analysis and “What If” Scenarios with AI Simulation

Description:
This module introduces Scenario Analysis with AI-driven simulation tools, allowing participants to create and explore multiple “What If” scenarios. AI simulations will provide insights into possible outcomes, helping participants prepare for various contingencies.

Learning Objectives:

• Use AI simulation tools to predict outcomes of different scenarios
• Apply “What If” analyses using AI to assess risks and impacts
• Develop adaptable strategies based on AI-simulated results

Module 7: Method 6 – The 80/20 Principle (Pareto Analysis) with AI for Big Data

Description:
Using Pareto Analysis, or the 80/20 Principle, participants will leverage AI to analyze large datasets, identifying the factors with the most significant impact on a problem. AI-driven insights make it easier to focus on high-impact areas, especially when analyzing complex data.

Learning Objectives:

• Apply the 80/20 Principle with AI to focus on high-impact areas of a problem
• Use AI data processing to quickly identify critical factors
• Allocate resources effectively based on AI-driven Pareto Analysis

Module 8: Method 7 – Mind Mapping for Problem Solving with AI Visualization Tools

Description:
Mind Mapping is a visual tool for organizing thoughts and connecting ideas. Participants will use AI-powered mind mapping software to break down complex problems, explore relationships, and create structured approaches to solutions.

Learning Objectives:

• Use AI visualization tools to create dynamic mind maps
• Identify and connect ideas through AI-supported mind mapping

Organize complex problems into manageable parts with AI assistance