Understanding Generative AI
Who Wants to Be a Millionaire
Who Wants to Be a Millionaire is a popular quiz show where contestants answer a series of multiple-choice questions to win increasing amounts of money, ultimately aiming for the top prize of one million dollars. The game progresses through a series of 15 questions (or fewer in some versions), each with four possible answers. Questions start relatively easy and become more difficult as the contestant advances. The contestant must choose the correct answer to move on to the next question, and they can decide to either continue playing for a higher amount or walk away with the money they've earned so far. If a contestant chooses an incorrect answer without using the lifelines available, they risk losing some or all of their accumulated winnings. The virtues of using Who Wants to Be a Millionaire for learning:
- Engagement and Motivation: The game’s high-stakes format and increasing difficulty levels keep learners invested and motivated to progress further.
- Incremental Learning and Confidence Building: The tiered question structure allows students to start with easier questions, gradually building confidence as they advance to more challenging ones.
- Lifelines as Support Mechanisms: Features like “Ask the Audience” or “Phone a Friend” can be adapted to encourage collaboration, peer support, or access to additional learning resources, enhancing understanding.
- Immediate Feedback: Students receive instant feedback on their answers, reinforcing correct responses or providing opportunities for reflection when answers are incorrect.
- Customizability: Educators can design questions that align with specific learning goals and curriculum content, making it versatile across different subjects and skill levels.