Students will collaboratively develop criteria to detect fake news, apply them to real-world articles, and use ChatGPT to assess its ability to evaluate information reliability. They will then compare AI-generated analyses with human judgment, discussing effectiveness, biases, and best practices for using AI in fact-checking.
Pre-requisites
- Basic understanding of media sources and journalistic standards.
- Familiarity with disinformation concepts (can be introduced via reading materials).
- Ability to navigate ChatGPT and input prompts.
- Experience with group discussions and critical analysis.
Explanation of activity
By the end of this activity, students will be able to:
- Identify key criteria for recognizing fake news based on deceptive content and persuasive techniques.
- Analyze real-world news articles and evaluate their credibility using ChatGPT.
- Compare AI-based analysis with human critical thinking in detecting fake news.
- Discuss limitations and best practices for using AI in fact-checking.
Activity Breakdown
Phase 1: Establishing Fake News Identification Criteria (45 minutes)
Step 1: Group Brainstorming (15 minutes)
- Discuss the question:
“How do you determine if a news source is credible or fake?” - Consider elements such as:
- Source reliability (author credibility, domain reputation)
- Fact-based reporting vs. opinion-based narratives
- Emotional manipulation (fear, outrage, exaggeration)
- Clickbait headlines and misleading images
- Use of anonymous sources or unverifiable claims
Step 2: Creating a Criteria List (10 minutes)
- Each group compiles a list of fake news detection criteria.
- Example template:
| Criterion | Description | Example |
| Source Credibility | Check if the news comes from a reputable organization | “Reported by BBC vs. an unknown blog” |
| Sensationalism | Look for exaggerated claims or emotional triggers | “Shocking cure for all diseases revealed!” |
Step 3: Class Sharing & Feedback (10 minutes)
- Groups post their criteria list on a class forum.
- Students review and refine based on peer feedback.
Phase 2: Applying Fake News Criteria with ChatGPT (45 minutes)
Step 1: Testing ChatGPT’s Fact-Checking Capabilities (20 minutes)
- Each group selects a real news article (from given links or recent viral content).
- They ask ChatGPT to analyze the article using their established fake news criteria.
- Example prompts for ChatGPT:
- “Analyze this article and assess if it contains any elements of fake news.”
- “Does this source seem credible? Justify your answer.”
Step 2: Comparing AI vs. Human Analysis (15 minutes)
- Groups compare their own evaluation with ChatGPT’s response.
- Key discussion points:
- What criteria did ChatGPT use?
- Did ChatGPT miss any deceptive techniques?
- How reliable was its analysis?
- What criteria did ChatGPT use?
Step 3: Uploading Findings (10 minutes)
- Groups upload a summary of their AI vs. human comparison in the forum.
Phase 3: Evaluating ChatGPT’s Strengths & Limitations (30 minutes)
Step 1: Effectiveness Discussion (15 minutes)
- Class discussion:
- “Is AI effective in detecting fake news?”
- “How can prompts improve ChatGPT’s accuracy?”
- “Is AI effective in detecting fake news?”
Step 2: AI Reliability & Best Practices (15 minutes)
- Reflect on AI’s potential biases and limitations:
- Can AI fully replace human critical thinking?
- What strategies improve AI’s fact-checking performance?
- What are the risks of over-reliance on AI for news evaluation?
- Can AI fully replace human critical thinking?
- Students post responses on the forum and discuss, agreeing or disagreeing with reasoning.
Teacher materials
- Slides on fake news detection and AI fact-checking
- Handout: Pre-made template for evaluating sources.
- Sample news articles (both fake and legitimate).
- List with criteria for evaluating the reliability and credibility of sources
- Luo, M., Hancock, J. T., & Markowitz, D. M. (2023). Combating disinformation or reinforcing cognitive bias: Effect of news labels on fake news consumption. Media and Communication, 11(2), 123-134. https://www.ssoar.info/ssoar/bitstream/handle/document/88194/ssoar-mediacomm-2023-2-luo_et_al-Combating_Disinformation_or_Reinforcing_Cognitive.pdf;jsessionid=8EC5BEA0A8752BB594B2E10334EE3108?sequence=1
Student Materials
- Reading:
- EU DisinfoLab’s Disinformation Glossary
- Worksheet:
- Fake news detection criteria template.
- AI vs. human evaluation reflection questions.
Assessment & Evaluation
- Fake News Criteria (30%) – Depth and clarity of detection framework.
- ChatGPT Analysis (30%) – Quality of AI vs. human comparison.
- Discussion Participation (20%) – Engagement in class discussions and forums.
- Reflection & Justification (20%) – Thoughtful evaluation of AI’s role in fake news detection.
Modulations
- Alternative Format: Instead of a written report, students create a video explaining their findings.
- Advanced Challenge: Compare ChatGPT’s responses with another AI tool (e.g., Google Bard) for fact-checking.
- Real-World Application: Students apply their criteria to analyze a trending news story and debunk misinformation online.
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