Data4Good Case Challenge

The Data4Good Competition (see https://www.datacamp.com/event/data4goodcompetition) is a national event challenging undergraduate and master's students to tackle a real-world case study using data analysis, artificial intelligence, and critical thinking. Participants can compete for prize money while gaining valuable skills through free training and certification programs. There will be winners and runner-ups for each US region. Regional winners will be invited to present their case challenge solution in person at The Johns Hopkins University. Artificial Intelligence (AI) is rapidly transforming education by providing students with instant access to information and adaptive learning tools. Still, it also introduces significant risks, such as the spread of misinformation and fabricated content. Research indicates that large language models (LLMs) often confidently generate factually incorrect or hallucinated responses, which can mislead learners and erode trust in digital learning platforms. The 4th Annual Data4Good Competition challenges participants to develop innovative analytics solutions to detect and improve factuality in AI-generated educational content, ensuring that AI advances knowledge rather than confusion. Use the training set to explore, model, and classify AI-generated answers as factual, contradiction, or irrelevant. Then generate predictions for the held-out test set and document your full approach. Scoring notes: Your submission will be scored using a custom weighted confusion matrix to account for cost-based priorities. Each class receives an equal weighting to calculate your overall prediction performance. Thus, factual prediction score counts for 33.3%, contradiction classification for 33.3%, and irrelevant for 33.3%. Your classification evaluation on the test set will be ranked among all teams in the c