By discussing the measured impact of PLUS, this case study demonstrates that instead of replacing tutors and teachers, generative AI can supplement them to excel at a large scale. Specifically, this piece features Maerah Mahmood, a sophomore at Carnegie Mellon University, as she navigated using PLUS while teaching virtually at a school in California. With the help of PLUS’ human tutoring framework and AI-powered dashboard, Mahmood dramatically increased student engagement and improved their performance in a short period. Mahmood’s experience is a testament to the power of PLUS, and its ability to identify struggling students and help teachers initiate academic interventions and personal connections.
AI Tutoring Can Safely And Effectively Support Students: An Exploratory RCT In UK Classrooms
AI Tutoring Can Safely And Effectively Support Students: An Exploratory RCT In UK Classrooms LearnLM Team, Google & Eedi One-to-one tutoring is widely considered the gold standard for personalized education, yet it remainsprohibitively expensive to scale. To evaluate whether generative AI might help expand access to thisresource, we conducted an exploratory randomized controlled trial (RCT) […]
A Study To Evaluate The Effectiveness Of Eedi On Raising Attainment In Mathematics At KS3 (Year 7)
A Study To Evaluate The Effectiveness Of Eedi On Raising Attainment In Mathematics At KS3 (Year 7) Executive Summary This report evaluates the impact of Eedi, a digital mathematics platform, on raising maths attainment among Key Stage 3 students (Year 7). Eedi is an innovative EdTech platform offering over 60,000 diagnostic maths questions and engaging […]
Improving The Validity Of Automatically Generated Feedback Via Reinforcement Learning
Improving The Validity Of Automatically Generated Feedback Via Reinforcement Learning Abstract Automatically generating feedback via large language models (LLMs) in intelligent tutoring systems and online learning platforms has the potential to improve the learning outcomes of many students. However, both feedback generation and evaluation are challenging: feedback content has to be valid especially in subjects […]
Math Multiple Choice Question Generation Via Human-Large Language Model Collaboration
Math Multiple Choice Question Generation Via Human-Large Language Model Collaboration Abstract Multiple choice questions (MCQs) are a popular method for evaluating students’ knowledge due to their efficiency in administration and grading. Crafting high-quality math MCQs is a labor-intensive process that requires educators to formulate precise stems and plausible distractors. Recent advances in large language models […]