Applied research papers from our ongoing work in AI-powered personalized education. All studies are conducted in active school settings.
Compares AI-customized vs. generic quizzes with 20 students using an AB/BA crossover design. Measures weekly affect (PANAS-C + Smileyometer) alongside accuracy and time-on-task, analyzed via mixed-effects models. Investigates whether personalization of question content meaningfully shifts how students feel about quizzes — not only how they perform on them.
Compares student engagement, affect, and free-response sentiment when learners are permitted to skip lessons in subjects they have already demonstrated mastery of, versus proceeding through full sequencing. Twenty students complete an AB/BA crossover. Measures weekly affect (PANAS-C + Smileyometer), behavioral engagement (time-on-task, voluntary practice, lesson-completion rate), and NLP-based semantic and sentiment analysis of weekly student journal entries; analyzed via mixed-effects models.