We investigated the possibility of predicting students’ engagement and learning gains during a tutoring session from trait measures of motivation, engagement, burnout, cognitive ability, prior knowledge, and task related measures. Participants completed a multiple choice pretest, a learning session, a posttest, and a battery of individual differences tests and questionnaires. Multiple regression and exploratory factor analyses indicated that the individual differences measures yielded medium sized effects at predicting learning gains as well as engagement levels that were self-reported during the tutorial session. In general, self-reported interest in the task and confidence in learning from a computer tutor coupled with working memory capacity and attentional abilities were the major predictors of both engagement and learning.