Using Adaptive Learning Technologies to Personalize Instruction: The Impact of Interest-Based Scenarios on Performance in Algebra

Context personalization refers to the idea of adapting learning activities based on students’ individual interests and experiences. While new learning technologies make such innovations feasible, little research supports whether and how context personalization may mediate important learner outcomes, especially in mathematics. Here, we present results of a large (N = 145) randomized control study of Algebra I students receiving context personalization within an intelligent tutoring system, Cognitive Tutor Algebra. Results suggest that personalization allowed students to form more accurate and meaningful situation models of story problems, facilitating algebraic symbolization. Interest-based interventions may allow learners to make critical connections between personally relevant scenarios and abstract representational systems. Adaptive learning environments that personalize instruction by leveraging interests are an important future direction for advanced learning technologies.