Personalized Course Delivery: An Empirical Analysis of the Feasibility of Adapting Distance Learning Courses to Individual Students' Learning Preferences

Personalization will be a key element in the future of executive education. Personalization is based on a match between student characteristics (user model) and didactic treatments (teaching model). This article distinguishes two matching strategies: an educational institution can deliver on demand, or can anticipate the demand and offer students the most appropriate treatment based on prior knowledge of each student's characteristics. Anticipating demand is the most challenging strategy. Its validity depends on the independence of the students' characteristics: in the case of interdependency, prediction of an optimal match is virtually impossible. The assumption of independence was investigated for a subset of students' characteristics – that of learning preferences. A conceptual model, consisting of four dimensions, was used to construct 16 combinations of didactic treatments. We found evidence in favour of a high degree of interdependency among the dimensions of the conceptual model. With these results in mind, students must be allowed to choose for themselves whether more didactic treatments should be made available.