Personalization for specific users: Designing decision support systems to support stimulating learning environments

Abstract

Creating adaptive systems becomes increasingly attractive in the context of specific groups of users, such as agricultural users. This group of users seems to differ with respect to information processing, knowledge management and learning styles. In this work we aim to offer directions toward increasing decision support systems usability, by tailoring toward user learning styles. The results show that decision support systems need to be redesigned toward providing agricultural users with a more efficient time management and study environment, and facilitating group interaction. © 2009 Springer Berlin Heidelberg.