Intelligent Interfaces for Technology-Enhanced Learning

The chapter elaborates on intelligent interfaces for Technology-Enhanced Learning (TEL) systems, stressing the need to move from the traditional one-size-fits-all paradigm to adaptive and personalized one that takes into account various users’ personal characteristics. In order to enrich the process of knowledge acquisition and enhance the system ability to improve the learning experience, TEL systems need to adapt continuously to their users. This can be achieved by initiating and updating a relevant user model. Although acknowledging that differences among individuals have an effect on learning, as of now, user modelling has not yet happened as expected in addressing the variety of the learning environment in terms of personalization and individual user profiles. First, the chapter introduces TEL system with interaction style adaptation developed in order to support intelligent tutoring. The main objective of a research is both, to improve the learning experience and increase the system’ s intelligent behaviour. The system offers interaction adaptivity through the provision of suitable interaction styles rather then functionality. Different interface types along with adequate interaction styles are automatically switched basing on knowledge about the individual user and her/his interaction session, which is acquired dynamically during run-time. The user model developed to support interface adaptation strongly relies on user individual differences. In order to consider innovations in user sensitive research, the engaged user model should be enhanced with personal characteristics that affect learning and its outcomes. Second, an experimental study aiming to examine the affect of users' individual differences in technology-enhanced environment specifically of the ones which need to be accommodated through the system’ s intelligent behaviour is presented and evaluated. Personal user features assumed to affect learning process and learning outcomes are clearly identified and the methods how to measure them are determined. The study indicated that motivation to learn along with to expectations of learning in TEL environment significantly affects on users' learning achievement. Consequently, an appropriate user model should be engaged in order to accommodate users’ characteristics which have an impact on learning process, thus ensuring system accurate usage. The chapter presents how an employment of user sensitive research provides strong foundations for designing usable and effective TEL systems within responsive environments that motivate, engage and inspire learners of this emerging knowledge society for all.