Learning Preferences and Self-Regulation – Design of a Learner-Directed E-Learning Model Stella Lee 1 , Dr. Trevor Barker 2 , Vive Kumar 3 1 Computer Science Department, University of Hertfordshire, Hatfield, UK; Golder Associates, Inc., Calgary, Canada 2 Computer Science Department, University of Hertfordshire, Hatfield, UK 3 School of Computing & Information Systems, Athabasca University, Edmonton, Canada stella_lee@golder.com t.1.barker@herts.ac.uk vive@athabascau.ca Abstract. The main challenge of learning online remains how learners can accurately direct and regulate their own learning without the presence of tutors to provide instant feedback. Furthermore, learning a complex topic structured in various media and modes of delivery require learners to make certain instructional decisions concerning what to learn and how to go about their learning. In other words, learning requires learners to self-regulate their own learning[1]. Very often, learners have difficulty self-directing when topics are complex and unfamiliar. It is not always clear to the learners if their instructional decisions are optimal.[2] The aim of this research is to explore how learners can self-direct and self-regulate their online learning both in terms of domain knowledge and meta knowledge in the subject of computer science. Two educational theories: experiential learning theory (ELT) and self-regulated learning (SRL) theory are used as the underpinning instructional design principle. To assess the usefulness of this approach, we plan to measure: changes in domain-knowledge; changes in meta-knowledge; learner satisfaction; perceived controllability; and system usability. In sum, this paper describes the research work being done on the initial development of the e- learning model, instructional design framework, research design as well as issues relating to the implementation of such approach. Keywords: learning theory, learning preferences, self-regulated learning, E- Learning, instructional design, learning design 1 Introduction In e-learning, questions concerned how one can create online material that support and motivate students in guiding their own learning and make meaningful instructional decisions have attracted an increasing number of research interests ranging from areas in adaptive learning systems design to personal learning environments and learning styles/preferences theories. The main challenge of learning online remains how learners can self-regulate their own learning without the presence