Learning preferences and self-regulation - Design of a learner-directed e-learning model

Stella Lee, Trevor Barker, Vive Kumar

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

2 Citations (Scopus)

Abstract

In e-learning, questions concerned how one can create course material that motivate and support students in guiding their own learning have attracted an increasing number of research interests ranging from adaptive learning systems design to personal learning environments and learning styles/preferences theories. 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] Research into adaptive e-learning systems has attempted to facilitate this process by providing recommendations, classifying learners into different preferred learning styles, or highlighting suggested learning paths[3]. However, system-initiated learning aid is just one way of supporting learners; a more holistic approach, we would argue, is to provide a simple, all-in-one interface that has a mix of delivery modes and self-regulation learning activities embedded in order to help individuals learn how to improve their learning process. 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.

Original languageEnglish
Title of host publicationSoftware Eng. Business Continuity and Education-Int. Conf ASEA, DRBC and EL 2011,Held as Part of the Future Generation Inf. Technology Conf. FGIT 2011, in Conjunction with GDC 2011,Proc.
Pages579-589
Number of pages11
DOIs
Publication statusPublished - 2011
Event2011 Int.Conf.on Advanced Software Eng.and Its Applications,ASEA 2011,Disaster Recovery and Business Continuity,DRBC 2011,and Education and Learning,EL 2011,Held as Part of the 3rd Int.Mega-Conf.on Future-Generation Inform.Tech.FGIT 2011 - Jeju Island, Korea, Republic of
Duration: 8 Dec. 201110 Dec. 2011

Publication series

NameCommunications in Computer and Information Science
Volume257 CCIS
ISSN (Print)1865-0929

Conference

Conference2011 Int.Conf.on Advanced Software Eng.and Its Applications,ASEA 2011,Disaster Recovery and Business Continuity,DRBC 2011,and Education and Learning,EL 2011,Held as Part of the 3rd Int.Mega-Conf.on Future-Generation Inform.Tech.FGIT 2011
Country/TerritoryKorea, Republic of
CityJeju Island
Period8/12/1110/12/11

Keywords

  • E-Learning
  • instructional design
  • learning design
  • learning preferences
  • learning theory
  • self-regulated learning

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