TY - GEN
T1 - Learning preferences and self-regulation - Design of a learner-directed e-learning model
AU - Lee, Stella
AU - Barker, Trevor
AU - Kumar, Vive
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
KW - E-Learning
KW - instructional design
KW - learning design
KW - learning preferences
KW - learning theory
KW - self-regulated learning
UR - http://www.scopus.com/inward/record.url?scp=83755220977&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-27207-3_63
DO - 10.1007/978-3-642-27207-3_63
M3 - Published Conference contribution
AN - SCOPUS:83755220977
SN - 9783642272066
T3 - Communications in Computer and Information Science
SP - 579
EP - 589
BT - Software 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.
T2 - 2011 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
Y2 - 8 December 2011 through 10 December 2011
ER -