University of Hertfordshire

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

Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

Standard

Learning preferences and self-regulation : Design of a learner-directed e-learning model. / Lee, Stella; Barker, T.; Kumar, V.

Software Engineering, Business Continuity and Education. ed. / Tai-hoon Kim; Haeng-kon Kim; Kyung Jung Kim; Hojjat Adeli; Heau-jo Kang; Akingbehin Kiumi. Springer, 2011. p. 579-589 (Communications in Computer and Information Science; Vol. 257).

Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

Harvard

Lee, S, Barker, T & Kumar, V 2011, Learning preferences and self-regulation: Design of a learner-directed e-learning model. in T Kim, H Kim, KJ Kim, H Adeli, H Kang & A Kiumi (eds), Software Engineering, Business Continuity and Education. Communications in Computer and Information Science, vol. 257, Springer, pp. 579-589. https://doi.org/10.1007/978-3-642-27207-3_63

APA

Lee, S., Barker, T., & Kumar, V. (2011). Learning preferences and self-regulation: Design of a learner-directed e-learning model. In T. Kim, H. Kim, K. J. Kim, H. Adeli, H. Kang, & A. Kiumi (Eds.), Software Engineering, Business Continuity and Education (pp. 579-589). (Communications in Computer and Information Science; Vol. 257). Springer. https://doi.org/10.1007/978-3-642-27207-3_63

Vancouver

Lee S, Barker T, Kumar V. Learning preferences and self-regulation: Design of a learner-directed e-learning model. In Kim T, Kim H, Kim KJ, Adeli H, Kang H, Kiumi A, editors, Software Engineering, Business Continuity and Education. Springer. 2011. p. 579-589. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-642-27207-3_63

Author

Lee, Stella ; Barker, T. ; Kumar, V. / Learning preferences and self-regulation : Design of a learner-directed e-learning model. Software Engineering, Business Continuity and Education. editor / Tai-hoon Kim ; Haeng-kon Kim ; Kyung Jung Kim ; Hojjat Adeli ; Heau-jo Kang ; Akingbehin Kiumi. Springer, 2011. pp. 579-589 (Communications in Computer and Information Science).

Bibtex

@inbook{317d3b189fc24b56b2c78ed5f8266af8,
title = "Learning preferences and self-regulation: Design of a learner-directed e-learning model",
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.",
author = "Stella Lee and T. Barker and V. Kumar",
note = "International Conferences ASEA, DRBC and EL 2011, Held as Part of the Future Generation Information Technology Conference, FGIT 2011, in Conjunction with GDC 2011, Jeju Island, Korea, December 8-10, 2011. Proceedings",
year = "2011",
doi = "10.1007/978-3-642-27207-3_63",
language = "English",
isbn = "978-3-642-27206-6",
series = "Communications in Computer and Information Science",
publisher = "Springer",
pages = "579--589",
editor = "Tai-hoon Kim and Haeng-kon Kim and Kim, {Kyung Jung} and Hojjat Adeli and Heau-jo Kang and Akingbehin Kiumi",
booktitle = "Software Engineering, Business Continuity and Education",

}

RIS

TY - CHAP

T1 - Learning preferences and self-regulation

T2 - Design of a learner-directed e-learning model

AU - Lee, Stella

AU - Barker, T.

AU - Kumar, V.

N1 - International Conferences ASEA, DRBC and EL 2011, Held as Part of the Future Generation Information Technology Conference, FGIT 2011, in Conjunction with GDC 2011, Jeju Island, Korea, December 8-10, 2011. Proceedings

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.

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 - Other chapter contribution

AN - SCOPUS:83755220977

SN - 978-3-642-27206-6

T3 - Communications in Computer and Information Science

SP - 579

EP - 589

BT - Software Engineering, Business Continuity and Education

A2 - Kim, Tai-hoon

A2 - Kim, Haeng-kon

A2 - Kim, Kyung Jung

A2 - Adeli, Hojjat

A2 - Kang, Heau-jo

A2 - Kiumi, Akingbehin

PB - Springer

ER -