Deakin University
Browse

Strategies for accommodating individuals` styles and preferences in flexible learning programmes

journal contribution
posted on 2004-07-20, 00:00 authored by E Sadler-Smith, Peter Smith
There has been a considerable growth in the use of flexible methods of delivery for workplace learning and development. However, in designing programmes of flexible learning there is often the assumption that learners will exhibit uniformity in the ways in which they process and organise information (cognitive style), in their predispositions towards particular learning formats and media (instructional preferences) and the conscious actions they employ to deal with the demands of specific learning situations (learning strategies). In adopting such a stance one runs the risk of ignoring important aspects of individual differences in styles, preferences and strategies. Our purpose in this paper will be to: (i) consider some aspects of individual difference that are pertinent to the delivery of flexible learning in the workplace; (ii) identify some of the challenges that extant differences in styles and preferences between individuals may raise for instructional designers and learning facilitators; (iii) suggest ways in which models of flexible learning design and delivery may acknowledge and accommodate individual differences in styles and preferences through the use of an appropriate range of instructional design, learning and support strategies.

History

Journal

British journal of educational technology

Volume

35

Issue

4

Pagination

395 - 412

Publisher

Wiley-Blackwell Publishing Ltd.

Location

Oxford, England

ISSN

0007-1013

eISSN

1467-8535

Language

eng

Notes

Published Online: 20 Jul 2004

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2004, British Educational Communications and Technology Agency

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC