Harfield, Antony (2007) Empirical modelling as a new paradigm for educational technology. PhD thesis, University of Warwick.

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Abstract

Educational technology has yet to deliver the benefits or successes that were expected in educational practice, especially in relation to issues other than the communication and delivery of teaching materials. Evidence suggests that these difficulties stem from the mismatch between formalised virtual learning environments and everyday sensemaking and between the rich potential for enhanced learning afforded by new technology and the constraints of old-style educational practice. In addressing this mismatch, some commentators suggest that the primary need is for a new culture of educational practice-and even that such a culture is already emerging, and others identify the need for a new paradigm for educational technology. The aim of this thesis is to explore the potential for a new paradigm for educational technology based on the principles and tools of Empirical Modelling (see http://dcs.warwick.ac.uk/modelling). The thesis builds upon previous research on Empirical Modelling as a constructionist approach to learning, and in particular Roe's doctoral thesis 'Computers for learning: an Empirical Modelling perspective'. Roe's treatment of Empirical Modelling can be viewed as generalising the use of spreadsheets for learning through applying 'programming by dependency' within the framework of existing educational practice. In contrast, this thesis is concerned at a more fundamental level with the contribution that Empirical Modelling can make to technology enhanced learning that may lead to new educational practices. In particular, it identifies eight significant characteristics of learning that are well-matched to Empirical Modelling activity, and associates these with experimental, flexible and meaningful strands in learning. The credentials of Empirical Modelling as a potential new foundation for educational technology are enhanced by demonstrating that Empirical Modelling is radically different from traditional software development and use. It provides a methodology for modelling with dependency that is more closely related to the use of spreadsheets for learning. The thesis elaborates on the relationship between Empirical Modelling and learning in a variety of different contexts, ways and applications. Three examples drawn from computer science higher education are explored to emphasise the experimental, flexible and meaningful characteristics of Empirical Modelling. This discussion of Empirical Modelling in a specific educational context is complemented by an investigation of its relevance to learning in a wider context, with reference to a broad range of subjects, to specific issues in language learning, and to the topics of lifelong learning and collaborative learning. Although the application of Empirical Modelling for learning is as yet too immature for large scale empirical studies, its potential is evaluated using informal empirical evidence arising from Empirical Modelling practice at Warwick. The sources for this evaluation are well-established teaching activities relating to Empirical Modelling in Computer Science at the University of 'Warwick, comprising an introductory module and a number of final year undergraduate projects. The thesis concludes by considering the extent to which Empirical Modelling can go beyond the support for constructionism envisaged by Roe, to address the broader agenda of supporting constructivist learning using computers. To this end, a close relationship between Empirical Modelling and a vision of constructivism recently set out by Bruno Latour in his paper 'The Promises of Constructivism' is demonstrated.

Item Type:	Thesis or Dissertation (PhD)
Subjects:	L Education > LB Theory and practice of education
Library of Congress Subject Headings (LCSH):	Empiricism, Educational technology, Virtual reality in education, Constructivism (Education)
Official Date:	2007
Dates:	Date Event 2007 Submitted
Institution:	University of Warwick
Theses Department:	Department of Computer Science
Thesis Type:	PhD
Publication Status:	Unpublished
Supervisor(s)/Advisor:	Beynon, Meurig
Format of File:	pdf
Extent:	267 leaves : ill., charts
Language:	eng

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