Learning with multiple representations
Author(s)
Bibliographic Information
Learning with multiple representations
（Advances in learning and instruction series）
Pergamon, 1998
1st ed.
- : hc
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Note
Includes bibliographical references (p. 335-357) and index
Description and Table of Contents
Description
The book is written in the framework of a European collaborative research programme, Learning in Humans and Machines, funded by the European Science Foundation. The book's purpose is to collect papers on learning declarative knowledge and problem solving skills that involve multiple representations such as verbal, graphical and mathematical representations, knowledge at different levels of abstraction (e.g. qualitative and quantitative, specific cases or general models). One of the goals of the research programme is to demonstrate existing and to initiate new collaboration between educational sciences, psychology and machine learning. The first aim of this book is to give an overview of the state of the art of the topic of learning involving different representations in the form of overview chapters. The book covers approaches to this topic from different perspectives: educational, cognitive modelling and machine learning. It includes both theoretical analyses and studies in application contexts. The second aim of the book is to present current research on these topics and to articulate research issues for future research. This is done in the form of a collection of research papers and two reflective chapters.
Table of Contents
Introduction (M.W. van Someren et al.). Multiple Representations in Learning Concepts from Physics and Mathematics. Acquiring knowledge in science and mathematics: the use of multiple representations in technology-based learning environments (T. de Jong et al.). Reasoning with multiple representations when acquiring the particulate model of matter (M. Rohr, P. Reinmann). How beginning students use graphs of motion (E. Scanlon). Toward decision support for multiple representations in teaching early logic (M. Dobson). The role of prior qualitative knowledge in inductive learning (M.W. van Someren, H. Tabbers). Analysing the costs and benefits of multi-representational learning environments (S.E. Ainsworth et al.). Problem Solving and Learning with Multiple Representations. Problem solving with multiple representations by multiple and single agents: an analysis of the issues involved (H.P.A. Boshuizen, H.J.M. (Tabachneck-) Schiff). Accidentology: an example of problem solving by multiple agents with multiple representations (L. Alpay et al.). Perspective-taking between medical doctors and nurses: a study of multiple representations of different experts with common tasks (R. Bromme, M. Nuckles). One person, multiple representations: an analysis of a simple, realistic multiple representation learning task (H.J.M. (Tabachneck-) Schiff, H.A. Simon). Using multiple representations in medicine: how students struggle with them (H.P.A. Boshuizen, M.W.J. van de Wiel). Competence-related differences in problem representations: a study in physics problem solving (E.R. Savelsbergh et al.). A utility-based approach to speedup learning with multiple representations (M.W. van Someren et al.). General Issues and Implications for Education. Multiple representations and their implications for learning (A. Lesgold). Representation and conceptualisation in educational communication (K. Stenning).
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