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This book addresses key issues concerning visualization in the teaching and learning of science at any level in educational systems. It is the first book specifically on visualization in science education. The book draws on the insights from cognitive psychology, science, and education, by experts from five countries. It unites these with the practice of science education, particularly the ever-increasing use of computer-managed modelling packages.
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International Journal of Science Education
Vol. 30, No. 15, 15 December 2008, pp. 2091a "2096
ISSN 0950-0693 (print)/ISSN 1464-5289 (online)/08/152091a "06
DOI: 10.1080/09500690802065940
BOOK REVIEW
T1I0B2T0Jjrna090aSaoty.50myeEo1a080rlk0sDo@n-0h 8r0raR0_ r0ht6a&e2Aei/b9noe0v _c3dRnF09is3e ar85a(eF0wlapm0. r6ntJra0i7oiacfnn6rdi6ucs.t9a0r)i0ne/s.1s8sag4.l0i m6n2o40f -6S55c29i8e49n0 c(eo nEldinuec)ation Visualization in Science Education
John K. Gilbert (Ed.), 2005
Dordrecht, The Netherlands: Springer
346 pp., a, ¬49.95 (hbk)
ISBN 978-1-4020-3612-5
Visualisation is an area that has fascinated scientists and science educators alike, yet
it has proved problematic for research and study (Mathewson, 1999). It is only in
the past 10 years that science educators have had some success in understanding and
tackling the questions related to visualisation and its role in learning. Research in
this area has been eclectic in nature, often spurred by the entry of new visualisation
technologies into the classroom, and drawing on theoretical frameworks and analytical
tools developed by cognitive scientists as well as historians of science and science
educators. The studies have so far remained scattered over a range of disciplines and
several interdisciplinary journals and books. The present volume does an exemplary
service in bringing together the research in this new and emerging field, placing it
firmly on the radar of science educationists.
In science education, the closely related area of models and modelling has been of
interest for some time now. Visualization in Science Education is in fact the first in a
series of volumeson a ~Models and Modelling in Science Educationa (TM) edited by John
Gilbert and published by Springer. Several articles in this volume examine in detail
the relationship between a ~modelsa (TM) and a ~visualizationa (TM) in science education.
The book is organised into four sections that recall a classic sequence in education:
a ~The Significance of Visualization in Science Educationa (TM), a ~Developing the Skills
of Visualizationa (TM), a ~Integrating Visualization into Curricula in the Sciencesa (TM), and
a ~Assessing the Development of Visualization Skillsa (TM). John Gilberta (TM)s introductory
chapter brings out the relationship between models, both a ~in the worlda (TM) and a ~in the
minda (TM), and visualisations, which also could be both external and internal. Gilbert
sees visualisation as a metacognitive skill, involving the monitoring and control of an
image being learnt, knowing how to rehearse and retain it in memory, retrieving the
appropriate image when necessary, and, finally, amending and transforming the
image according to the reasoning demanded by the task at hand. This chapter gives
several examples to bring out the role of visualisation in student learning and in
classroom practice.
Chapter 2 by Barbara Tversky looks at the many ways in which external depictions
convey information. Tversky is a psychologist who has researched visualisation
in relatively complex domains. She therefore easily moves beyond the common
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2092 Book Review
psychological paradigm of visuals as percepts, to consider visuals that could be
related with mental models. Herexamples are drawn from route maps, mechanical
diagrams, and animations used in education. Tversky suggests some cognitive
design principles for effective visualisations, both static diagrams and animations.
In Chapter 3 David Rapp draws on work in cognitive and educational psychology
to outline the characteristics of mental models. He looks at the evidence for mental
models coming from the domains of text comprehension, logical reasoning, and
understanding of mechanical systems. Rapp then goes on to examine some qualities
of educational situations that influence learning with mental models. Identifying
a ~cognitive engagementa (TM) and a ~interactivitya (TM) as two supporting factors, Rapp points out
the mixed evidence for effectiveness of a ~multimedia learninga (TM). Thus visualisations,
used here in the sense of a ~novel visual presentations of dataa (TM), are shown to be not
consistently helpful in learning, or in building mental models.
In Chapter 4 Michael Briggs and George Bodner use a phenomenographic
approach to propose a theoretical model of molecular visualisation. Drawing on data
from an exploratory study with college undergraduates the authors describe the role
of visualisation in understanding molecular structures, arguing that this process
leads to the construction of a mental model. Briggs and Bodner see visualisation as
an operation that brings about a one-to-one correspondence between a mental
representation and its referent, serving therefore as the dynamic component of
model-based reasoning.
Chapter 5 by Janice Gobert focuses on external visualisations and their role in
supporting learning. Gobertreviews the literature on the processing of textual and
graphic information in both static and dynamic form, finding that expertsa (TM) use of
visualisations is highly sensitive to domain and task contexts. Although Gobert holds
that mental visualisations are not tractable to empirical research, she does use the
framework of model-based teaching and learning to examine studentsa (TM) mental
models as they work in a technology-supported environment. She describes two
projects developed to enhance studentsa (TM) model-based reasoning: a ~Making Thinking
Visiblea (TM) and a ~Modeling across the Curriculuma (TM). a ~Making Thinking Visiblea (TM) used
WISE, a web-based science learning environment that allowed students to access
real-time data (related to plate tectonics) through the Web and also to interact with
peers from geographically distinct locations. In a ~Modeling across the Curriculuma (TM),
Pedagogicaa"[ was used to track studentsa (TM) interactions with models (from genetics,
classical mechanics, and chemistry) and to gain an index of their reasoning and
modelling skills. Studentsa (TM) domain knowledge as well as their understanding of the
nature of modelling was found to be enhanced.
Section B, consisting of four chapters, is concerned with ways of developing the
skills of visualisation. Chapter 6 by Mike Steiff, Robert Bateman, and David Uttal
critically examines the role of computer-based visualisation tools in the science classroom.
The authors review both content-specific tools and general modelling environments.
They note that research in the effectiveness of these tools has suffered
from limitations of design and occasional mixed results, while both research and
development of visualisation strategies have lacked a clear theoretical perspective on
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Book Review 2093
why the particular tools are likely or unlikely to help learning. Steiff et al. offer some
cognitively grounded principles for the design of effective visualisation tools in
chemistry, investigation of their role and efficacy, and development of suitable pedagogies
for their use. Visualisation tools should support spatial cognition by helping
students comprehend spatial relationships as well as manipulate molecules to solve a
given problem.
In Chapter 7 Robert Kozma and Joel Russell review the research related to developing
representational competence in students of chemistry. They consider the
chemical curriculum in terms of two important goals: studentsa (TM) acquisition of chemical
concepts and principles, and their participation in the investigative practices of
chemistrya "a ~students becoming chemistsa (TM). These goals pertain to cognitive or learning
theory and to situative theory respectively. Beginning with the latter, the authors
look at the everyday practices of chemists during scientific investigations and
compare them with those of students, showing that competence in using visual
representations is a feature distinguishing the two practices. They then review the
literature on learning theories applied to multimedia learning and consider their
implications for investigative work, particularly in defining representational practices
in chemistry. The chapter concludes with an extensive review of research pertaining
to chemical visualisation technologies of two major kinds: molecular modelling, and
computer simulations and animations of dynamic chemical processes.
Chapter 8, by Galit Botzer and Miriam Reiner, recalls the practice of physics in
history, focusing on the specific case of electromagnetic theory. Mental models and
visual imagery are believed to have played a major role in the work of Galileo,
Newton, Faraday, Maxwell, and Einstein. Botzer and Reiner begin with a scheme of
classification derived by Arthur Miller from the history of physics, in which modes
of representation are seen as sensory based, pure imaginary, or formalism based.
They look at case studies of ninth-grade students collaboratively exploring magnetic
phenomena, and find that the historically derived classification works well with
studentsa "when nuanced with cognitive considerations like projections of former
experiences to explain a new situation, and transformations of mental images.
Implications for physics learning are suggested in terms of conceptual understanding,
communication and tools for research and evaluation.
In Chapter 9, John Clement, Aletta Zietsman, and James Monaghan take on the
challenge of studying mental imagery in science learning. They review three prior
studies in elementary mechanics with the aim to develop observable indicators for the
presence ofimager
Visualization, meaning both the perception of an object that is seen or touched and the mental imagery that is the product of that perception, is believed to be a major strategy in all thought. It is particularly important in science, which seeks causal explanations for phenomena in the world-as-experienced. Visualization must therefore play a major role in science education. This book addresses key issues concerning visualization in the teaching and learning of science at any level in educational systems.
‘Visualization in Science Education’ draws on the insights from cognitive psychology, science, and education, by experts from Australia, Israel, Slovenia, UK, and USA. It unites these with the practice of science education, particularly the ever-increasing use of computer-managed modelling packages, especially in chemistry. The first section explores the significance and intellectual standing of visualization. The second section shows how the skills of visualization have been developed practically in science education. This is followed by accounts of how the educational value of visualization has been integrated into university courses in physics, genomics, and geology. The fourth section documents experimental work on the classroom assessment of visualization. An endpiece summarises some of the research and development needed if the contribution of this set of universal skills is to be fully exploited at all levels and in all science subjects.
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