Models and Modeling in Science Education – serie

“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.

External representations (pictures, diagrams, graphs, concrete models) have always been valuable tools for the science teacher. The formation of personal, internal, representations – visualizations – from them plays a key role in all learning, especially in that of science. The use of personal computers and sophisticated software has expanded into the areas of simulation, virtual reality, and animation, and students now engage in the creation of models, a key aspect of scientific methodology. Several academic disciplines underlie these developments, yet act independently of each other, to the detriment of an attainment of what is possible. This book brings together the insights of practicing scientists, science education researchers, computer specialists, and cognitive scientists, to produce a coherent overview. It links presentations about the cognitive theory of representation and visualization, its implications for science curriculum design, and for learning and teaching in classrooms and laboratories.

“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.

This book describes new, model based teaching methods for science instruction. It presents research that describes these new methods in a very diverse group of settings: middle school biology, high school physics, and college chemistry classrooms. Mental models in these areas such as understanding the structure of the lungs or cells, molecular structures and reaction mechanisms in chemistry, or causes of current flow in electricity are notoriously difficult for many students to learn. Yet these lie at the core of conceptual understanding in these areas. The studies focus on a variety of teaching strategies such as discrepant questioning, analogies, animations, model competition, and hands on activities. Five different levels of organization for teaching strategies are described, from those operating over months (design of the sequence of units in a curriculum) to those operating over minutes (teaching tactics for guiding discussion minute by minute).

Chemistry seeks to provide qualitative and quantitative explanations for the observed behaviour of elements and their compounds. Doing so involves making use of three types of representation: the macro (the empirical properties of substances); the sub-micro (the natures of the entities giving rise to those properties); and the symbolic (the number of entities involved in any changes that take place). Although understanding this triplet relationship is a key aspect of chemical education, there is considerable evidence that students find great difficulty in achieving mastery of the ideas involved. In bringing together the work of leading chemistry educators who are researching the triplet relationship at the secondary and university levels, the book discusses the learning involved, the problems that students encounter, and successful approaches to teaching. Based on the reported research, the editors argue for a coherent model for understanding the triplet relationship in chemical education.

This book covers the current state of thinking and what it means to have a framework of representational competence and how such theory can be used to shape our understanding of the use of representations in science education, assessment, and instruction. Currently, there is not a consensus in science education regarding representational competence as a unified theoretical framework. There are multiple theories of representational competence in the literature that use differing perspectives on what competence means and entails. Furthermore, dependent largely on the discipline, language discrepancies cause a potential barrier for merging ideas and pushing forward in this area. While a single unified theory may not be a realistic goal, there needs to be strides taken toward working as a unified research community to better investigate and interpret representational competence.  An objective of this book is to initiate thinking about a representational competence theoretical framework across science educators, learning scientists, practitioners and scientists. As such, we have divided the chapters into three major themes to help push our thinking forward: presenting current thinking about representational competence in science education, assessing representational competence within learners, and using our understandings to structure instruction.

The book takes a closer look at the theoretical and empirical basis for a competence-based view of models and modeling in science learning and science education research. Current thinking about models and modeling is reflected. The focus lies on the development of modeling competence in science education, and on philosophical aspects, including perspectives on nature of science. The book explores, interprets, and discusses models and modeling from the perspective of different theoretical frameworks and empirical results. The extent to which these frameworks can be integrated into a competence-based approach for science education is discussed. In addition, the book provides practical guidance by outlining evidence-based approaches to diagnosing and promoting modeling competence. The aim is to convey a strong understanding of models and modeling for professions such as teacher educators, science education researchers, teachers, and scientists. Different methods for the diagnosis and assessment of modeling competence are presented and discussed with regard to their potential and limitations. The book provides evidence-based ideas about how teachers can be supported in teaching with models and modeling implementing a competence-based approach and, thus, how students can develop their modeling competence. Based on the findings, research challenges for the future are identified.

The book takes a closer look at the theoretical and empirical basis for a competence-based view of models and modeling in science learning and science education research. Current thinking about models and modeling is reflected. The focus lies on the development of modeling competence in science education, and on philosophical aspects, including perspectives on nature of science. The book explores, interprets, and discusses models and modeling from the perspective of different theoretical frameworks and empirical results. The extent to which these frameworks can be integrated into a competence-based approach for science education is discussed. In addition, the book provides practical guidance by outlining evidence-based approaches to diagnosing and promoting modeling competence. The aim is to convey a strong understanding of models and modeling for professions such as teacher educators, science education researchers, teachers, and scientists. Different methods for the diagnosis and assessment of modeling competence are presented and discussed with regard to their potential and limitations. The book provides evidence-based ideas about how teachers can be supported in teaching with models and modeling implementing a competence-based approach and, thus, how students can develop their modeling competence. Based on the findings, research challenges for the future are identified.

This book examines the diverse use of visual representations by teachers in the science classroom. It contains unique pedagogies related to the use of visualization, presents original curriculum materials as well as explores future possibilities.The book begins by looking at the significance of visual representations in the teaching of science. It then goes on to detail two recent innovations in the field: simulations and slowmation, a process of explicit visualization. It also evaluates the way teachers have used different diagrams to illustrate concepts in biology and chemistry.Next, the book explores the use of visual representations in culturally diverse classrooms, including the implication of culture for teachers’ use of representations, the crucial importance of language in the design and use of visualizations and visualizations in popular books about chemistry. It also shows the place of visualizations in the growing use of informal, self-directed science education.Overall, the book concludes that if the potential of visualizations in science education is to be realized in the future, the subject must be included in both pre-service and in-service teacher education. It explores ways to develop science teachers’ representational competence and details the impact that this will have on their teaching.The worldwide trend towards providing science education for all, coupled with the increased availability of color printing, access to personal computers and projection facilities, has lead to a more extensive and diverse use of visual representations in the classroom. This book offers unique insights into the relationship between visual representations and science education, making it an ideal resource for educators as well as researchers in science education, visualization and pedagogy.

This book argues that modelling should be a component of all school curricula that aspire to provide ‘authentic science education for all’. The literature on modelling is reviewed and a ‘model of modelling’ is proposed. The conditions for the successful implementation of the ‘model of modelling’ in classrooms are explored and illustrated from practical experience. The roles of argumentation, visualisation, and analogical reasoning, in successful modelling-based teaching are reviewed. The contribution of such teaching to both the learning of key scientific concepts and an understanding of the nature of science are established. Approaches to the design of curricula that facilitate the progressive grasp of the knowledge and skills entailed in modelling are outlined. Recognising that the approach will both represent a substantial change from the ‘content-transmission’ approach to science teaching and be in accordance with current best-practice in science education, the design of suitable approaches to teacher education are discussed. Finally, the challenges that modelling-based education pose to science education researchers, advanced students of science education and curriculum design, teacher educators, public examiners, and textbook designers, are all outlined.

This book examines the diverse use of visual representations by teachers in the science classroom. It contains unique pedagogies related to the use of visualization, presents original curriculum materials as well as explores future possibilities.The book begins by looking at the significance of visual representations in the teaching of science. It then goes on to detail two recent innovations in the field: simulations and slowmation, a process of explicit visualization. It also evaluates the way teachers have used different diagrams to illustrate concepts in biology and chemistry.Next, the book explores the use of visual representations in culturally diverse classrooms, including the implication of culture for teachers’ use of representations, the crucial importance of language in the design and use of visualizations and visualizations in popular books about chemistry. It also shows the place of visualizations in the growing use of informal, self-directed science education.Overall, the book concludes that if the potential of visualizations in science education is to be realized in the future, the subject must be included in both pre-service and in-service teacher education. It explores ways to develop science teachers’ representational competence and details the impact that this will have on their teaching.The worldwide trend towards providing science education for all, coupled with the increased availability of color printing, access to personal computers and projection facilities, has lead to a more extensive and diverse use of visual representations in the classroom. This book offers unique insights into the relationship between visual representations and science education, making it an ideal resource for educators as well as researchers in science education, visualization and pedagogy.

This volume is important because despite various external representations, such as analogies, metaphors, and visualizations being commonly used by physics teachers, educators and researchers, the notion of using the pedagogical functions of multiple representations to support teaching and learning is still a gap in physics education. The research presented in the three sections of the book is introduced by descriptions of various psychological theories that are applied in different ways for designing physics teaching and learning in classroom settings. The following chapters of the book illustrate teaching and learning with respect to applying specific physics multiple representations in different levels of the education system and in different physics topics using analogies and models, different modes, and in reasoning and representational competence. When multiple representations are used in physics for teaching, the expectation is that they should be successful. To ensure this is the case, the implementation of representations should consider design principles for using multiple representations. Investigations regarding their effect on classroom communication as well as on the learning results in all levels of schooling and for different topics of physics are reported. The book is intended for physics educators and their students at universities and for physics teachers in schools to apply multiple representations in physics in a productive way.

This book argues that modelling should be a component of all school curricula that aspire to provide ‘authentic science education for all’. The literature on modelling is reviewed and a ‘model of modelling’ is proposed. The conditions for the successful implementation of the ‘model of modelling’ in classrooms are explored and illustrated from practical experience. The roles of argumentation, visualisation, and analogical reasoning, in successful modelling-based teaching are reviewed. The contribution of such teaching to both the learning of key scientific concepts and an understanding of the nature of science are established. Approaches to the design of curricula that facilitate the progressive grasp of the knowledge and skills entailed in modelling are outlined. Recognising that the approach will both represent a substantial change from the ‘content-transmission’ approach to science teaching and be in accordance with current best-practice in science education, the design of suitable approaches to teacher education are discussed. Finally, the challenges that modelling-based education pose to science education researchers, advanced students of science education and curriculum design, teacher educators, public examiners, and textbook designers, are all outlined.

This volume is important because despite various external representations, such as analogies, metaphors, and visualizations being commonly used by physics teachers, educators and researchers, the notion of using the pedagogical functions of multiple representations to support teaching and learning is still a gap in physics education. The research presented in the three sections of the book is introduced by descriptions of various psychological theories that are applied in different ways for designing physics teaching and learning in classroom settings. The following chapters of the book illustrate teaching and learning with respect to applying specific physics multiple representations in different levels of the education system and in different physics topics using analogies and models, different modes, and in reasoning and representational competence. When multiple representations are used in physics for teaching, the expectation is that they should be successful. To ensure this is the case, the implementation of representations should consider design principles for using multiple representations. Investigations regarding their effect on classroom communication as well as on the learning results in all levels of schooling and for different topics of physics are reported. The book is intended for physics educators and their students at universities and for physics teachers in schools to apply multiple representations in physics in a productive way.

This book covers the current state of thinking and what it means to have a framework of representational competence and how such theory can be used to shape our understanding of the use of representations in science education, assessment, and instruction. Currently, there is not a consensus in science education regarding representational competence as a unified theoretical framework. There are multiple theories of representational competence in the literature that use differing perspectives on what competence means and entails. Furthermore, dependent largely on the discipline, language discrepancies cause a potential barrier for merging ideas and pushing forward in this area. While a single unified theory may not be a realistic goal, there needs to be strides taken toward working as a unified research community to better investigate and interpret representational competence.  An objective of this book is to initiate thinking about a representational competence theoretical framework across science educators, learning scientists, practitioners and scientists. As such, we have divided the chapters into three major themes to help push our thinking forward: presenting current thinking about representational competence in science education, assessing representational competence within learners, and using our understandings to structure instruction.

External representations (pictures, diagrams, graphs, concrete models) have always been valuable tools for the science teacher. The formation of personal, internal, representations – visualizations – from them plays a key role in all learning, especially in that of science. The use of personal computers and sophisticated software has expanded into the areas of simulation, virtual reality, and animation, and students now engage in the creation of models, a key aspect of scientific methodology. Several academic disciplines underlie these developments, yet act independently of each other, to the detriment of an attainment of what is possible. This book brings together the insights of practicing scientists, science education researchers, computer specialists, and cognitive scientists, to produce a coherent overview. It links presentations about the cognitive theory of representation and visualization, its implications for science curriculum design, and for learning and teaching in classrooms and laboratories.

Chemistry seeks to provide qualitative and quantitative explanations for the observed behaviour of elements and their compounds. Doing so involves making use of three types of representation: the macro (the empirical properties of substances); the sub-micro (the natures of the entities giving rise to those properties); and the symbolic (the number of entities involved in any changes that take place). Although understanding this triplet relationship is a key aspect of chemical education, there is considerable evidence that students find great difficulty in achieving mastery of the ideas involved. In bringing together the work of leading chemistry educators who are researching the triplet relationship at the secondary and university levels, the book discusses the learning involved, the problems that students encounter, and successful approaches to teaching. Based on the reported research, the editors argue for a coherent model for understanding the triplet relationship in chemical education.

Science education at school level worldwide faces three perennial problems that have become more pressing of late. These are to a considerable extent interwoven with concerns about the entire school curriculum and its reception by students. The rst problem is the increasing intellectual isolation of science from the other subjects in the school curriculum. Science is too often still taught didactically as a collection of pre-determined truths about which there can be no dispute. As a con- quence, many students do not feel any “ownership” of these ideas. Most other school subjects do somewhat better in these regards. For example, in language classes, s- dents suggest different interpretations of a text and then debate the relative merits of the cases being put forward. Moreover, ideas that are of use in science are presented to students elsewhere and then re-taught, often using different terminology, in s- ence. For example, algebra is taught in terms of “x, y, z” in mathematics classes, but students are later unable to see the relevance of that to the meaning of the universal gas laws in physics, where “p, v, t” are used. The result is that students are c- fused and too often alienated, leading to their failure to achieve that “extraction of an education from a scheme of instruction” which Jerome Bruner thought so highly desirable.

The process of developing models, known as modeling, allows scientists to visualize difficult concepts, explain complex phenomena and clarify intricate theories. In recent years, science educators have greatly increased their use of modeling in teaching, especially real-time dynamic modeling, which is central to a scientific investigation. Modeling in science teaching is being used in an array of fields, everything from primary sciences to tertiary chemistry to college physics, and it is sure to play an increasing role in the future of education. Models and Modeling: Cognitive Tools for Scientific Enquiry is a comprehensive introduction to the use of models and modeling in science education. It identifies and describes many different modeling tools and presents recent applications of modeling as a cognitive tool for scientific enquiry.

Science education at school level worldwide faces three perennial problems that have become more pressing of late. These are to a considerable extent interwoven with concerns about the entire school curriculum and its reception by students. The rst problem is the increasing intellectual isolation of science from the other subjects in the school curriculum. Science is too often still taught didactically as a collection of pre-determined truths about which there can be no dispute. As a con- quence, many students do not feel any “ownership” of these ideas. Most other school subjects do somewhat better in these regards. For example, in language classes, s- dents suggest different interpretations of a text and then debate the relative merits of the cases being put forward. Moreover, ideas that are of use in science are presented to students elsewhere and then re-taught, often using different terminology, in s- ence. For example, algebra is taught in terms of “x, y, z” in mathematics classes, but students are later unable to see the relevance of that to the meaning of the universal gas laws in physics, where “p, v, t” are used. The result is that students are c- fused and too often alienated, leading to their failure to achieve that “extraction of an education from a scheme of instruction” which Jerome Bruner thought so highly desirable.

The process of developing models, known as modeling, allows scientists to visualize difficult concepts, explain complex phenomena and clarify intricate theories. In recent years, science educators have greatly increased their use of modeling in teaching, especially real-time dynamic modeling, which is central to a scientific investigation. Modeling in science teaching is being used in an array of fields, everything from primary sciences to tertiary chemistry to college physics, and it is sure to play an increasing role in the future of education. Models and Modeling: Cognitive Tools for Scientific Enquiry is a comprehensive introduction to the use of models and modeling in science education. It identifies and describes many different modeling tools and presents recent applications of modeling as a cognitive tool for scientific enquiry.

This new publication in the Models and Modeling in Science Education series synthesizes a wealth of international research on using multiple representations in biology education and aims for a coherent framework in using them to improve higher-order learning. Addressing a major gap in the literature, the volume proposes a theoretical model for advancing biology educators’ notions of how multiple external representations (MERs) such as analogies, metaphors and visualizations can best be harnessed for improving teaching and learning in biology at all pedagogical levels. The content tackles the conceptual and linguistic difficulties of learning biology at each level—macro, micro, sub-micro, and symbolic, illustrating how MERs can be used in teaching across these levels and in various combinations, as well as in differing contexts and topic areas. The strategies outlined will help students’ reasoning and problem-solving skills, enhance their ability to construct mental models and internal representations, and, ultimately, will assist in increasing public understanding of biology-related issues, a key goal in today’s world of pressing concerns over societal problems about food, environment, energy, and health. The book concludes by highlighting important aspects of research in biological education in the post-genomic, information age.

This new publication in the Models and Modeling in Science Education series synthesizes a wealth of international research on using multiple representations in biology education and aims for a coherent framework in using them to improve higher-order learning. Addressing a major gap in the literature, the volume proposes a theoretical model for advancing biology educators’ notions of how multiple external representations (MERs) such as analogies, metaphors and visualizations can best be harnessed for improving teaching and learning in biology at all pedagogical levels. The content tackles the conceptual and linguistic difficulties of learning biology at each level—macro, micro, sub-micro, and symbolic, illustrating how MERs can be used in teaching across these levels and in various combinations, as well as in differing contexts and topic areas. The strategies outlined will help students’ reasoning and problem-solving skills, enhance their ability to construct mental models and internal representations, and, ultimately, will assist in increasing public understanding of biology-related issues, a key goal in today’s world of pressing concerns over societal problems about food, environment, energy, and health. The book concludes by highlighting important aspects of research in biological education in the post-genomic, information age.