Learning to Solve Problems is a much-needed book thatdescribes models for designing interactive learning environments tosupport how to learn and solve different kinds of problems. Using aresearch-based approach, author David H. Jonassen?a recognizedexpert in the field?shows how to design instruction to supportthree kinds of problems: story problems, troubleshooting, and caseand policy analysis problems. Filled with models and job aids, thisbook describes different approaches for representing problems tolearners and includes information about technology-based tools thatcan help learners mentally represent problems for themselves.Jonassen also explores methods for associating different solutionsto problems and discusses various processes for reflecting on theproblem solving process. Learning to Solve Problems alsoincludes three methods for assessing problem-solvingskills?performance assessment, component skills; and argumentation.

This book presents both theoretical and empirical contributions from a global perspective on problem solving and posing (PS/PP) and their application, in relation to the teaching and learning of mathematics in schools. The chapters are derived from selected presentations in the PS/PP Topical Study Group in ICME14. Although mathematical problem posing is a much younger field of inquiry in mathematics education, this topic has grown rapidly. The mathematics curriculum frameworks in many parts of the world have incorporated problem posing as an instructional focus, building on problem solving as its foundation. The juxtaposition of problem solving and problem posing in mathematics presented in this book addresses the needs of the mathematics education research and practice communities at the present day. In particular, this book aims to address the three key points: to present an overview of research and development regarding students’ mathematical problem solving and posing; to discuss new trends and developments in research and practice on these topics; and to provide insight into the future trends of mathematical problem solving and posing.

Critical inquiry, critical thinking and problem-solving are key concepts in contemporary physical education. But how do physical educators actually do critical inquiry and critical thinking? Critical Inquiry and Problem-Solving in Physical Education explains the principles and assumptions underpinning these concepts and provides detailed examples of how they can be used in the teaching of physical education for different age groups and in a range of different contexts. Topics covered include: sport education and critical thinking dance as critical inquiry media analysis understanding cultural perspectives student-led research and curriculum reflective coaching practice. The authors are teachers, teacher educators, policymakers and academics. Each shares a commitment to the notion that school students can do more than learn to move in physical education classes.

The PISA 2003 Assessment Framework presents the conceptual underpinning of the PISA 2003 assessments. Within each assessment area, the volume defines the content that students need to acquire, the processes that need to be performed and the contexts in which knowledge and skills are applied.

Learning, Problem Solving, and Mindtools is inspired by the substantial body of learning research by David H. Jonassen in the areas of mind tools and problem solving. The focus of the volume is on educational technology, especially with regard to how new technologies have facilitated and supported problem solving and critical thinking. Each chapter focuses on a particular aspect of learning with technology and elaborates the implications for the design and implementation of learning environments and activities aimed at improving the conceptualization of problems, reasoning and higher-order thinking, and solving challenging problems. This collection of scholarly essays provides a highly engaging treatment of using tools and technologies to improve problem solving; multiple perspectives on integrating educational technology to support learning in complex and challenging problem solving domains; guidance for the design of instruction to support problem solving; a systemic account of the relationships between mental models, instructional models, and assessment models; and a look into the future of educational technology research and practice.

From 3rd to 5th of September 2015 the 17th international ProMath conference (Problem Solving in Mathematics Education) took place at the Faculty of Education of the Martin Luther University Halle-Wittenberg (Germany). For the first time, it was combined with the annual meeting of the working group “Problem Solving” of the Society of Didactics of Mathematics. This book contains 20 peer reviewed articles of researchers from five European countries. The topics of the papers evolved around different areas of learning and problem solving. There are some theoretical papers on problem oriented mathematics instruction and specific aspects of problem solving and creativity as well as reports on detailed studies of problem solving processes of pupils and preservice teachers. Authors also present experiences with “real” problem solving instruction in different countries, considerations and teaching experiments on didactic concepts to foster pupils’ problem solving abilities, and they describe mathematically rich problem fields and their potentials for mathematical investigations in class. ProMath is a group of experienced and early career researchers in the field of mathematics education who are interested in investigating and fostering mathematical problem solving and problem oriented mathematics teaching.

Problem solving is central to the teaching and learning of chemistry at secondary, tertiary and post-tertiary levels of education, opening to students and professional chemists alike a whole new world for analysing data, looking for patterns and making deductions. As an important higher-order thinking skill, problem solving also constitutes a major research field in science education. Relevant education research is an ongoing process, with recent developments occurring not only in the area of quantitative/computational problems, but also in qualitative problem solving. The following situations are considered, some general, others with a focus on specific areas of chemistry: quantitative problems, qualitative reasoning, metacognition and resource activation, deconstructing the problem-solving process, an overview of the working memory hypothesis, reasoning with the electron-pushing formalism, scaffolding organic synthesis skills, spectroscopy for structural characterization in organic chemistry, enzyme kinetics, problem solving in the academic chemistry laboratory, chemistry problem-solving in context, team-based/active learning, technology for molecular representations, IR spectra simulation, and computational quantum chemistry tools. The book concludes with methodological and epistemological issues in problem solving research and other perspectives in problem solving in chemistry. With a foreword by George Bodner.

Problem solving is implicit in the very nature of all science, and virtually all scientists are hired, retained, and rewarded for solving problems. Although the need for skilled problem solvers has never been greater, there is a growing disconnect between the need for problem solvers and the educational capacity to prepare them. Learning to Solve Complex Scientific Problems is an immensely useful read offering the insights of cognitive scientists, engineers and science educators who explain methods for helping students solve the complexities of everyday, scientific problems. Important features of this volume include discussions on: *how problems are represented by the problem solvers and how perception, attention, memory, and various forms of reasoning impact the management of information and the search for solutions; *how academics have applied lessons from cognitive science to better prepare students to solve complex scientific problems; *gender issues in science and engineering classrooms; and *questions to guide future problem-solving research. The innovative methods explored in this practical volume will be of significant value to science and engineering educators and researchers, as well as to instructional designers.

A provocative collection of papers containing comprehensive reviews of previous research, teaching techniques, and pointers for direction of future study. Provides both a comprehensive assessment of the latest research on mathematical problem solving, with special emphasis on its teaching, and an attempt to increase communication across the active disciplines in this area.

There is a tremendous need for computer scientists, data scientists, and software developers to learn how to develop Socratic problem-solving applications. While the amount of data and information processing has been accelerating, our ability to learn and problem-solve with that data has fallen behind. Meanwhile, problems have become too complex to solve in the workplace without a concerted effort to follow a problem-solving process. This problem-solving process must be able to deal with big and disparate data. Furthermore, it must solve problems that do not have a “rule” to apply in solving them. Moreover, it must deal with ambiguity and help humans use informed judgment to build on previous steps and create new understanding. Computer-based Socratic problem-solving systems answer this need for a problem-solving process using big and disparate data. Furthermore, computer scientists, data scientists, and software developers need the knowledge to develop these systems. Socrates Digital™ for Learning and Problem Solving presents the rationale for developing a Socratic problem-solving application. It describes how a computer-based Socratic problem-solving system called Socrates Digital™ can keep problem-solvers on track, document the outcome of a problem-solving session, and share those results with problem-solvers and larger audiences. In addition, Socrates Digital™ assists problem-solvers in combining evidence about their quality of reasoning for individual problem-solving steps and their overall confidence in the solution. Socrates Digital™ also captures, manages, and distributes this knowledge across organizations to improve problem-solving. This book also presents how to build a Socrates Digital™ system by detailing the four phases of design and development: understand, explore, materialize, and realize. The details include flow charts and pseudo-code for readers to implement Socrates Digital™ in a general-purpose programming language. The completion of the design and development process results in a Socrates Digital™ system that leverages artificial intelligence services from providers that include Apple, Microsoft, Google, IBM, and Amazon. In addition, an appendix provides a demonstration of a no-code implementation of Socrates Digital™ in Microsoft Power Virtual Agent.