Modes Of Representation In Developing Statistical Thinking In Education
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Modes of Representation in Developing Statistical Thinking in Education
Developing the ability to understand and use multiple representations is vital for deepening students’ comprehension of statistical, probabilistic, and mathematical concepts. This skill enhances problem-solving by enabling learners to translate ideas across various forms, leading to more flexible and meaningful understanding. Representational competency is closely linked to communication, critical thinking, and the ability to engage with real-world data. Moreover, students’ attitudes, emotions, and self-confidence significantly influence their motivation and success in these subjects. Strengthening these aspects in education can lead to more effective learning experiences and greater long term achievement in math and statistics. Modes of Representation in Developing Statistical Thinking in Education explores different modes of representations in teaching and learning statistical, probabilistic notions, and attitudes in developing statistical thinking in education. By bringing together contributions from global experts, the volume fosters interdisciplinary collaboration, inspires new research directions, and provides the knowledge and tools necessary to navigate the evolving landscape of statistics education. Covering topics such as artificial intelligence, mathematics education, and web tools, this book is an excellent resource for researchers, academicians, educators, policymakers, data scientists, and more.
Developing Students’ Statistical Reasoning
Author: Joan Garfield
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-09-08
Increased attention is being paid to the need for statistically educated citizens: statistics is now included in the K-12 mathematics curriculum, increasing numbers of students are taking courses in high school, and introductory statistics courses are required in college. However, increasing the amount of instruction is not sufficient to prepare statistically literate citizens. A major change is needed in how statistics is taught. To bring about this change, three dimensions of teacher knowledge need to be addressed: their knowledge of statistical content, their pedagogical knowledge, and their statistical-pedagogical knowledge, i.e., their specific knowledge about how to teach statistics. This book is written for mathematics and statistics educators and researchers. It summarizes the research and highlights the important concepts for teachers to emphasize, and shows the interrelationships among concepts. It makes specific suggestions regarding how to build classroom activities, integrate technological tools, and assess students’ learning. This is a unique book. While providing a wealth of examples through lessons and data sets, it is also the best attempt by members of our profession to integrate suggestions from research findings with statistics concepts and pedagogy. The book’s message about the importance of listening to research is loud and clear, as is its message about alternative ways of teaching statistics. This book will impact instructors, giving them pause to consider: "Is what I’m doing now really the best thing for my students? What could I do better?" J. Michael Shaughnessy, Professor, Dept of Mathematical Sciences, Portland State University, USA This is a much-needed text for linking research and practice in teaching statistics. The authors have provided a comprehensive overview of the current state-of-the-art in statistics education research. The insights they have gleaned from theliterature should be tremendously helpful for those involved in teaching and researching introductory courses. Randall E. Groth, Assistant Professor of Mathematics Education, Salisbury University, USA
The Assessment Challenge in Statistics Education
This book discusses conceptual and pragmatic issues in the assessment of statistical knowledge and reasoning skills among students at the college and precollege levels, and the use of assessments to improve instruction. It is designed primarily for academic audiences involved in teaching statistics and mathematics, and in teacher education and training. The book is divided in four sections: (I) Assessment goals and frameworks, (2) Assessing conceptual understanding of statistical ideas, (3) Innovative models for classroom assessments, and (4) Assessing understanding of probability.