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.
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Dr. Lambrini Seremeti is an Assistant Professor in the Department of Agricultural Economics & Rural Development at the School of Applied Economics and Social Science of the Agricultural University of Athens. She holds a PhD in Computer Science with a focus on propagating knowledge in networks of aligned ontologies from Hellenic Open University; a Master in Special Education from University of Rome; a Master in Pure Mathematics from University of Patras; a Bachelor in Mathematics from University of Patras; a Bachelor in Informatics from University of Western Greece; and a Bachelor in Law from University of Nicosia. She has also participated as a researcher in EU-funded projects, in which, her tasks involved mathematical modeling, data processing, knowledge representation and management, and conceptualization of heterogeneous environments (socio-economic, educational, biomedical, ambient intelligent). Her research interests focus on theories applied in interpretation of Law in ambient intelligent environments, knowledge representation and management through ontologies, and mathematical modeling of co-evolving systems. She can be contacted at email: lambrini.seremeti@gmail.com
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Taschenbuch. Condición: Neu. Modes of Representation in Developing Statistical Thinking in Education | Sofia D. Anastasiadou (u. a.) | Taschenbuch | Englisch | 2025 | IGI Global | EAN 9798369399354 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Nº de ref. del artículo: 133466011
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9798369399354
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