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In most countries, only very limited time resources are available for statistics education within mathematics education. Thus, statistics education research needs to develop teaching-learning arrangements that are compact and applicable to classrooms. Christian Büscher designs and investigates a compact teaching-learning arrangement which aims at mathematical and reflective knowledge about statistics. Central results include the specification of the learning content of statistical measures, an empirical reconstruction of students’ learning processes towards statistical measures, and the identification of students’ situated reflections about mathematics within their learning processes.
Unique in that it collects, presents, and synthesizes cutting edge research on different aspects of statistical reasoning and applies this research to the teaching of statistics to students at all educational levels, this volume will prove of great value to mathematics and statistics education researchers, statistics educators, statisticians, cognitive psychologists, mathematics teachers, mathematics and statistics curriculum developers, and quantitative literacy experts in education and government.
This book reveals the development of students' understanding of statistical literacy. It provides a way to "see" student thinking and gives readers a deeper sense of how students think about important statistical topics. Intended as a complement to curriculum documents and textbook series, it is consistent with the current principles and standards of the National Council of Teachers of Mathematics. The term "statistical literacy" is used to emphasize that the purpose of the school curriculum should not be to turn out statisticians but to prepare statistically literate school graduates who are prepared to participate in social decision making. Based on ten years of research--with reference to other significant research as appropriate--the book looks at students' thinking in relation to tasks based on sampling, graphical representations, averages, chance, beginning inference, and variation, which are essential to later work in formal statistics. For those students who do not proceed to formal study, as well as those who do, these concepts provide a basis for decision making or questioning when presented with claims based on data in societal settings. Statistical Literacy at School: Growth and Goals: *establishes an overall framework for statistical literacy in terms of both the links to specific school curricula and the wider appreciation of contexts within which chance and data-handling ideas are applied; *demonstrates, within this framework, that there are many connections among specific ideas and constructs; *provides tasks, adaptable for classroom or assessment use, that are appropriate for the goals of statistical literacy; *presents extensive examples of student performance on the tasks, illustrating hierarchies of achievement, to assist in monitoring gains and meeting the goals of statistical literacy; and *includes a summary of analysis of survey data that suggests a developmental hierarchy for students over the years of schooling with respect to the goal of statistical literacy. Statistical Literacy at School: Growth and Goals is directed to researchers, curriculum developers, professionals, and students in mathematics education as well those across the curriculum who are interested in students' cognitive development within the field; to teachers who want to focus on the concepts involved in statistical literacy without the use of formal statistical techniques; and to statisticians who are interested in the development of student understanding before students are exposed to the formal study of statistics.
This book presents the breadth and diversity of empirical and practical work done on statistics education around the world. A wide range of methods are used to respond to the research questions that form it's base. Case studies of single students or teachers aimed at understanding reasoning processes, large-scale experimental studies attempting to generalize trends in the teaching and learning of statistics are both employed. Various epistemological stances are described and utilized. The teaching and learning of statistics is presented in multiple contexts in the book. These include designed settings for young children, students in formal schooling, tertiary level students, vocational schools, and teacher professional development. A diversity is evident also in the choices of what to teach (curriculum), when to teach (learning trajectory), how to teach (pedagogy), how to demonstrate evidence of learning (assessment) and what challenges teachers and students face when they solve statistical problems (reasoning and thinking).
Assessment Methods in Statistical Education: An International Perspective provides a modern, international perspective on assessing students of statistics in higher education. It is a collection of contributions written by some of the leading figures in statistical education from around the world, drawing on their personal teaching experience and educational research. The book reflects the wide variety of disciplines, such as business, psychology and the health sciences, which include statistics teaching and assessment. The authors acknowledge the increasingly important role of technology in assessment, whether it be using the internet for accessing information and data sources or using software to construct and manage individualised or online assessments. Key Features: Presents successful assessment strategies, striking a balance between formative and summative assessment, individual and group work, take-away assignments and supervised tests. Assesses statistical thinking by questioning students’ ability to interpret and communicate the results of their analysis. Relates assessment to the real world by basing it on real data in an appropriate context. Provides a range of individualised assessment methods, including those that deter plagiarism and collusion by providing each student with a unique problem to solve or dataset to analyse. This book is essential reading for anyone involved in teaching statistics at tertiary level or interested in statistical education research.
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.
This is the ninth time we are hosting this seminar and we are proud to inform you that this seminar is an annual event in our calendar and has been held every year since 2014. This year, for the third year, we are holding it via Zoom meeting (online meeting) due to Covid-19 pandemic. We are inviting internationally recognized speakers from several countries to share their latest discoveries in the fields of Biology, Chemistry, Physics, Mathematics and Science Education. Well-known researchers in science and science education will share their experiences and knowledge so that we can stay up-to-date with the latest information. This is one of the goals of this seminar. As science researchers, we realize the importance of information exchange among us. The new information enlightens our minds and gives us ideas on what to do next in our research and how to do it. This new information often becomes the foundation for our next project in particular and sets the research trends for the upcoming year in general. Information exchange also keeps us updated, allowing us to give and receive suggestions and critiques that will lead to better results. Therefore, we need a forum where we can share and exchange information. Seminars, conferences, and other scientific gatherings are the media through which we can do this. Organizer Faculty of Mathematics and Natural Sciences of Universitas Negeri Medan Where Web Seminar via Zoom Meeting When Tuesday, 8th November 2022 Theme The development of industrial-based research in science and science education to improve research innovation strategy Topics: AISTSSE-2020 included following topics: 1. Mathematics Science 2. Mathematics Education 3. Physics Science 4. Physics Education 5. Biology Science 6. Biology Education 7. Chemistry Science 8. Chemistry Education 9. Computer Science 10.Science Education Scientific Committee 1. Prof. Dr. Syawal Gultom, M.Pd, Universitas Negeri Medan (Indonesia) 2. Prof. Dr. Marleen Kamperman, University of Groningen (Netherland) 3. Prof. Manihar Situmorang, M.Sc., Ph.D , Universitas Negeri Medan (Indonesia) 4. Prof. Tsunenori Mine, School of Engineering, Department of Electrical Engineering and Computer Science, Kyushu University (Japan) 5. Prof. Dian Armanto, M.Pd, Universitas Negeri Medan (Indonesia) 6. Prof. Dr. Herbert Sipahutar, M.Sc , Universitas Negeri Medan (Indonesia) 7. Prof. Abedel Karrem Nasser M Alomari Department of Mathematics, Faculty of Science, Yarmouk University (Jordan) 8. Prof. Dr. Bornok Sinaga, M.Pd , Universitas Negeri Medan (Indonesia) 9. Prof. Dr. Muhammad Sattar Rasul Universitas Kebangsaan Malaysia, (Malaysia) 10. Prof. Motlan, M.Sc., Ph.D , Universitas Negeri Medan (Indonesia) 11. Prof. Dr. Asmin, M.Pd , Universitas Negeri Medan (Indonesia) 12. Prof. Dr. Fauziyah Harahap, M.Si, Universitas Negeri Medan (Indonesia) 13. Prof. Dr. Mukhtar, M.Pd , Universitas Negeri Medan (Indonesia) 14. Prof. Dr. Pargaulan Siagian, M.Pd , Universitas Negeri Medan (Indonesia) 15. Prof. Dr. Sahat Saragih, M.Pd , Universitas Negeri Medan (Indonesia) 16. Prof. Dr. Edi Syahputra, M.Pd , Universitas Negeri Medan (Indonesia) 17. Prof. Dr. Hasratuddin, M.Pd , Universitas Negeri Medan (Indonesia) 18. Prof. Dr. Ramlan Silaban, M.Si, Universitas Negeri Medan (Indonesia) 19. Prof. Dr. Retno Dwi Suyanti, M.Si , Universitas Negeri Medan (Indonesia) 20. Prof. Dr. Nurdin Bukit, M.Si , Universitas Negeri Medan (Indonesia) 21. Prof. Dr. Sahyar, M.S , Universitas Negeri Medan (Indonesia) 22. Prof. Dr. rer. nat. Binari Manurung, M.Si , Universitas Negeri Medan (Indonesia) 23. Prof. Dr. Makmur Sirait, M.Si , Universitas Negeri Medan (Indonesia) 24. Prof. Dr. Eva Marlina Ginting, M.Si , Universitas Negeri Medan (Indonesia) 25. Prof. Dr. Drs. Tri Harsono, M.Si, Universitas Negeri Medan (Indonesia) 26. Prof. Dr. Martina Restuati, M.Si, Universitas Negeri Medan (Indonesia) 27. Prof. Drs. Zul Amry, M.Si., Ph.D, Universitas Negeri Medan (Indonesia) Supported by: FORUM MIPA LPTK INDONESIA