Using Technology in Teaching Statistics
Seminar by Dr. Thomas Jaki Department of Mathematics and Statistics; Lancaster University You can download the slides from this talk in PDF format. This talk focuses on enhancing students experiences through the use of technology. The first part discusses the use of screen capture, a fast and easy way of recording lectures, through an example of an introductory statistics course for first year biology students, and provides student feedback on the use of these recordings. In the second half discusses a partial distance learning course at postgraduate level, that is based upon the experiences with screen capture. Student feedback is used to deduce the advantages and disadvantages of this hybrid course.
2 Jun 2010
Teaching Statistics as a University Service Course: An Overview of Past Experiences, Present Dilemmas, and Future Challenges
Seminar by Irena Ograjenšek University of Ljubljana The video was recorded at the 2009 International Conference of the Royal Statistical Society and is provided for use under a Creative Commons Attribution Licence. You can download the slides from this talk in PDF format Please note: The video resolution is not optimal for desktop viewing. Educational organizations should not be regarded solely as vehicles for social and structural change. They are also expected to preserve and transmit traditional values to younger members of society and thus represent an element of stability in a rapidly changing world. At the same time, they have to react to rapid changes in their environments and offer access to new knowledge to active population as well. It would thus seem that educational services nowadays must somehow succeed in integrating stability and change at the same time. This is best reflected in curricula of the university service courses on statistics: they have been continuously adapted to the latest developments in information and telecommunication technology (ITT). On the other hand, statistical philosophy, inherent to all steps of the statistical production and dissemination process, represents one of the key elements of the curricula stability. In other words, while ITT enables a simplified access to course materials, a steady electronic communication flow between lecturers and students, easier and less time-consuming computing, etc., the underlying logic of quantitative reasoning which should be conveyed to students in the teaching and learning process remains unchanged. Additionally (and sadly), another element of stability in university service courses on statistics can be identified: the negative attitude of students towards statistics. In the framework of this paper we focus both on elements of change and stability while reflecting on past experiences, present dilemmas, and future challenges faced by the teachers of university service courses on statistics. This work is licensed under a Creative Commons Attribution 3.0 Unported License
25 Nov 2010
Constructing Environments for Early Learning of Statistical Thinking in High Education
Seminar by Dr Helen Johnson and Professor Helen MacGillivray Queensland University of Technology The video was recorded at the 2009 International Conference of the Royal Statistical Society and is provided for use under a Creative Commons Attribution Licence. You can download the slides from this talk in PDF format Please note: The video resolution is not optimal for desktop viewing. Concepts of statistical citizenship, statistical literacy, statistical reasoning and statistical thinking are increasingly influencing educational developments, policy and research. Combinations of research in learning and teaching in statistics, considerations of the nature of statistical enquiry and how statisticians think, and general educational research have contributed to educational development, principles and strategies in statistics teaching in higher education. Previous strategies that were teacher-centred, with theory followed by examples, are supplanted by student-centred, data- and context-driven, experiential learning, with emphasis on concepts and development of statistical thinking. Although opinions differ on the balance of structured and unstructured styles, the strengths of problem-solving approaches, student ownership of contexts, and carefully designed and managed constructs of learning and assessment are widely accepted by statistical educators. Although mathematical models underpin statistical thinking in both data analysis and statistical modelling, the need for greater clarity in distinguishing statistical and mathematical thinking is recognised. This presentation will discuss the development, implementation and evaluation of higher education learning environments that aim to develop sound foundations in statistical thinking in both data and models, with approaches that integrate experiential learning in data, contexts, problem-solving and communication, within learning constructs designed for steady development of concepts, operational knowledge and skills. This work is licensed under a Creative Commons Attribution 3.0 Unported License
24 Nov 2010
Some Curriculum Initiatives for Undergraduate Statistics in the US
Seminar by Allan Rossman California Polytechnic State University The video was recorded at the 2009 International Conference of the Royal Statistical Society and is provided for use under a Creative Commons Attribution Licence. You can download the slides from this talk in PDF format Please note: The video resolution is not optimal for desktop viewing. This work is licensed under a Creative Commons Attribution 3.0 Unported License
16 Nov 2010
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What do doctors (think they) need to know?
Seminar by Dr Jenny Freeman School of Health and Related Research, University of Sheffield You can download the slides from this talk in PDF format Key to any educational development work is the question of what learners need to know. It is easy for statistical educators to feel they know what students need to know, but it is also clear that when teaching non-statisticians, these non-specialists, who will be expected to use statistics after graduation, will have a view on what they need to know. We surveyed both current medical students and practicing doctors about what they would like to know and how it should be delivered. This informed a new curriculum covering the topics found to be most important and lead to the development of a new mode of delivery, based around the problem-based learning model. The understanding produced provides valuable knowledge for both medical education and other disciplines where understanding statistics is essential.
8 Nov 2010