Journal Article

  • Technology-assisted instruction is a core focus of educational reform in most disciplines. This exploratory study (N=227) examined instructors’ attitudes toward technology integration for the teaching of introductory statistics at the college level. Salient attitudinal elements (including perceived usefulness, self-efficacy, and comfort), which can serve as barriers to, and facilitators of, technology integration were identified. Additionally, a preliminary scale (ATTIS) for measuring instructors’ attitudes toward technology integration was developed with acceptable levels of internal reliability and validity. The results underscore the need for training and support for instructors, by way of workshops, modeling of best practices through team teaching and mentoring, and other targeted professional development activities.

  • The teaching and learning of statistics has evolved tremendously over the years owing to the reformation in statistics education and the advancement of technology that revolutionized the pedagogy in statistics classrooms. With technological tools students can focus in learning and understanding the important statistical concepts instead of concentrating on lengthy and repetitive calculations. Hand-held technologies such as the graphics calculators have paved the way for constructive and exciting learning experience. However, in a developing country like Malaysia the use of graphics calculators in statistics classrooms is not without challenges. This paper explores the advantages and limitations of the use of graphics calculators in the teaching of statistics in Malaysia.

  • Technology has become an inseparable part of modern statistical practice (Gould, 2010), and, to a large extent, modern statistics courses. The literature on technology in statistics education has focused heavily on the role of technology for improving students’ understanding. However, limited research has examined the development of technological skills for “doing” statistics, e.g. using statistical packages. This paper proposes a distinction between these two roles of technology and how both benefit student learning. The paper then applies Kanfer and Ackerman’s (1989) integrative model of skill acquisition to explain the variability in students’ technological skill development. The ability to use statistical packages, arguably the most pervasive example of statistics technology, is used as an example to illustrate this model. The implications of the model are then discussed in the context of teaching technological skills in statistics courses. Future directions and challenges related to this area of are discussed

  • The case is made for a new type of statistical master’s program called MSc in Research Methods. The name of the course reflects the fact it is broader than one in statistics, partly because of the changing nature of research. It is designed to be accessible to two types of students: those who have a mathematical background and those who have a more applied background from their first degree. The program is intended primarily for working professionals so it is delivered in a way that is suitable for part-time students. The implementation of an e-learning version of this course in Kenya is also described.

  • Hypothesis testing reasoning is recognized as a difficult area for students. Changing to a new paradigm for learning inference through computer intensive methods rather than mathematical methods is a pathway that may be more successful. To explore ways to improve students’ inferential reasoning at the Year 13 (last year of school) and introductory university levels, our research group developed new learning trajectories and dynamic visualizations for the randomization method. In this paper we report on the findings from a pilot study including student learning outcomes and on the modifications we intend to make before the main study. We discuss how the randomization method using dynamic visualizations clarifies concepts underpinning inferential reasoning and why the nature of the argument still remains a challenge.

  • Ordinarily, when a student plays a game on a computer, a great deal of data are generated, but never used. This paper describes a technological innovation: games designed for learning mathematics or statistics concepts in which success requires data analysis. These “Data Games” are small-scale, short, web-based games, embedded in a data analysis environment, suitable for students in about year 7 onwards, and in teacher preparation. We discuss design for the games themselves, curriculum and assessment issues, and connections to research.

  • The need for people fluent in working with data is growing rapidly and enormously, but U.S. K–12 education does not provide meaningful learning experiences designed to develop understanding of data science concepts or a fluency with data science skills. Data science is inherently inter-disciplinary, so it makes sense to integrate it with existing content areas, but difficulties abound. Consideration of the work involved in doing data science and the habits of mind that lie behind it leads to a way of thinking about integrating data science with mathematics and science. Examples drawn from current activity development in the Data Games project shed some light on what technology-based, data-driven might be like. The project’s ongoing research on learners’ conceptions of organizing data and the relevance to data science education is explained.

  • The concept of statistical literacy needs to be refreshed, regularly. Major changes in the ways that data can be accessed from government and non-government agencies allow everyone to access huge databases, to create new variables, and to explore new relationships. New ways of visualizing data provide further challenges and opportunities. The Open Data movement, and the rise of data driven journalism are increasing public access to large scale data via the media. Here, we map out some opportunities and potential pitfalls, and discuss the rebalancing of statistics curricula that is required. The most obvious challenge is the need to introduce students to the exploration and analysis of large scale multivariate data sets. The curriculum should also address issues of data provenance and quality. We present an example of our visualisations of complex multivariate data, used in classroom trials. General issues of pedagogy and curriculum innovation are discussed.

  • Technology has revolutionised society and it has revolutionised the way in which statistics, as a professional discipline, is done. The collection of data is growing exponentially both in relation to the quantity of data assembled on any particular measure and also in relation to the range of topics, and the measures, on which data is collected. Accessing data has become much simpler, and tools for exploring, manipulating and representing that data visually have multiplied, both in commercially available software and open-source freeware. However, the curriculum in schools in the UK is constrained by important factors which restrict the use of technology in assessment. The statistics curriculum is largely dull and does not address the core issues of most relevance in statistics today. Here, we explore ways in which technology can enhance the teaching of subjects in which statistics are used, and also the teaching of statistics within mathematics.

  • One of the challenges of teaching is engaging students in a subject they may not see as relevant to them. This issue is especially prevalent when teaching statistics to health science students as many do not consider statistics an important piece of their medical training. Additional difficulty is presented when teaching courses via distance technology or courses that are partially or completely online as the valuable class discussion component is lost. This paper focuses on fostering “discussion” about statistical concepts and how they relate to each student on an individual level. This paper describes the online discussion board as a tool incorporated to supplement classroom activities and not as one to be limited to the online class. Two activities where the discussion board can be utilized are described: one where students participate in a series of guided discussions through instructor provided, thought-provoking questions and another where students critique an article related to their field of study and post for discussion. The objectives are to enhance knowledge, develop critical thinking, gain an appreciation of how statistics is used in different fields, and provide opportunities for discussion outside the classroom. Students are able to discuss issues with classmates who can be in the classroom or abroad using a virtual environment. This approach has been successfully used in both purely online classes and in large graduate level biostatistics classes including both synchronous and asynchronous distance learners.

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