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Publisher: eScholarship   (Total: 18 journals)   [Sort by number of followers]

Showing 1 - 18 of 18 Journals sorted alphabetically
Berkeley Scientific J.     Full-text available via subscription  
Berkeley Undergraduate J.     Full-text available via subscription   (Followers: 1)
California Agriculture     Open Access   (Followers: 2)
California Italian Studies J.     Full-text available via subscription   (Followers: 5)
Electronic Green J.     Open Access   (Followers: 5, SJR: 0.115, h-index: 8)
InterActions: UCLA J. of Education and Information     Open Access   (Followers: 26)
J. for Learning Through the Arts     Open Access   (Followers: 7)
J. of Transnational American Studies     Open Access   (Followers: 3, SJR: 0.174, h-index: 5)
L2 J.     Open Access   (Followers: 5)
Nutrition Bytes     Open Access   (Followers: 5)
Places     Full-text available via subscription   (Followers: 4)
San Francisco Estuary and Watershed Science     Open Access   (SJR: 0.233, h-index: 2)
Spaces for Difference: An Interdisciplinary J.     Open Access   (Followers: 1)
Streetnotes     Open Access   (Followers: 1)
Structure and Dynamics: eJ. of Anthropological and Related Sciences     Open Access   (Followers: 2)
Technology Innovations in Statistics Education (TISE)     Open Access   (Followers: 2)
TRANSIT     Open Access  
World Cultures eJ.     Full-text available via subscription  
Journal Cover Technology Innovations in Statistics Education (TISE)
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   ISSN (Print) 1933-4214
   Published by eScholarship Homepage  [18 journals]
  • Data Visualization on Day One: Bringing Big Ideas into Intro Stats Early
           and Often. Wang, Xiaofei; Rush, Cynthia; Horton, Nicholas Jon

    • Abstract: In a world awash with data, the ability to think and compute with data has become an important skill for students in many fields. For that reason, inclusion of some level of statistical computing in many introductory-level courses has grown more common in recent years. Existing literature has documented multiple success stories of teaching statistics with R, bolstered by the capabilities of R Markdown. In this article, we present an in-class data visualization activity intended to expose students to R and R Markdown during the first week of an introductory statistics class. The activity begins with a brief lecture on exploratory data analysis in R. Students are then placed in small groups tasked with exploring a new dataset to produce three visualizations that describe particular insights that are not immediately obvious from the data. Upon completion, students will have produced a series of univariate and multivariate visualizations on a real dataset and practiced describing them.
      PubDate: Sun, 01 Jan 2017 12:00:00 GMT
  • Comment: Focusing on Learning. Rossman, Allan; Chance, Beth

    • Abstract: Commentary on The Future of the Textbook.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Comment: Let's All Write and Teach with e-Books!. Velleman, Paul

    • Abstract: Commentary on The Future of the Textbook.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Comment: Technology and the Future of Statistics Education. Cobb, George

    • Abstract: Commentary on The Future of the Textbook.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Comment: The Future of the Textbook. Utts, Jessica

    • Abstract: Commentary on The Future of the Textbook.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • The Course as Textbook: A Symbiotic Relationship in the Introductory
           Statistics Class. Zieffler, Andrew; Isaak, Rebekah; Garfield, Joan

    • Abstract: In the past several decades, the statistics textbook has evolved to include a variety of ancillary materials intended to supplement students’ learning and assist the teacher (e.g., workbooks, study guides, audio program, test banks, PowerPoint slides, links to applets and websites, etc.). Given the capabilities of modern technology and the need for change in content and pedagogy in the introductory statistics course, a new vision of a textbook is offered, one that exploits new technology, provides modern content, and is a more integral part of the course. Rather than serving as a supplement to a course, the modern textbook needs to embody the course. An example of such a text in the context of a unique, new introductory statistics course is provided.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Introduction to Special Edition: The Future of the Textbook. Gould, Robert

    • Abstract: A brief overview of the papers and commentaries in this special edition.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • OpenIntro Statistics: an Open-source Textbook. Cetinkaya-Rundel, Mine;
           Diez, David M; Barr, Christopher D

    • Abstract: The traditional textbook is a familiar and useful tool that has served well for centuries.  Here, we discuss OpenIntro Statistics, a new textbook that seeks to retain the long-standing points of excellence among traditional textbooks, while overcoming what is potentially the most important traditional limitation: exclusivity.  OpenIntro Statistics is a completely open-source textbook, which can be downloaded for free and edited by anybody.  Its content meets the highest established standards, and is is written, edited, and reviewed by faculty from leading universities.  In this paper, we provide support for the assertion that OpenIntro Statistics retains as many of the advantages of a traditional textbook as possible, while empowering the largest possible audience to owna nd edit introductory content in statistics.  We also discuss how the open-source textbook model differs from other technologically enabled alternatives to the traditional textbook, and consider trends in the textbook over the coming years.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Response: C-RDB. Cetinkaya-Rundel, Mine; Diez, David; Barr, Christopher

    • Abstract: Response to Commentaries.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Textbooks 2.0. West, Webster

    • Abstract: Technology allows us to offer great improvements on the traditional paper-bound textbook.  I describe reasons for why electronic textbooks will become the norm in the near future.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • West: Response. West, Webster

    • Abstract: Response to Commentaries.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • ZIG: Response. Isaak, Rebekah; Joan, Garfield; Zieffler, Andrew

    • Abstract: Response to Commentaries.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Applying a Theoretical Model for Explaining the Development of
           Technological Skills in Statistics Education. Baglin, James

    • Abstract: 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 disc...
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • The Data Science Education Dilemma. Finzer, William

    • Abstract: 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.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Designing Games for Understanding in a Data Analysis Environment.
           Erickson, Tim

    • Abstract: 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.  
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Developing Statistics Education in Kenya Through Technological Innovations
           at all Academic Levels. Stern, David

    • Abstract: It is well recognised that statistics teaching in Kenya needs to change, in both the course content and in the approaches to teaching.  Also clear is the important role that can be played through the recent wide availability of modern technology to students at all levels.  A wide range of resources are available and various initiatives have also recently been undertaken.  However, the system has remained resistant to change.  The case is made that teaching and learning of statistics could benefit from initiatives that cut across all educational levels from school through undergraduate to MSc and PhD.  
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Discussion: How Can Technology be Used to Teach Statistical Practice'.
           Bilgin, Ayse Aysin

    • Abstract: This discussion will summarize the two papers presented (Stern et al 2012; Baglin et al 2012) in 2012 IASE Roundtable Conference – “Technology in Statistics Education: Virtualities and Realities” – in Cebu, Philippines and the following discussions that took place after the presentations. In the last section a list of recommendations on learning and teaching and research will be provided.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Discussion: What do Instructors of Statistics Need to Know About
           Technology, and How Can They Best Be Taught'. Molnar, Adam

    • Abstract: At the 2012 IASE Roundtable, Thursday speakers covered diverse technological subjects in developed and developing countries. They demonstrated that the technological frontier varies based on current position and resources. Complexity and acclimation challenges affect all implementations. Discussion of several papers considered the foundation of statistics, whether data or mathematics made more sense and generated more beauty. Plenary discussion had two major topics – comparative benefits of real and realistic data, and ways to attract students to research in statistics.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Dynamic Visualizations and the Randomization Test. Budgett, Stephanie;
           Pfannkuch, Maxine; Regan, Matt; Wild, Chris J.

    • Abstract: 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.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Faculty Attitude towards Technology-Assisted Instruction for Introductory
           Statistics in the Context of Educational Reform. Hassad, Rossi A.

    • Abstract: 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.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Getting Real Statistics into all Curriculum Subject Areas: Can Technology
           Make this a Reality'. Nicholson, James; Ridgway, Jim; McCusker, Sean

    • Abstract: 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.  
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • MSc Training in Research Methods Support. Stern, R.D.; Coe, R.; Stern,
           D.A.; McDermott, B.M.

    • Abstract: 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.  
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • 'Open Data' and the Semantic Web Require a Rethink on Statistics Teaching.
           Ridgway, Jim; Nicholson, James; McCusker, Sean

    • Abstract: 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.  
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT

    • Abstract: In response to the need for reformed, outcome-based higher education statistics curricula in the Philippines, this paper draws from current research on the role of technology in statistics education and presents a framework for technology integration in teaching undergraduate and graduate-level statistics for non-majors. Anchored on the principles of Outcome-Based Education, this framework combines ideas from Pearson and Gallagher’s Gradual Release of Responsibility Model and Taggart’s Reflective Thinking Model to guide the attainment of the goals and intended learning outcomes for teaching statistics with technology as expanded opportunity and support for learning success. The Gradual Release of Responsibility Model describes how responsibility of learning shifts gradually over time from teacher to student ownership and from modeled and guided instruction to collaborative and independent learning.  The Reflective Thinking Model guides the course design where focus in teaching with technology moves from techn...
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Preface to the Special Edition. Gould, Robert; Kaplan, Jennifer

    • Abstract: Introductory remarks
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Selecting Technology to Promote Learning in an Online Introductory
           Statistics Course. Mocko, Megan

    • Abstract: Online courses are becoming an increasingly more common option for college students and technology plays a critically important role. How can a course be taught in a way that engages the students so that they master the material as well as they would in a traditional classroom' In order to help accomplish these goals various technological packages must be chosen to bridge the gap between the traditional and online course. This paper will discuss the technological setup of an online Statistics course, and review the technology choices, implementations, and problems that arose. The paper will concentrate on the discussion of five areas: location of course, class conduct, communication, assessment and any additional hardware requirements.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Students' Experiences and Perceptions of Using a Virtual Environment for
           Project-Based Assessment in an Online Introductory Statistics Course.
           Baglin, James; Bedford, Anthony; Bulmer, Michael

    • Abstract: Course projects have been argued to help develop students’ statistical thinking, but implementing authentic and realistic course projects still presents major challenges. This paper evaluated students’ experiences and perceptions of using an online simulated virtual environment, known as the Island, for implementing major course projects within an online masters level introductory statistics course. The use of the Island aimed to overcome significant practical and ethical constraints imposed on project-based work in online courses. The project required students to answer a self-posed research question by gathering and analysing data using methods covered in the course. The project was divided into two parts, a mid-semester proposal and an end of semester online presentation. Following completion of the projects, forty-two students responded to a questionnaire which rated their level of agreement to three aspects of using the Island: engagement, ease of use and contributes to understanding. Students ...
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • The Use of Graphics Calculator in a Matriculation Statistics Classroom: A
           Malaysian Perspective. Krishnan, Saras; Idris, Noraini

    • Abstract: 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.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Characterising Students' Interaction with TinkerPlots. Fitzallen, Noleine

    • Abstract: Exploration of the way in which students interacted with the software package, TinkerPlots Dynamic Data Exploration, to answer questions about a data set using different forms of graphical representations, revealed that the students used three dominant strategies – Snatch and Grab, Proceed and Falter, and Explore and Complete. The participants in the study were 12 year 5-and-6 students (11-12 years old) who completed data analysis activities and answered questions about the data analysis process undertaken. The data for the inquiry were collected by on-screen capture video as the students worked at the computer with TinkerPlots. Thematic analysis was used to explore the data to determine the students’ strategies when conducting data analysis within the software environment.
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Virtual Discussion for Real Understanding: The Use of an Online Discussion
           Board in an Introductory Biostatistics Course. Schmid, Kendra K

    • Abstract: 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...
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Comparing Training Approaches for Technological Skill Development in
           Introductory Statistics Courses. Baglin, James; Da Costa, Cliff

    • Abstract: Technology has transformed the modern introductory statistics course, but little is known about how students develop the skills required to use this technology. This study compares two different training approaches for learning to operate statistical software packages. Guided training (GT) uses direct instruction and explicit guidance during training, whereas active-exploratory training types, such as error-management training (EMT), promote self-directed exploration. Previous studies in general software training suggest that EMT outperforms GT at promoting adaptive skill transfer. This study recruited a sample of 115 psychology students enrolled in introductory statistics courses that ran concurrently across two campuses. These students completed weekly, one-hour training sessions learning to use the statistical package SPSS. In the final week of the semester, students completed an SPSS certification task to measure adaptive skill transfer. The EMT and GT approach was implemented in Campus A and B respective...
      PubDate: Tue, 01 Jan 2013 12:00:00 GMT
  • Learning Statistics Using Motivational Videos, Real Data and Free
           Software. Harraway, John A

    • Abstract: Website and software products that have the potential to raise the profile of statistics in society are described. The website has links to case study videos describing contexts, study designs, data files and lessons using the new software for data exploration and analysis. Case study videos dealing with current research applying statistics have been selected to motivate discussion in class, and further “hands on” learning can be achieved through use of the software. During the development phase in New Zealand in 2010 the software was trialed and student and teacher experiences are reported. A full day professional development workshop for teachers involving lessons using the software was recorded and these are on the website to assist teachers and students. The software is free for teachers and students at education institutes, and the procedure for obtaining a license is outlined.
      PubDate: Wed, 04 Jan 2012 12:00:00 GMT
  • An Exploration of the Exact Distribution and Probabilities for Sample
           Means for Small Random Samples. Hoff, Steven; Heiny, Robert L; Perrett,
           Jamis J

    • Abstract: The computer algebra system, MathematicaTM, is used to determine the exact distributions for sums and means of small random samples taken from a specific probability density function. The method used is the Inverse Laplace Transform for real-valued functions. These distributions are used to compare exact probabilities for probability interval statements for sums and means with normal approximations for these probabilities using the Central Limit Theorem. The maximum normal approximation errors are determined for probability intervals for various sample sizes.
      PubDate: Wed, 04 Jan 2012 12:00:00 GMT
  • Data Visualisation: A Motivational and Teaching Tool in Official
           Statistics. Forbes, Sharleen Denise

    • Abstract: This paper reports on the use, in 2011, of some recent data visualizations to both motivate students and assist them to understanding underlying official statistics concepts. Examples of visualisations used in a Masters course in public policy and an applied statistics honours course are presented. These visualizations are free, either on-line or open-source and easy to access. Although they are of aggregates of very large official data sets and so may mask some of the underlying variation they provide students with fun tools to explore the patterns and relationships between variables in the data set, discuss its implications and sometimes lead to new questions and analyses. Geo-visualisations help demonstrate the inter-disciplinary nature of official statistics in the real world. Initial feedback from students in these courses was enthusiastic. The on-going challenge for the teacher is to keep up-to-date in a world of rapidly evolving technology and to see the learning opportunities that it may pro...
      PubDate: Sun, 01 Jan 2012 12:00:00 GMT
  • Independent Interactive Inquiry-Based Learning Modules Using Audio-Visual
           Instruction In Statistics. McDaniel, Scott N.; Green, Lisa

    • Abstract: Simulations can make complex ideas easier for students to visualize and understand. It has been shown that guidance in the use of these simulations enhances students’ learning. This paper describes the implementation and evaluation of the Independent Interactive Inquiry-based (I3) Learning Modules, which use existing open-source Java applets, combined with audio-visual instruction. Students are guided to discover and visualize important concepts in post-calculus and algebra-based courses in probability and statistics. Topics include the binomial distribution, confidence intervals, significance testing, and randomization. We show that this format can be used independently by students at the introductory and advanced levels. The percentage of students answering correctly on posttests was larger than that for pretests for three of the four modules described.
      PubDate: Sun, 01 Jan 2012 12:00:00 GMT
  • Online Homework vs. Traditional Homework: Statistics Anxiety and
           Self-Efficacy in an Educational Statistics Course. Williams, Amanda

    • Abstract: The purpose of the study was to investigate whether online homework benefits students over traditional homework in the areas of statistics self-efficacy, statistics anxiety, and grades.  Using a nonequivalent control-group design, one section of students was assigned traditional homework while the other section was assigned online homework.  The two groups were then compared on measures of self-efficacy, statistics anxiety, and homework, test, and final grades. Results indicated that homework delivery method affected only student homework grades, but did not affect their other grades, self-efficacy, or anxiety.
      PubDate: Sun, 01 Jan 2012 12:00:00 GMT
  • Using Applets and Video Instruction to Foster Students' Understanding of
           Sampling Variability. McDaniel, Scott N.; Green, Lisa B.

    • Abstract: Online instructional modules that combine an applet, audio-visual tutorials, and guided discovery questions were created to teach the concept of sampling variability. The modules did contribute to an increase in understanding. However, they are a supplement to, not a replacement for, traditional instruction. The researchers found, using pretests and posttests, that student understanding of sampling distributions increased. There is room for futher improvement, which could be accomplished in two ways. A focus on designing for the introductory, rather than advanced, statistics student could be helpful. Also, giving students more feedback could help their performance in later modules.
      PubDate: Sun, 01 Jan 2012 12:00:00 GMT
  • Innovative Activities: How Clickers can Facilitate the Use of Simulations
           in Large Lecture Classes. Kaplan, Jennifer J

    • Abstract: This paper is a technology case study that addresses the theme of using technology in a large lecture format undergraduate introduction to statistics class to develop student conceptual understanding of inference. In the activities described, each student in the lecture performs a simulation once on a calculator and the results are collected via a personal response system (clicker). This provides not only an active learning environment, but also allows students to experience statistical concepts such as distributions or models, variability, and the Central Limit Theorem, in ways that they cannot experience without these technologies. The large class, therefore, becomes a learning asset, rather than a liability. The two activities that are described in detail are part of a set of twelve activities that were designed to improve conceptual understanding of statistical inference.
      PubDate: Tue, 14 Jun 2011 12:00:00 GMT
  • Introductory Statistics Unconstrained by Computability: A New Cobb Salad.
           Carver, Robert H

    • Abstract: Technology continues to change not only how we teach, but also what we teach in the introductory course. Recently there has been lively discussion about which topics belong in the course. George Cobb has challenged us to rethink the curriculum in light of the computational power of our technologies. This paper proposes a framework for structuring a course using JMP, omitting some traditional topics, leaving space for emphasis on concepts, on data production, on visualization, and on topics that are rarely included in an introductory course. Through such a structure, we can more directly connect statistics education to students’ disciplinary contexts in business, engineering, social and natural sciences, etc. Additionally, we can strengthen students’ conceptual foundations in the field so that, in their roles as citizens and professionals, they can become more critical consumers of statistical arguments.
      PubDate: Tue, 14 Jun 2011 12:00:00 GMT
  • Assessing Statistical Understanding in Middle Schools: Emerging Issues in
           a Technology-Rich Environment. Callingham, Rosemary

    • Abstract: The increased importance of developing statistical understanding in school education is recognised in curriculum documents across the world. The role of technology in enhancing the teaching of statistics is emphasised in these documents and the emergence of quality computer software and websites provides teachers with access to unprecedented resources for teaching statistics to young students. Assessment processes, however, have not kept pace with the advances in technology. This paper highlights some emerging and existing issues in the assessment of statistical understanding at the school level, and includes discussion of the implications for teachers and researchers.
      PubDate: Tue, 14 Jun 2011 12:00:00 GMT
  • Life on an Island: a Simulated Population to Support Student Projects in
           Statistics. Bulmer, Michael; Haladyn, J. Kimberly

    • Abstract: It is important for students learning statistical reasoning to see data in context. One of the best ways of achieving this is to involve students in data production and so in the past ten years we have had first-year students undertake real experiments of their own choosing as part of our introductory statistics course. However in practice students are limited in what they can do. Many want to conduct experiments involving human subjects, requiring ethics approval, while even those not wanting to use humans may have general health and safety issues. Epidemiological studies have really not been possible at all. We present an open-ended virtual environment, the Island, to help overcome these limitations while still engaging students with study design and data collection. Students work with a population of virtual humans living on the Island and are able to conduct a wide variety of experiments with them as subjects. The Islanders also live in villages, have ancestors and die from a range of diseases, allowing s...
      PubDate: Sun, 27 Feb 2011 12:00:00 GMT
  • A Randomized Experiment Exploring How Certain Features of Clicker Use
           Effect Undergraduate Students' Engagement and Learning in Statistics.
           McGowan, Herle M; Gunderson, Brenda K

    • Abstract: This paper describes a randomized experiment conducted in an undergraduate introductory statistics course that investigated the impact of clickers on students. Specifically, the effects of three features of clicker use on engagement and learning were explored. These features included: 1) the number of questions asked during a class period, 2) the way those questions were incorporated into the material, and 3) the grading or monitoring of clicker use. Several hierarchical linear models of both engagement and learning outcomes were fit. Based on these analyses, there was little evidence that clicker use increased students' engagement. There was some evidence, however, that clicker use improved students' learning. Increases in learning seemed to take place when the clicker questions were well incorporated into the material, particularly if the number of questions asked was low.
      PubDate: Fri, 04 Jun 2010 12:00:00 GMT
  • VISA: Reducing Technological Impact on Student Learning in an Introductory
           Statistics Course. Shaltayev, Dmitriy S.; Hodges, Harland; Hasbrouck,
           Robert B.

    • Abstract: In this empirical study we compare student performance using two different teaching methods in introductory business statistics course. Two groups were taught in the computer lab with software available at students’ fingertips while one was taught in the regular classroom with only a computer workstation for the instructor. VISA (Visual Interactive Statistical Analysis), an Excel-based analysis software package was used in classroom to perform computational analysis of the data in all three groups. Exam data and final course grades indicate that student performance between the two methods was not affected by presence of the software in classroom for use by students. This leads us to conclude that VISA is an intuitive enough tool, which does not require a major learning curve, and can be mastered by students with minimal supervision. Second, we conclude that if the software used for statistics instruction is “teaching-friendly”, then technology availability in the classroom does not affect learning effici...
      PubDate: Fri, 04 Jun 2010 12:00:00 GMT
  • Alternative Representations of Statistical Measures in Computer Tools to
           Promote Communication between Employees in Automotive Manufacturing.
           Bakker, Arthur; Kent, Phillip; Noss, Richard; Hoyles, Celia

    • Abstract: In manufacturing industry, many employees need to interpret and communicate statistical information to monitor and improve production processes. Often the information is reduced to the form of numerical measures, on the logic that numbers are a convenient and understandable type of information to pass among the diverse groups of employees that make up a manufacturing operation. We investigated by means of interviews and observation how several numerical measures, ‘process capability indices’, were used in an automotive factory and how employees were trained to use them. We found that the typical introduction to the measures deployed statistical and algebraic symbolism as well as laborious manual calculations that did not appear to support employees’ understanding of the underlying mathematical relationships. These measures therefore failed to be ‘boundary objects’ – artifacts that inhabit different social worlds and satisfy the informational requirements of each. The goal of our subsequent design-based resear...
      PubDate: Wed, 23 Dec 2009 12:00:00 GMT
  • Discrete Bayes with R. Albert, Jim

    • Abstract: An attractive way of introducing Bayesian thinking is through a discrete model approach where the parameter is assigned a discrete prior. Two generic R functions are introduced for implementing posterior and predictive calculations for arbitrary choices of prior and sampling densities. Several examples illustrate the usefulness of these functions in summarizing the posterior distributions for one and two parameter problems and for comparing models by the use of Bayes factors.
      PubDate: Wed, 23 Dec 2009 12:00:00 GMT
  • Extending Galton's Binomial Quincunx to the Trinomial Septcunx. Harlow,
           Jennifer; Ashman, Bry; Sainudiin, Raazesh

    • Abstract: This paper discusses the development of graphical user interfaces (GUIs) to illustrate sampling from a trinomial distribution by the natural extension of Galton's Quincunx to three dimensions.
      PubDate: Wed, 23 Dec 2009 12:00:00 GMT
  • A Note on Using Individualised Data Sets for Statistics Coursework.
           Shutes, Karl

    • Abstract: This paper addresses the problem of generating a large number of data sets for classes of students that exhibit certain characteristics but which are sufficiently different to minimise the possiblity of plagiarism. A number of R functions are provided to perform the production of the data and the answers to the relevant data.
      PubDate: Wed, 23 Dec 2009 12:00:00 GMT
  • Reasoning about Probabilistic Phenomena: Lessons Learned and Applied in
           Software Design. Lee, Hollylynne S; Lee, J. Todd

    • Abstract: In this paper we provide a glimpse of the iterations of design, research and theorizing of a probability simulation tool, Probability Explorer, that have occurred over the past decade. We provide a brief description of the key features of the technology designed to allow young students opportunities to explore probabilistic situations. This is followed by details about several research observations made in multiple investigations of student explorations with this probability micro-world software package. We then explicate how research results suggest that a focus on a bidirectional interplay between theoretical distribution and empirical data can promote reasoning about probabilistic phenomena, and offer implications for instruction. The paper concludes with a discussion of a next generation innovation in the software for representing a theoretical distribution that we believe may promote better students reasoning about the bidirectional connection between theoretical distributions and empirical data.
      PubDate: Wed, 23 Dec 2009 12:00:00 GMT
  • Social Data Analysis with StatCrunch: Potential Benefits to Statistical
           Education. West, Webster

    • Abstract: StatCrunch ( is an online data analysis package that can be used as a low cost alternative to traditional statistical software for introductory statistics courses. StatCrunch offers a wide array of numerical and graphical routines for analyzing data along with several features such as interactive graphics which can be used for pedagogical purposes. StatCrunch has a number of new features related to social data analysis where users may share data sets and associated analysis results via the StatCrunch site. Users may also interact via online discussions related to shared items. This manuscript provides a brief description of the mechanics of uploading and sharing information via the StatCrunch site and then discusses some of the potential benefits that these social data analysis capabilities offer to both students and instructors.
      PubDate: Tue, 17 Mar 2009 12:00:00 GMT
  • TinkerPlots as a Research Tool to Explore Student Understanding. Watson,
           Jane; Donne, Julie

    • Abstract: This paper explores the use of the dynamic software package, TinkerPlots, as a research tool to assist in assessing students’ understanding of aspects of beginning inference. Two interview protocols used previously with middle school students in printed format without computer software were introduced to a new sample of students through data sets entered in TinkerPlots. The later group of students had experienced a series of lessons using TinkerPlots but the activities were based on different data sets. Of interest in this exploratory study is an analysis of the affordances provided by TinkerPlots to researchers in their quest to assist students in explaining their thinking about the data sets. These are considered in relation to those provided by the format of the earlier interviews.
      PubDate: Tue, 17 Mar 2009 12:00:00 GMT
  • An Innovative Approach to Teaching Online Statistics Courses. Everson,
           Michelle G; Garfield, Joan

    • Abstract: This paper describes two innovative online introductory statistics courses that utilize technology to create unique interactive learning environments. In these courses, technology is used to enable students to collaborate and learn from each other, in addition to learning from required course materials and the instructor. Technology is also introduced into the courses as a way to better illustrate important statistical concepts and provide students with tools to describe and analyze data. In this paper, special attention is paid to the way in which the GAISE recommendations have been implemented in one key component of the online courses: small-group discussion. Evaluative data gathered from students is used to describe how students perceive the discussion component of the courses, as well as how desired learning outcomes are being achieved. The paper concludes with a discussion of lessons learned from teaching an online statistics course, and implications for future development of online staiststics co...
      PubDate: Tue, 30 Dec 2008 12:00:00 GMT
  • A Model to Evaluate Online Educational Resources in Statistics. Ooms, Ann;
           Garfield, Joan

    • Abstract: The Iterative Evaluation Model for Improving Online Educational Resources (IEM) was developed to provide a valid evaluation model to be used to improve online resources, to make them more effective and have a greater positive impact on student learning. The model focuses on the iterative evaluation of four components: (a) evaluation planning, (b) web design and content, (c) use of the educational resource, and (d) educational impact. This paper describes the IEM which was developed as part of the NSF-funded ARTIST (Assessment Resource Tools for Improving Statistical Thinking) project and used to evaluate the online resources developed by this project. The ARTIST evaluation is described in order to illustrate how the IEM may be used.
      PubDate: Tue, 30 Dec 2008 12:00:00 GMT
  • Reconnecting Data and Chance. Konold, Cliff; Kazak, Sibel

    • Abstract: For the past 15 years, pre-university students in many countries including the United States have encountered data analysis and probability as separate, mostly independent strands. Classroom-based research suggests, however, that some of the difficulties students have in learning basic skills in Exploratory Data Analysis stem from a lack of rudimentary ideas in probability. We describe a recent project that is developing materials to support middle-school students in coming to see the “data in chance” and the “chance in data.” Instruction focuses on four main ideas: model fit, distribution, signal-noise, and the Law of Large Numbers. Central to our approach is a new modeling and simulation capability that we are building into a future version of the data-analysis software TinkerPlots. We describe three classroom-tested probability investigations that employ an iterative model-fit process in which students evaluate successive theories by collecting and analyzing data. As distribution features become a focal po...
      PubDate: Tue, 30 Dec 2008 12:00:00 GMT
  • Computing and Introductory Statistics. Kaplan, Daniel

    • Abstract: Much of the computing that students do in introductory statistics courses is based on techniques that were developed before computing became inexpensive and ubiquitous. Now that computing is readily available to all students, instructors can change the way we teach statistical concepts. This article describes computational ideas that can support teaching George Cobb's Three Rs of statistical inference: Randomize, Repeat, Reject.
      PubDate: Fri, 12 Oct 2007 12:00:00 GMT
  • The Introductory Statistics Course: A Ptolemaic Curriculum'. Cobb,
           George W

    • Abstract: As we begin the 21st century, the introductory statistics course appears healthy, with its emphasis on real examples, data production, and graphics for exploration and assumption-checking. Without doubt this emphasis marks a major improvement over introductory courses of the 1960s, an improvement made possible by the vaunted “computer revolution.” Nevertheless, I argue that despite broad acceptance and rapid growth in enrollments, the consensus curriculum is still an unwitting prisoner of history. What we teach is largely the technical machinery of numerical approximations based on the normal distribution and its many subsidiary cogs. This machinery was once necessary, because the conceptually simpler alternative based on permutations was computationally beyond our reach. Before computers statisticians had no choice. These days we have no excuse. Randomization-based inference makes a direct connection between data production and the logic of inference that deserves to be at the core of every introductory cour...
      PubDate: Fri, 12 Oct 2007 12:00:00 GMT
  • Much Has Changed; Little Has Changed: Revisiting the Role of Technology in
           Statistics Education 1992-2007. Rubin, Andee

    • Abstract: The author of this article reflects on the uses of technology in statistics education, comparing the state of the art as described in her article from 1992 with current developments. She reviews five categories of software: software that uses video as data, Geographical Information Systems, graph construction tools, systems with distribution and data manipulation capabilities, and probability generation tools. Considering how software has changed in the past fifteen years, the author argues that while remarkable technological progress has been made, many of the same pedagogical caveats apply as in 1992. These concerns are an integral part of studying the uses of technology as a learning tool in any content area, so it is important that we put them front and center as this journal begins and keep them there as it grows.
      PubDate: Fri, 12 Oct 2007 12:00:00 GMT
  • On Getting More and Better Data Into the Classroom. Finzer, William;
           Erickson, Tim; Swenson, Kirk; Litwin, Matthew

    • Abstract: The authors’ work to develop capabilities for getting data into the data analysis software Fathom™ is described. Heuristics of detecting data on a web page allow drag and drop of a URL into a document. A collaboration with the Minnesota Population Center makes possible sampling from census microdata from 1850 through 2000. With direct support for Vernier sensors, students can build a model during the process of realtime data collection. Finally, a survey capability makes it easy for teachers and students to create simple data entry forms hosted on a web site such that the collated data is instantly downloadable for data analysis in Fathom. By taking some of the drudgery out of gathering data, these capabilities carry implications for teaching and curriculum development; namely that students should have experience throughout their learning with data that they individually have chosen to explore. It is argued that the skills they gain by engaging in exploratory data analysis with self-chosen and self-generated ...
      PubDate: Fri, 12 Oct 2007 12:00:00 GMT
  • The Role of Technology in Improving Student Learning of Statistics.
           Chance, Beth; Ben-Zvi, Dani; Garfield, Joan; Medina, Elsa

    • Abstract: This paper provides a broad overview of the role technological tools can play in helping students understand and reason about important statistical ideas. We summarize recent developments in the use of technology in teaching statistics in light of changes in course content, pedagogical methods, and instructional formats. Issues and practical challenges in selecting and implementing technological tools are presented discussed, and examples of exemplary tools are provided along with suggestions for their use.
      PubDate: Fri, 12 Oct 2007 12:00:00 GMT
  • Using Wiki to Promote Collaborative Learning in Statistics Education.
           Ben-Zvi, Dani

    • Abstract: This article attempts to make a strong case for the use of Wiki to support collaborative learning experiences for students in the statistics classroom. Wiki is an innovative Website that allows all users to add and edit content with relative simplicity. Wiki features empowered learners and bottom-up organization that enable easy authoring of Web content, open access and unrestricted collaboration. We first introduce statistics as a collaborative discipline and therefore compatible with Wiki as a collaborative learning space. We then show evidence that collaboration can improve the learning of individuals in the statistics classroom as well as the whole class. Finally we demonstrate how Wiki can facilitate collaborative learning and bring about instructional change to improve student learning of statistics. We present several types of Wiki-based activities: collaborative writing, glossaries, discussion and review, statistical projects, self-reflective journals, and assessment.
      PubDate: Fri, 12 Oct 2007 12:00:00 GMT
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