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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: 5)
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)
  [2 followers]  Follow
  This is an Open Access Journal Open Access journal
   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
  • Student Approaches to Constructing Statistical Models using TinkerPlots TM
           . Noll, Jennifer; Kirin, Dana

    • Abstract: Statistical literacy skills and technological literacy skills are becoming increasingly entwined as the practice of statistics grows to rely on the power of technology. More and more, statistics educators suggest reforming introductory college statistics courses to include more emphasis on technology and modeling. But what is the impact of such a focus on student learning' This research uses a case study approach, examining two groups of students’ solutions to a statistical inference problem. One group received a reform-oriented curriculum focused on modeling and simulation using technology and another group received a traditional treatment of introductory statistics. We describe fundamental differences in the way these two groups conceived of this statistical inference problem as well as how the technology used in the reform class appeared to reframe students ways of thinking about inference. We also discuss challenges of both approaches for student thinking and share implications for teaching and future res...
      PubDate: Fri, 01 Jan 2016 12:00:00 GMT
  • Comparison of Learning Outcomes for Simulation-based and Traditional
           Inference Curricula in a Designed Educational Experiment. Maurer, Karsten;
           Lock, Dennis

    • Abstract: Conducting inference is a cornerstone upon which the practice of statistics is based. As such, a large portion of most introductory statistics courses is focused on teaching the fundamentals of statistical inference. The goal of this study is to make a formal comparison of learning outcomes under the traditional and simulation-based inference curricula. A randomized experiment was conducted to administer the two curricula to students in an introductory statistics course. Students of the simulation-based curriculum were found to have improved learning outcomes on topics in statistical inference; however, a clear violation of between-student independence due to group administration of curriculum treatments casts considerable doubt on the statistical significance of these results. A simulation study is used to demonstrate the volatility of Type I error rates in educational studies where classroom level covariance structures exist by comparisons are made on the student level.
      PubDate: Fri, 01 Jan 2016 12:00:00 GMT
  • Web Application Teaching Tools for Statistics Using R and Shiny. DOI,

    • Abstract: Technology plays a critical role in supporting statistics education, and student comprehension is improved when simulations accompanied by dynamic visualizations are employed. Many web-based teaching tool applets programmed in Java/Javascript are publicly available (e.g.,, These provide a user-friendly interface which is accessible and appealing to students in introductory statistics courses. However, not all statistics educators are fluent in Java/Javascript and may not be able to tailor these apps or develop their own. Shiny, a web application framework for R created by RStudio, facilitates applet development for educators who are familiar with R. We illustrate the utility, convenience, and versatility of Shiny through our collection of 17 freely available apps covering a range of topics and levels (found at Our Shiny source code is publicly available so that anyone may tailor our apps as desired. We provide feedback on how our app...
      PubDate: Fri, 01 Jan 2016 12:00:00 GMT
School of Mathematical and Computer Sciences
Heriot-Watt University
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Fax: +00 44 (0)131 4513327
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