How to use these modules
Many students in psychology, neuroscience, management, and the social sciences enter introductory statistics courses with trepidation, claiming that they are not good with math. The true difficulty that students encounter, however, is not the math, but with the concepts. Most calculations necessary for an undergraduate statistics course do not go beyond a typical 9th or 11th grade curriculum. The conceptual material, however, such as sampling error, unbiased estimators, co-variance, and sampling distributions, is experienced as abstract and students often fail to see their connections with everyday issues or with the data that researchers collect and analyze.
Our overarching aim is to support learners in conceptual understanding and integration of fundamental statistical principles and procedures. Our immediate goal is to provide instructors and students with a set of interactive web-based software tools that foster the connections between the conceptual and the numerical dimensions of basic statistical procedures, modelled upon data-based scenarios that are scaffolded to assist students in building data visualization literacy.
The structure of the modules follows a student-centric design with self-directed study, where activities, resources, and assessments will be designed to reinforce individual learning. Our modular approach, however, will also enable alternate use-cases, such as peer-to-peer activities in asynchronous or synchronous learning environments or discussion tools (blogs, journals, etc.). These modules will be applicable to individual or group assignments in online courses or in the classroom component of hybrid courses.
Module Components
Pre-Test Quiz: Each module contains initial diagnostic test questions. Students may use these diagnostic tests to reaffirm their grasp of the concepts; or, to identify areas in need of further study using the module resources. The comprehensive test is in multiple-choice format. Instructors may also assign the diagnostic tests to measure their students’ level of strengths in basic skills.
Interactive Software Visualizations: Each module includes problem sets designed with its interface to guide students through an exploration of principles and concepts by generating data that fit specific statistical outcomes. We are working across disciplines (psychology, management, and neuroscience) and universities (Guelph) to create appropriate data analysis scenarios. Experience has taught us that having students work backwards, from results to data, facilitates insight into the nature of the concept and the related procedure.
Intro Video and Lessons: While the visualization software is the focus of this project, we have created a set of introductory and recapitulation videos to bookend the software. The introductory video introduces the statistical concepts and principles to be covered, along with the software application in a discipline specific context. The recapitulation videos outline the specific relationships between the conceptual level, the formulae, and the data that students should have discovered as they worked through the problem sets.
Post-Test Assessment: Each module concludes with a series of test questions that the instructor may use as appropriate according to course or program needs.