Inferential reasoning is an integral part of science and civic society, but research shows that it is a problematic domain for many people. One possibility for a more accessible approach to inferential reasoning is to use randomization tests via computer simulations. A case study was conducted with primary preservice teachers after they had passed…

Using software to teach statistical inference in introductory courses opens the door for methods and practices that are more conceptually appealing to students. With an increasing number of fields requiring competency in statistics including data science, natural and social sciences, public health and more, it is crucial that we as instructors…

R is becoming the standard for teaching statistics due to its flexibility, and open-source nature, replacing software programs like Minitab and SPSS. The main driver for reform within Scottish statistical undergraduate programs is the creation of the Scottish Qualification Authority's Higher Applications of Mathematics course which has statistics…

The flipped classroom (FC) is a pedagogical model with an active learning concept and a hybrid course design that reverses the typical lecture process. Given the widespread use of online delivery methods, there is a need to explore the FC in delivering statistics courses. This study employs a prospective quasi-experimental study design to evaluate…

Background/purpose: This study addresses the lack of statistical thinking skills among Applied College students, a key requirement for professional success. Traditional statistics education focuses on procedural and computational methods rather than conceptual understanding, leading to misconceptions and difficulties in data organization,…

The statistical package chosen to aid in teaching quantitative methods is at the instructor's discretion, but little research has investigated student attitude toward these different packages. This study compared Google Sheets, a spreadsheet package similar to Microsoft Excel, and a traditional package, SPSS, to determine which of the two programs…

Laboratory automation and data science are valuable new skills for all chemists, but most pedagogical activities involving automation to date have focused on upper-level coursework. Herein, we describe a combined computational and experimental lab suitable for a first-year undergraduate general chemistry course, in which these topics are…

Data science has become an increasingly popular topic among engineering students and practitioners as high-profile engineering applications of machine learning and artificial intelligence continue to make headlines. Companies in engineering domains are placing a growing emphasis on hiring engineers who can extract insights and create value from…

Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…

With reference to the framework in The International Data Science in Schools Project, this paper aims to discuss the course design, teaching and learning, and assessment of a foundation course offered in an undergraduate statistics and data science programme. SAS® University Edition (a free software package) is adopted in this foundation course.…

Despite the centrality of data analysis to the discipline, sociology departments are currently falling short of teaching both undergraduate and graduate students crucial computing and statistical software skills. We argue that sociology instructors must intentionally and explicitly teach computing skills alongside statistical concepts to prepare…

This paper proposes a framework for integrating generative artificial intelligence (AI) tools into statistical training for Doctor of Education (EdD) students. The rigorous demands of doctoral education, coupled with the challenges of learning complex statistical software and coding language, often lead to anxiety and frustration among students,…

Statistical software is commonly used in undergraduate social sciences statistics courses. Due to the increase in online/hybrid courses and the cost of SPSS, instructors may wish to switch to another statistical software. We cover seven programs: Excel, Google Sheets, jamovi, JASP, PSPP, R, and SOFA. We compare programs using the following…

Support vector classifiers are one of the most popular linear classification techniques for binary classification. Different from some commonly seen model fitting criteria in statistics, such as the ordinary least squares criterion and the maximum likelihood method, its algorithm depends on an optimization problem under constraints, which is…

The current study sought to evaluate the SASTSc in two samples of students taking a statistics course that incorporates statistical software. The SASTSc was given at two time points, once at the beginning of the semester and then again at the end of the semester. Our evaluation included examining competing factor analytic models, examining…