Despite the increasing use of the statistical programming language R in statistics and data analysis (SDA), its implementation in communication science education is limited. Experiences, recommendations, and a critical exchange are therefore scarce. The following contribution addresses this very gap. At the Department of Journalism and…

Teaching software engineering (SWE) as a core computer science course (ACM, 2013) is a challenging task. The challenge lies in the emphasis on what a large-scale software means, implementing teamwork, and teaching abstraction in software design while simultaneously engaging students into reasonable coding tasks. The abstraction of the system…

The author of this article describes a new undergraduate course where students use Python programming for macroeconomic data analysis and modeling. Students develop basic familiarity with dynamic optimization and simulating linear dynamic models, basic stochastic processes, real business cycle models, and New Keynesian business cycle models.…

A significant activity in the business analytics process is enrichment, which deals with acquiring and combining data from external sources. While different strategies for enrichment are possible, it can be accomplished more efficiently through automation using Python scripts. Since business students may not be immersed in technology skills and…

Over the past few years, academics have undertaken initiatives to bridge the gap between theory and practice in the ever-growing field of business analytics, including implementing real-life student projects in all shapes and forms. Every year since 2015, Manhattan College has invited student teams from across North America and elsewhere in the…

For undergraduate students to be prepared for graduate school and industry, it is imperative that they understand how to merge the theoretical insights gleaned through their undergraduate education with the raw data sets acquired through materials analysis. Thus, the ability to implement data analysis is a vital skill that students should develop.…

Addressing societal issues in civil and environmental engineering increasingly requires skills in data science and programming. To date, there is not much known about the extent students are learning these skills in current civil and environmental engineering curricula. We conducted a survey of accredited civil and environmental engineering…

In the era of big data, many business organizations consider data analytics skills as important criteria in the acquisition of qualified applicants. As numerous managerial decisions in the field of marketing are becoming evidence-based, business schools have integrated case studies about different stages of data analytics such as problem…

In the era of artificial intelligence (AI), big data (BD), and digital transformation (DT), analytics students should gain the ability to solve business problems by integrating various methods. This teaching brief illustrates how two such methods--Bayesian analysis and Markov chains--can be combined to enhance student learning using the Analytics…

In this article, we outline several activities revolving around soccer players who participated in the 2018 FIFA World Cup and 2019 FIFA Women's World Cup. Classroom activities are described from different perspectives, useful for a range of different statistics courses. In a first semester probability theory course, students investigate the…

The proliferation of vast quantities of available datasets that are large and complex in nature has challenged universities to keep up with the demand for graduates trained in both the statistical and the computational set of skills required to effectively plan, acquire, manage, analyze, and communicate the findings of such data. To keep up with…

Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…

Applying Herzberg's motivation-hygiene theory, we studied the determinants of student satisfaction in using R in a Decision Support Systems course that previously used Excel to teach Data Mining and Business Analytics (DMBA). The course is a degree requirement, and prior programming experience is not a prerequisite. We hypothesized that motivators…

Increasingly, students training in the biological sciences depend on a proper grounding in biological statistics, data science and experimental design. As biological datasets increase in size and complexity, transparent data management and analytical methods are essential skills for undergraduate biologists. We propose that using the software R…

Students learn many concepts in the introductory statistics course, but even our most successful students end up with rigid, ritualized knowledge that does not transfer easily to new situations. In this article we describe our attempt to apply theories and findings from learning science to the design of a statistics course that aims to help…