Traditionally, statistical computing courses have taught the syntax of a particular programming language or specific statistical computation methods. Since Nolan and Temple Lang's seminal paper, we have seen a greater emphasis on data wrangling, reproducible research, and visualization. This shift better prepares students for careers working with…

Teaching programming efficiently to students in the first year of computer science education is challenging. It is especially cumbersome to retain the interest of both groups, when the student group consists of novice (i.e., those who have never programmed before) and expert programmers in the same crowd. Thus, individualized teaching cannot be…

Scientific programming has become increasingly essential for manipulating, visualizing, and interpreting the large volumes of data acquired in earth science research. Yet few discipline-specific instructional approaches have been documented and assessed for their effectiveness in equipping geoscience undergraduate students with coding skills. Here…

Many introductory computer science (CS) courses are intended to address the increased demand for computer literacy and the development of cross-cutting concepts and practices of computational thinking (CT). Colleges and universities offer introductory CS courses every semester toward this end. The issue is centered on how to support CT learning in…

The current and ongoing challenges brought on by climate change will require future scientists who have hands-on experience using advanced molecular techniques, can work with large data sets, and can make correlations between metadata and microbial diversity. A course-embedded research project can prepare students to answer complex research…

Computer Science students need to acquire knowledge about both the hardware and software aspects of computing systems. It is necessary for them to understand how each layer interacts with one another. However, since Graphical User Interfaces have become ubiquitous, the opportunities to interact with the computer via a command prompt as part of…

Learning programming is a painful process for most students, especially those learning text- based programming languages. In this study, based on the principle of Bandura's social learning theory, the vicarious real-life experiences of several pioneers in the field of IT and programming were presented as 15-minutes stories to a group of 9th…

One approach to teaching game design to students with a wide variety of disciplinary backgrounds is through team game projects that span multiple weeks, up to an entire term. However, open-ended, creative projects introduce a gamut of challenges to novice programmers. My goal is to assist game design students with the planning stage of their…

In this paper we present a model for designing professional courses in a blended learning context as a tool to help the interaction between students, teachers and learning resources. This model aims to promote new concepts, new approaches and new strategies that have been changing the paradigm of teaching and learning. To develop a course based on…

Computing technology is reshaping the way in which professionals in the architecture, engineering, and construction industries conduct their business. The execution of construction tasks is changing from traditional 2D to 3D building information modeling (BIM)-based concepts. The use of BIM is expanded and enriched by the introduction of advanced…

It has become increasingly important for future business professionals to understand statistical computing methods as data science has gained widespread use in contemporary organizational decision processes in recent years. Used by scores of academics and practitioners in a variety of fields, Monte Carlo simulation is one of the most broadly…

Data analytics is a rapidly growing field that plays a crucial role in extracting valuable insights from large volumes of data. A data analytics practicum course provides students with hands-on experience in applying data analytics techniques and tools to real-world scenarios. This practicum is intended to serve as a bridge between the student's…

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…

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…