This paper shows a method for integrating computer programming into a standard physical chemistry laboratory sequence to augment student data analysis abilities and allow them to carry programming skills forward to other courses. The Python programming language is used, taking advantage of the pedagogical benefits of Jupyter notebooks, primarily…

To meet the demands of industry, undergraduate business curricula must evolve to prepare analytics-enabled professionals in fields such as finance, accounting, human resource management, and marketing. In this article, we provide a case study of developing a rigorous, integrated finance and data analytics course that was delivered using a…

Integrating computational thinking (CT) into STEM disciplines requires secondary teachers to develop their pedagogical content knowledge of computing and content integration. Experienced teachers who choose to integrate CT in their secondary STEM courses may struggle in the same ways as novice teachers as they learn about programming and its…

We developed an interactive online textbook that interleaves R programming activities with text as a way to facilitate students' understanding of statistical ideas while minimizing the cognitive and emotional burden of learning programming. In this exploratory study, we characterize the attitudes and experiences of 672 undergraduate students as…

Data science is a highly interdisciplinary field that comprises various principles, methodologies, and guidelines for the analysis of data. The creation of appropriate curricula that use computational tools and teaching activities is necessary for building skills and knowledge in data science. However, much of the literature about data science…

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…

Recent educational policies advocate a radical revision of science curricula and pedagogy, to support interdisciplinary practices, a distinguishing feature of contemporary science. Computational modeling (CM) is a core methodology of interdisciplinary science, as such models allow intertwining of data and theoretical perspectives from multiple…

Background and Context: Computational Thinking (CT) has been recently integrated into new and revised Digital Technologies content (DTC) in the Technology learning area of the New Zealand School Curriculum. Objective: To aid this change, this research examined how CT supports learning outcomes in both music and programming with the Sonic Pi…

Data Mining (DM) is one of the most offered courses in data analytics education. However, the design and delivery of DM courses present a number of challenges and issues that stem from the DM's interdisciplinary nature and the industry expectations to generate a broader range of skills from the analytics programs. In this research, we identified…