The flipped classroom method, which could be considered as one of the crucial new generation teaching approaches, is a permutation of the educational activities that are carried out inside and outside of the classroom environment. The main purpose of the present study is to determine the impact of the flipped classroom approach on students'…

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…

Machine learning, a subdomain of artificial intelligence, is a widespread technology that is molding how chemists interact with data. Therefore, it is a relevant skill to incorporate into the toolbox of any chemistry student. This work presents a workshop that introduces machine learning for chemistry students based on a set of Python notebooks…

Data science is collaborative and its students should learn teamwork and collaboration. Yet it can be a challenge to fit the teaching of such skills into the data science curriculum. Team-Based Learning (TBL) is a pedagogical strategy that can help educators teach data science better by flipping the classroom to employ small-group collaborative…

Contemporary education calls for innovative strategies to move away from traditional teacher-centered methods to methods that engage students and enhance learning outcomes. This shift toward student-centered learning is crucial for achieving educational goals and making the next generation more adaptable to the modern era. This paper examines the…

The ability to program in R, an open-source statistical program, is increasingly valued across job markets, including ecology. The benefits of teaching R to undergraduates are abundant, but learning to code in R may induce anxiety for students, potentially leading to negative learning outcomes and disengagement. Anecdotes suggest a gender…

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.…

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…

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…

Programming is becoming increasingly common in mathematics degrees as it is a desirable skill for new graduates. However, research shows that its use is mostly restricted to computational or modelling tasks. This paper reports a study on students' perceptions of and difficulties with Lean, an interactive theorem prover introduced as part of a…

In education, space exists for a tool that valorizes generic student course evaluation formats by organizing and recapitulating students' views on the pedagogical practices to which they are exposed. Often, student opinions about a course are gathered using a general comment section that does not solicit feedback concerning specific course…

In this article, we seek to understand how university students learn to use programming as an instrument for 'authentic' mathematical investigations. We use the instrumental approach as a framework, focusing on how the transformation of the programming language into an instrument requires that the user develops or mobilizes multiple schemes at…

University students in other disciplines without prior knowledge in statistics and/or programming language are introduced to the statistical method of decision trees in the programming language R during a 45-minute teaching and practice session. Statistics and programming skills are now frequently required within a wide variety of research fields…

This study aims to provide a descriptive and bibliometric analysis of the trend of artificial intelligence (AI) application in the development of computational thinking (CT) skills in publications from 2007 to 2024. A total of 191 articles were obtained from Scopus database with certain keywords, and analyzed using Biblioshiny and VOSviewer. The…

Data and its applications are increasingly ubiquitous in the rapidly digitizing world and consequently, students across different disciplines face increasing demand to develop skills to answer both academia's and businesses' increasing need to collect, manage, evaluate, apply and extract knowledge from data and critically reflect upon the derived…