Background: Problem-solving competences have evolved into key skills for professionals. Computer-based business simulations enable the analysis of problem-solving processes beyond end results. An important aspect of successful problem-solving is to systematically use built-in tools and process the provided information efficiently. Objectives: This…

This research examines the application of students' computational thinking (CT) in solving numerical method problems through computer software. Data collection involved observing their learning process and conducting tests to evaluate their CT skills within the context of the root approach material using Newton-Raphson method. The results indicate…

Computational thinking is seen as a basic and essential skill in the 21st century, but its development issue in accounting education is still relatively limited. Therefore, anchored in Wing's (2006) computational thinking theory, this study makes a case for developing problem-solving skills, which involve abstraction, decomposition,…

In today's global economy, the origin of the food we eat is becoming more and more difficult to identify. Verifying the authenticity of products to protect supply chains is a complicated problem that requires a multidisciplinary approach. Chemical authentication of foodstuffs often includes a mass spectrometer detector; however, they are costly…

There are a variety of discrete facility location models that have practical relevance for operations management and management science courses. Integer linear programming (ILP) is the standard technique for solving such problems. An alternative approach that is often conceptually appealing to students is to pose the problem as one of finding the…

Logistic regression is one of the most fundamental tools in predictive analytics. Graduate business analytics students are often familiarized with implementation of logistic regression using Python, R, SPSS, or other software packages. However, an understanding of the underlying maximum likelihood model and the mechanics of estimation are often…

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…

This paper presents the results of an exploratory case study that examined a veteran secondary teacher's knowledge for teaching non-routine mathematical problem-solving with digital technologies. Data was collected through the observation of a veteran mathematics teacher, in real time, solving a mathematical problem with the digital tools of his…

Extant research has demonstrated that problem-posing and problem-solving mutually affect one another. However, the exact nature and extent of this relationship requires a detailed elaboration. This is especially true when adidactical problem-posing arises within a problem-solving context. In this study, we analyze the scripting journey used by two…

In Hungary, K-12 informatics/computer science education focuses on mostly surface-based methods. This approach can be observed in the teaching of several topics in the subject, of which we focus on spreadsheet management. This is further emphasized by regulatory documents -- the Hungarian National Core Curriculum and Hungarian Curriculum…

In this research we investigate how mathematics teachers, as graduate students, estimate the value of [pi] by exploring the problem of "squaring the circle" using digital technology. Initially, we mention some aspects of teaching and learning of calculus in the literature, emphasizing studies that use the notion of humans-with-media to…

The purpose of this study is to examine the effect of randomized versus nonrandomized data using an Excel case study project to measure students' academic performance. Specifically, the study examines whether randomized data strengthens students' analytical, problem-solving, and Excel skills while manipulating and analyzing accounting data. The…

Previous research proved that teaching spreadsheeting from a programming perspective is much more effective than the widely accepted tool-centered surface approach methods. Spreadsheeting as an introductory programming approach allows students to build up schemata leading to contextualized, concept-based problem-solving. Furthermore, it provides…

The scale-invariant way to analyze two-dimensional experimental and theoretical data with statistical errors in both the independent and dependent variables is revisited by using what we call the triangular linear regression method. This is compared to the standard least-squares fit approach by applying it to typical simple sets of example data…

This paper presents issues related to the use of technology by secondary school pre-service mathematics teachers engaged in open mathematical modelling projects. Pre-service teachers developed these projects within a regular mathematics education course during the teacher education program at the university concerned. This environment, called a…