The heterogeneous data acquired by educational institutes about students' careers (e.g., performance scores, course preferences, attendance record, demographics, etc.) has been a source of investigation for Educational Data Mining (EDM) researchers for over two decades. EDM researchers have primarily focused on course-specific data analyses of…

Educational data mining is widely deployed to extract valuable information and patterns from academic data. This research explores new features that can help predict the future performance of undergraduate students and identify at-risk students early on. It answers some crucial and intuitive questions that are not addressed by previous studies.…

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.…

The aim of this study is to compare the master's (MA) theses in Türkiye (TR) and Finland (FIN) published between 2015-2019. A total of 765 theses were analysed in terms of year, discipline, methodological approach, research method, didactic foci, data collection tool, target group, and sample size. The results showed that FIN theses grounded on…

BRIDGES is a software framework for creating engaging assignments for required courses such as data structures and algorithms. It provides students with a simplified API that populates their own data structure implementations with live and real-world data, and provides the ability for students to easily visualize the data structures they create as…

National failure rates seen in undergraduate introductory CS courses are quite high. In this paper, we develop a predictive model for student in-class performance in an introductory CS course. The model can serve as an early warning system, flagging struggling students who might benefit from additional support. We use a variety of features from…

In the fall of 2009 and in the spring of 2012, supported by the National Institute of General Medical Sciences (NIGMS) in the National Institutes of Health (NIH), we designed a course "Phylogenetic Analysis and Molecular Evolution" (PAME), the first cross-listed course across three different colleges (College of Arts and Sciences,…

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…

The influx of data and the advances in computing have led to calls to update the introductory statistics curriculum to better meet the needs of the contemporary workforce. To this end, we developed the COMputational Practices in Undergraduate TEaching of Statistics (COMPUTES) instrument, which can be used to measure the extent to which computation…

Learning analytics have proved promising capabilities and opportunities to many aspects of academic research and higher education studies. Data-driven insights can significantly contribute to provide solutions for curbing costs and improving education quality. This paper adopts a two-phase machine learning approach, which utilizes both…

Python is a popular, general purpose programming language that is gaining wide adoption in beginning programming courses. This paper describes the development and implementation of an introductory Python course at a business university open to students in a variety of majors and minors. Given the growing number of career opportunities in…

Recent years have witnessed a growing demand for business analytics-oriented curricula. This paper presents the implementation of an introductory Python course at a business university and the attempt to elevate the course's relevance by introducing data analytics topics. The results from a survey of 64 undergraduate students of the course are…

Revisiting the seminal 2010 Nolan and Temple Lang article on the role of computing in the statistics curricula, we discuss several trends that have emerged over the last ten years. The rise of data science has coincided with a broadening audience for learning statistics and using computational packages and tools. It has also increased the need for…