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Maqsood, Rabia; Ceravolo, Paolo; Ahmad, Muhammad; Sarfraz, Muhammad Shahzad – International Journal of Educational Technology in Higher Education, 2023
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…
Descriptors: Foreign Countries, Computer Science, Undergraduate Students, Private Colleges
Wen-shuang Fu; Jia-hua Zhang; Di Zhang; Tian-tian Li; Min Lan; Na-na Liu – Journal of Educational Computing Research, 2025
Cognitive ability is closely associated with the acquisition of programming skills, and enhancing learners' cognitive ability is a crucial factor in improving the efficacy of programming education. Adaptive feedback strategies can provide learners with personalized support based on their learning context, which helps to stimulate their interest…
Descriptors: Feedback (Response), Cognitive Ability, Programming, Computer Science Education
Richards, Bryant; Kolodziejczak, Nicholas; Mentzer, Kevin; Calnan, Kerry – Information Systems Education Journal, 2023
Organizations are keenly interested in employees trained in business analysis and robotic process automation. This is because those methods are growing in demand for improving efficiency in business processes. Business students exiting college must understand how to map out business processes and implement automation fundamentals to be competitive…
Descriptors: Robotics, Business Administration Education, Automation, Employment Potential
Zareen Alamgir; Habiba Akram; Saira Karim; Aamir Wali – Informatics in Education, 2024
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.…
Descriptors: Data Analysis, Information Retrieval, Content Analysis, Information Technology
Dorodchi, Mohsen; Dehbozorgi, Nasrin; Fallahian, Mohammadali; Pouriyeh, Seyedamin – Informatics in Education, 2021
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…
Descriptors: Computer Science Education, Computer Software, Teaching Methods, Undergraduate Students
Jenkins, Brian C. – Journal of Economic Education, 2022
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.…
Descriptors: Undergraduate Students, Programming Languages, Macroeconomics, Familiarity
Ozlem Oktay; Ilknur Reisoglu; Seyda Gul; Dilek Teke; Mustafa Sozbilir; Ilayda Gunes; Rumeysa Yildiz; Gulsah Atila; Aysegul Yazar; Lauri Malmi; Päivi Kinnunen; Jarkko Lampiselkä; Arja Kaasinen – Scandinavian Journal of Educational Research, 2025
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…
Descriptors: Foreign Countries, Masters Theses, STEM Education, Intellectual Disciplines
David Burlinson; Matthew Mcquaigue; Alec Goncharow; Kalpathi Subramanian; Erik Saule; Jamie Payton; Paula Goolkasian – Education and Information Technologies, 2024
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…
Descriptors: Computer Science Education, Majors (Students), Student Interests, College Faculty
Paassen, Benjamin; McBroom, Jessica; Jeffries, Bryn; Koprinska, Irena; Yacef, Kalina – Journal of Educational Data Mining, 2021
Educational data mining involves the application of data mining techniques to student activity. However, in the context of computer programming, many data mining techniques can not be applied because they require vector-shaped input, whereas computer programs have the form of syntax trees. In this paper, we present ast2vec, a neural network that…
Descriptors: Data Analysis, Programming Languages, Networks, Novices
Schwieger, Dana – Information Systems Education Journal, 2023
Many small organizations sponsor events and activities that could benefit from the data management and reporting capabilities provided through a centralized database. However, many of those organizations do not have the budget to afford a commercial solution or an on-going subscription to a cloud-based solution for a small scope event with limited…
Descriptors: Databases, Computer Software, Information Systems, Volunteers
Abdur R. Shahid; Sushma Mishra – Journal of Information Systems Education, 2024
Due to the increasing demand for efficient, effective, and profitable applications of Artificial Intelligence (AI) in various industries, there is an immense need for professionals with the right skills to meet this demand. As a result, several institutions have started to offer AI programs. Yet, there is a notable gap in academia: the absence of…
Descriptors: Masters Programs, Information Systems, Computer Science Education, Artificial Intelligence
Gitinabard, Niki; Okoilu, Ruth; Xu, Yiqao; Heckman, Sarah; Barnes, Tiffany; Lynch, Collin – International Educational Data Mining Society, 2020
Teamwork, often mediated by version control systems such as Git and Apache Subversion (SVN), is central to professional programming. As a consequence, many colleges are incorporating both collaboration and online development environments into their curricula even in introductory courses. In this research, we collected GitHub logs from two…
Descriptors: Teamwork, Group Activities, Student Projects, Programming
Naseem, Mohammed; Chaudhary, Kaylash; Sharma, Bibhya – Education and Information Technologies, 2022
The need for a knowledge-based society has perpetuated an increasing demand for higher education around the globe. Recently, there has been an increase in the demand for Computer Science professionals due to the rise in the use of ICT in the business, health and education sector. The enrollment numbers in Computer Science undergraduate programmes…
Descriptors: College Freshmen, Student Attrition, School Holding Power, Dropout Prevention
Hunt-Isaak, Noah; Cherniavsky, Peter; Snyder, Mark; Rangwala, Huzefa – International Educational Data Mining Society, 2020
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…
Descriptors: Textbooks, Surveys, Grade Prediction, Undergraduate Students
Yoshida, R.; Page, R. – PRIMUS, 2022
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,…
Descriptors: Molecular Biology, Evolution, Molecular Structure, Graduate Students