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Thin-Yin Leong; Nang-Laik Ma – INFORMS Transactions on Education, 2024
This paper develops a spreadsheet simulation methodology for teaching simulation and performance analysis of priority queues with multiple servers, without resorting to macros, add-ins, or array formula. The approach is made possible by a "single overtaking" simplifying assumption under which any lower-priority customer may be passed in…
Descriptors: Spreadsheets, Simulation, Teaching Methods, Computer Science Education
Gyuhun Jung; Markel Sanz Ausin; Tiffany Barnes; Min Chi – International Educational Data Mining Society, 2024
We presented two empirical studies to assess the efficacy of two Deep Reinforcement Learning (DRL) frameworks on two distinct Intelligent Tutoring Systems (ITSs) to exploring the impact of Worked Example (WE) and Problem Solving (PS) on student learning. The first study was conducted on a probability tutor where we applied a classic DRL to induce…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Artificial Intelligence, Teaching Methods
Joe Michael Allen – ProQuest LLC, 2021
A well-run introductory CS1 course is essential for all students within CS education. CS1 is necessary to keep students in the major and important to attract non-majors to the CS field. Unfortunately, there are many well-known issues that most CS1 courses have in common: high drop rates, low retention, high student stress, student struggle,…
Descriptors: Undergraduate Students, Computer Science Education, Computer Science, Required Courses
Gerit Wagner; Laureen Thurner – Journal of Information Systems Education, 2025
Git, as the leading version-control system, is frequently employed by software developers, digital product managers, and knowledge workers. Information systems (IS) students aspiring to fill software engineering, management, or research positions would therefore benefit from familiarity with Git. However, teaching Git effectively can be…
Descriptors: Computer Science Education, Information Systems, Teaching Methods, Computer Software
Michele Scalera; Agostino Marengo; Vita Santa Barletta; Danilo Caivano; Giovanni Dimauro; Jenny Pange – Education and Information Technologies, 2025
Computer architecture is considered one of the dry and hard-to-learn courses for students in the computer science discipline. Therefore, educational institutions experiment with different pedagogical approaches to enhance students' performance and interest in courses. This study introduces a Simplified Approach to Teach a Processor (SAtTaP), a…
Descriptors: Computer Science Education, Teaching Methods, Computer System Design, Undergraduate Students
Dan Sun; Fan Xu – Journal of Educational Computing Research, 2025
Real-time collaborative programming (RCP), which allows multiple programmers to work concurrently on the same codebase with changes instantly visible to all participants, has garnered considerable popularity in higher education. Despite this trend, little work has rigorously examined how undergraduates engage in collaborative programming when…
Descriptors: Cooperative Learning, Programming, Computer Science Education, Undergraduate Students
Haley A. Delcher; Enas S. Alsatari; Adeyeye I. Haastrup; Sayema Naaz; Lydia A. Hayes-Guastella; Autumn M. McDaniel; Olivia G. Clark; Devin M. Katerski; Francois O. Prinsloo; Olivia R. Roberts; Meredith A. Shaddix; Bridgette N. Sullivan; Isabella M. Swan; Emily M. Hartsell; Jeffrey D. DeMeis; Sunita S. Paudel; Glen M. Borchert – Biochemistry and Molecular Biology Education, 2025
Today, due to the size of many genomes and the increasingly large sizes of sequencing files, independently analyzing sequencing data is largely impossible for a biologist with little to no programming expertise. As such, biologists are typically faced with the dilemma of either having to spend a significant amount of time and effort to learn how…
Descriptors: Artificial Intelligence, Technology Uses in Education, Training, Teaching Methods
Ruijie Zhou; Chong Xie; Xiuling He; Yangyang Li; Qiong Fan; Ying Yu; Zhonghua Yan – Journal of Educational Computing Research, 2024
Computational thinking (CT), an essential competency for comprehending and addressing intricate issues in the digital world, has been incorporated into curriculum planning as a goal for programming education. This study introduced flow design into programming curricula to investigate its impact on undergraduates 'CT skills during pair work. Two…
Descriptors: Undergraduate Students, Thinking Skills, Computation, Programming
Jonathan Liu; Seth Poulsen; Erica Goodwin; Hongxuan Chen; Grace Williams; Yael Gertner; Diana Franklin – ACM Transactions on Computing Education, 2025
Algorithm design is a vital skill developed in most undergraduate Computer Science (CS) programs, but few research studies focus on pedagogy related to algorithms coursework. To understand the work that has been done in the area, we present a systematic survey and literature review of CS Education studies. We search for research that is both…
Descriptors: Teaching Methods, Algorithms, Design, Computer Science Education
Sharmin, Sadia – ACM Transactions on Computing Education, 2022
Computer science is a fast-growing field in today's digitized age, and working in this industry often requires creativity and innovative thought. An issue within computer science education, however, is that large introductory programming courses often involve little opportunity for creative thinking within coursework. The undergraduate…
Descriptors: Creativity, Computer Science Education, Literature Reviews, Introductory Courses
Xiaojun Luo; Ismail Adelopo – Journal of International Education in Business, 2025
Purpose: This study aims to develops an interdisciplinary business and computer science pedagogy for teaching and learning computer programming in business schools at higher education institutions and explores its associated benefits, challenges and improvement. Design/methodology/approach: Based on a body of theories, an interdisciplinary…
Descriptors: Teaching Methods, Educational Opportunities, Difficulty Level, Business Administration Education
Amelia McNamara – Journal of Statistics and Data Science Education, 2024
When incorporating programming into a statistics course, there are many pedagogical considerations. In R, one consideration is the particular R syntax used. This article reports on a head-to-head comparison of a pair of introductory statistics labs, one conducted in the formula syntax, the other in tidyverse. Pre- and post-surveys show minimal…
Descriptors: Teaching Methods, Introductory Courses, Statistics Education, Programming Languages
Paul Mayer; Rich Baraniuk – ACM Transactions on Computing Education, 2025
It is argued that logic, and in particular mathematical logic, should play a key role in the undergraduate curriculum for students in the computing fields, which include electrical engineering (EE), computer engineering (CE), and computer science (CS). This is based on (1) the history of the field of computing and its close ties with logic, (2)…
Descriptors: Teaching Methods, Logical Thinking, Computer Science Education, Engineering Education
Dorian Stoilescu; Andreea Molnar – ACM Transactions on Computing Education, 2025
This article explores differences between women's and men's views on teaching and learning in undergraduate computer science studies at a Canadian university. The research focuses on perceptions and experiences about learning activities and teaching computer science and how students and teachers view these aspects as valuable for these activities.…
Descriptors: Foreign Countries, Undergraduate Students, Computer Science Education, Preferences
Xu, Weiqi; Wu, Yajuan; Ouyang, Fan – International Journal of Educational Technology in Higher Education, 2023
Pair programming (PP), as a mode of collaborative problem solving (CPS) in computer programming education, asks two students work in a pair to co-construct knowledge and solve problems. Considering the complex multimodality of pair programming caused by students' discourses, behaviors, and socio-emotions, it is of critical importance to examine…
Descriptors: Cooperative Learning, Problem Solving, Computer Science Education, Programming

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