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Wolz, Sabine; Bergande, Bianca; Brune, Philipp – Cogent Education, 2022
Programming is an essential part of the curriculum of computer science non-major students. The motivation for the various elements of interdisciplinary degrees is often very low in computer science, which faces a gender gap as well. Differences between study courses and gender in confidence, attitude, student numbers, and motivation in computer…
Descriptors: Introductory Courses, Gender Differences, Computer Science Education, Nonmajors
Secules, Stephen; Gupta, Ayush; Elby, Andrew; Turpen, Chandra – Journal of Engineering Education, 2018
Background: To explain educational problems such as student attrition, engineering education literature often focuses on the characteristics of individuals. In 2006, Ray McDermott and Hervé Varenne called for examining the "cultural construction" of educational problems, uncovering how multiple actors create and inscribe meaning to the…
Descriptors: Undergraduate Students, Engineering Education, School Holding Power, Student Characteristics
Vieira, Camilo; Magana, Alejandra J.; Roy, Anindya; Falk, Michael L. – Cognition and Instruction, 2019
Creating explanations is an important process for students, not only to make connections between novel information and background knowledge, but also to be able to communicate their understanding of any given topic. This article explores students' explanations in the context of computational science and engineering, an important interdisciplinary…
Descriptors: Student Attitudes, Comprehension, Computation, Programming
Silva-Maceda, Gabriela; Arjona-Villicaña, P. David; Castillo-Barrera, F. Edgar – IEEE Transactions on Education, 2016
Learning to program is a complex task, and the impact of different pedagogical approaches to teach this skill has been hard to measure. This study examined the performance data of seven cohorts of students (N = 1168) learning programming under three different pedagogical approaches. These pedagogical approaches varied either in the length of the…
Descriptors: Programming, Teaching Methods, Intermode Differences, Cohort Analysis
Williams, Julie Ann Stuart; Stanny, Claudia J.; Reid, Randall C.; Hill, Christopher J.; Rosa, Katie Martin – Journal of Education for Business, 2015
Frequently in Management Science courses, instructors focus primarily on teaching students the mathematics of linear programming models. However, the ability to discuss mathematical expressions in business terms is an important professional skill. The authors present an analysis of student abilities to discuss management science concepts through…
Descriptors: Educational Practices, Mathematical Applications, Programming, Administrator Education
Hamer, John; Purchase, Helen; Luxton-Reilly, Andrew; Denny, Paul – Assessment & Evaluation in Higher Education, 2015
We report on a study comparing peer feedback with feedback written by tutors on a large, undergraduate software engineering programming class. Feedback generated by peers is generally held to be of lower quality to feedback from experienced tutors, and this study sought to explore the extent and nature of this difference. We looked at how…
Descriptors: Feedback (Response), Programming, Engineering Education, Undergraduate Students
Yoder, S. Elizabeth; Kurz, M. Elizabeth – Journal of Education for Business, 2015
Linear programming (LP) is taught in different departments across college campuses with engineering and management curricula. Modeling an LP problem is taught in every linear programming class. As faculty teaching in Engineering and Management departments, the depth to which teachers should expect students to master this particular type of…
Descriptors: Programming, Educational Practices, Engineering, Engineering Education
Robins, Anthony – Computer Science Education, 2010
Compared to other subjects, the typical introductory programming (CS1) course has higher than usual rates of both failing and high grades, creating a characteristic bimodal grade distribution. In this article, I explore two possible explanations. The conventional explanation has been that learners naturally fall into populations of programmers and…
Descriptors: Programming, Learning Processes, Grading, Simulation
Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction