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Student Performance in Computing Education: An Empirical Analysis of Online Learning in Programming Education Environments
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Xia, Belle Selene; Liitiäinen, Elia – European Journal of Engineering Education, 2017
The benefits of using online exercises have been analysed in terms of distance learning, automatic assessment and self-regulated learning. In this study, we have not found a direct proportional relationship between student performance in the course exercises that use online technologies and the exam grades. We see that the average submission rate…
Descriptors: Computer Science Education, Electronic Learning, Programming, Academic Achievement
The Impact of Prior Programming Knowledge on Lecture Attendance and Final Exam
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Veerasamy, Ashok Kumar; D'Souza, Daryl; Lindén, Rolf; Laakso, Mikko-Jussi – Journal of Educational Computing Research, 2018
In this article, we report the results of the impact of prior programming knowledge (PPK) on lecture attendance (LA) and on subsequent final programming exam performance in a university level introductory programming course. This study used Spearman's rank correlation coefficient, multiple regression, Kruskal-Wallis, and Bonferroni correction…
Descriptors: Prior Learning, Programming, Computer Science Education, Lecture Method
On Study Habits on an Introductory Course on Programming
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Willman, Salla; Lindén, Rolf; Kaila, Erkki; Rajala, Teemu; Laakso, Mikko-Jussi; Salakoski, Tapio – Computer Science Education, 2015
Computer aided assessment systems enable the collection of exact time and date information on students' activity on a course. These activity patterns reflect students' study habits and these study habits further predict students' likelihood to pass or fail a course. By identifying such patterns, those who design the courses can enforce positive…
Descriptors: Foreign Countries, Study Habits, Introductory Courses, Programming
Proceedings of the Seventh International Conference on Educational Data Mining (EDM) (7th, London, United Kingdom, July 4-7, 2014)
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Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection