Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 3 |
Descriptor
Academic Achievement | 3 |
Dropouts | 3 |
Foreign Countries | 3 |
Programming | 3 |
Computer Science Education | 2 |
Academic Persistence | 1 |
At Risk Students | 1 |
Barriers | 1 |
College Faculty | 1 |
Educational Technology | 1 |
Electronic Learning | 1 |
More ▼ |
Author
Bart Mesuere | 1 |
Bram De Wever | 1 |
Charlotte Van Petegem | 1 |
Denis Zhidkikh | 1 |
Feklistova, Lidia | 1 |
Lauri Kettunen | 1 |
Lepp, Marina | 1 |
Luik, Piret | 1 |
Miitta Jarvinen | 1 |
Peter Dawyndt | 1 |
Raija Hämäläinen | 1 |
More ▼ |
Publication Type
Journal Articles | 3 |
Reports - Research | 3 |
Education Level
Higher Education | 2 |
Postsecondary Education | 2 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Denis Zhidkikh; Ville Heilala; Charlotte Van Petegem; Peter Dawyndt; Miitta Jarvinen; Sami Viitanen; Bram De Wever; Bart Mesuere; Vesa Lappalainen; Lauri Kettunen; Raija Hämäläinen – Journal of Learning Analytics, 2024
Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…
Descriptors: Learning Analytics, Prediction, School Holding Power, Academic Achievement
Feklistova, Lidia; Lepp, Marina; Luik, Piret – Education Sciences, 2021
In every course, there are learners who successfully pass assessments and complete the course. However, there are also those who fail the course for various reasons. One of such reasons may be related to success in assessment. Although performance in assessments has been studied before, there is a lack of knowledge on the degree of variance…
Descriptors: Online Courses, Educational Technology, Programming, Learner Engagement
Varga, Erika B.; Sátán, Ádám – Hungarian Educational Research Journal, 2021
The purpose of this paper is to investigate the pre-enrollment attributes of first-year students at Computer Science BSc programs of the University of Miskolc, Hungary in order to find those that mostly contribute to failure on the Programming Basics first-semester course and, consequently to dropout. Our aim is to detect at-risk students early,…
Descriptors: Identification, At Risk Students, Computer Science Education, Undergraduate Students