Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 2 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 3 |
Descriptor
Academic Persistence | 3 |
Foreign Countries | 3 |
Programming | 3 |
Academic Achievement | 2 |
Computer Science Education | 2 |
Dropouts | 2 |
Electronic Learning | 2 |
Introductory Courses | 2 |
Models | 2 |
Prediction | 2 |
Prior Learning | 2 |
More ▼ |
Author
Publication Type
Journal Articles | 2 |
Reports - Research | 2 |
Collected Works - Proceedings | 1 |
Education Level
Higher Education | 3 |
Postsecondary Education | 3 |
Elementary Education | 1 |
Grade 6 | 1 |
Intermediate Grades | 1 |
Junior High Schools | 1 |
Middle Schools | 1 |
Secondary Education | 1 |
Audience
Location
Finland | 3 |
France | 1 |
Laws, Policies, & Programs
Assessments and Surveys
Program for International… | 1 |
What Works Clearinghouse Rating
Antti-Jussi Lakanen; Ville Isomöttönen – Informatics in Education, 2023
This research investigates university students' success in their first programming course (CS1) in relation to their motivation, mathematical ability, programming self-efficacy, and initial goal setting. To our knowledge, these constructs have not been measured in a single study before in the Finnish context. The selection of the constructs is in…
Descriptors: Foreign Countries, College Students, Student Motivation, Self Efficacy
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
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