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Ankora, Carlos; Bolatimi, Stephen Oladagba; Bensah, Lily; Mahama, Francois; Kuadey, Noble Arden; Adu, Adolph Sedem Yaw; Adjei, Laurene – Journal of Computer Assisted Learning, 2023
Background: The degree to which Computer Science (CS) and Information Communication Technology (ICT) students are motivated to learn greatly impacts their study habits, academic achievement in school and ultimately their job prospects. In recent times, skills in programming languages have become vital in searching for employment. Objective: This…
Descriptors: College Students, Student Motivation, Course Selection (Students), Programming Languages
Katharine Childs; Sue Sentance – International Journal of Computer Science Education in Schools, 2024
Gender balance in computing education is a decades-old issue that has been the focus of much previous research. In K-12, the introduction of mandatory computing education goes some way to giving all learners the opportunity to engage with computing throughout school, but a gender imbalance still persists when computer science becomes an elective…
Descriptors: Computer Science Education, Females, Student Attitudes, Elementary School Students
Crues, R. Wes; Henricks, Genevieve M.; Perry, Michelle; Bhat, Suma; Anderson, Carolyn J.; Shaik, Najmuddin; Angrave, Lawrence – ACM Transactions on Computing Education, 2018
Massive Open Online Courses (MOOCs)--in part, because of their free, flexible, and relatively anonymous nature--may provide a means for helping overcome the large gender gap in Computer Science (CS). This study examines why women and men chose to enroll in a CS MOOC and how this is related to successful behavior in the course by (a) using k-means…
Descriptors: Online Courses, Computer Science Education, Persistence, Gender Differences
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
Zinth, Jennifer – Education Commission of the States, 2016
Allowing high school students to fulfill a math or science high school graduation requirement via a computer science credit may encourage more student to pursue computer science coursework. This Education Trends report is an update to the original report released in April 2015 and explores state policies that allow or require districts to apply…
Descriptors: High School Graduates, Graduation Requirements, Computer Science Education, Educational Trends
Sakurai, Yoshitaka; Dohi, Shinichi; Tsuruta, Setsuo; Knauf, Rainer – Educational Technology & Society, 2009
In high-level education such as university studies, there is a flexible but complicated system of subject offerings and registration rules such as prerequisite subjects. Those offerings, connected with registration rules, should be matched to the students' learning needs and desires, which change dynamically. Students need assistance in such a…
Descriptors: Feasibility Studies, Academic Education, Foreign Countries, College Students
Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Pechenizkiy, Mykola; Calders, Toon; Conati, Cristina; Ventura, Sebastian; Romero, Cristobal; Stamper, John – International Working Group on Educational Data Mining, 2011
The 4th International Conference on Educational Data Mining (EDM 2011) brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large datasets to answer educational research questions. The conference, held in Eindhoven, The Netherlands, July 6-9, 2011, follows the three previous editions…
Descriptors: Academic Achievement, Logical Thinking, Profiles, Tutoring