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Download full textXia, Belle Selene – Journal of Learning Design, 2017
Previous research has shown that, despite the importance of programming education, there is limited research done on programming education experiences from the students' point of view and the need to do so is strong. By understanding the student behaviour, their learning styles, their expectation and motivation to learn, the quality of teaching…
Descriptors: Programming, Higher Education, Educational Theories, Student Centered Learning
Direct linkTaherkhani, Ahmad; Korhonen, Ari; Malmi, Lauri – Computer Science Education, 2012
In this study, we examined freshmen students' sorting algorithm implementations in data structures and algorithms' course in two phases: at the beginning of the course before the students received any instruction on sorting algorithms, and after taking a lecture on sorting algorithms. The analysis revealed that many students have insufficient…
Descriptors: Foreign Countries, Classification, Mathematics, Computer Science Education
Laakso, Mikko-Jussi; Myller, Niko; Korhonen, Ari – Educational Technology & Society, 2009
In this paper, two emerging learning and teaching methods have been studied: collaboration in concert with algorithm visualization. When visualizations have been employed in collaborative learning, collaboration introduces new challenges for the visualization tools. In addition, new theories are needed to guide the development and research of the…
Descriptors: Visualization, Teaching Methods, Classification, Comparative Analysis
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
