Interactive Learning of Greedy Algorithms: from the Individual to the Collaborative
- Speaker: Dr. Ouafae Debdi recently, LKL, Birkbeck, University of London.
- Date: Thursday, 2 July 2015 from 15:00
- Location: Room TBC, Birkbeck Main Building
The main contribution of this work is the creation of a unique teaching method that integrates the experimental and collaborative pedagogical taxonomies for the learning of greedy algorithms which has been evaluated positively with respect to its usability, efficiency, and student motivation. On the other hand, when teaching methodology is consistent with the student’s learning style, the learning process is more efficient; therefore, we studied the relationship that may exist in applying two different teaching methods (traditional and active learning) regarding the educational efficiency and students’ motivation in learning of greedy algorithms using the model of Felder-Silverman.
Bio: Dr. Ouafae Debdi received a BSc in Management and Computing in 2007, two MSc degrees in Computer Science and Statistics in 2008 and 2009 respectively, and a PhD degree in Computer Science in 2014 all from Rey Juan Carlos University of Madrid (Spain). Currently a honorary collaborator at the Laboratory of Information Technologies in Education, research interests include human-computer interaction and software for programming.