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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
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Scott, Michael James; Counsell, Steve; Lauria, Stanislao; Swift, Stephen; Tucker, Allan; Shepperd, Martin; Ghinea, Gheorghita – IEEE Transactions on Education, 2015
Computer programming is notoriously difficult to learn. To this end, regular practice in the form of application and reflection is an important enabler of student learning. However, educators often find that first-year B.Sc. students do not readily engage in such activities. Providing each student with a programmable robot, however, could be used…
Descriptors: Robotics, Introductory Courses, Programming, Educational Practices
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Blikstein, Paulo; Worsley, Marcelo; Piech, Chris; Sahami, Mehran; Cooper, Steven; Koller, Daphne – Journal of the Learning Sciences, 2014
New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…
Descriptors: Programming, Computer Science Education, Learning Processes, Introductory Courses
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Ford, Marilyn; Venema, Sven – Journal of Information Technology Education, 2010
With universities having difficulty attracting students to study information technology (IT), the scores needed for entry into IT degrees have dropped markedly. IT schools are thus having to cope by adjusting their introductory courses to ensure that students will still learn what is expected but without negatively impacting on pass rates. This…
Descriptors: Fundamental Concepts, Introductory Courses, Multiple Choice Tests, Information Technology
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Ventura, Philip R., Jr. – Computer Science Education, 2005
The paper reports on an examination of predictors of success for an "objects-first" course. The predictors considered included prior programming experience, mathematical ability, academic and psychological variables, gender, and measures of student effort. Cognitive and academic factors such as SAT scores and critical thinking ability…
Descriptors: Academic Achievement, Predictor Variables, Computer Science Education, Programming