Collaborative learning: a case study for CS1 at Grinnell College and Austin
SIGCSE '97 Proceedings of the twenty-eighth SIGCSE technical symposium on Computer science education
Why? When an otherwise successful intervention fails
ITiCSE '99 Proceedings of the 4th annual SIGCSE/SIGCUE ITiCSE conference on Innovation and technology in computer science education
A framework approach to teaching data structures
SIGCSE '03 Proceedings of the 34th SIGCSE technical symposium on Computer science education
The role of the data structures course in the computing curriculum
Journal of Computing Sciences in Colleges
The dimensions of variation in the teaching of data structures
Proceedings of the 9th annual SIGCSE conference on Innovation and technology in computer science education
Design process for a non-majors computing course
Proceedings of the 36th SIGCSE technical symposium on Computer science education
Collaborative, problem-based learning in computer science
Journal of Computing Sciences in Colleges
FIE '01 Proceedings of the Frontiers in Education Conference, 2001. 31st Annual - Volume 02
Problem solving and student performance in data structures and algorithms
Proceedings of the 12th annual SIGCSE conference on Innovation and technology in computer science education
Treisman workshops for computer science
Journal of Computing Sciences in Colleges
ACM SIGCSE Bulletin
Student-generated active-learning exercises
Proceedings of the 40th ACM technical symposium on Computer science education
Proceedings of the 40th ACM technical symposium on Computer science education
Journal of Computing Sciences in Colleges
Experiences with active learning in CS 3
Journal of Computing Sciences in Colleges
Study habits of CS1 students: what do they do outside the classroom?
Proceedings of the Twelfth Australasian Conference on Computing Education - Volume 103
ITiCSE 2010 working group report motivating our top students
Proceedings of the 2010 ITiCSE working group reports
Helping first year novice programming students PASS
ACE '11 Proceedings of the Thirteenth Australasian Computing Education Conference - Volume 114
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Active learning techniques, including collaborative programming and problem solving environments, have been widely adopted by many computer science educators. A related approach is the Treisman model, which was originally designed for the first-year calculus course and involves intensive workshops where students collaborate in small groups to solve problems. We have adapted the model for both the data structures and algorithms courses at our institution. Regression analysis indicates that students who participate in the workshops for the algorithms course perform better (0.561 grade points on a 4-point scale) than those who do not, even after accounting for prior academic performance. However, the workshops appear to have less of an effect on student grades in the data structures course. This study provides evidence that the workshop model can be an effective learning environment for students in courses primarily involving analysis, but that for courses that involve large amounts of programming, further adaptations to the model might be needed.