CS for All: Catering to Diversity of Master's Students through Assignment Choices

Alhazmi, S, Hamilton, M and Thevathayan, C 2018, 'CS for All: Catering to Diversity of Master's Students through Assignment Choices', in Proceedings of the 49th ACM Technical Symposium on Computer Science Education, Baltimore, 21-24 February 2018, pp. 38-43.


Document type: Conference Paper
Collection: Conference Papers

Title CS for All: Catering to Diversity of Master's Students through Assignment Choices
Author(s) Alhazmi, S
Hamilton, M
Thevathayan, C
Year 2018
Conference name SIGCSE 2018
Conference location Baltimore
Conference dates 21-24 February 2018
Proceedings title Proceedings of the 49th ACM Technical Symposium on Computer Science Education
Publisher ACM Digital Library
Place of publication Maryland, United States
Start page 38
End page 43
Total pages 6
Abstract Increasingly, students enrolled into foundational CS courses such as programming fundamentals include those from many non-CS majors including Data Analytics, Business, Science and Social Sciences. Staff teaching foundational programming courses must therefore cater for varying student backgrounds, cognitive abilities and interests while teaching abstract concepts such as encapsulation, inheritance and polymorphism. In the past assignments played a major role in learning such abstract concepts as they allowed students to construct their own meanings experientially. However, a single assignment in a given domain pitched at an average student cannot cater effectively to students with varying cognitive abilities and backgrounds resulting in poor learning outcomes and student satisfaction. In this paper we report our experience, substantially improving learning outcomes and student satisfaction in a Master's level introductory programming course with weak learning outcomes and poor student satisfaction by offering a choice of assignments. Our novel approach requires designing assignments which take into account the interests of students and their zone of proximal development which determines the extent to which a learner can grasp new concepts. Our pre and post assignment tests and survey feedback clearly show a substantial improvement in learning outcomes and student perception.
Subjects Computer-Human Interaction
Education not elsewhere classified
Keyword(s) Assessment Design
Novice Programming
DOI - identifier 10.1145/3159450.3159464
Copyright notice © 2018 Association for Computing Machinery
ISBN 9781450351034
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