Teaching growth of functions using equivalence classes: an alternative to big O notation
Proceedings of the 35th SIGCSE technical symposium on Computer science education
Didactic strategies for promoting significant learning in formal languages and automata theory
Proceedings of the 9th annual SIGCSE conference on Innovation and technology in computer science education
Teaching bit-level algorithm analysis to the undergraduates in computer science
ACM SIGCSE Bulletin
Personalizing and discussing algorithms within CS1 studio experiences: an observational study
Proceedings of the first international workshop on Computing education research
Using O(n) ProxmapSort and O(1) ProxmapSearch to motivate CS2 students (Part I)
ACM SIGCSE Bulletin
Reductive thinking in undergraduate CS courses
Proceedings of the 11th annual SIGCSE conference on Innovation and technology in computer science education
What do teachers teach in introductory programming?
Proceedings of the second international workshop on Computing education research
A big-O experiment: which function is it?
Proceedings of the 43rd annual Southeast regional conference - Volume 1
Algorithms
Engaging students in formal language theory and theory of computation
Proceedings of the 38th SIGCSE technical symposium on Computer science education
The impact of question generation activities on performance
Proceedings of the 43rd ACM technical symposium on Computer Science Education
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We are interested in increasing comprehension of how students understand big-O analysis. We conducted a qualitative analysis of interviews with two undergraduate students to identify sources of difficulty within the topic of big-O. This demonstrates the existence of various difficulties, which contribute to the sparse research on students' understanding of pedagogy. The students involved in the study have only minimal experience with big-O analysis, discussed within the first two introductory computer science classes. During these hour-long interviews, the students were asked to analyze code or a paragraph to find the runtime of the algorithm involved and invited students to write code that would in a certain runtime. From these interactions, we conclude that students that have difficulties with big-O could be having trouble with the mathematical function used in the analysis and/or the techniques they used to solve the problem.