Why is big-O analysis hard?

Miranda Parker, Colleen Lewis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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 courses. 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 run 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.

Original languageEnglish (US)
Title of host publicationProceedings - 13th Koli Calling International Conference on Computing Education Research, Koli Calling 2013
Pages201-202
Number of pages2
DOIs
StatePublished - 2013
Externally publishedYes
Event13th Koli Calling International Conference on Computing Education Research, Koli Calling 2013 - Koli, Finland
Duration: Nov 14 2013Nov 17 2013

Publication series

NameACM International Conference Proceeding Series

Conference

Conference13th Koli Calling International Conference on Computing Education Research, Koli Calling 2013
CountryFinland
CityKoli
Period11/14/1311/17/13

Keywords

  • algorithmic complexity
  • big-O
  • runtime analysis

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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