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On the Effect of Question Ordering on Performance and Confidence in Computer Science Examinations

Published: 22 February 2019 Publication History

Abstract

Most computer science examinations tend to start with the easiest questions and progress towards the more difficult material. Whether this is because of the highly scaffolded nature of the course, an attempt to 'ease students in', or simply by convention, is unclear. However, there is a great deal of data from the psychology literature to suggest that human perception of the difficulty or discomfort of a task is disproportionately affected by the last part of the task completed. Therefore, is it possible that by structuring our exams in an easy-to-hard fashion, we are causing students to perceive the test as more difficult than it actually is? Could changing the question order allow us to change students' perception of their own achievement? What effect could this have on actual performance? This paper attempts to answer these questions by randomly assigning students to write exams ordered either easy-to-hard (referred as 'Easy-Difficult') or hard-to-easy ('Difficult-Easy), then ask them to predict their marks on per-question basis. We find that the question ordering has a small but not statistically significant effect on the performance, and virtually no effect on predicted marks when treating the entire class as one unstratified sample. However, the effect was significant for certain subgroups created via stratification. In particular, swapping the order of the questions may have hurt the performance of international students, but significantly raised both the performance and confidence of female students.

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Cited By

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  • (2024)Sound symbolic associations: evidence from visual, tactile, and interpersonal iconic perception of Mandarin rimesHumanities and Social Sciences Communications10.1057/s41599-024-03502-711:1Online publication date: 2-Aug-2024
  • (2023)Does question order matter on online math assessments? A big data analysis of undergraduate mathematics final examsJournal of Computer Assisted Learning10.1111/jcal.1281639:5(1539-1552)Online publication date: 24-Apr-2023
  • (2021)Evidence for Teaching Practices that Broaden Participation for Women in ComputingProceedings of the 2021 Working Group Reports on Innovation and Technology in Computer Science Education10.1145/3502870.3506568(57-131)Online publication date: 28-Dec-2021

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  1. On the Effect of Question Ordering on Performance and Confidence in Computer Science Examinations

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cover image ACM Conferences
SIGCSE '19: Proceedings of the 50th ACM Technical Symposium on Computer Science Education
February 2019
1364 pages
ISBN:9781450358903
DOI:10.1145/3287324
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 22 February 2019

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Author Tags

  1. confidence
  2. cs1
  3. examination
  4. gender
  5. international students
  6. question ordering

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SIGCSE '19 Paper Acceptance Rate 169 of 526 submissions, 32%;
Overall Acceptance Rate 1,595 of 4,542 submissions, 35%

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Cited By

View all
  • (2024)Sound symbolic associations: evidence from visual, tactile, and interpersonal iconic perception of Mandarin rimesHumanities and Social Sciences Communications10.1057/s41599-024-03502-711:1Online publication date: 2-Aug-2024
  • (2023)Does question order matter on online math assessments? A big data analysis of undergraduate mathematics final examsJournal of Computer Assisted Learning10.1111/jcal.1281639:5(1539-1552)Online publication date: 24-Apr-2023
  • (2021)Evidence for Teaching Practices that Broaden Participation for Women in ComputingProceedings of the 2021 Working Group Reports on Innovation and Technology in Computer Science Education10.1145/3502870.3506568(57-131)Online publication date: 28-Dec-2021
  • (2019)A Statistical Analysis of Drop Rates in Introductory Computer Science by Gender and Partial GradeProceedings of the 24th Western Canadian Conference on Computing Education10.1145/3314994.3325081(1-2)Online publication date: 3-May-2019

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