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Most difficult topics in CS1: results of an online survey of educators

Author:

Nell B. DaleAuthors Info & Claims

ACM SIGCSE Bulletin, Volume 38, Issue 2

Pages 49 - 53

https://doi.org/10.1145/1138403.1138432

Published: 01 June 2006 Publication History

Abstract

In the spring of 2004, a survey was posted on the Internet concerning the content of the first course in computing (CS1) and email messages were sent to approximately 3,500 instructors asking them to participate in the survey. Three hundred fifty one faculty members responded. The responses to one survey item form the basis of this paper: "In your experience, what is the most difficult topic to teach in CS1?" This paper describes the demographics of the respondents and present a content analysis of the responses to this item. The analysis indicates that the difficult topics fall into four categories: problem solving and design, general programming topics, object-oriented constructs, and student maturity (or lack thereof). The paper presents the specific topics within each category along with sample comments.

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Cited By

Graf OThorgeirsson SSu ZMonga MLonati VBarendsen ESheard JPaterson J(2024)Assessing Live Programming for Program ComprehensionProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653547(520-526)Online publication date: 3-Jul-2024
https://dl.acm.org/doi/10.1145/3649217.3653547
Prather JDenny PLeinonen JBecker BAlbluwi ICraig MKeuning HKiesler NKohn TLuxton-Reilly AMacNeil SPetersen APettit RReeves BSavelka JLaakso MMonga MSimon Sheard J(2023)The Robots Are Here: Navigating the Generative AI Revolution in Computing EducationProceedings of the 2023 Working Group Reports on Innovation and Technology in Computer Science Education10.1145/3623762.3633499(108-159)Online publication date: 22-Dec-2023
https://dl.acm.org/doi/10.1145/3623762.3633499
Nelson MHossain MHasan MHaque E(2023)A Semi-Automatic Knowledge Discovery Tool to Identify and Visualize Course Bottlenecks2023 IEEE Frontiers in Education Conference (FIE)10.1109/FIE58773.2023.10342941(1-5)Online publication date: 18-Oct-2023
https://doi.org/10.1109/FIE58773.2023.10342941
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Index Terms

Most difficult topics in CS1: results of an online survey of educators
1. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Computing education programs
        Computer science education

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Published In

cover image ACM SIGCSE Bulletin

ACM SIGCSE Bulletin Volume 38, Issue 2

June 2006

199 pages

ISSN:0097-8418

DOI:10.1145/1138403

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Copyright © 2006 Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 June 2006

Published in SIGCSE Volume 38, Issue 2

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Cited By

Graf OThorgeirsson SSu ZMonga MLonati VBarendsen ESheard JPaterson J(2024)Assessing Live Programming for Program ComprehensionProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653547(520-526)Online publication date: 3-Jul-2024
https://dl.acm.org/doi/10.1145/3649217.3653547
Prather JDenny PLeinonen JBecker BAlbluwi ICraig MKeuning HKiesler NKohn TLuxton-Reilly AMacNeil SPetersen APettit RReeves BSavelka JLaakso MMonga MSimon Sheard J(2023)The Robots Are Here: Navigating the Generative AI Revolution in Computing EducationProceedings of the 2023 Working Group Reports on Innovation and Technology in Computer Science Education10.1145/3623762.3633499(108-159)Online publication date: 22-Dec-2023
https://dl.acm.org/doi/10.1145/3623762.3633499
Nelson MHossain MHasan MHaque E(2023)A Semi-Automatic Knowledge Discovery Tool to Identify and Visualize Course Bottlenecks2023 IEEE Frontiers in Education Conference (FIE)10.1109/FIE58773.2023.10342941(1-5)Online publication date: 18-Oct-2023
https://doi.org/10.1109/FIE58773.2023.10342941
Morena MSmith M(2023)The Euclidean Discus TossPRIMUS10.1080/10511970.2023.222981133:10(1071-1090)Online publication date: 25-Jul-2023
https://doi.org/10.1080/10511970.2023.2229811
Zhang VJeffries BKoprinska I(2023)Predicting Progress in a Large-Scale Online Programming CourseArtificial Intelligence in Education10.1007/978-3-031-36272-9_76(810-816)Online publication date: 3-Jul-2023
https://dl.acm.org/doi/10.1007/978-3-031-36272-9_76
Brieven GLiénardy SMalcev LDonnet B(2023)Graphical Loop Invariant Based ProgrammingFormal Methods Teaching10.1007/978-3-031-27534-0_2(17-33)Online publication date: 23-Feb-2023
https://doi.org/10.1007/978-3-031-27534-0_2
Sanchez‐Santillan MFernandez‐Medina CPerez‐Perez JPaule‐Ruiz M(2023)An empirical evaluation of the formative feedback supported by dashboard in the context of compilation errorComputer Applications in Engineering Education10.1002/cae.2264031:5(1289-1305)Online publication date: 17-May-2023
https://doi.org/10.1002/cae.22640
Getseva VKumar ABecker BQuille KLaakso MBarendsen ESimon (2022)An Empirical Analysis of Code-Tracing ConceptsProceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education Vol. 110.1145/3502718.3524794(262-268)Online publication date: 7-Jul-2022
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Cheng QTao AChen HSamary M(2022)Design an Assessment for an Introductory Computer Science Course: A Systematic Literature Review2022 IEEE Frontiers in Education Conference (FIE)10.1109/FIE56618.2022.9962584(1-8)Online publication date: 8-Oct-2022
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Gutiérrez LGuerrero CLópez-Ospina H(2022)Ranking of problems and solutions in the teaching and learning of object-oriented programmingEducation and Information Technologies10.1007/s10639-022-10929-527:5(7205-7239)Online publication date: 1-Jun-2022
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