More Web Proxy on the site http://driver.im/

research-article

Public Access

CodeWorkout: Short Programming Exercises with Built-in Data Collection

Authors:

Stephen H. Edwards,

Krishnan Panamalai MuraliAuthors Info & Claims

ITiCSE '17: Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education

Pages 188 - 193

https://doi.org/10.1145/3059009.3059055

Published: 28 June 2017 Publication History

Abstract

Learning programming techniques can be challenging and frustrating for many students. Many instructors use drill-and-practice strategies to help students develop basic programming techniques and improve their confidence. Online systems that provide short programming exercises with immediate, automated feedback are often seen as a valuable approach to drill-and-practice. However, the relationship between practicing with short programming exercises and performance on larger programming assignments or exams is unclear. This paper describes CodeWorkout, an open-source drill-and-practice system that supports short programming exercises and multiple choice questions. CodeWorkout combines an open, gradual engagement model that allows any student to practice exercises, whether or not they have an account or are enrolled in a course, together with powerful course management features that support graded assignments, quizzes, and even practicum style exams. It also provides a rich data collection and evaluation infrastructure for educational research purposes. We report on initial experiences using CodeWorkout in a CS1 course, including student perceptions of the tool and its benefits.

References

[1]

J. D. Bransford, A. L. Brown, R. R. Cocking, et al. How people learn, 2000.

[2]

P. Denny, D. Cukierman, and J. Bhaskar. Measuring the effect of inventing practice exercises on learning in an introductory programming course. In Proceedings of the 15th Koli Calling Conference on Computing Education Research, Koli Calling '15, pages 13--22, New York, NY, USA, 2015. ACM.

Digital Library

[3]

P. Denny, A. Luxton-Reilly, E. Tempero, and J. Hendrickx. Codewrite: Supporting student-driven practice of java. In Proceedings of the 42Nd ACM Technical Symposium on Computer Science Education, SIGCSE '11, pages 471--476, New York, NY, USA, 2011. ACM.

Digital Library

[4]

S. Edwards. Web-CAT. http://web-cat.org. last accessed 04-07-2016.

[5]

O. Gotel, C. Scharff, and A. Wildenberg. Extending and contributing to an open source web-based system for the assessment of programming problems. In Proceedings of the 5th International Symposium on Principles and Practice of Programming in Java, PPPJ '07, pages 3--12, New York, NY, USA, 2007. ACM.

Digital Library

[6]

M. J. Hull, D. Powell, and E. Klein. Infandango: Automated grading for student programming. In Proceedings of the 16th Annual Joint Conference on Innovation and Technology in Computer Science Education, ITiCSE '11, pages 330--330, New York, NY, USA, 2011. ACM.

Digital Library

[7]

P. Ihantola, T. Ahoniemi, V. Karavirta, and O. Seppälä. Review of recent systems for automatic assessment of programming assignments. In Proceedings of the 10th Koli Calling International Conference on Computing Education Research, Koli Calling '10, pages 86--93, New York, NY, USA, 2010. ACM.

Digital Library

[8]

K. R. Koedinger and E. L. F. Sueker. Pat goes to college: Evaluating a cognitive tutor for developmental mathematics. In Proceedings of the 1996 International Conference on Learning Sciences, ICLS '96, pages 180--187. International Society of the Learning Sciences, 1996.

Digital Library

[9]

P. D. Palma. Viewpoint: Why women avoid computer science. Commun. ACM, 44(6):27--30, June 2001.

Digital Library

[10]

A. Papancea, J. Spacco, and D. Hovemeyer. An open platform for managing short programming exercises. In Proceedings of the Ninth Annual International ACM Conference on International Computing Education Research, ICER '13, pages 47--52, New York, NY, USA, 2013. ACM.

Digital Library

[11]

N. Parlante. CodingBat. http://codingbat.com/. last accessed 04-06-2016.

[12]

V. Pieterse. Automated assessment of programming assignments. In Proceedings of the 3rd Computer Science Education Research Conference on Computer Science Education Research, CSERC '13, pages 4:45--4:56, Open Univ., Heerlen, The Netherlands, The Netherlands, 2013. Open Universiteit, Heerlen.

Digital Library

[13]

J. Spacco. Marmoset. http://marmoset.cs.umd.edu/. last accessed 04-16-2016.

[14]

E. Thompson, A. Luxton-Reilly, J. L. Whalley, M. Hu, and P. Robbins. Bloom's taxonomy for cs assessment. In Proceedings of the Tenth Conference on Australasian Computing Education - Volume 78, ACE '08, pages 155--161, Darlinghurst, Australia, Australia, 2008. Australian Computer Society, Inc.

Digital Library

[15]

G. Weber and P. Brusilovsky. Elm-art: An adaptive versatile system for web-based instruction. International Journal of Artificial Intelligence in Education (IJAIED), 12:351--384, 2001.

[16]

C. Wilcox. The role of automation in undergraduate computer science education. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education, SIGCSE '15, pages 90--95, New York, NY, USA, 2015. ACM.

Digital Library

Cited By

Cipriano BBaltazar BFachada NVourvopoulos AAlves P(2024)Bridging the Gap between Project-Oriented and Exercise-Oriented Automatic Assessment ToolsComputers10.3390/computers1307016213:7(162)Online publication date: 30-Jun-2024
https://doi.org/10.3390/computers13070162
Decker AEdwards SMcSkimming BEdmison BRorrer APérez Quiñones MStephenson BStone JBattestilli LRebelsky SShoop L(2024)Transforming Grading Practices in the Computing Education CommunityProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630953(276-282)Online publication date: 7-Mar-2024
https://dl.acm.org/doi/10.1145/3626252.3630953
Shen SLiu QHuang ZZheng YYin MWang MChen E(2024)A Survey of Knowledge Tracing: Models, Variants, and ApplicationsIEEE Transactions on Learning Technologies10.1109/TLT.2024.338332517(1898-1919)Online publication date: 2024
https://doi.org/10.1109/TLT.2024.3383325
Show More Cited By

Index Terms

CodeWorkout: Short Programming Exercises with Built-in Data Collection
1. Applied computing
  1. Education
    1. Interactive learning environments
2. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Computing education programs
        Computer science education
        CS1
      2. Student assessment

Recommendations

The Relationship Between Voluntary Practice of Short Programming Exercises and Exam Performance
CompEd '19: Proceedings of the ACM Conference on Global Computing Education

Learning to program can be challenging. Many instructors use drill-and-practice strategies to help students develop basic programming techniques and improve their confidence. Online systems that provide short programming exercises with immediate, ...
Introducing CodeWorkout: an adaptive and social learning environment (abstract only)
SIGCSE '14: Proceedings of the 45th ACM technical symposium on Computer science education

Rudimentary programming skills are essential to developing fundamental proficiency in computer science. However, learning programming techniques can be challenging and frustrating for many students. CodeWorkout is an online learning environment that ...
The Effects of Combined Training of Web-Based Problem-Based Learning and Self-Regulated Learning

This study explored, via quasi-experiments, the effects of the combined training in web-based problem-based learning PBL and self-regulated learning SRL on low achieving students' skill development. Two classes of 76 undergraduates in a one-semester ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

ITiCSE '17: Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education

June 2017

412 pages

ISBN:9781450347044

DOI:10.1145/3059009

Conference Chairs:
Renzo Davoli
University of Bologna, Italy
,
Michael Goldweber
Xavier University, USA
,
Program Chairs:
Guido Rößling
Technische Universität Darmstadt, Germany
,
Irene Polycarpou
University of Central Lancashire, Cyprus

Copyright © 2017 ACM.

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].

Sponsors

SIGCSE: ACM Special Interest Group on Computer Science Education

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 June 2017

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

National Science Foundation

Conference

ITiCSE '17

Sponsor:

SIGCSE

ITiCSE '17: Innovation and Technology in Computer Science Education

July 3 - 5, 2017

Bologna, Italy

Acceptance Rates

ITiCSE '17 Paper Acceptance Rate 56 of 175 submissions, 32%;

Overall Acceptance Rate 552 of 1,613 submissions, 34%

Upcoming Conference

ITiCSE '25

Sponsor:
sigcse

Innovation and Technology in Computer Science Education

June 27 - July 2, 2025

Nijmegen , Netherlands

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

8
Total Citations
View Citations
1,013
Total Downloads

Downloads (Last 12 months)262
Downloads (Last 6 weeks)42

Reflects downloads up to 03 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Cipriano BBaltazar BFachada NVourvopoulos AAlves P(2024)Bridging the Gap between Project-Oriented and Exercise-Oriented Automatic Assessment ToolsComputers10.3390/computers1307016213:7(162)Online publication date: 30-Jun-2024
https://doi.org/10.3390/computers13070162
Decker AEdwards SMcSkimming BEdmison BRorrer APérez Quiñones MStephenson BStone JBattestilli LRebelsky SShoop L(2024)Transforming Grading Practices in the Computing Education CommunityProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630953(276-282)Online publication date: 7-Mar-2024
https://dl.acm.org/doi/10.1145/3626252.3630953
Shen SLiu QHuang ZZheng YYin MWang MChen E(2024)A Survey of Knowledge Tracing: Models, Variants, and ApplicationsIEEE Transactions on Learning Technologies10.1109/TLT.2024.338332517(1898-1919)Online publication date: 2024
https://doi.org/10.1109/TLT.2024.3383325
Rajesh SRao VThushara M(2024)Comprehensive Investigation of Code Assessment Tools in Programming Courses2024 IEEE 9th International Conference for Convergence in Technology (I2CT)10.1109/I2CT61223.2024.10543863(1-6)Online publication date: 5-Apr-2024
https://doi.org/10.1109/I2CT61223.2024.10543863
Pankiewicz MZambrano ABarany ABaker R(2024)How We Code Code: Leveraging GPT and Ordered Networks for Understanding Introductory Programming EducationAdvances in Quantitative Ethnography10.1007/978-3-031-76332-8_19(225-240)Online publication date: 2-Nov-2024
https://doi.org/10.1007/978-3-031-76332-8_19
Akhuseyinoglu KKlašnja-Milicevic ABrusilovsky P(2024)The Impact of Connecting Worked Examples and Completion Problems for Introductory Programming PracticeTechnology Enhanced Learning for Inclusive and Equitable Quality Education10.1007/978-3-031-72315-5_1(3-18)Online publication date: 13-Sep-2024
https://doi.org/10.1007/978-3-031-72315-5_1
Rocha HCosta ETedesco P(2023)Helping to provide adaptive feedback to novice programmers: a framework to assist the Teachers2023 18th Iberian Conference on Information Systems and Technologies (CISTI)10.23919/CISTI58278.2023.10212000(1-6)Online publication date: 20-Jun-2023
https://doi.org/10.23919/CISTI58278.2023.10212000
Han SWang YLu XChen HDuh WHuang HKato MMothe JPoblete B(2023)ErrorCLR: Semantic Error Classification, Localization and Repair for Introductory Programming AssignmentsProceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3539618.3591680(1345-1354)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3539618.3591680

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Figures

Tables

Media

View Table of Conten