research-article

Comparing international indicators of student engagement for computer science

Authors:

Matthew Butler,

Michael Morgan,

Sara KalvalaAuthors Info & Claims

ACSW '16: Proceedings of the Australasian Computer Science Week Multiconference

Article No.: 6, Pages 1 - 10

https://doi.org/10.1145/2843043.2843065

Published: 01 February 2016 Publication History

Abstract

This paper investigates the design, structure and results produced by several widely used international surveys of student engagement, with specific regard to their validity in the Computer Science (CS) context. Of particular interest is the way that different survey instruments measure the multi-dimensional concept of 'student engagement'. By comparing the performance of CS in several contexts, key issues emerge regarding the impact of instrument design on results, how these results should be interpreted and if these results can actually be used to improve course delivery. The results highlight the need for reliable instruments that produce a clear and accurate picture of student engagement in specific disciplines, such as CS. This may lead to the design of more appropriate engagement measures for the CS context which can facilitate a more effective evidence-based response to any significant issues that may exist. It may also allow a more positive view to emerge of CS than is portrayed by current indicators.

References

[1]

Brogt, E., & Comer, K. (2013). Interpreting differences between the United States and New Zealand university students' engagement scores as measured by the NSSE and AUSSE. Assessment & Evaluation in Higher Education, 38(6), 713--736.

[2]

Buckley, A. (2014). Engagement for enhancement: Report of a UK survey pilot Higher Education Academy, UK.

[3]

Buckley, A. (2015). UK Engagement Survey 2014: The second pilot year. Higher Education Academy, UK.

[4]

Coates, H. (2010). Development of the Australasian survey of student engagement (AUSSE). Higher Education, 60(1), 1--17.

[5]

Coates, H. (Ed.). (2014). Engaging university students: International insights from system-wide studies. Springer.

[6]

Douglas, J. A., Douglas, A., McClelland, R. J., & Davies, J. (2015). Understanding student satisfaction and dissatisfaction: an interpretive study in the UK higher education context. Studies in Higher Education, 40(2), 329--349.

[7]

Fredricks, J. A., & McColskey, W. (2012). The measurement of student engagement: A comparative analysis of various methods and student self-report instruments. In Handbook of research on student engagement (pp. 763--782). Springer US.

[8]

Garland, R. (1991). The mid-point on a rating scale: Is it desirable. Marketing bulletin, 2(1), 66--70.

[9]

Graduate Careers Australia (2015). 2014 University Experience Survey National Report, {ONLINE} Available at: http://docs.education.gov.au/system/files/doc/other/ues14_report_final_access2a.pdf/ {Accessed 11 September 15}.

[10]

Harper, S. R., & Quaye, S. J. (2009). Beyond sameness, with engagement and outcomes for all. Student engagement in higher education, 1--15.

[11]

Kahu, E. R. (2013). Framing student engagement in higher education. Studies in Higher Education, 38(5), 758--773.

[12]

Krause, K. L., & Coates, H. (2008). Students' engagement in first-year university. Assessment & Evaluation in Higher Education, 33(5), 493--505.

[13]

Kuh, G. D. (2001). The national survey of student engagement: Conceptual framework and overview of psychometric properties. Bloomington: Indiana University Center for Postsecondary Research.

[14]

Kuh, G. D., Kinzie, J., Buckley, J. A., Bridges, B. K., & Hayek, J. C. (2011). Piecing Together the Student Success Puzzle: Research, Propositions, and Recommendations: ASHE Higher Education Report (Vol. 116). John Wiley & Sons.

[15]

Pascarella, E. T., Seifert, T. A., & Blaich, C. (2010). How effective are the NSSE benchmarks in predicting important educational outcomes? Change: The Magazine of Higher Learning, 42(1), 16--22.

[16]

Porter, S. R. (2011). Do college student surveys have any validity?. The Review of Higher Education, 35(1), 45--76.

[17]

Porter, S. R. (2013). Self-reported learning gains: A theory and test of college student survey response. Research in Higher Education, 54(2), 201--226.

[18]

Porter, S. R., & Umbach, P. D. (2006). Student survey response rates across institutions: Why do they vary?. Research in Higher education, 47(2), 229--247.

[19]

Radloff, A., Coates, H., James, R., & Krause, K. L. (2011). Report on the development of the University Experience Survey.

[20]

Robinson, L., & Sykes, A. (2014). Listening to Students' Views on NSS Data for Quality Enhancement. Health and Social Care Education, 3(1), 35--40.

[21]

Sinclair, J., Butler, M., Morgan, M., & Kalvala, S. (2015). Measures of student engagement in Computer Science. In Proceedings of the 2015 Conference on Innovation & Technology in Computer Science Education. ACM.

Digital Library

[22]

Trustees of Indiana University. (2015). About NSSE. {ONLINE} Available at: http://nsse.indiana.edu/ {Accessed 11 September 15}.

[23]

Trowler, V. (2010). Student engagement literature review. York: Higher Education Academy.

Cited By

Schorr R(2020)Experience Report on Key Success Factors for Promoting Students’ Engagement in Software Development Group Projects2020 IEEE World Conference on Engineering Education (EDUNINE)10.1109/EDUNINE48860.2020.9149536(1-5)Online publication date: Mar-2020
https://doi.org/10.1109/EDUNINE48860.2020.9149536
Morgan MButler MSinclair JGonsalvez CThota NRößling GScharlau B(2018)Contrasting CS student and academic perspectives and experiences of student engagementProceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education10.1145/3293881.3295777(1-35)Online publication date: 2-Jul-2018
https://dl.acm.org/doi/10.1145/3293881.3295777
Morgan MButler MThota NSinclair JPolycarpou IRead JAndreou PArmoni M(2018)How CS academics view student engagementProceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education10.1145/3197091.3197092(284-289)Online publication date: 2-Jul-2018
https://dl.acm.org/doi/10.1145/3197091.3197092
Show More Cited By

Index Terms

Comparing international indicators of student engagement for computer science
1. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Computing education programs
        Computer science education
        Information science education

Recommendations

Measures of Student Engagement in Computer Science
ITiCSE '15: Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education

Data relating to university students' engagement is collected internationally via several large-scale student surveys such as the North American National Survey of Student Engagement. The instruments employed measure the extent to which students put ...
Understanding International Benchmarks on Student Engagement: Awareness and Research Alignment from a Computer Science Perspective
ITiCSE-WGR '17: Proceedings of the 2017 ITiCSE Conference on Working Group Reports

There is an increasing trend to use national survey instruments to measure student engagement. Unfortunately, Computer Science (CS) rates poorly on a number of measures in these surveys, even when compared to related STEM disciplines. Initial research ...
Computer science in context: pathways to computer science
Koli Calling '07: Proceedings of the Seventh Baltic Sea Conference on Computing Education Research - Volume 88

In order to increase participation in Computer Science (CS), contextual approaches are often suggested for teaching. Although these approaches are quite promising, we do not know what exactly context means and how CS teaching should implement these ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Other conferences

ACSW '16: Proceedings of the Australasian Computer Science Week Multiconference

February 2016

654 pages

ISBN:9781450340427

DOI:10.1145/2843043

Copyright © 2016 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 ACM 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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 February 2016

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

ACSW '16

ACSW '16: Australasian Computer Science Week

February 1 - 5, 2016

Canberra, Australia

Acceptance Rates

ACSW '16 Paper Acceptance Rate 77 of 172 submissions, 45%;

Overall Acceptance Rate 204 of 424 submissions, 48%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

5
Total Citations
View Citations
168
Total Downloads

Downloads (Last 12 months)10
Downloads (Last 6 weeks)0

Reflects downloads up to 10 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Schorr R(2020)Experience Report on Key Success Factors for Promoting Students’ Engagement in Software Development Group Projects2020 IEEE World Conference on Engineering Education (EDUNINE)10.1109/EDUNINE48860.2020.9149536(1-5)Online publication date: Mar-2020
https://doi.org/10.1109/EDUNINE48860.2020.9149536
Morgan MButler MSinclair JGonsalvez CThota NRößling GScharlau B(2018)Contrasting CS student and academic perspectives and experiences of student engagementProceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education10.1145/3293881.3295777(1-35)Online publication date: 2-Jul-2018
https://dl.acm.org/doi/10.1145/3293881.3295777
Morgan MButler MThota NSinclair JPolycarpou IRead JAndreou PArmoni M(2018)How CS academics view student engagementProceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education10.1145/3197091.3197092(284-289)Online publication date: 2-Jul-2018
https://dl.acm.org/doi/10.1145/3197091.3197092
Morgan MSinclair JButler MThota NFraser JCross GJackova JSheard JKorhonen A(2018)Understanding International Benchmarks on Student EngagementProceedings of the 2017 ITiCSE Conference on Working Group Reports10.1145/3174781.3174782(1-24)Online publication date: 30-Jan-2018
https://dl.acm.org/doi/10.1145/3174781.3174782
Miljanovic MBradbury J(2018)Making Serious Programming Games AdaptiveSerious Games10.1007/978-3-030-02762-9_27(253-259)Online publication date: 17-Oct-2018
https://doi.org/10.1007/978-3-030-02762-9_27

View Options

Get Access

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

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents