Article

Why students drop out CS1 course?

Authors:

Päivi Kinnunen,

Lauri MalmiAuthors Info & Claims

ICER '06: Proceedings of the second international workshop on Computing education research

Pages 97 - 108

https://doi.org/10.1145/1151588.1151604

Published: 09 September 2006 Publication History

Get Access

Abstract

This study focuses on CS minor students' decisions to drop out from the CS1 course. The high level of drop out percentage has been a problem at Helsinki University of Technology for many years. This course has yearly enrolment of 500-600 students and the drop out percentage has varied from 30-50 percents.Since we did not have clear picture of drop out reasons we conducted a qualitative interview research in which 18 dropouts from the CS1 course were interviewed. The reasons of drop out were categorized and, in addition, each case was investigated individually. This procedure enabled us to both list the reasons and to reveal the cumulative nature of drop out reasons.The results indicate that several reasons affect students' decision to quit the CS1 course. The most frequent reasons were the lack of time and the lack of motivation. However, both of these reasons were in turn affected by factors, such as the perceived difficulty of the course, general difficulties with time managing and planning studies, or the decision to prefer something else. Furthermore, low comfort level and plagiarism played a role in drop out. In addition, drop out reasons cumulated.This study shows that the complexity and large variety of factors involved in students' decision to drop the course. This indicates that simple actions to improve teaching or organization on a CS1 course to reduce drop out may be ineffective. Efficient intervention to the problem apparently requires a combination of many different actions that take into consideration the versatile nature of reasons involved in drop out.

References

[1]

L. J. Barker and K. Garvin-Doxas. Making visible the behaviors that influence learning environment: A qualitative exploration of computer science classrooms. Computer Science Education, 14(2):119--145, 2004.

Crossref

Google Scholar

[2]

M. Ben-Ari. Situated learning in computer science education. Computer Science Education, 14(2):85--100, 2004.

Crossref

Google Scholar

[3]

M. Ben-Ari. Situated learning in 'this high-technology world'. Science & Education, 14:367--376, 2005.

Crossref

Google Scholar

[4]

R. Bennett. Determinants of undergraduate student drop out rates in a university business studies department. Journal of Further and Higher Education, 27(2):123--141, 2003.

Crossref

Google Scholar

[5]

R. Boyle, J. Carter, and M. Clark. What makes them succeed? entry, progression and graduation in computer science. Journal of Further and Higher Education, 26(1):3--18, 2002.

Crossref

Google Scholar

[6]

A. Cook and J. Leckey. Do expectations meet reality? a survey of changes in first-year student opinion. Journal of Further and Higher Education, 23(2):157--171, 1999.

Crossref

Google Scholar

[7]

J. Dewey. Experience and Education. The Macmillan Publishing, New York, 1938/1953.

Google Scholar

[8]

D. Fazey and J. Fazey. Perspectives on motivation: The implications for effective learning in higher education. In S. A. Sally Brown and G. Thompson, editors, Motivating Students, chapter 7, pages 59--72. Kogan Page, London, UK, 1998.

Google Scholar

[9]

K. Garvin-Doxas and L. J. Barker. Communication in computer science classrooms: Understanding defensive climates asa means of creating supportive behaviors. ACM Journal of Educational Resources in Computing, 4(1):1--18, April 2005.

Digital Library

Google Scholar

[10]

R. Gunstone. Constructivism and learning in science education. In D. Phillips, editor, Constructivism in Education. Opinions and Second Opinions on Controversial Issues. Ninety-ninth Yearbook of the National Society for the Study of Education. Part 1. The University of Chicago Press, Chicago, 2002.

Google Scholar

[11]

K. Isoroff and T. del Soldato. Students' motivation in higher eduction contexts. In S. A. Sally Brown and G. Thompson, editors, Motivating Students, chapter 8, pages 73--83. Kogan Page, London, UK, 1998.

Google Scholar

[12]

B. Johnson and L. Christensen. Educational Research. Quantitative, qualitative, and mixed approaches. Pearson, Boston, 2004.

Google Scholar

[13]

P. Kinnunen and L. Malmi. Problems in problem-based learning - experisences, analysis and lessons learned on an introductory programming course. Informatics in Education, 4(2):193--214, 2005.

Google Scholar

[14]

D. A. Kolb. Experiental Learning. Experience as the Source of Learning and Cevelopment. N.J, Prentice Hall, Engelwood Cliffs, 1984.

Google Scholar

[15]

J. Lave and E. Wenger. Situated Learning: Legitimate Peripheral Participation. Cambridge University Press, Cambridge, 1991.

Crossref

Google Scholar

[16]

R. Lister, O. Seppälä, B. Simon, L. Thomas, E. S. Adams, S. Fitzgerald, W. Fone, J. Hamer, M. Lindholm, R. McCartney, J. E. Moström, and K. Sanders. A multi-national study of reading and tracing skills in novice programme rs. SIGCSE Bulletin, 36(4):119--150, 2004.

Digital Library

Google Scholar

[17]

L. M. Louis Cohen and K. Morrison. Research Methods in Education. Routledge Falmer, London and New York, 2000.

Google Scholar

[18]

H. Lowe and A. Cook. Mind the gap: are students prepared for higher education? Journal of Further and Higher Education, 27(1):52--76, 2003.

Crossref

Google Scholar

[19]

M. McCracken, V. Almstrum, D. Diaz, M. G. and Dianne Hagan, Y. B. Kolikant, C. Laxer, L. Thomas, I. Utting, and T. Wilusz. A multi-national, multi-institutional study of assessment of programmingskills of first-year CS students. SIGCSE Bulletin, 33(4):125--180, 2001.

Digital Library

Google Scholar

[20]

C. P. Michalis Xenos and P. Pintelas. A survey on studen dropout rates and dropout causes concerning the students in the course of informatics of the hellenic open university. Computers & Education, 39:361--194, 2002.

Crossref

Google Scholar

[21]

T. R. Mitchell. Motivation: New directions for theory, research, and practice. Academy of Management Review, 7(1):80--88, 1982.

Crossref

Google Scholar

[22]

J. Philip R. Ventura. Identifying predictors of success for an objects-first cs1. Computer Science Education, 15(3):223--243, 2005.

Crossref

Google Scholar

[23]

J. Tenenberg and S. F. et al. Students designing software: a multi-national, multi-institutional study. Informatics in Education, 4(1):143--162, 2005.

Crossref

Google Scholar

[24]

V. Tinto. Classrooms as communities: Exploring the educational character of student persistence. Journal of Higher Education, 68(6):599--623, Nov. - Dec. 1997.

Google Scholar

[25]

L. S. Vygotsky. Mind in Society: The Development of Higher Psychological Processes. Harvard University Press, Cambridge, Mass., 1978.

Google Scholar

[26]

E. Wenger. Communities of Practice. Cambridge University Press, Cambridge, 1998.

Crossref

Google Scholar

[27]

B. C. Wilson. A study of factors promoting success in computer science including gender differences. Computer Science Education, 12(1-2):141--164, 2002.

Crossref

Google Scholar

[28]

S. Winn. Student motivation: a socio-economic perspective. Studies in Higher Education, 27(4):445--457, 2002.

Crossref

Google Scholar

[29]

C. A. Wolters. Regulation of motivation: Evaluating an underemphasized aspect of self-regulated learning. Educational Psychologist, 38(4):189--205, 2003.

Crossref

Google Scholar

Cited By

View all

Dawar D(2024)Student-Driven Programming Instruction: A Follow-Up StudyInformation Systems Education Journal10.62273/UQWB419222:1(14-29)Online publication date: 2024
https://doi.org/10.62273/UQWB4192
Kaila ELeppänen LLuukkainen MLemström K(2024)Flowthrough Analysis on Student Intake PathsProceedings of the 24th Koli Calling International Conference on Computing Education Research10.1145/3699538.3699545(1-8)Online publication date: 12-Nov-2024
https://dl.acm.org/doi/10.1145/3699538.3699545
Yang SBaird MO’Rourke EBrennan KSchneider B(2024)Decoding Debugging Instruction: A Systematic Literature Review of Debugging InterventionsACM Transactions on Computing Education10.1145/369065224:4(1-44)Online publication date: 5-Sep-2024
https://dl.acm.org/doi/10.1145/3690652
Show More Cited By

Index Terms

Why students drop out CS1 course?
1. Applied computing
  1. Education
2. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Computing education programs
        Computer science education

Recommendations

Revisiting why students drop CS1
Koli Calling '16: Proceedings of the 16th Koli Calling International Conference on Computing Education Research

This paper describes a qualitative study of the factors that contribute to a student's decision to withdraw from CS1. Individual interviews were held with 18 students in a majors-focused CS1 at a large, research-intensive North American university, and ...
CS minors in a CS1 course
ICER '08: Proceedings of the Fourth international Workshop on Computing Education Research

The focus of this paper is on science students (CS minors) in a CS1 Java course at a technical university. The following three questions are discussed: 1) Which programming related topics the students at the target CS1 course find difficult to learn, ...
Experiences with a CS0 course targeted for CS1 success
SIGCSE '05: Proceedings of the 36th SIGCSE technical symposium on Computer science education

In this paper, we report on an approach taken addressing the issue of the preparedness of students entering CS1. Specifically, we discuss the adoption of a first-day assessment test in lieu of completed course prerequisites for determining students' ...

Reviews

Reviewer: Stewart Mark Godwin

Many institutions report that computer science courses record high levels of student dropout during the first year. This research paper seeks to explain why students decide to withdraw from computer science courses, and from programming language subjects in particular. The study has targeted the computer course at the Helsinki University of Finland. From the literature review, the authors identified similar studies that suggest the comfort level of students in computer science courses is the best predictor of success. However, these studies have also mentioned a lack of motivation, commitment, and confidence as issues that also affect dropout levels. The case study methodology in this research used an initial questionnaire, followed by a series of interviews with selected students. The results from the questionnaire highlighted three reasons why students withdrew from computer science: lack of time to complete assignments, lack of knowledge to complete coursework, and underestimating the time required to successfully complete the computer science course. The interviews supported the questionnaire, with data that confirmed students lacked sufficient time, or underestimated the time necessary to complete coursework. Furthermore, students also indicated they lacked motivation to complete coursework. In conclusion, the study corroborates previous research, which indicates that success in computer science can be improved when students enjoy a high level of comfort with the course. Finally, the study indicates that active interventions can be employed that will improve the learning environment, and thus positively affect student comfort levels and success. The authors suggest that future research should concentrate on the identified dropout reasons, and the specific programming-related difficulties faced by students in computer science courses. This timely research supports the urgent need to address the high dropout rates of students from computer science courses. Online Computing Reviews Service

Reviewer: Keith Harrow

A near-universal issue is addressed in this paper: Why do so many students drop out of the introductory programming course__?__ The focus of the paper is a course in Java, given at a technical university in Helsinki, Finland, but the problems are remarkably similar to those that I face teaching C++ at a liberal arts college in Brooklyn, New York. The authors are familiar with previous research on dropouts, and the paper includes a summary of this research and an overview of the many factors involved. This part of the paper is interesting, but not news to anyone who has been teaching a first course in programming over the past few years. The part that is innovative is the idea of pursuing the students who drop out of a course, first with a questionnaire, which more than 100 responded to, and then with much more detailed, face-to-face interviews with a fairly large number of students (18 completed the interview process). On the one hand, the results of these interviews are not surprising: the major problems cited by the students were motivation and persistence, the social aspects of the course, the transition from high school to college, and cultural issues. What is novel is seeing how the reasons feed on each other, cascading together to force the student to drop out of the course. For example, a student who did not budget enough time for the course would start to fall behind, then get caught up in the complexities of the language, have to work on other courses, not get enough help from teaching assistants, and so on. This implies that simple “solutions” that address only one of these issues will not work. The authors’ native language is not English and there are a number of misspelled words and mangled phrases, especially in the excerpts from the interviews. (As the authors note, it is especially hard to translate a student’s oral response from one language to another.) Despite this, the paper is still quite easy to read, and the substance of what is being said is always clear. Overall, I recommend this paper to anyone who is concerned about the dropout rate in our introductory programming courses. To those looking for easy solutions (like many college administrators), the results are not promising. Nevertheless, the paper makes an important contribution to our understanding of the dropout phenomenon. Online Computing Reviews Service

Access critical reviews of Computing literature here

Become a reviewer for Computing Reviews.

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

ICER '06: Proceedings of the second international workshop on Computing education research

September 2006

144 pages

ISBN:1595934944

DOI:10.1145/1151588

Program Chairs:
Richard Anderson
University of Washington, Seattle, USA
,
Sally A. Fincher
University of Kent at Canterbury, UK
,
Mark Guzdial
Georgia Institute of Technology, Atlanta, USA

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: 09 September 2006

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

ICER06

Sponsor:

ICER06: International Computing Education Research Workshop 2006

September 9 - 10, 2006

Canterbury, United Kingdom

Acceptance Rates

Overall Acceptance Rate 189 of 803 submissions, 24%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

183
Total Citations
View Citations
2,548
Total Downloads

Downloads (Last 12 months)177
Downloads (Last 6 weeks)21

Reflects downloads up to 12 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Dawar D(2024)Student-Driven Programming Instruction: A Follow-Up StudyInformation Systems Education Journal10.62273/UQWB419222:1(14-29)Online publication date: 2024
https://doi.org/10.62273/UQWB4192
Kaila ELeppänen LLuukkainen MLemström K(2024)Flowthrough Analysis on Student Intake PathsProceedings of the 24th Koli Calling International Conference on Computing Education Research10.1145/3699538.3699545(1-8)Online publication date: 12-Nov-2024
https://dl.acm.org/doi/10.1145/3699538.3699545
Yang SBaird MO’Rourke EBrennan KSchneider B(2024)Decoding Debugging Instruction: A Systematic Literature Review of Debugging InterventionsACM Transactions on Computing Education10.1145/369065224:4(1-44)Online publication date: 5-Sep-2024
https://dl.acm.org/doi/10.1145/3690652
Zavaleta Bernuy AChung AHodge ATayyiba ALiut MPetersen A(2024)Student Transitions Through an Entire Computing ProgramProceedings of the 26th Western Canadian Conference on Computing Education10.1145/3660650.3660661(1-7)Online publication date: 2-May-2024
https://dl.acm.org/doi/10.1145/3660650.3660661
Sanhueza FGutierrez FVasquez AMonga MLonati VBarendsen ESheard JPaterson J(2024)Exploring the Acceptance and Effectiveness of Parsons Problems on Scaffolding CS1 RetakersProceedings of the 2024 on Innovation and Technology in Computer Science Education V. 110.1145/3649217.3653590(681-687)Online publication date: 3-Jul-2024
https://dl.acm.org/doi/10.1145/3649217.3653590
Yang SZhao HXu YBrennan KSchneider B(2024)Debugging with an AI Tutor: Investigating Novice Help-seeking Behaviors and Perceived LearningProceedings of the 2024 ACM Conference on International Computing Education Research - Volume 110.1145/3632620.3671092(84-94)Online publication date: 12-Aug-2024
https://dl.acm.org/doi/10.1145/3632620.3671092
Silva de Oliveira GGao ZHeckman SLynch CStephenson BStone JBattestilli LRebelsky SShoop L(2024)Exploring Novice Programmers' Testing Behavior: A First Step to Define Coding StruggleProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 110.1145/3626252.3630851(1251-1257)Online publication date: 7-Mar-2024
https://dl.acm.org/doi/10.1145/3626252.3630851
Silva DCarvalho DSilla C(2024)A Clustering-Based Computational Model to Group Students With Similar Programming Skills From Automatic Source Code Analysis Using Novel FeaturesIEEE Transactions on Learning Technologies10.1109/TLT.2023.327392617(428-444)Online publication date: 2024
https://doi.org/10.1109/TLT.2023.3273926
de Almeida RGomes AMendes A(2024)Challenges and Possibilities in Motivating Students to Learn Programming in Distance Education: A Systematic Mapping Study2024 IEEE Global Engineering Education Conference (EDUCON)10.1109/EDUCON60312.2024.10578759(1-10)Online publication date: 8-May-2024
https://doi.org/10.1109/EDUCON60312.2024.10578759
Kuo YChang P(2024)Flipped classroom combined with WPACQ learning mode on student learning effect - exemplified by program design coursesEducation and Information Technologies10.1007/s10639-023-12384-229:10(12621-12651)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1007/s10639-023-12384-2
Show More Cited By

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.

Cited By

Index Terms

Recommendations

Revisiting why students drop CS1

CS minors in a CS1 course

Experiences with a CS0 course targeted for CS1 success

Reviews

Access critical reviews of Computing literature here