Soohyun Nam Liao
William G. Griswold
Leo Porter
ABSTRACT
Our prior work found differences in study habits between high- and low-performers in a small-scale qualitative study, and this work seeks to verify and extend these findings by examining the study habits of a larger population of CS1 students. To do this, we devised a survey based on the findings of our prior qualitative study. The responses of CS1 students reveals that some study habits are more frequently practiced by higher-performers then lower-performers or vice versa. One concern with these findings is that the differences in study habits might simply be explained by prior experience. As such, we compare study habits between students with and without prior experience as well. We find that although prior experience translates to better class performance, it is not associated with the same study habits as lower- and higher-performers, suggesting that prior experience and study habits are separately associated with better student performance. These findings encourage further inquiry into the role of study habits in student success and whether explicit instruction on better study habits might be the basis for successful future interventions.
- A. Ahadi, R. Lister, H. Haapala, and A. Vihavainen. Exploring machine learning methods to automatically identify students in need of assistance. In Proceedings of the 11th Conference on International Computing Education Research, pages 121--130, 2015.Google Scholar
Digital Library
- C. Alvarado, C. B. Lee, and G. Gillespie. New cs1 pedagogies and curriculum, the same success factors? In Proceedings of the 45th ACM Technical Symposium on Computer Science Education, SIGCSE '14, page 379--384, New York, NY, USA, 2014. Association for Computing Machinery.Google ScholarDigital Library
- S. Bergin and R. Reilly. Programming: Factors that influence success. In Proceedings of the 36th SIGCSE Technical Symposium on Computer Science Education, SIGCSE '05, page 411--415, New York, NY, USA, 2005. Association for Computing Machinery.Google ScholarDigital Library
- J. D. Bransford, A. L. Brown, R. R. Cocking, et al. How people learn, volume 11. Washington, DC: National academy press, 2000.Google Scholar
- P. Byrne and G. Lyons. The effect of student attributes on success in programming. In Proceedings of the 6th Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE '01, page 49--52, New York, NY, USA, 2001. Association for Computing Machinery.Google ScholarDigital Library
- M. Cerna and K. Pavliushchenko. Influence of study habits on academic performance of international college students in shanghai. Higher Education Studies, 5, 07 2015.Google ScholarCross Ref
- D. Chinn, J. Sheard, A. Carbone, and M.-J. Laakso. Study habits of cs1 students: What do they do outside the classroom? In Proceedings of the Twelfth Australasian Conference on Computing Education - Volume 103, ACE '10, page 53--62, AUS, 2010. Australian Computer Society, Inc.Google ScholarDigital Library
- M. Credé and N. R. Kuncel. Study habits, skills, and attitudes: The third pillar supporting collegiate academic performance. Perspectives on Psychological Science, 3(6):425--453, 2008. PMID: 26158971.Google ScholarCross Ref
- C. Crouch, A. P. Fagen, J. P. Callan, and E. Mazur. Classroom demonstrations: Learning tools or entertainment? American journal of physics, 72(6):835--838, 2004.Google Scholar
- C. H. Crouch and E. Mazur. Peer instruction: Ten years of experience and results. American Journal of Physics, 69, 2001.Google Scholar
- S. Fincher, J. Tenenberg, and A. Robins. Research design: necessary bricolage. In Proceedings of the seventh international conference on Computing education research, pages 27--32, 2011.Google ScholarDigital Library
- D. Hagan and S. Markham. Does it help to have some programming experience before beginning a computing degree program? In Proceedings of the 5th Annual SIGCSE/SIGCUE ITiCSEconference on Innovation and Technology in Computer Science Education, ITiCSE '00, page 25--28, New York, NY, USA, 2000. Association for Computing Machinery.Google ScholarDigital Library
- A. Hassanbeigi, J. Askari, M. Nakhjavani, S. Shirkhoda, K. Barzegar., M. R. Mozayyan, and H. Fallahzadeh. The relationship between study skills and academic performance of university students. Procedia - Social and Behavioral Sciences, 30:1416--1424, 2011.Google Scholar
- E. Holden and E. Weeden. The experience factor in early programming education. In Proceedings of the 5th Conference on Information Technology Education, CITC5 '04, page 211--218, New York, NY, USA, 2004. Association for Computing Machinery.Google ScholarDigital Library
- H. Jafari, A. Aghaei, and A. Khatony. Relationship between study habits and academic achievement in students of medical sciences in kermanshah-iran. Advances in Medical Education and Practice, Volume 10:637--643, 08 2019.Google ScholarCross Ref
- S. Krause-Levy, L. Porter, B. Simon, and C. Alvarado. Investigating the impact of employing multiple interventions in a cs1 course. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education, SIGCSE '20, page 1082--1088, New York, NY, USA, 2020. Association for Computing Machinery.Google ScholarDigital Library
- L. Lambert. Factors that predict success in cs1. J. Comput. Sci. Coll., 31(2):165--171, Dec. 2015.Google ScholarDigital Library
- S. N. Liao, S. Valstar, K. Thai, C. Alvarado, D. Zingaro, W. G. Griswold, and L. Porter. Behaviors of higher and lower performing students in cs1. In Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE '19, page 196--202, New York, NY, USA, 2019. Association for Computing Machinery.Google ScholarDigital Library
- S. N. Liao, D. Zingaro, M. A. Laurenzano, W. G. Griswold, and L. Porter. Lightweight, early identification of at-risk CS1 students. In Proceedings of the 12th Conference on International Computing Education Research, pages 123--131, 2016.Google ScholarDigital Library
- A. Lishinski, A. Yadav, J. Good, and R. Enbody. Learning to program: Gender differences and interactive effects of students' motivation, goals, and self-efficacy on performance. In Proceedings of the 12th Conference on International Computing Education Research, pages 211--220, 2016.Google ScholarDigital Library
- D. Loksa and A. J. Ko. The role of self-regulation in programming problem solving process and success. In Proceedings of the 12th Conference on International Computing Education Research, pages 83--91, 2016.Google ScholarDigital Library
- S. A. Nonis and G. I. Hudson. Performance of college students: Impact of study time and study habits. Journal of Education for Business, 85(4):229--238, 2010.Google ScholarCross Ref
- A. Petersen, M. Craig, J. Campbell, and A. Tafliovich. Revisiting why students drop CS1. In Proceedings of the 16th Koli Calling International Conference on Computing Education Research, pages 71--80, 2016.Google ScholarDigital Library
- L. Porter, C. Bailey Lee, and B. Simon. Halving fail rates using peer instruction: a study of four computer science courses. In Proceedings of the 44th technical symposium on Computer science education, pages 177--182, 2013.Google ScholarDigital Library
- L. Porter, C. Bailey Lee, B. Simon, and D. Zingaro. Peer instruction: Do students really learn from peer discussion in computing? In ICER'11, 2011.Google ScholarDigital Library
- L. Porter, D. Zingaro, and R. Lister. Predicting student success using fine grain clicker data. In Proceedings of the 10th Conference on International Computing Education Research, pages 51--58, 2014.Google ScholarDigital Library
- N. Rahim and H. Meon. Relationships between study skills and academic performance. volume 1522, 12 2012.Google Scholar
- N. Rountree, J. Rountree, A. Robins, and R. Hannah. Interacting factors that predict success and failure in a cs1 course. In Working Group Reports from ITiCSE on Innovation and Technology in Computer Science Education, ITiCSE-WGR '04, page 101--104, New York, NY, USA, 2004. Association for Computing Machinery.Google ScholarDigital Library
- S. Samuel and S. Shetty. Effectiveness of study skills on academic performance of dental students. Journal of Education and Ethics in Dentistry, 4:28--31, 01 2014.Google ScholarCross Ref
- J. Sheard, A. Carbone, S. Markham, A. J. Hurst, D. Casey, and C. Avram. Performance and progression of first year ict students. In Proceedings of the Tenth Conference on Australasian Computing Education - Volume 78, ACE '08, page 119--127, AUS, 2008. Australian Computer Society, Inc.Google Scholar
- B. Simon, J. Parris, and J. Spacco. How we teach impacts learning: peer instruction vs. lecture in CS0. In Proceedings of the 44th ACM Technical Symposium on Computer Science Education, 2013.Google ScholarDigital Library
- A. Tafliovich, J. Campbell, and A. Petersen. A student perspective on prior experience in cs1. In Proceeding of the 44th ACM Technical Symposium on Computer Science Education, SIGCSE '13, page 239--244, New York, NY, USA, 2013. Association for Computing Machinery.Google ScholarDigital Library
- C. Watson and F. W. Li. Failure rates in introductory programming revisited. In Proceedings of the 2014 conference on Innovation & technology in computer science education, pages 39--44, 2014.Google ScholarDigital Library
- C. Wilcox and A. Lionelle. Quantifying the benefits of prior programming experience in an introductory computer science course. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education, SIGCSE '18, page 80--85, New York, NY, USA, 2018. Association for Computing Machinery.Google ScholarDigital Library
- B. C. Wilson and S. Shrock. Contributing to success in an introductory computer science course: A study of twelve factors. In Proceedings of the Thirty-Second SIGCSE Technical Symposium on Computer Science Education, SIGCSE '01, page 184--188, New York, NY, USA, 2001. Association for Computing Machinery.Google ScholarDigital Library
- B. Zimmerman and M. Martinez-Pons. Student differences in self-regulated learning: Relating grade, sex, and giftedness to self-efficacy and strategy use. Journal of Educational Psychology, 82:51--59, 03 1990.Google ScholarCross Ref
- D. Zingaro, M. Craig, L. Porter, B. A. Becker, Y. Cao, P. Conrad, D. Cukierman, A. Hellas, D. Loksa, and N. Thota. Achievement goals in CS1: Replication and extension. In Proceedings of the 49th Technical Symposium on Computer Science Education, pages 687--692, 2018.Google ScholarDigital Library
- D. Zingaro and L. Porter. Impact of student achievement goals on cs1 outcomes. In Proceedings of the 47th Technical Symposium on Computer Science Education, SIGCSE '16, pages 279--296, 2016.Google ScholarDigital Library
Index Terms
- A Quantitative Analysis of Study Habits Among Lower- and Higher-Performing Students in CS1
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