Janet Hughes
D. Ramanee Peiris
ABSTRACT
Identifying and managing students who experience difficulty with learning to program is a challenge for CS educators. In an attempt to answer the familiar question "What makes for success in CS1?" we have investigated student approaches to learning using the ASSIST measure of learning approach. This measure considers three dimensions related to studying - deep (related to meaning), surface (reproducing) and strategic (achieving).Two cohorts of CS1 students completed an online ASSIST questionnaire midway through their first semester. Their three ASSIST scores were analysed together with their CS1 performance. The strongest relationships were a significant, negative correlation between a surface approach to learning and CS1 performance and a significant positive correlation between a strategic approach to learning and CS1 performance. Participants were classified via a cluster analysis according to the extent to which they showed deep, strategic, and surface learning profiles. Members of the cluster favouring a surface approach had the poorest performances, whereas members of the cluster favouring strategic or deep approaches rather than a surface approach had the best performances.
- Alexander, S., Amillo, J., Boyle, R., Clark, M., Daniels, M., Laxer, C., Loose, K., and Shinners-Kennedy, D. Case Studies in Admissions to and Early Performance in Computer Science Degrees. ACM SIGCSE Bulletin, 35, 4 (December 2003), 137--147. Google Scholar
Digital Library
- Allert, J. D. The Effectiveness of Innovative Approaches to CS1: Comparing Opinion to Outcome. Proceedings of the Twenty Sixth Australian Computer Science Conference (ACSC 2004), Dunedin, N.Z. (2004), 151--157. Google ScholarDigital Library
- Bergin, S. and Reilly, R. Programming: Factors That Influence Success. ACM SIGCSE Bulletin, 37, 1 (2005), 411--415. Google ScholarDigital Library
- Boyle, R., Carter, J., and Clark, M. What makes them succeed? Entry, progression and graduation in Computer Science. Journal of Further & Higher Education, 26, 1 (2002), 3--18.Google ScholarCross Ref
- Byrne, M., Flood, B., and Willis, P. Using the Student Learning Framework to Explore the Variation in Academic Performance of European Business Students. Journal of Further & Higher Education, 28, 1 (2004), 67--78.Google ScholarCross Ref
- Chamillard, A.T. and Sward, R.E. Learning Styles across the Curriculum. ACM SIGCSE Bulletin, 37, 3 (2005), 241--245. Google ScholarDigital Library
- Entwistle, N. Supporting Effective Learning: a research perspective. Centre for Research on Learning and Instruction, University of Edinburgh, Edinburgh (1996).Google Scholar
- Hands, K., Peiris, D. R. and Gregor, P. Development of a computer-based interviewing tool to enhance the requirements gathering process. Requirements Engineering, 9, 3 (2004), 204--216. Google ScholarDigital Library
- McCune, V. and Entwistle, N. The Deep Approach to Learning: Analytic Abstraction and Idiosyncratic Development. Proceedings of Innovations in Higher Education, Helsinki, Finland (2000).Google Scholar
- Morrison, M. and Newman, T. S. A Study of the Impact of Student Background and Preparedness on Outcomes in CS1. ACM SIGCSE Bulletin, 33, 1 (2001), 179--183. Google ScholarDigital Library
- Murphy, S. M. and Tyler, S. The Relationship between Learning Approaches to Part-Time Study of Management Courses and Transfer of Learning to the Workplace. Educational Psychology 25, 5 (2005), 455--469.Google ScholarCross Ref
- Ramalingam, V. and Wiedenbeck S. Development and Validation of Scores on a Computer Programming Self-Efficacy Scale and Group Analyses of Novice Programmer Self-Efficacy. Journal of Educational Computing Research, 19, 4 (1998), 367--381.Google ScholarCross Ref
- Rountree, N., Rountree, J., and Robins, A. Predictors of Success and Failure in a CS1 Course. ACM SIGCSE Bulletin 34, 4 (2002), 121--124. Google ScholarDigital Library
- Tait, H., Entwistle, N., and McCune, V. ASSIST: a reconceptualization of the Approaches to Studying Inventory. In Improving Student Learning: Improving Students as Learners (1998), Ed. C. Rust, The Oxford Centre for Staff & Learning Development, Oxford, 262--271.Google Scholar
- The British Psychological Society Code of Conduct, Ethical Principles and Guidelines, http://www.bps.org.uk/documentdownload-area/documentdownload$.cfm?file_uuid=6D0645CC-7E96-C67FD75E2648E5580115&ext=pdf, 2004.Google Scholar
- Ventura, P. Identifying Predictors of Success for an Objects-First CS1. Computer Science Education, 15, 3 (2005), 223--243.Google ScholarCross Ref
- Webster, R. Learning styles and design: The use of ASSIST for reflection and assessment. In A. Goody, J. Herrington & M. Northcote (Eds.), Proceedings of the 2002 Annual International Conference of the Higher Education Research and Development Society of Australasia (HERDSA), Perth, Australia (2002), 713--720.Google Scholar
- Wilson, B. A Study of Factors Promoting Success in Computer Science including Gender Differences. Computer Science Education, 12, 1-2 (2002), 141--164.Google ScholarCross Ref
Index Terms
- ASSISTing CS1 students to learn: learning approaches and object-oriented programming
Recommendations
ASSISTing CS1 students to learn: learning approaches and object-oriented programming
Identifying and managing students who experience difficulty with learning to program is a challenge for CS educators. In an attempt to answer the familiar question "What makes for success in CS1?" we have investigated student approaches to learning ...
What did students learn in programming workshops?: Comparison of students' reports from two programming workshops in Japan
FabLearn '16: Proceedings of the 6th Annual Conference on Creativity and Fabrication in EducationTeaching programming in elementary schools is becoming popular nowadays so that students can acquire logical thinking and programming abilities as 21st century skills. However, it remains unclear what students actually learn when they engage in ...
Experiences Teaching Coral Before C++ in CS1
SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1Coral was introduced several years ago to ease the learning in college-level introductory programming courses. Coral consists of a simple textual code language and corresponding flowchart language and a free web-based educational simulator. Previous ...
Comments