Toward an Inventory of Plans and Patterns, and Their Use to Foster Strategic Knowledge in Programming Novices
Page 305
Abstract
When learning to program, different types of knowledge and skills have to be built: syntactic knowledge, i.e., knowledge of the language features; conceptual knowledge, i.e., knowledge of the semantics of the various constructs; strategic knowledge, i.e. the ability to use syntactic and conceptual knowledge in the most appropriate and effective way to solve programming problems. Strategic knowledge also includes the ability to exploit and combine solutions to known problems to solve new ones and is one of the hardest skills to acquire when learning to programm [5, 6, 11]. Terms such as goals[10] patterns [5, 6, 11]. schema,[9] strategies[4], and variables' roles[3] have been used to refer to this kind of knowledge. Several authors suggest that strategic knowledge should be taught explicitly, however there are three main issues to address:
plans/patterns/schema are used sometimes interchangeably and sometimes similarly but not correspondingly; it is claimed that a small number of plans/patterns is needed in an introductory programming course, however there is no agreed upon inventory of plans/patterns among the CS community;
the notion of variables' roles isn't always explicitly linked to the notion of plans/patterns;
little instructional material is available that explicitly teaches strategies, and it is neither easy nor obvious how to design such material.
The aim of this study is to investigate whether and how such notions of plans/patterns/schema and variables' roles can be integrated into introductory programming courses.
The idea is to establish a framework that includes and arranges the different definitions presented in literature. The framework developed will be used for building a catalogue of plans/pattern and variables' roles encountered in CS1 practice, in CS1 assessment, and in the literature on introductory programming; this catalogue will be the basis for designing new instructional/learning material for fostering strategic knowledge. The developed material will be used in one of our introductory programming courses and in peer tutoring activities for the students. The effectiveness will be tested evaluating students programming skills with a pre-test and a post-test, using a group as a treatment group and another one as control group.
References
[1]
Piraye Bayman and Richard E Mayer. 1988. Using conceptual models to teach BASIC computer programming. Journal of Educational Psychology, Vol. 80, 3 (1988), 291.
[2]
Walter Beck, S. Rebecca Thomas, Janet Drake, J. Philip East, and Eugene Wallingford. 1996. Pattern Based Programming Instruction. In 1996 Annual Conference. ASEE Conferences, Washington, District of Columbia. https://peer.asee.org/6228.
[3]
Pauli Byckling and Jorma Sajaniemi. 2006. Roles of variables and programming skills improvement. ACM SIGCSE Bulletin, Vol. 38, 1 (2006), 413--417.
[4]
Michael de Raadt, Richard Watson, and Mark Toleman. 2009. Teaching and assessing programming strategies explicitly. Conferences in Research and Practice in Information Technology Series, Vol. 95 (2009), 45--54.
[5]
David Ginat, Eti Menashe, and Amal Taya. 2013. Novice difficulties with interleaved pattern composition. In Informatics in Schools. Sustainable Informatics Education for Pupils of all Ages - 6th ISSEP 2013, Oldenburg, Germany, Proceedings, Vol. 7780 LNCS. Springer, 57--67. https://doi.org/10.1007/978-3-642-36617-8_5
[6]
Michael McCracken, Tadeusz Wilusz, Vicki Almstrum, Danny Diaz, Mark Guzdial, Dianne Hagan, Yifat Ben-David Kolikant, Cary Laxer, Lynda Thomas, and Ian Utting. 2001. A multi-national, multi-institutional study of assessment of programming skills of first-year CS students. ACM SIGCSE Bulletin, Vol. 33, 4 (dec 2001), 125. https://doi.org/10.1145/572139.572181
[7]
Orna Muller. 2005. Pattern oriented instruction and the enhancement of analogical reasoning. ICER 2005 (2005), 57--67. https://doi.org/10.1145/1089786.1089792
[8]
Viera K. Proulx. 2004. Programming patterns and design patterns in the introductory computer science course. ACM SIGCSE Bulletin, Vol. 32, 1 (jul 2004), 80--84. https://doi.org/10.1145/331795.331819
[9]
Robert S. Rist. 1989. Schema creation in programming. Cognitive Science, Vol. 13, 3 (1989), 389--414. https://doi.org/10.1016/0364-0213(89)90018--9
[10]
Elliot Soloway. 1986. Learning to Program = Learning to Construct Mechanisms and Explanations. Communication of the ACM, Vol. 29, 9 (1986), 850--858.
[11]
Jacqueline L. Whalley, Raymond Lister, Errol Thompson, Tony Clear, Phil Robbins, P. K. Ajith Kumar, and Christine Prasad. 2006. An Australasian Study of Reading and Comprehension Skills in Novice Programmers, Using the Bloom and SOLO Taxonomies. In Proceedings of the 8th Australasian Conference on Computing Education - Volume 52 (Hobart, Australia) (ACE '06). Australian Computer Society, Inc., Darlinghurst, Australia, Australia, 243--252. http://dl.acm.org/citation.cfm?id=1151869.1151901
Index Terms
- Toward an Inventory of Plans and Patterns, and Their Use to Foster Strategic Knowledge in Programming Novices
Recommendations
How Plans Occur in Novices' Programs: A Method to Evaluate Program-Writing Skills
SIGCSE '20: Proceedings of the 51st ACM Technical Symposium on Computer Science EducationProgram-writing skills are often assessed with computer-based practical exams where students are required to design, write and test small programs according to specifications written in natural language. The evaluation of such tasks is usually based on ...
Validating, Refining, and Identifying Programming Plans Using Learning Curve Analysis on Code Writing Data
ICER '24: Proceedings of the 2024 ACM Conference on International Computing Education Research - Volume 1Background and Context: A major difference between expert and novice programmers is the ability to recognize and apply common and meaningful patterns in code. Previous works have attempted to identify these patterns as programming plans, such as counting ...
Teaching Introductory Programming: A Quantitative Evaluation of Different Approaches
Teaching programming to beginners is a complex task. In this article, the effects of three factors—choice of programming language, problem-solving training, and the use of formative assessment—on learning to program were investigated. The study adopted ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
August 2020
364 pages
ISBN:9781450370929
DOI:10.1145/3372782
- General Chairs:
- Anthony Robins,
- Adon Moskal,
- Amy J. Ko,
- Renée McCauley,
- Program Chairs:
- Anthony Robins,
- Amy J. Ko
Copyright © 2020 Owner/Author.
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 07 August 2020
Check for updates
Author Tags
Qualifiers
- Poster
Conference
ICER '20
Sponsor:
ICER '20: International Computing Education Research Conference
August 1 - 5, 2020
Virtual Event, New Zealand
Acceptance Rates
Overall Acceptance Rate 189 of 803 submissions, 24%
Upcoming Conference
ICER 2025
- Sponsor:
- sigcse
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 98Total Downloads
- Downloads (Last 12 months)11
- Downloads (Last 6 weeks)0
Reflects downloads up to 24 Nov 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in