Abstract
The tasks of programming include complex knowledge and skills that is, from understanding problems to evaluating validity of program. Novice students often face difficulties in learning programming due to various issues and the nature of the subject, which can be vague and invisible. A survey was conducted on 294 students from two universities to study novices’ problems in dealing with tracking the logical flow and writing a simple code. The average score for tracking and writing skills were quite disappointing. Students were only able to master the static part of programming knowledge. They lacked the knowledge in understanding and tracing the dynamic behavior of the program. This research attempts to propose a model to shift the internal working memory load of students through integrated visualization tools that can reveal the dynamic behavior of programs and related concepts that appear in each level of program abstractions.
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References
Association for Computing Machinery.:Curriculum and guidelines for undergraduate degree programs in information technology. (ACM) - IEEE Computer Society (2008)
Paivi, K., Malmi, L.: Why Students Drop Out CS1 Course? In: ICER 2006 - 2nd International Computing Education Research Workshop, pp. 97–108. ACM, New York (2006)
McCracken, M., Almstrum, V., Diaz, D., Thomas, L., Guzdial, M., Utting, I., Hagan, D.: A multi-national, multi-institutional study of assessment of programming skills of first-year CS students A framework for first-year learning objectives. ACM SIGCSE Bulletin 33, 125–180 (2001)
Lister, R., Seppälä, O., Simon, B., Thomas, L., Adams, E.S., Fitzgerald, S., Fone, W., Hamer, J., Lindholm, M., McCartney, R., Moström, J.E., Sanders, K.: A multi-national study of reading and tracing skills in novice programmers. ACM SIGCSE Bulletin 36, 119 (2004)
Hundhausen, C.D., Douglas, S.A., Stasko, J.T.: A meta-study of algorithm visualization effectiveness. Journal of Visual Languages & Computing 13, 259–290 (2002)
Ihantola, P., Karavirta, V., Korhonen, A., Nikander, J.: Taxonomy of effortless creation of algorithm visualizations. In: ICER 2005 - International Workshop on Computing Education Research, pp. 123–133. ACM Press, New York (2005)
Levy, R.B.B., Ben-Ari, M.: We work so hard and they don’t use it: acceptance of software tools by teachers. ACM SIGCSE Bulletin 39, 250 (2007)
Cliburn, D.C.: Student opinions of Alice in CS1. In: 38th Annual Frontiers in Education Conference, FIE 2008, p. T3B–1. IEEE, New York (2008)
Maryhauser, A.V., Vans, A.M.: Program Understanding - A Survey. Technical Report, Colorado State University (1994)
Pennington, N.: Stimulus structures and mental representations in expert comprehension of computer programs. Cognitive psychology 19, 295–341 (1987)
von Mayrhauser, A., Vans, A.M.: From code understanding needs to reverse engineering tool capabilities. In: Proceedings of 6th International Workshop on Computer-Aided Software Engineering, pp. 230–239. IEEE Comput. Soc. Press, New Jersey (1993)
Robins, A., Rountree, J., Rountree, N.: Learning and teaching programming: A review and discussion. Computer Science Education 13, 137–172 (2003)
Pennington, N.: Comprehension strategies in programming. Ablex Publishing Corp., New York (1987)
Soloway, E.: Learning to program = learning to construct mechanisms and explanations. Communications of the ACM 29, 850–858 (1986)
Storey, M.-A.: Theories, tools and research methods in program comprehension: past, present and future. Software Quality Control 14, 187–208 (2006)
Cooper, S., Dann, W., Pausch, R.: Alice: a 3-D tool for introductory programming concepts. Journal of Computing Sciences in Colleges 15, 107–116 (2000)
Hundhausen, C., Brown, J.: What You See Is What You Code: A ‘live’ algorithm development and visualization environment for novice learners. Journal of Visual Languages & Computing 18, 22–47 (2007)
Robling, G., Schuler, M., Freisleben, B.: The ANIMAL Algorithm Animation Tool. In: The 5th Annual SIGCSE/SIGCUE ITiCSE Conference on Innovation and Technology in Computer Science Education, pp. 37–40 (2000)
DSN: Data Structure Navigator, http://dbs.mathematik.uni-marburg.de/research/projects/dsn/
Data Structure Visualization, http://www.cs.usfca.edu/~galles/visualization/
Moreno, A., Myller, N., Sutinen, E., Ben-Ari, M.: Visualizing programs with Jeliot 3. In: The Working Conference on Advanced Visual Interfaces - AVI 2004, p. 373. ACM Press, New York (2004)
Karavirta, V., Korhonen, A., Malmi, L., Stalnacke, K.: MatrixPro -a tool for demonstrating data structures and algorithms ex tempore. In: International Conference on Advanced Learning Technologies, pp. 892–893. IEEE, Los Alamitos (2004)
Carlisle, M.C., Wilson, T.A., Humphries, J.W., Hadfield, S.M.: RAPTOR: A Visual Programming Environment for Teaching Algorithmic Problem Solving. ACM SIGCSE Bulletin 37, 176 (2005)
Teaching Machine, http://www.engr.mun.ca/~theo/TM/
Rajala, T., Laakso, M.J., Kaila, E., Salakoski. VILLE–A, T.: language-independent program visualization tool. In: The Seventh Baltic Sea Conference on Computing Education Research (Koli Calling 2007), pp. 15–18. Australian Computer Society, Inc. (2007)
Interim Review Task Force.: Computer Science Curriculum 2008: An Interim Revision of CS 2001. Report from the Interim Review Task Association for Computing Machinery and IEEE Computer Society (2008)
Naps, T.L., Rodger, S., Velázquez-Iturbide, J.Á., Rößling, G., Almstrum, V., Dann, W., Fleischer, R., Hundhausen, C., Korhonen, A., Malmi, L., McNally, M.: Exploring the role of visualization and engagement in computer science education. ACM SIGCSE Bulletin 35 (2003)
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Affandy, Herman, N.S., Salam, S.B., Noersasongko, E. (2011). A Study of Tracing and Writing Performance of Novice Students in Introductory Programming. In: Zain, J.M., Wan Mohd, W.M.b., El-Qawasmeh, E. (eds) Software Engineering and Computer Systems. ICSECS 2011. Communications in Computer and Information Science, vol 181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22203-0_48
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DOI: https://doi.org/10.1007/978-3-642-22203-0_48
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