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Computational thinking with the web crowd using CodeMapper

Published:08 April 2019Publication History

ABSTRACT

It has been argued that computational thinking should precede computer programming in the course of a career in computing. This argument is the basis for the slogan "logic first, syntax later" and the development of many cryptic syntax removed programming languages such as Scratch!, Blockly and Visual Logic. The goal is to focus on the structuring of the semantic relationships among the logical building blocks to yield solutions to computational problems. In this paper, we introduce a new programming platform, called the CodeMapper, in which learners are able to build computational logic in independent modules and aggregate them to create complex modules. CodeMapper is an abstract development environment in which rapid visual prototyping of systems is possible by combining already developed independent modules in logical steps.

References

  1. D. W. Barowy, E. D. Berger, D. G. Goldstein, and S. Suri. Voxpl: Programming with the wisdom of the crowd. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, Denver, CO, USA, May 06-11, 2017., pages 2347--2358, 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. F. Chen and S. Kim. Crowd debugging. In Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, ESEC/FSE 2015, pages 320--332, New York, NY, USA, 2015. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. S. Ferrán, A. Beghelli, G. H. Cánepa, and F. Jensen. Correctness assessment of a crowdcoding project in a computer programming introductory course. Comp. Applic. in Engineering Education, 26(1):162--170, 2018.Google ScholarGoogle ScholarCross RefCross Ref
  4. J. Ferrante, K. J. Ottenstein, and J. D. Warren. The program dependence graph and its use in optimization. ACM Trans. Program. Lang. Syst., 9(3):319--349, 1987. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. F. Giunchiglia, A. Autayeu, and J. Pane. S-match: An open source framework for matching lightweight ontologies. Semantic Web, 3(3):307--317, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. H. M. Jamil. Automated personalized assessment of computational thinking MOOC assignments. In Proceedings of The 17th IEEE International Conference on Advanced Learning Technologies, ICALT 2017, Timisoara, Romania, July 3-7, pages 261--263, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  7. H. M. Jamil. Visual computational thinking using Patch. In Proceedings of The 16th International Conference on Web-based Learning, ICWL 2017, Cape Town, South Africa, September 20-22, pages 208--214. Springer, LNCS 10473, 2017.Google ScholarGoogle ScholarCross RefCross Ref
  8. H. M. Jamil. A free-choice social learning network for computational thinking. In Proceedings of The 18th IEEE International Conference on Advanced Learning Technologies, ICALT 2018, Mumbai, India, July 9-13, 2018. To appear.Google ScholarGoogle ScholarCross RefCross Ref
  9. H. M. Jamil, X. Mou, R. B. Heckendorn, C. L. Jeffery, F. T. Sheldon, C. S. Hall, and N. M. Peterson. Authoring adaptive digital computational thinking lessons using vTutor for web-based learning. In Proceedings of The 16th International Conference on Web-based Learning, ICWL 2018, Chiang Mai, Thailand, August 22-24. Springer, 2018. To appear.Google ScholarGoogle ScholarCross RefCross Ref
  10. M. Kölling, N. C. C. Brown, and A. AlTadmri. Frame-based editing: Easing the transition from blocks to text-based programming. In WiPSCE, pages 29--38. ACM, 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. W. M. Kunkle and R. B. Allen. The impact of different teaching approaches and languages on student learning of introductory programming concepts. TOCE, 16(1):3:1--3:26, 2016. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. T. Mattauch. Innovate through crowd sourcing. In Proceedings of the 41st Annual ACM SIGUCCS Conference on User Services, SIGUCCS '13, pages 39--42, New York, NY, USA, 2013. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. L. Porter, M. Guzdial, C. McDowell, and B. Simon. Success in introductory programming: what works? Commun. ACM, 56(8):34--36, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. P. Vanvorce and H. M. Jamil. Computational thinking with the web crowd using codemapper. CoRR, abs/1811.04162, 2018.Google ScholarGoogle Scholar
  15. A. Vihavainen, J. Airaksinen, and C. Watson. A systematic review of approaches for teaching introductory programming and their influence on success. In ICER, pages 19--26. ACM, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. C. Watson and F. W. B. Li. Failure rates in introductory programming revisited. In ITiCSE, pages 39--44. ACM, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. D. Weintrop and N. R. Holbert. From blocks to text and back: Programming patterns in a dual-modality environment. In SIGCSE, pages 633--638. ACM, 2017. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. J. M. Wing. Computational thinking, 10 years later. https://tinyurl.com/yapf5zas, Mar. 2016. Accessed: August 31, 2017.Google ScholarGoogle Scholar
  19. C. Yen and T. Wang. Using self-explanation and ontology for providing proper feedbacks in a programming environment. In 6th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2017, Hamamatsu, Japan, July 9-13, 2017, pages 585--590, 2017.Google ScholarGoogle ScholarCross RefCross Ref

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              cover image ACM Conferences
              SAC '19: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing
              April 2019
              2682 pages
              ISBN:9781450359337
              DOI:10.1145/3297280

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              • Published: 8 April 2019

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