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Educational Model for Improving Programming Skills Based on Conceptual Microlearning Framework

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The Challenges of the Digital Transformation in Education (ICL 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 916))

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Abstract

The teachers of programming ask often students to develop complete programs in the early stages of the course. This strategy is inadequate for many students because learning programming is a complicated process. Taxonomies of educational objectives, such as Bloom’s and its derivatives can be an excellent source to define and validate proposed educational models developed for teaching programming not only at the introductory programming level at the universities but also for teaching quite complex programming tasks, which require specialized skills and technologies. Several learning approaches and taxonomies from the teaching programming point of view are analyzed in the paper. Subsequently, individual phases of the selected taxonomies are mapped to the interrelated parts of the proposed conceptual model of microlearning framework prepared in the university environment. Finally, their mutual consistency and contribution to the teaching programming theory are discussed.

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References

  1. Skalka, J., Drlik, M.: Conceptual framework of microlearning-based training mobile application for improving programming skills. In: Auer M., Tsiatsos T. (eds.) Interactive Mobile Communication Technologies and Learning, IMCL 2017. Advances in Intelligent Systems and Computing, vol. 725 (2018)

    Google Scholar 

  2. Looi, H.C., Seyal, A.H.: Problem-based learning: an analysis of its application to the teaching of programming. In: Conference Problem-Based Learning: An Analysis of its Application to the Teaching of Programming, pp. 68–75 (2014)

    Google Scholar 

  3. Razvi, S., Trevor-Roper, S., Goodliffe, T., Al-Habsi, F., Al-Rawahi, A.: Evolution of OAAA strategic planning: using ADRI as an analytical tool to review its activities and strategic planning. In: Proceedings of 7th Annual International Conference on Strategic Planning for Quality Assurance and Accreditation of Universities and Educational Arab Institutions (2012)

    Google Scholar 

  4. Sohail, M., Coldwell-Neilson, J.: Comparison of traditional and ADRI based teaching approaches in an introductory programming course. J. Inf. Technol. Educ. Res. 16, 267–283 (2016)

    Google Scholar 

  5. Keller, J.M.: The use of the ARCS model of motivation in teacher training. In: Aspects of Educational Technology, vol. 17, pp. 140–145 (1984)

    Google Scholar 

  6. Chang, Y.-H., Song, A.-C., Fang, R.-J.: The Study of Programming Language Learning by Applying Flipped Classroom (2018)

    Google Scholar 

  7. Alhazbi, S.: ARCS-based tactics to improve students’ motivation in computer programming course. In: 10th International Conference on Computer Science & Education (ICCSE), pp. 317–321 (2015)

    Google Scholar 

  8. Alhassan, R.: The effect of project-based learning and the ARCS motivational model on students’ achievement and motivation to acquire database program skills. J. Educ. Pract. 5(21), 158–164 (2014)

    Google Scholar 

  9. Saito, Y., Kaneko, K., Nohara, Y., Kudo, E., Yamada, M.: A game-based learning environment using the ARCS model at a university library. In: 2015 IIAI 4th International Congress on Advanced Applied Informatics (IIAI-AAI), pp. 403–408. IEEE (2015)

    Google Scholar 

  10. Albanese, M.A., Mitchell, S.: Problem-based learning: a review of literature on its outcomes and implementation issues. Acad. Med. 52–81 (1993)

    Google Scholar 

  11. Kolmos, A.e.a.: Problem Based Learning (2007)

    Google Scholar 

  12. Bransford, J.D., Stein, B.S.: The IDEAL Problem Solver: A Guide for Improving. WH Freeman and Company, New York (1984)

    Google Scholar 

  13. Gomes, A., Mendes, A.C.: An environment to improve programming education. Rousse. In: Proceedings of the 2007 International Conference on Computer systems and Technologies. ACM, p. 88 (2007)

    Google Scholar 

  14. Yip, W.: Generic skills development through the problem-based learning and information technology. In: Hamza, M.H., Potaturkin, 0.1., Shokin, Yu.1. (eds.) Proceeding of Automation, Control, and Information, pp. 72–80 (2002)

    Google Scholar 

  15. Huang, Y.-R., Cheng, Z., Feng, Y., Meng-Xiao, Y.: Research on teaching operating systems course using problem-based learning. In: 2010 5th International Conference on Computer Science and Education (ICCSE), pp. 691–694. IEEE (2010)

    Google Scholar 

  16. Ambrosio, A.P., Costa, F.M., Almeida, L., Franco, A., Macedo, J.: Identifying cognitive abilities to improve CS1 outcome. In: Frontiers in Education Conference (FIE), 2011, pp. F3G1–F3G7. IEEE (2011)

    Google Scholar 

  17. Miljanovic, M.A., Bradbury, J.S.: RoboBUG: a serious game for learning debugging techniques. In: Proceedings of the 2017 ACM Conference on International Computing Education Research, pp. 93–100 (2017)

    Google Scholar 

  18. Kazimoglu, C., Kiernan, M., Bacon, L., Mackinnon, L.: A serious game for developing computational thinking and learning introductory computer programming. Procedia-Soc. Behav. Sci. 47(2012), 1991–1999 (2012)

    Article  Google Scholar 

  19. Vosinakis, S., Anastassakis, G., Koutsabasis, P.: Teaching and learning logic programming in virtual worlds using interactive microworld representations. Br. J. Edu. Technol. 49(1), 30–44 (2018)

    Article  Google Scholar 

  20. Sung, K., Hillyard, C., Angotti, R., Panitz, M., Goldstein, D., Nordlinger, J.: Game-themed programming assignment modules: a pathway for gradual integration of gaming context into existing in-troductory programming courses. IEEE Trans. Educ. 54(3), 416–427 (2011)

    Article  Google Scholar 

  21. Gomes, A., Mendes, A.J.: Bloom’s taxonomy based approach to learn basic programming. In: EdMedia: World Conference on Educational Media and Technology. Association for the Advancement of Computing in Education (AACE), pp. 2547–2554 (2009)

    Google Scholar 

  22. Doran, M.V., Langan, D.D.: A cognitive based approach to introductory computer science courses: lesson learned. In: Proceeding SIGCSE 1995 Proceedings of the 26th SIGCSE Technical Symposium on Computer Science Education, pp. 218–222. ACM (1995)

    Google Scholar 

  23. Fuller, U., Johnson, C.G., Ahoniemi, T., Cukierman, D., Hernán-Losada, I., Jackova, J., Lahtinen, E., Lewis, T.L., Thompson, D.M., Riedesel, C., Thompson, E.: Developing a computer science-specific learning taxonomy. ACM SIGCSE Bull. 37(4), 152–170 (2007)

    Article  Google Scholar 

  24. Tovar, E., Soto, Ó.: Are new coming computer engineering students well prepared to begin future studies programs based on competences in the European Higher Education Area? In: 39th Frontiers in Education Conference, 2009, FIE 2009, pp. 1–6. IEEE (2009)

    Google Scholar 

  25. Bekki, J.M., Dalrymple, O., Butler, C.S.: A mastery-based learning approach for undergraduate engineering programs. In: Frontiers in Education Conference (FIE), pp. 1–6. IEEE (2012)

    Google Scholar 

  26. Bloom, B.S.: Taxonomy of educational objectives. Cogn. Domain 1, 20–24 (1956)

    Google Scholar 

  27. Anderson, L.W., Krathwohl, D.R., Airasian, P.W., Cruikshank, K.A., Mayer, R.E., Pintrich, P.R., Wittrock, M.C.: A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives, abridged edn. Addison Wesley Longman Inc, New York (2001)

    Google Scholar 

  28. Krathwohl, D.R.: A revision of Bloom’s taxonomy: an overview. Theory Pract. 41(4), 212–218 (2002)

    Article  Google Scholar 

  29. Machanick, P.: Experience of applying Bloom’s taxonomy. In: Proceeding Southern African Computer Lecturers’ Association Conference, pp. 135–144 (2000)

    Google Scholar 

  30. Azuma, M., Coallier, F., Garbajosa, J.: How to apply the Bloom taxonomy to software engineering. In: 11th Annual International Workshop on Software Technology and Engineering Practice, 2003, pp. 117–122. IEEE (2003)

    Google Scholar 

  31. Johnson, C.G., Fuller, U.: Is Bloom’s taxonomy appropriate for computer science? Proceedings of the 6th Baltic Sea conference on Computing Education Research: Koli Calling. ACM, pp. 120–123 (2006)

    Google Scholar 

  32. Biggs, J.B., Collis, K.F.: Evaluating the Quality of Learning. Academic Press, New York (1982)

    Google Scholar 

  33. Lister, R.: On blooming first year programming, and its blooming assessment. In: Australasian Conference on Computing Education, pp. 158–162. ACM (2000)

    Google Scholar 

  34. Lister, R., Simon, B., Thompson, E., Whalley, J.L., Prasad, C.: Not seeing the forest for the trees: novice programmers and the SOLO taxonomy. ACM SIGCSE Bull. 38(3) (2006)

    Google Scholar 

  35. Jimoyiannis, A.: Using SOLO taxonomy to explore students’ mental models of the programming variable and the assignment statement. Themes Sci. Technol. Educ. 4(2) (2013)

    Google Scholar 

  36. Thompson, E.: Holistic assessment criteria: applying SOLO to programming projects. In: Proceedings of the 9th Australasian Conference on Computing Education, vol. 66. Australian Computer Society (2007)

    Google Scholar 

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Acknowledgement

The research for this paper was financially supported by grant KEGA - 029UKF-4/2018 Innovative Methods in Programming Education in the University Education of Teachers and IT Professionals.

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Authors and Affiliations

  1. Constantine the Philosopher University in Nitra, Tr. A. Hlinku 1, 949 74, Nitra, Slovakia

    Ján Skalka & Martin Drlík

Authors
  1. Ján Skalka
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  2. Martin Drlík
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Correspondence to Martin Drlík .

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Editors and Affiliations

  1. Carinthia University of Applied Sciences , Villach, Kärnten, Austria

    Michael E. Auer

  2. Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Thrasyvoulos Tsiatsos

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Skalka, J., Drlík, M. (2020). Educational Model for Improving Programming Skills Based on Conceptual Microlearning Framework. In: Auer, M., Tsiatsos, T. (eds) The Challenges of the Digital Transformation in Education. ICL 2018. Advances in Intelligent Systems and Computing, vol 916. Springer, Cham. https://doi.org/10.1007/978-3-030-11932-4_85

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