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An Active Learning App Development Module for Novices: a Self-Assessment Approach

Published:05 October 2021Publication History

ABSTRACT

This paper is part of continuous research in an experimental educational project that started in 2013, whose methodology used was mainly action research. It is proposed and analyzed a module, offered in 2019, for teaching mobile applications development with a focus on Swift Playground and Xcode programming and UX/UI design. The audience are students beginning in programming and students beginning in design using the Challenge Based Learning active methodology. The module, called Crash Challenge, lasted eight weeks in two different classes, one with 25 students and the other with 24 students, with 44 applications published and several self-assessment touchpoints. The scope of the paper involves the perception of the programming learning of the subset of 23 non-programmer students. During the module, we collected data through surveys, feedbacks and self-reflection texts. The surveys allowed a quantitative analysis of a proposed self-perception and the texts of self-reflection investigated by a qualitative analysis of thematic networks to identify the perception of learning. The findings may be used as best practices to help the creation or improvement of app development courses in order to train students from areas not directly related to programming, and enhance self-assessment and self-pacing as learning practices in this area.

References

  1. A. Vihavainen, M. Paksula, and M. Luukkainen. 2011. Extreme apprenticeship method in teaching programming for beginners. In Proceedings of SIGCSE 11. New York, NY, USA, 93–98.Google ScholarGoogle Scholar
  2. M. Urban-Lurain and D. J. Weinshank, 2000. Is there a role for programming in non-major computer science courses?, 30th Annual FIE Conference. Building on A Century of Progress in Engineering Education. Conference Proceedings (IEEE Cat. No.00CH37135), Kansas City, MO, USA.Google ScholarGoogle ScholarCross RefCross Ref
  3. F. Amiri, 2011. Programming as Design: The Role of Programming in Interactive Media Curriculum in Art and Design, The International journal of Art & Design Education, vol. 30, issue 2, 200-210.Google ScholarGoogle Scholar
  4. R. F. Gonzatto. 2018. Usuários e Produção da Existência: contribuições de Álvaro Vieira Pinto e Paulo Freire à Interação Humano-Computador. Doctoral dissertation. Federal University of Technology – Paraná.Google ScholarGoogle Scholar
  5. J. Grudin, 1993. Interface: an evolving concept. Commun. ACM 36, 4, 110–119. DOI:https://doi.org/10.1145/255950.153585Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. L. Suchman, 1993. Working relations of technology production and use, Computer Supported Cooperative Work, vol 2, 21-39.Google ScholarGoogle ScholarCross RefCross Ref
  7. P. Agre, 1995. Conceptions of the user in computer systems design. The social and interactional dimensions of human-computer interfaces. Cambridge University Press, USA, 67–106.Google ScholarGoogle Scholar
  8. H. Thimbleby, 2008. Ignorance of interaction programming is killing people. interactions vol. 15, issue 5, 52–57.Google ScholarGoogle Scholar
  9. Apple, 2008. Classrooms of Tomorrow—Today Learning in the 21st Century.Google ScholarGoogle Scholar
  10. M. Nichols, K. Cator, M. Torres and D. Henderson, 2008. Challenge Based Learning User Guide. Redwood City, CA. Digital Promise.Google ScholarGoogle Scholar
  11. M. Nichols, K. Cator. 2008. Challenge Based Learning White Paper, Apple Inc.Google ScholarGoogle Scholar
  12. D. Baldwin, G. Braught, and A. Holland-Minkley, 2017. Computing Education in Liberal Arts Colleges: A Status Report of the SIGCSE Committee. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education. New York.Google ScholarGoogle Scholar
  13. H. Walker and C. Kelemen, 2010. Computer science and the liberal arts: a philosophical examination. ACM Transactions on Computing Education.Google ScholarGoogle Scholar
  14. M. Prince, 2004. Does Active Learning Work? A Review of the Research. Journal of Engineering Education, vol. 9, 223-231.Google ScholarGoogle ScholarCross RefCross Ref
  15. F. V. Binder, M. Nichols, S. Reinehr & A. Malucelli. 2017. Challenge Based Learning Applied to Mobile Software Development Teaching. In Proceedings - 30th IEEE Conference on Software Engineering Education and Training, CSEE and T 2017. https://doi.org/10.1109/CSEET.2017.19Google ScholarGoogle ScholarCross RefCross Ref
  16. N. Dehbozorgi, 2017. Active Learning Design Patterns for CS Education. In Proceedings of the 2017 ACM Conference on International Computing Education Research. Association for Computing Machinery, New York.Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. L. Echeverria, R. Cobos, L. Machuca and I. Claros, Iván, 2017. Using collaborative learning scenarios to teach programming to non-CS majors. Computer Applications in Engineering Education. vol. 25.Google ScholarGoogle Scholar
  18. J. McConnell, 1996. Active learning and its use in computer science. In ITiCSE ’96: Proceedings of the 1st conference on Integrating technology into computer science education, ACM Press, 52–54.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. M. Borrego , 2018. Systematic Literature Review of Students’ Affective Responses to Active Learning: Overview of Results, 2018 IEEE FIE San Jose, CA, USA, 1-7.Google ScholarGoogle Scholar
  20. L. Andrade, 2019. A Critical Review of Research on Student Self-Assessment, Frontiers in Education, vol. 4, doi: 10.3389/feduc.2019.00087Google ScholarGoogle ScholarCross RefCross Ref
  21. H. Andrade, 2010. Students as the definitive source of formative assessment: academic self-assessment and the self-regulation of learning, in Handbook of Formative Assessment, eds H. Andrade and G. Cizek, New York.Google ScholarGoogle Scholar
  22. R. Tejeiro, J. Gomez-Vallecillo, A. Romero, M. Pelegrina, A. Wallace, and E. Emberley. 2012. Summative self-assessment in higher education: implications of its counting towards the final mark. Electron. J. Res. Educ. Psychol. vol. 10.Google ScholarGoogle Scholar
  23. P. Coughlan, and D. Coghlan, 2002. Action research for operations management. International Journal of Ops & Production Management.Google ScholarGoogle Scholar
  24. F. V. Binder, R. Albuquerque, S. Reinehr & A. Malucelli. 2020. Innovation and active learning for training mobile app developers. In Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET '20). New York.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. J. Attridge-Stirling, 2001. Thematic networks: an analytic tool for qualitative research. Qualitative Research, vol. 1, issue 3, 385–405.Google ScholarGoogle Scholar
  26. B. Buxton, 2007. Sketching User Experiences: Getting the Design Right and the Right Design. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA.Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. E. Churchill, J. Preece and A. Bowser, 2014. Developing a living HCI curriculum to support a global community. In CHI ’14 Extended Abstracts on Human Factors in Computing Systems. New York, NY, USA, 135-138. doi:https://doi.org/10.1145/2559206.2559236 Google ScholarGoogle Scholar
  28. Marcelo H. Yamaguti, Flávio M. de Oliveira, Cássio A. W. Trindade, and Alessandra C. S. Dutra. 2017. AGES: An Interdisciplinary Space Based on Projects for Software Engineering Learning. In Proceedings of the 31st Brazilian Symposium on Software Engineering (SBES'17). New York.Google ScholarGoogle Scholar
  29. M. da C. O. de Souza, S. R. B. Oliveira, and S. R. L. Meira. 2017. A Systematic Review to Assist in Identifying Teaching Approaches to Guide the Application of an Interdisciplinary Software Factory in IT Undergraduation. In Proceedings of the 31st Brazilian Symposium on Software Engineering (SBES'17). Association for Computing Machinery, New York, NY, USA.Google ScholarGoogle ScholarDigital LibraryDigital Library
  1. An Active Learning App Development Module for Novices: a Self-Assessment Approach

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    • Published in

      cover image ACM Other conferences
      SBES '21: Proceedings of the XXXV Brazilian Symposium on Software Engineering
      September 2021
      473 pages
      ISBN:9781450390613
      DOI:10.1145/3474624

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      • Published: 5 October 2021

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