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Submitted
Sep 11, 2021
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Dec 15, 2021
Published
Dec 31, 2021
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Abstract

Gamification has been extensively used in educational environments and instructional practices to enhance students’ engagement and motivation through the employment of game elements. However, delivering CT to students through Gamification is a challenge. There is a lack of studies on integrating Gamification into CT especially when it comes to considering student preferences such as learning styles. Besides, according to the review, the existing adaptive framework work does not directly incorporate Gamification and CT into education. Therefore, this study proposes an adaptive gamified framework that supports adaptive features based on students dimensions (verbal, visual) using the Felder-Silverman Learning Style Model (FSLSM) to foster CT skills and enhance students’ motivation and performance through the use of a modified version of the Moodle platform that supports adaptive learning features. The proposed framework integrates an "adaptive gamification framework" with the "student-centered framework" by adopting the available gamification elements in the "student-centered framework". Additionally, it matches the results with the proposed conceptual model that investigates the relationship between gamification and CT in the field of education to provide adaptive gamification and adaptive learning features. Furthermore, the results of the work indicated that students had a positive impact on the use of gamification in learning in terms of motivation and performance, as the game elements contributed to an increase in the desire of children to retake the tests and thus improved the performance of students.

Keywords

Adaptive Computational Thinking e-Learning Gamification Game Elements Learning Styles Motivation Moodle

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How to Cite
Altaie, M. A., & Norhayati. Abang Jawawi , D. (2021). Adaptive gamification framework to promote computational thinking in 8-13 year olds. Journal of E-Learning and Knowledge Society, 17(3), 89-100. https://doi.org/10.20368/1971-8829/1135552

References

  1. Agbo, F. J., Oyelere, S. S., Suhonen, J. & Adewumi, S. (2019). ‘A systematic review of computational thinking approach for programming education in higher education institutions’, ACM International Conference Proceeding Series.
  2. Angeli, C. & Giannakos, M. (2020). ‘Computational thinking education: Issues and challenges’, Computers in Human Behavior. Elsevier Ltd, 105.
  3. Angeli, C., Voogt, J., Fluck, A., Webb, M., Cox, M., Malyn-Smith, J. & Zagami, J. (2016). ‘International Forum of Educational Technology & Society A K-6 Computational Thinking Curriculum Framework: Implications for Teacher Knowledge’, Source: Journal of Educational Technology & Society, 19(3), 47-57.
  4. Barr, V. & Stephenson, C. (2011). ‘Bringing computational thinking to K-12: What is involved and what is the role of the computer science education community?’, ACM Inroads, 2(1), 48-54.
  5. Böckle, M., Micheel, I. & Bick, M. (2018). ‘A Design Framework for Adaptive Gamification Applications 2 . Theoretical background and related’, Proceedings of the 51st Hawaii International Conference on System Sciences (HICSS), 1227-1236.
  6. Buitrago Flórez, F., Casallas, R., Hernández, M., Reyes, A., Restrepo, S. & Danies, G. (2017). ‘Changing a Generation’s Way of Thinking: Teaching Computational Thinking Through Programming’, Review of Educational Research, 87(4), 834-860.
  7. Chen, C. M. & Sun, Y. C. (2012). ‘Assessing the effects of different multimedia materials on emotions and learning performance for visual and verbal style learners’, Computers and Education. Elsevier Ltd, 59(4), 1273-1285.
  8. Ching, Y. H., Hsu, Y. C. & Baldwin, S. (2018). ‘Developing Computational Thinking with Educational Technologies for Young Learners’, TechTrends. TechTrends, 62(6), 563-573.
  9. CSTA (2017). CSTA K-12 Computer Science Standards Revised.Retrieved from https://www.doe.k12.de.us/cms/lib/DE01922744/Centricity/Domain/176/CSTA%20Computer%20Science%20Standards%20Revised%202017.pdf
  10. Duncan, C., Bell, T. & Atlas, J. (2017). ‘What do the Teachers Think?’, 65-74.
  11. Filipcik, R. & Bielikova, M. (2014). ‘Motivating learners by dynamic score and personalized activity stream’, Proceedings - 9th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2014, 20-25.
  12. Grover, S. & Pea, R. (2013). ‘Computational Thinking in K-12: A Review of the State of the Field’, Educational Researcher, 42(1), 38-43.
  13. Hassan, M. A., Habiba, U., Majeed, F. & Shoaib, M. (2019). ‘Adaptive gamification in e-learning based on students’ learning styles’, Interactive Learning Environments. Taylor & Francis, 0(0), 1-21.
  14. Hooshyar, D., Pedaste, M., Yang, Y., Malva, L., Hwang, G. J., Wang, M., Lim, H. & Delev, D. (2020). ‘From Gaming to Computational Thinking: An Adaptive Educational Computer Game-Based Learning Approach’, Journal of Educational Computing Research.
  15. Hsu, T. C., Chang, S. C. & Hung, Y. T. (2018). ‘How to learn and how to teach computational thinking: Suggestions based on a review of the literature’, Computers and Education. Elsevier, 126(June), 296-310.
  16. Ishak, M. K. (2016). Enhancement of Learning Management System with Adaptive Features. Universiti Teknologi Malaysia.
  17. Kazimoglu, C., Kiernan, M., Bacon, L. & MacKinnon, L. (2012). ‘Learning programming at the computational thinking level via digital game-play’, Procedia Computer Science. Elsevier Masson SAS, 9(0), 522-531.
  18. Klock, A. C. T., Gasparini, I. & Pimenta, M. S. (2019). ‘User-Centered Gamification for E-Learning Systems: A Quantitative and Qualitative Analysis of its Application’, Interacting with Computers, 31(5), 425–445.
  19. Kotini, I. & Tzelepi, S. (2015). ‘A gamification-based framework for developing learning activities of computational thinking’, in Gamification in Education and Business, 219-252.
  20. Kuo, W. C. ,& Hsu, T. C. (2019). ‘Learning Computational Thinking Without a Computer: How Computational Participation Happens in a Computational Thinking Board Game’, Asia-Pacific Education Researcher. Springer Singapore, 29(1), 67–83.
  21. Kusuma, G. P., Wigati, E. K., Utomo, Y. & Putera Suryapranata, L. K. (2018). ‘Analysis of Gamification Models in Education Using MDA Framework’, Procedia Computer Science. Elsevier B.V., 135, 385-392.
  22. Lopes, V., Reinheimer, W., Medina, R., Bernardi, G. & Nunes, F. B. (2019). ‘Adaptive gamification strategies for education: a systematic literature review’, (Cbie), 1032.
  23. Nurul, S., & Mohamad, M. (2018). ‘Gamification Approach in Education to Increase Learning Engagement’, International Journal of Humanities, Arts and Social Sciences, 4(1), 22-32.
  24. Raiyn, J. (2016). ‘The Role of Visual Learning in Improving Students’ High-Order Thinking Skills’, Journal of Education and Practice, 7(24), 115-121.
  25. Rozi, F., Rosmansyah, Y. & Dabarsyah, B. (2019). ‘A Systematic Literature Review on Adaptive Gamification: Components, Methods, and Frameworks’, Proceedings of the International Conference on Electrical Engineering and Informatics, 2019-July(July), 187-190.
  26. De Sousa Borges, S., Durelli, V. H. S., Reis, H. M. & Isotani, S. (2014). ‘A systematic mapping on gamification applied to education’, Proceedings of the ACM Symposium on Applied Computing, (Icmc), 216-222.
  27. Swaid, S., & Suid, T. (2019). ‘Computational thinking education: Who let the dog out?’, Proceedings - 6th Annual Conference on Computational Science and Computational Intelligence, CSCI 2019, 788-792.
  28. Tatar, C. (2019). ‘A Literature Review: Fostering Computational Thinking Through Game-Based Learning in K-12’, 38-43.
  29. Toda, A., Carmo, R., Silva, A., Bittencourt, I. & Isotani, S. (2018). ‘An approach for planning and deploying gamification concepts with social networks within educational contexts’, International Journal of Information Management, 46.
  30. Toda, Armando M, Klock, A. C. T., Oliveira, W., Palomino, P. T., Rodrigues, L., Shi, L., Bittencourt, I., Gasparini, I., Isotani, S. & Cristea, A. I. (2019). ‘Analysing gamification elements in educational environments using an existing Gamification taxonomy’, Smart Learning Environments, 6(1), 16.
  31. Toda, A M, Oliveira, W., Klock, A. C., Palomino, P. T., Pimenta, M., Gasparini, I., Shi, L., Bittencourt, I., Isotani, S. & Cristea, A. I. (2019). ‘A Taxonomy of Game Elements for Gamification in Educational Contexts: Proposal and Evaluation’, in 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT), 84–88.
  32. Toda, A., Toledo Palomino, P., Oliveira, W., Rodrigues, L., Klock, A., Gasparini, I., Cristea, A. & Isotani, S. (2019). ‘How to Gamify Learning Systems? An Experience Report using the Design Sprint Method and a Taxonomy for Gamification Elements in Education’, Educational Technology & Society, 22(3), 47–60.
  33. Tomé Klock, A. C., da Cunha, L. F., de Carvalho, M. F., Eduardo Rosa, B., Jaqueline Anton, A. & Gasparini, I. (2015). ‘Gamification in e-Learning Systems: A Conceptual Model to Engage Students and Its Application in an Adaptive e-Learning System BT - Learning and Collaboration Technologies’, in Zaphiris, P. and Ioannou, A. (eds). Cham: Springer International Publishing, pp. 595–607.
  34. Vlahu-Gjorgievska, E., Videnovik, M. & Trajkovik, V. (2019). ‘Computational Thinking and Coding Subject in Primary Schools: Methodological Approach Based on Alternative Cooperative and Individual Learning Cycles’, Proceedings of 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, TALE 2018, (December), pp. 77–83.
  35. Wing, J. M. (2006). ‘Computational thinking’, Communications of the ACM, 49(3), 33–35.
  36. Wongso, O., Rosmansyah, Y. & Bandung, Y. (2015). ‘Gamification framework model, based on social engagement in e-learning 2.0’, Proceedings of 2014 2nd International Conference on Technology, Informatics, Management, Engineering and Environment, TIME-E 2014, pp. 10–14.
  37. Yadav, A., Hong, H. & Stephenson, C. (2016). ‘Computational Thinking for All: Pedagogical Approaches to Embedding 21st Century Problem Solving in K-12 Classrooms’, TechTrends. TechTrends, 60(6), 565–568.