TY  - JOUR
T1  - A Neo-Piagetian Analysis of Algorithmic Thinking Development through the “Sorted” Digital Game
AU  - Nokkaew, Artorn
AU  - Chuechote, Suparat
AU  - Phongsasıthorn, Apichat
AU  - Laosınchaı, Parames
PY  - 2020
DA  - March
DO  - 10.30935/cet.685959
JF  - Contemporary Educational Technology
PB  - Ali ŞİMŞEK
WT  - DergiPark
SN  - 1309-517X
SP  - 1
EP  - 15
VL  - 12
IS  - 1
LA  - en
AB  - Sorting is a fundamental computing concept. As for today, it is taught at the secondary school level. However, this kind of algorithm is an obstacle for some students due to its high level of abstraction. To prevent discouragement as well as to incorporate a fun and challenging algorithmic task, a novel tablet-based digital game, Sorted, was created to serve the purpose. This research article embraces the neo-Piagetian framework of cognitive development and provides the theoretical-based explanation of how high school students establish sorting algorithms as a result of the digital gameplay. Twenty-three tenth-grade students, who have no proper knowledge of sorting algorithms, participated voluntarily in this study. They played the game with a multi-level design involving multiple unknowns. To later reflect on their operational reasoning and hence decision-making, the series of game actions were logged for individual empirical data. The sorting algorithm formation can be deduced from the logged sequential actions. They were coded and analyzed according to the neo-Piagetian framework to elicit the students’ operational reasoning. The discovery of the relations between actions and schematic reasoning to solve sorting problems suggests the impact of a digital game on algorithmic thinking development, and, in general, the use of a game for self-learning of computing concepts.
KW  - algorithmic thinking
KW  - digital game
KW  - neo-Piagetian theory
KW  - sorting algorithm
CR  - Almeida, F., & Simoes, J. (2019). The Role of Serious Games, Gamification and Industry 4.0 Tools in the Education 4.0 Paradigm. Contemporary Educational Technology, 10(2), 120-136.  https://doi.org/10.30935/cet.554469a
CR  - Baecker, R. (1998). Sorting out sorting: A case study of software visualization for teaching computer science. Software visualization: Programming as a multimedia experience, 1, 369381.
CR  - Beilin, H., & Pufall, P. B. (2013). Piaget’s theory: prospects and possibilities. Psychology Press.
CR  - Bell, T., Duncan, C., Jarman, S., & Newton, H. (2014). Presenting computer science concepts to high school students. Olympiads in Informatics, 8, 3-19.
CR  - Bell, T., Newton, H., Andreae, P., & Robins, A. (2012). The introduction of computer science to NZ high schools: an analysis of student work. Paper presented at the Proceedings of the 7th Workshop in Primary and Secondary Computing Education.
CR  - Boticki, I., Barisic, A., Martin, S., & Drljevic, N. (2013). Teaching and learning computer science sorting algorithms with mobile devices: A case study. Computer Applications in Engineering Education, 21(S1), E41-E50. https://doi.org/10.1002/cae.21561
CR  - Butler, J. (1997). How would Socrates teach games? A constructivist approach. Journal of Physical Education, Recreation & Dance, 68(9), 42-47. https://doi.org/10.1080/07303084.1997.10605029
CR  - Byrne, M. D., Catrambone, R., & Stasko, J. T. (1999). Evaluating animations as student aids in learning computer algorithms. Computers & education, 33(4), 253-278. https://doi.org/10.1016/S0360-1315(99)00023-8
CR  - Case, R. (1992). Neo-Piagetian theories of child development. In R. J. Sternberg & C. A. Berg (Eds.), Intellectual development (p. 161-196). Cambridge, UK: Cambridge University Press. Retrieved from https://assets.cambridge.org/97805213/97698/toc/9780521397698_toc.pdf
CR  - Case, R., & Sowder, J. T. (1990). The development of computational estimation: A neo-Piagetian analysis. Cognition and Instruction, 7(2), 79-104. https://doi.org/10.1207/s1532690xci0702_1
CR  - Csizmadia, A., Curzon, P., Dorling, M., Humphreys, S., Ng, T., Selby, C., & Woollard, J. (2015). Computational thinking-A guide for teachers. https://eprints.soton.ac.uk/424545/
CR  - Fancovicova, J., Prokop, P., & Usak, M. (2010). Web-Site as an educational tool in biology education: a case of nutrition issue. Educational Sciences: Theory and Practice, 10(2), 907-921.
CR  - Ginsburg, H. P., & Opper, S. (1988). Piaget’s theory of intellectual development. Upper Saddle River, NJ, USA: Prentice-Hall, Inc.
CR  - Harris, J. L., Al-Bataineh, M. T., & Al-Bataineh, A. (2016). One to One Technology and its Effect on Student Academic Achievement and Motivation. Contemporary Educational Technology, 7(4), 368-381.
CR  - Hunicke, R., LeBlanc, M., & Zubek, R. (2004). MDA: A formal approach to game design and game research. Paper presented at the Proceedings of the AAAI Workshop on Challenges in Game AI.
CR  - Knight, C. C., & Sutton, R. E. (2004). Neo-Piagetian theory and research: Enhancing pedagogical practice for educators of adults. London Review of Education, 2(1), 47-60. https://doi.org/10.1080/1474846042000177474
CR  - Lister, R. (2011). Concrete and other neo-Piagetian forms of reasoning in the novice programmer. Paper presented at the Proceedings of the Thirteenth Australasian Computing Education Conference-Volume 114.
CR  - Malan, D. J., & Leitner, H. H. (2007). Scratch for budding computer scientists. ACM Sigcse Bulletin, 39(1), 223-227. https://doi.org/10.1145/1227310.1227388
CR  - Meolic, R. (2013). Demonstration of sorting algorithms on mobile platforms. Paper presented at the CSEDU.
CR  - Phongsasithorn, A., Laosinchai, P., & Nokkaew, A. (2019). Sorted: An educational digital game for learning sorting algorithms. Paper presented at the International Symposium on Education and Psychology.
CR  - Piaget, J. (1964). Part I: Cognitive development in children: Piaget development and learning. Journal of Research in Science Teaching, 2(3), 176-186.
CR  - Shiue, Y., & Hsu, Y. (2017). Understanding factors that affecting continuance usage intention of game-based learning in the context of collaborative learning. Eurasia Journal of Mathematics, Science and Technology Education, 13(10), 6445-6455. https://doi.org/10.12973/ejmste/77949
CR  - Solaz-Portolés, J. J., & Sanjosé, V. (2008). Piagetian and Neo-Piagetian variables in science problem solving: directions for practice. Ciências & Cognição, 13(2), 192-200.
CR  - Teague, D., Corney, M., Ahadi, A., & Lister, R. (2013). A qualitative think aloud study of the early neo-piagetian stages of reasoning in novice programmers. Paper presented at the Proceedings of the Fifteenth Australasian Computing Education Conference-Volume 136.
CR  - Yildiz, H. D., Yilmaz, F. G. K., & Yilmaz, R. (2017). Examining the relationship between digital game preferences and computational thinking skills. Contemporary Educational Technology, 8(3), 359-369.
CR  - Yohannis, A., & Prabowo, Y. (2015). Sort attack: Visualization and gamification of sorting algorithm learning. Paper presented at the 2015 7th international conference on games and virtual worlds for serious applications (vs-games).
UR  - https://doi.org/10.30935/cet.685959
L1  - https://dergipark.org.tr/en/download/article-file/959968
ER  -