Algorithmic Thinking Skills without Computers for Prospective Computer Science Teachers

Öz

Algorithmic thinking skills may be considered as an important attribute of any person lives in this century, especially for teachers, more particularly for computer science teachers. This study examines an elective course offered under the title of Algorithmic Thinking for prospective computer science teachers. A mixed method approach was followed for the current study. The study was carried out with the participation of sixth semester students of a Computer Education and Instructional Technology Department of an Education Faculty who may be considered as prospective computer science teachers. Twenty-eight students were enrolled the selective AT course opened for the period. Within the scope of the study, development of the course curriculum, instructional process of the course and evaluation of the course in line with students’ views and exam scores, are presented. Findings of the research suggest that the students find the Algorithmic Thinking course helping them to acquire some algorithmic thinking skills as well as some other academic and life related thinking abilities. Also, the course may be considered as a necessary course particularly for the training process of computer science teachers. In addition, the students think that the offered course was an effective and beneficial course.

Anahtar Kelimeler

• algorithmic thinking
• computational thinking
• computer science
• course
• prospective teacher

Bilgisayar Öğretmen Adayları için Bilgisayar Kullanmadan Algoritmik Düşünme Becerileri

Öz

Algoritmik düşünme becerileri bu yüzyılda yaşayan herkes için gerekli bir özellik olarak düşünülebilir. Günümüzde bireyler ve toplumlar bilgi iletişim teknolojilerini (BİT) kullanmak durumunda kalıyorlar. Bu durum onların BİT okuryazarı olmalarını gerektirmektedir. Bu gerekliliğin karşılanmasında öğretmenlere önemli görev düştüğü söylenebilir. Bu çalışmada, bilişim teknolojileri öğretmen adayları için Algoritmik Düşünme adıyla sunulan seçmeli bir ders ele alınmıştır. Çalışmada karma yöntem yaklaşımı izlenmiştir. Çalışma, bir Eğitim Fakültesi Bilgisayar ve Öğretim Teknolojileri Eğitimi Bölümü altıncı yarıyılında öğrenim gören bilgisayar bilimleri öğretmen adayları ile gerçekleştirilmiştir. Söz konusu dönem için açılan seçmeli dersi 28 öğrenci almıştır. Çalışma kapsamında öğrencilerin görüşleri ve sınav puanları doğrultusunda dersin öğretim süreci ve dersin değerlendirilmesine yer verilmiştir. Bununla beraber ders programının gelişim sürecine de yer verilmiştir. Araştırmanın bulguları, öğrencilerin bazı algoritmik düşünme becerilerinin yanı sıra diğer akademik ve yaşamla ilgili düşünme becerilerini kazanmaları noktasında Algoritmik Düşünme dersini yararlı bulduklarını göstermektedir. Ayrıca ders, özellikle bilgisayar bilimleri öğretmenlerinin yetiştirilmesi açısından gerekli bir ders olarak değerlendirilebilir. Ek olarak öğrencilerin, sunulan dersin etkili ve faydalı bir ders olduğu yönünde görüşler belirttikleri de belirtilebilir. 

Anahtar Kelimeler

• Algoritmik düşünme
• bilgi-işlemsel düşünme
• bilgisayar bilimleri
• ders
• öğretmen adayı
• Algoritmik düşünme, bilgi-işlemsel düşünme, bilgisayar bilimleri, ders, öğretmen adayı

Kaynakça

1. Aho, A. V. (2012). Computation and Computational Thinking. Computer Journal, 55(7), 832-835. https://doi.org/10.1093/comjnl/bxs074
2. Akpınar, Y., & Altun, A. (2014). Bilgi toplumu okullarında programlama eğitimi gereksinimi (The need of teaching programming in knowledge society schools). İlköğretim Online, 13(1).
3. Angeli, C., & Valanides, N. (2020). Developing young children's computational thinking with educational robotics: An interaction effect between gender and scaffolding strategy. Computers in Human Behavior, 105. https://doi.org/10.1016/j.chb.2019.03.018
4. Athanasiou, L., Topali, P., & Mikropoulos, T. A. (2017). The use of robotics in introductory programming for elementary students Advances in Intelligent Systems and Computing, https://link.springer.com/chapter/10.1007%2F978-3-319-55553-9_14
5. Ayaz, M. F., Oral, B., & Söylemez, M. (2015). Evaluation of the Post-Graduate Theses on Teacher Education in Turkey. Elementary Education Online, 14(2), 787-802.
6. Brusilovsky, P., Calabrese, E., Hvorecky, J., Kouchnirenko, A., & Miller, P. (1997). Mini-languages: A way to learn programming principles. Education and Information Technologies, 2(1), 65-83.
7. Bryant, E. A. (2017). An Unnamed Intersection: Where Computing Meets Liberal Arts. In New Directions for Computing Education (pp. 103-118). https://doi.org/10.1007/978-3-319-54226-3_7
8. Citta, G., Gentile, M., Allegra, M., Arrigo, M., Conti, D., Ottaviano, S., Reale, F., & Sciortino, M. (2019). The effects of mental rotation on computational thinking. Computers & Education, 141, 103613. https://doi.org/ARTN 103613 10.1016/j.compedu.2019.103613

9. Coates, P. (2010). Programming.Architecture (Vol. 9780203841488) [Book]. https://doi.org/10.4324/9780203841488
10. Cooper, S., Dann, W., & Pausch, R. (2000). Developing algorithmic thinking with Alice. The proceedings of ISECON,
11. Coufal, P., Hornik, T., Hubalovsky, S., & Musilek, M. (2017). Simulation of the Automatic Parking Assist System as a Method of the Algorithm Development Thinking. International Journal of Education and Information Technologies, 11, 37-43. ://WOS:000417788400006
12. Dagiene, V., Sentance, S., & Stupuriene, G. (2017). Developing a Two-Dimensional Categorization System for Educational Tasks in Informatics. Informatica, 28(1), 23-44. https://doi.org/10.15388/Informatica.2017.119
13. Dasso, A., Funes, A., Riesco, D. E., Montejano, G. A., Peralta, M., & Salgado, C. (2005). Teaching programming. I Jornadas de Educación en Informática y TICs en Argentina,
14. Essl, K. (2007). Algorithmic composition. In The Cambridge Companion to Electronic Music (pp. 107-125). https://doi.org/10.1017/CCOL9780521868617.008
15. Fidge, C., & Teague, D. (2009). Losing their marbles: syntax-free programming for assessing problem-solving skills. Proceedings of the Eleventh Australasian Conference on Computing Education-Volume 95,
16. Fincher, S. (1999). What are we doing when we teach programming? Frontiers in Education Conference, 1999. FIE'99. 29th Annual,
17. Futschek, G. (2006). Algorithmic thinking: the key for understanding computer science. International conference on informatics in secondary schools-evolution and perspectives,
18. Galezer, J., Beeri, C., Harel, D., & Yehudai, A. (1995). A High-School Program in Computer-Science. Computer, 28(10), 73-&. https://doi.org/Doi 10.1109/2.467599
19. Gao, P., Chee, T. S., Wang, L. L., Wong, A., & Choy, D. (2011). Self reflection and preservice teachers' technological pedagogical knowledge: Promoting earlier adoption of student-centred pedagogies. Australasian Journal of Educational Technology, 27(6), 997-1013. ://WOS:000295774400010
20. Grover, S., Pea, R., & Cooper, S. (2015). Designing for deeper learning in a blended computer science course for middle school students. Computer Science Education, 25(2), 199-237. https://doi.org/10.1080/08993408.2015.1033142
21. Ham, D. (2015). Playful Calculation. In Revolutionizing Arts Education in K-12 Classrooms through Technological Integration (pp. 125-144). https://doi.org/10.4018/978-1-4666-8271-9.ch006
22. Hromkovič, J. (2006). Contributing to general education by teaching informatics. International Conference on Informatics in Secondary Schools-Evolution and Perspectives,
23. Hromkovic, J., Kohn, T., Komm, D., & Serafini, G. (2017). Algorithmic Thinking from the Start. Bulletin of the European Association for Theoretical Computer Science(121), 132-139. ://WOS:000411843800008
24. Hsu, C. C., & Wang, T. I. (2018). Applying game mechanics and student-generated questions to an online puzzle-based game learning system to promote algorithmic thinking skills. Computers & Education, 121, 73-88. https://doi.org/10.1016/j.compedu.2018.02.002
25. Hubalovsky, S. (2012). Modeling and computer simulation of real process - solution of Mastermind board game. International Journal of Mathematics and Computers in Simulation, 6(1), 107-118.
26. Hubálovský, S. (2013). Modeling and simulation of real process - passing through the labyrinth as a method of development of algorithm thinking and programming skills. International Journal of Mathematics and Computers in Simulation, 7(2), 125-133.
27. Hubálovský, S., & Korinek, O. (2015). Evaluation of Algorithmic Thinking of Students Using Control Testing Environment. International Journal of Education and Information Technologies, 9, 205-208.
28. Hubálovský, S., Milková, E., & Pražák, P. (2010). Modeling of a real situation as a method of the algorithmic thinking development and recursively given sequences. WSEAS Transactions on Information Science and Applications, 7(8), 1090-1100.
29. Hubalovsky, S., & Musilek, M. (2013). Modeling, simulation and visualization of real processes in LOGO programming language as a method of development of algorithm thinking and programming skills. International Journal of Mathematics and Computers in Simulation, 7(2), 144-152.
30. Hubalovsky, S., & Šedivý, J. (2013). Algorithm development and computer simulation of position order decoding of Mastermind board game. Applied mechanics and materials,
31. Hunter, B. (1987). What is fundamental in an information age? A focus on curriculum. Education and Computing, 3(1-2), 63-73. https://doi.org/10.1016/s0167-9287(87)80513-7
32. Katai, Z. (2015). The challenge of promoting algorithmic thinking of both sciences- and humanities-oriented learners. Journal of Computer Assisted Learning, 31(4), 287-299. https://doi.org/10.1111/jcal.12070
33. Knuth, D. E. (1985). Algorithmic Thinking and Mathematical Thinking. American Mathematical Monthly, 92(3), 170-181. https://doi.org/Doi 10.2307/2322871
34. Kordaki, M. (2013). High school computing teachers' beliefs and practices: A case study. Computers & Education, 68, 141-152. https://doi.org/10.1016/j.compedu.2013.04.020
35. Mayer, R. E. (1981). The Psychology of How Novices Learn Computer-Programming. Computing Surveys, 13(1), 121-141. ://WOS:A1981NB99300006
36. Milková, E. (2005). Developing of algorithmic thinking: The base of programming. International Journal of Continuing Engineering Education and Life-Long Learning, 15(3-6), 135-147.
37. Milková, E., & Hùlková, A. (2013). Algorithmic and logical thinking development: Base of programming skills. WSEAS Transactions on Computers, 12(2), 41-51.
38. Milkova, E., & Sevcikova, A. (2017). Algorithmic thinking and mathematical competences supported via entertaining problems. International Journal of Education and Information Technologies, 11, 80-86. ://WOS:000417788400012
39. Papert, S. (1993). The children's machine: Rethinking school in the age of the computer. ERIC.
40. Pérez-Marín, D., Hijón-Neira, R., Bacelo, A., & Pizarro, C. (2020). Can computational thinking be improved by using a methodology based on metaphors and scratch to teach computer programming to children? Computers in Human Behavior, 105. https://doi.org/10.1016/j.chb.2018.12.027
41. Plerou, A., Vlamos, P., & Triantafillidis, C. (2017). The effectiveness of neurofeedback training in algorithmic thinking skills enhancement Advances in Experimental Medicine and Biology, https://link.springer.com/chapter/10.1007%2F978-3-319-56246-9_14
42. Saeli, M., Perrenet, J., Jochems, W. M., & Zwaneveld, B. (2011). Teaching programming in secondary school: a pedagogical content knowledge perspective. Informatics in Education, 10(1).
43. Silapachote, P., & Srisuphab, A. (2017). Engineering Courses on Computational Thinking Through Solving Problems in Artificial Intelligence. International Journal of Engineering Pedagogy, 7(3), 34-49. https://doi.org/10.3991/ijep.v7i3.6951
44. Thomas, J. O., Rankin, Y., Minor, R., & Sun, L. (2017). Exploring the Difficulties African-American Middle School Girls Face Enacting Computational Algorithmic Thinking over three Years while Designing Games for Social Change. Computer Supported Cooperative Work-the Journal of Collaborative Computing and Work Practices, 26(4-6), 389-421. https://doi.org/10.1007/s10606-017-9292-y
45. Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/Doi 10.1145/1118178.1118215
46. Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical transactions of the royal society of London A: mathematical, physical and engineering sciences, 366(1881), 3717-3725.
47. Zhang, L. C., & Nouri, J. (2019). A systematic review of learning computational thinking through Scratch in K-9. Computers & Education, 141, 103607. https://doi.org/ARTN 103607 10.1016/j.compedu.2019.103607
48. Zhao, D. C., Ma, X. R., & Qiao, S. B. (2017). What aspects should be evaluated when evaluating graduate curriculum: Analysis based on student interview. Studies in Educational Evaluation, 54, 50-57. https://doi.org/10.1016/j.stueduc.2016.11.003
49. Zhao, W., & Shute, V. J. (2019). Can playing a video game foster computational thinking skills? Computers & Education, 141, 103633. https://doi.org/10.1016/j.compedu.2019.103633