Çevrimiçi Arduino Programlama Öğretiminde Bağlılık ve Özyeterlilik Algısı

Bu araştırmada çevrimiçi Arduino programlama öğretiminin bağlılık ve öz-yeterlik algısı açısından değerlendirilmesi amaçlanmıştır. Araştırma kapsamında geliştirilen çevrimiçi öğretim Tinkercad benzetim ortamında hazırlanmış etkileşimli Arduino videolarının yanı sıra iki haftada bir yapılan sanal sınıf toplantılarından oluşmaktadır. Öğretim Millî Eğitim Bakanlığı’nın Hayat Boyu Öğrenme Genel Müdürlüğü tarafından geliştirilen Arduino Programlama ve Uyum Eğitimi modülünün Arduino Uygulamaları ünitesi kapsamındaki hedef ve kazanımları içerecek şekilde sekiz hafta sürmüştür. Nicel araştırma yöntemlerinin kullanıldığı araştırmada tek gruplu ön test son test deneysel desen araştırma deseni olarak benimsenmiştir. Araştırmanın bağımsız değişkeni çevrimiçi Arduino öğretimi bağımlı değişkenleri ise çevrimiçi bağlılık ve programlama öz-yeterlik algısıdır. Çevrimiçi öğretime Kırklareli Üniversitesi’nde eğitim alan 37 öğrenci katılım göstermiştir. Araştırmada ön-test son test farklarının normal dağılım gösterdiği durumlarda bağımlı örneklemler için t-testi normal dağılım göstermediği durumlarda ise Wilcoxon sıra sayıları işaret testi uygulanmıştır. Yapılan veri analizi sonuçlarına göre öğrenciler çevrimiçi Arduino programlama öğretiminde programlama öz-yeterlik algıları basit ve karmaşık düzeyde son test lehine anlamlı olarak değişmiştir. Çevrimiçi bilişsel ve duyuşsal bağlılıkta benzer şekilde son test lehine anlamlı değişim gözlemlenirken davranışsal bağlılıkta oluşan fark anlamlı değildir. Araştırma sonuçlarına göre geliştirilen çevrimiçi Arduino programlama öğretimi Tinkercad ’in uygulama olanağı sunması, soru cevap etkileşimi ve iki haftada bir yapılan sanal sınıf toplantıları gibi özellikleriyle birlikte düşünüldüğünde programlama öz-yeterlik algısını ve çevrimiçi bağlılığı olumlu etkilemektedir. Araştırma sonuçları ve alanyazında yapılan çalışmalar dikkate alınarak Tinkercad ve Arduino’nun çevrimiçi programlama öğretiminde kullanılmasına yönelik araştırmacılara ve uygulayıcılara öneriler getirilmiştir.

Anahtar Kelimeler:

arduino programlama, çevrimiçi bağlılık, çevrimiçi öğrenme öz-yeterlilik algısı, Tinkercad

Perception of Engagement and Self-Efficacy in Online Arduino Instruction

In this research, it is aimed to evaluate the online Arduino programming teaching in terms of university students' perception of engagement and self-efficacy. The online teaching developed within the scope of the research consists of interactive Arduino videos prepared in the Tinkercad simulation environment, as well as virtual classroom meetings held every two weeks. The education lasted for eight weeks, including the objectives and achievements within the scope of the Arduino Applications unit of the Arduino Programming and Adaptation Training module developed by the General Directorate of Lifelong Learning of the Ministry of National Education. In the study, in which quantitative research methods were used, a single-group pre-test post-test experimental design was adopted as the research design. The independent variable of the research is online Arduino teaching, and the dependent variables are online engagement and programming self-efficacy perception. 37 students studying at Kırklareli University participated in the online teaching. In the study, in cases where the pre-test and post-test differences were normally distributed, the t-test for dependent samples was not normally distributed, and the Wilcoxon ordinal number sign test was applied. According to the results of the data analysis, the students' self-efficacy perceptions of programming in online Arduino programming teaching changed significantly in favor of the simple and complex posttest. Similarly, a significant change in favor of the posttest was observed in online cognitive and affective engagement, while the difference in behavioral engagement was not significant. The online Arduino programming teaching developed according to the results of the research, when considered together with the features of Tinkercad such as providing application opportunity, question-answer interaction and virtual class meetings held every two weeks, positively affects the perception of programming self-efficacy and online engagement. Considering the research results and the studies in the literature, suggestions have been made to researchers and practitioners for the use of Tinkercad and Arduino in online programming teaching.

Keywords:

online engagement online learning, self-efficacy, tinkercad, arduino programming,

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2022 EDUCAUSE Horizon Report Teaching and Learning Edition. (2022, Nisan 18). Geliş tarihi 27 Nisan 2023, gönderen https://library.educause.edu/resources/2022/4/2022-educause-horizon-report-teaching-and-learning-edition
Ahmadzadeh, M., Elliman, D., & Higgins, C. (2005). An analysis of patterns of debugging among novice computer science students. Proceedings of the 10th annual SIGCSE conference on Innovation and technology in computer science education, 84-88. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/1067445.1067472
Altun, A., & Mazman, S. G. (2012). Programlamaya İlişkin Öz Yeterlilik Algısı Ölçeğinin Türkçe Formumun Geçerlilik ve Güvenirlik Çalışması. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 3(2), 297-308.
Arduino Project Hub. (2023). Geliş tarihi 27 Mart 2023, gönderen https://projecthub.arduino.cc/
Arslan, K., & Tanel, Z. (2021). Analyzing the effects of Arduino applications on students’ opinions, attitude and self-efficacy in programming class. Education and Information Technologies, 26(1), 1143-1163. https://doi.org/10.1007/s10639-020-10290-5
Askar, P., & Davenport, D. (2009). An Investıgatıon of Factors Related to Self-Effıcacy for Java Programmıng Among Engıneerıng Students. The Turkish Online Journal of Educational Technology, 8(1).
Astin, A. W. (1999). Student involvement: A developmental theory for higher education. Journal of College Student Development, 40, 518-529.
Bandura, A. (1997). Self-Efficacy: The Exercise of Control. Worth Publishers.
Bandura, A., & Locke, E. A. (2003). Negative self-efficacy and goal effects revisited. Journal of Applied Psychology, 88, 87-99. https://doi.org/10.1037/0021-9010.88.1.87
Blackwell, A. F. (2002). What is programming? PPIG, 14, 204-218.
Cevahi̇r, H., & Özdemi̇r, M. (2017). Programlama Öğretiminde Karşılaşılan Zorluklara Yönelik Öğretmen Görüşleri Ve Çözüm Önerileri.
Cheah, C. S. (2020). Factors Contributing to the Difficulties in Teaching and Learning of Computer Programming: A Literature Review. Contemporary Educational Technology, 12(2), ep272. https://doi.org/10.30935/cedtech/8247
Coates, H. (2007). A model of online and general campus-based student engagement. Assessment & Evaluation in Higher Education, 32(2), 121-141.
Cohen, L., Manion, L., & Morrison, K. (2017). Research Methods in Education. Routledge.
Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Pearson education, Inc. Geliş tarihi gönderen http://nuir.nkumbauniversity.ac.ug/xmlui/handle/20.500.12383/985
DesPortes, K., & DiSalvo, B. (2019). Trials and Tribulations of Novices Working with the Arduino. Proceedings of the 2019 ACM Conference on International Computing Education Research, 219-227. Toronto ON Canada: ACM. https://doi.org/10.1145/3291279.3339427
Ekici, M., & Çınar, M. (2020). The Validity and Reliability Study of The Turkish Version of Computer Programming Self-Efficacy Scale. Anadolu Journal Of Educational Sciences International, 1019-1042. https://doi.org/10.18039/ajesi.725161
Erol, O. (2020). How do Students’ Attitudes Towards Programming and Self-Efficacy in Programming Change in the Robotic Programming Process? International Journal of Progressive Education, 16(4), 13-26. https://doi.org/10.29329/ijpe.2020.268.2
Eryılmaz, S., & Deni̇z, G. (2021). Effect of Tinkercad on Students’ Computational Thinking Skills and Perceptions: A Case of Ankara Province. The Turkish Online Journal of Educational Technology, 20(1).
Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (C. 7). McGraw-hill New York.
Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School Engagement: Potential of the Concept,State of the Evidence. Review of Educational Research, 74(1), 59-109.
Gagne, R. M., Briggs, L. J., & Wager, W. W. (1992). Principles of instructional design (4. bs). New York, NY, USA: Harcourt Brace College Publishers.
Groccia, J. E., & Hunter, M. S. (2012). The first-year seminar: Designing, implementing, and assessing courses to support student learning and success: Volume II—Instructor training and development. The National Resource Center for the First-Year Experience and Students in ….
Grover, S., & Pea, R. (2013). Computational Thinking in K–12: A Review of the State of the Field. Educational Researcher, 42(1), 38-43. https://doi.org/10.3102/0013189X12463051
Gunes, H., & Kucuk, S. (2022). A systematic review of educational robotics studies for the period 2010–2021. Review of Education, 10(3). https://doi.org/10.1002/rev3.3381
He, W., Xu, G., & Kruck, S. (2014). Online IS Education for the 21st Century. Journal of Information Systems Education, 25(2), 101-106.
Kadar, R., Abdul Wahab, N., Othman, J., Shamsuddin, M., & Mahlan, S. B. (2021). A Study of Difficulties in Teaching and Learning Programming: A Systematic Literature Review. International Journal of Academic Research in Progressive Education and Development, 10(3), Pages 591-605. https://doi.org/10.6007/IJARPED/v10-i3/11100
Kadriu, A., Abazi-Bexheti, L., Abazi-Alili, H., & Ramadani, V. (2020). Investigating trends in learning programming using YouTube tutorials. International Journal of Learning and Change, 12(2), 190-208. https://doi.org/10.1504/IJLC.2020.106721
Kanaparan, G., Cullen, R., & Mason, D. (2019). Effect of Self-efficacy and Emotional Engagement on Introductory Programming Students. Australasian Journal of Information Systems, 23. https://doi.org/10.3127/ajis.v23i0.1825
Kellermayer, B., Meyer, D., Stirzel, M., Kirmaier, A., & Bergande, B. (2020). Raising Motivation of Programming Novices? Findings from a Controlled Laboratory Experiment Using Anki Vector TM Robots. 2020 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 150-156.
Takamatsu, Japan: IEEE. https://doi.org/10.1109/TALE48869.2020.9368406
Konecki, M., & Petrlić, M. (2014). Main problems of programming novices and the right course of action. Kuh, G. D. (2003). What We’re Learning About Student Engagement From. Change: The Magazine of Higher Learning, 35(2), 24-32. https://doi.org/10.1080/00091380309604090
Kuh, G. D., Kinzie, J., Buckley, J. A., Bridges, B. K., & Hayek, J. C. (2006). What Matters to Student Success: A Review of the Literature.
Luchaninov, D., Bazhenov, R., Sabirova, V., Mamyrova, M., & Zholdosheva, A. (2021). Online training of students of applied physics in the field of circuitry. Journal of Physics: Conference Series, 1889(2), 022030. https://doi.org/10.1088/1742-6596/1889/2/022030
Mayer, R. E., Fiorella, L., & Stull, A. (2020). Five ways to increase the effectiveness of instructional video. Educational Technology Research and Development, 68(3), 837-852. https://doi.org/10.1007/s11423-020-09749-6
Milne, I., & Rowe, G. (2002). Difﬁculties in Learning and Teaching Programming—Views of Students and Tutors. Kluwer Academic Publishers, 7(1), 55-66. https://doi.org/10.1023/A:1015362608943
Newmann, F. M. (1992). Student Engagement and Achievement in American Secondary Schools. Teacher College Press.
Ocak, M. A., & Efe, A. A. (2019). Arduino ile Robotik Uygulamalar (1. Baskı). Ankara: Anı Yayıncılık.
Özmen, B., & Altun, A. (2014). Undergraduate Students’ Experiences in Programming: Difficulties and Obstacles. Turkish Online Journal of Qualitative Inquiry, 5(3), 1-27. https://doi.org/10.17569/tojqi.20328
Park, J., & Kim, S. (2020). Analysis of Influencing Factors of Learning Engagement and Teaching Presence in Online Programming Classes.
Perenc, I., Jaworski, T., & Duch, P. (2019). Teaching programming using dedicated Arduino Educational Board. Computer Applications in Engineering Education, 27(4), 943-954. https://doi.org/10.1002/cae.22134
Perera, P., Tennakoon, G., Ahangama, S., Panditharathna, R., & Chathuranga, B. (2021). A Systematic Mapping of Introductory Programming Languages for Novice Learners. IEEE Access, 9, 88121-88136. https://doi.org/10.1109/ACCESS.2021.3089560
Pryor, B. W. (2022). Understanding Belief, Attitude, and Behavior: How to Use Fishbein and Ajzen’s Theories in Evaluation and Educational Research.
Ramalingam, V., & Wiedenbeck, S. (1998). Development and Validation of Scores on a Computer Programming Self-Efficacy Scale and Group Analyses of Novice Programmer Self-Efficacy. Journal of Educational Computing Research, 19(4), 367-381. https://doi.org/10.2190/C670-Y3C8-LTJ1-CT3P
Rocha, H. J. B., Azevedo, P. C. D., Tedesco, R., & Costa, E. D. B. (2023). On the use of feedback in learning computer programming by novices: A systematic literature mapping.
Severance, C. (2014). Massimo Banzi: Building Arduino. Computer, 47(1), 11-12. https://doi.org/10.1109/MC.2014.19
Sezgin, S. (2020). Roles of massive open online courses in teacher education: Examining the massive open online course experiences of preservice computer and instructional technologies teachers about programming. Journal of Higher Education and Science, 10(1), 166. https://doi.org/10.5961/jhes.2020.378
Shargabi, A., Aljunid, S. A., Annamalai, M., Mohamed Shuhidan, S., & Mohd Zin, A. (2015). Program comprehension levels of abstraction for novices. 2015 International Conference on Computer, Communications, and Control Technology (I4CT), 211-215. Kuching, Sarawak, Malaysia: IEEE. https://doi.org/10.1109/I4CT.2015.7219568
Shen, R., & Lee, M. J. (2020). Learners’ Perspectives on Learning Programming from Interactive Computer Tutors in a MOOC. 2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), 1-5. Dunedin, New Zealand: IEEE. https://doi.org/10.1109/VL/HCC50065.2020.9127270
Staubitz, T., Klement, H., Renz, J., Teusner, R., & Meinel, C. (2015). Towards practical programming exercises and automated assessment in Massive Open Online Courses. 2015 IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE), 23-30. https://doi.org/10.1109/TALE.2015.7386010
Sun, J. C.-Y., & Rueda, R. (2012). Situational interest, computer self-efficacy and self-regulation: Their impact on student engagement in distance education. British Journal of Educational Technology, 43(2), 191-204. https://doi.org/10.1111/j.1467-8535.2010.01157.x
Talan, T. (2020). Eğitsel Robotik Uygulamaları Üzerine Yapılan Çalışmaların İncelenmesi. Yaşadıkça Eğitim, 34(2), 503-522. https://doi.org/10.33308/26674874.2020342177
Tan, W. L., Venema, S., & Gonzalez, R. (2017). Using Arduino to Teach Programming to First-Year Computer Science Students.
Topal, M., İstanbullu, A., & Akgün, Ö. E. (2020). Psychometric properties of university student form of student engagement scale in online learning: Çevrimiçi öğrenmede öğrenci bağlılığı ölçeği üniversite öğrencisi formunun psikometrik özellikleri. Journal of Human Sciences, 17(1), 104-116. https://doi.org/10.14687/jhs.v17i1.5698
Trowler, V. (2010). Student engagement literature review. Dimension of Engagement. Lancaster. Tsai, C.-Y. (2019). Improving students’ understanding of basic programming concepts through visual programming language: The role of self-efficacy. Computers in Human Behavior, 95, 224-232. https://doi.org/10.1016/j.chb.2018.11.038
Tsai, M.-J., Wang, C.-Y., & Hsu, P.-F. (2019). Developing the Computer Programming Self-Efficacy Scale for Computer Literacy Education. Journal of Educational Computing Research, 56(8), 1345-1360. https://doi.org/10.1177/0735633117746747
Vahid, F., & Allen, J. M. (2020). An online course for freshmen? The evolution of a successful online CS1 course. American Society for Engineering Education.
Walker, C. O., Greene, B. A., & Mansell, R. A. (2006). Identification with academics, intrinsic/extrinsic motivation, and self-efficacy as predictors of cognitive engagement. Learning and Individual Differences, 16(1), 1-12. https://doi.org/10.1016/j.lindif.2005.06.004
Wang, X.-M., & Hwang, G.-J. (2017). A problem posing-based practicing strategy for facilitating students’ computer programming skills in the team-based learning mode. Educational Technology Research and Development, 65(6), 1655-1671. https://doi.org/10.1007/s11423-017-9551-0
Watson, C., & Li, F. W. (2014). Failure Rates in Introductory Programming Revisited. ITiCSE ’14: Proceedings of the 2014 Conference on Innovation & Technology in Computer Science, 39-44. https://doi.org/10.1145/2591708.2591749
Xinogalos, S. (2016). Designing and deploying programming courses: Strategies, tools, difficulties and pedagogy. Education and Information Technologies, 21(3), 559-588. https://doi.org/10.1007/s10639-014-9341-9
Yauney, J., Bartholomew, S. R., & Rich, P. (2021). A systematic review of “Hour of Code” research. Computer Science Education, 0(0), 1-33. https://doi.org/10.1080/08993408.2021.2022362
Zimmerman, B. J. (2000). Self-efficacy: An essential motive to learn. Contemporary Educational Psychology, 25, 82-91. https://doi.org/10.1006/ceps.1999.1016
Zinovieva, I. S., Artemchuk, V. O., Iatsyshyn, A. V., Popov, O. O., Kovach, V. O., Iatsyshyn, A. V., … Radchenko, O. V. (2021). The use of online coding platforms as additional distance tools in programming education. Journal of Physics: Conference Series, 1840(1), 012029. https://doi.org/10.1088/1742-6596/1840/1/012029