Research trends in programming education: A systematic review of the articles published between 2012-2020

Year 2023, , 48 - 81, 31.01.2023

Atajan Rovshenov , Fırat Sarsar

https://doi.org/10.31681/jetol.1201010

Cited By: 1

Abstract

This study examines the methodological dimensions of programming education articles published in educational sciences journals indexed in SSCI by exploring their general trends. To do this, 162 articles published between January 2012 and February 2020 in 30 international journals indexed in SSCI were analyzed with a systematic review method using the "Educational Technology Publication Classification Form" as a data collection tool. The results revealed that most of the studies in this field were conducted in the United States and Turkiye. The number of these studies has increased since 2015, and those studies were carried out using quantitative research methodology. Mostly questionnaires and achievement tests were used as a data collection tool, a convenience sampling method was used, and descriptive analyses were adopted to analyze the data. As a result, the articles examined in this study showed that programming education positively contributes to learners' learning and success levels and the development of their computational thinking skills. We believe that these results will shed light on future studies related to programming education.

Keywords

Programming Education, Programming Teaching, Computer Science Education, Systematic Review

References

• Alaqsam, A., Ghabban, F., Ameerbakhsh, O., Alfadli, I., & Fayez, A. (2021). Current Trends in OnlineProgramming Languages Learning Tools: A Systematic Literature Review. Journal of Software Engineering and Applications, 14(7), 277-297. 10.4236/jsea.2021.147017
• Agbo, F. J., Oyelere, S. S., Suhonen, J., & Adewumi, S. (2019, November). A systematic review of computational thinking approach for programming education in higher education institutions. In Proceedings of the 19th Koli Calling International Conference on Computing Education Research (pp. 1-10). https://doi.org/10.1145/3364510.3364521
• Ahadi, A., Hellas, A., Ihantola, P., Korhonen, A., & Petersen, A. (2016, November). Replication in computing education research: researcher attitudes and experiences. In Proceedings of the 16th Koli Calling International Conference on Computing Education Research (pp. 2-11). https://doi.org/10.1145/2999541.2999554
• Anindyaputri, N. A., Yuana, R. A., & Hatta, P. (2020). Enhancing Students’ Ability in Learning Process of Programming Language using Adaptive Learning Systems: A Literature Review. Open Engineering, 10(1), 820-829.
• Apiola, M., Saqr, M., López-Pernas, S., & Tedre, M. (2022). Computing Education Research Compiled: Keyword Trends, Building Blocks, Creators, and Dissemination. IEEE Access. 10.1109/ACCESS.2022.3157609
• Balanskat, A., & Engelhardt, K. (2015). Computer programming and coding priorities, school curricula, and initiatives across Europe. European schoolnet. http://www.eun.org/documents/411753/817341/Computing+our+future_final_2015.pdf/d3780a64-1081-4488-8549-6033200e3c03
• Bati, T. B., Gelderblom, H., & Van Biljon, J. (2014). A blended learning approach for teaching computer programming: design for large classes in Sub-Saharan Africa. Computer Science Education, 24(1), 71-99. https://doi.org/10.1080/08993408.2014.897850
• Bati, K. (2021). A systematic literature review regarding computational thinking and programming in early childhood education. Education and Information Technologies, 1-24. https://doi.org/10.1007/s10639-021-10700-2
• Battal, A., Afacan Adanır, G., & Gülbahar, Y. (2021). Computer Science Unplugged: A Systematic Literature Review. Journal of Educational Technology Systems, 50(1), 1-24. https://doi.org/10.1177/00472395211018801
• Becker, B. A., & Quille, K. (2019, February). 50 years of cs1 at sigcse: A review of the evolution of introductory programming education research. In Proceedings of the 50th acm technical symposium on computer science education (pp. 338-344). https://doi.org/10.1145/3287324.3287432
• Benitti, F. B. V. (2012). Exploring the educational potential of robotics in schools: A systematic review. Computers & Education, 58(3), 978-988. https://doi.org/10.1016/j.compedu.2011.10.006
• Berssanette, J. H., & de Francisco, A. C. (2021). Active learning in the context of the teaching/learning of computer programming: A systematic review. Journal of Information Technology Education. Research, 20, 201. https://doi.org/10.28945/4767
• Bishop-Clark, C., Courte, J., & Howard, E. V. (2006). Programming in pairs with Alice to improve confidence, enjoyment, and achievement. Journal of educational computing research, 34(2), 213-228. https://doi.org/10.2190/CFKF-UGGC-JG1Q-7T40
• Borrego, M., Foster, M. J., & Froyd, J. E. (2014). Systematic literature reviews in engineering education and other developing interdisciplinary fields. Journal of Engineering Education, 103(1), 45-76. https://doi.org/10.1002/jee.20038
• Butterfield, A., Ngondi, G. E., & Kerr, A. (Eds.). (2016). A dictionary of computer science. Oxford University Press. https:/doi.org/10.1093/acref/9780199688975.001.0001
• Caeli, E. N., & Yadav, A. (2020). Unplugged approaches to computational thinking: A historical perspective. TechTrends, 64(1), 29-36. https://doi.org/10.1007/s11528-019-00410-5
• Chalmers, C. (2018). Robotics and computational thinking in primary school. International Journal of Child-Computer Interaction, 17, 93-100. https://doi.org/10.1016/j.ijcci.2018.06.005
• Cheah, C. S. (2020). Factors contributing to the difficulties in teaching and learning of computer programming: A literature review. Contemporary Educational Technology, 12(2), 1-14. https://doi.org/10.30935/cedtech/8247
• Chen, C., Haduong, P., Brennan, K., Sonnert, G., & Sadler, P. (2019). The effects of first programming language on college students’ computing attitude and achievement: a comparison of graphical and textual languages. Computer Science Education, 29(1), 23-48. https://doi.org/10.1080/08993408.2018.1547564
• Cheng, G. (2019). Exploring factors influencing the acceptance of visual programming environment among boys and girls in primary schools. Computers in Human Behavior, 92, 361-372. https://doi.org/10.1016/j.chb.2018.11.043
• Claypool, M. (2013). Dragonfly: strengthening programming skills by building a game engine from Scratch. Computer Science Education, 23(2), 112-137. https://doi.org/10.1080/08993408.2013.781840
• Crellin, J., Duke-Williams, E., Chandler, J., & Collinson, T. (2009). Virtual worlds in computing education. Computer Science Education, 19(4), 315-334. https://doi.org/10.1080/08993400903384950
• Cukierman, D. (2015, June 4-8). Predicting success in university first year computing science courses: The role of student participation in reflective learning activities and in i-clicker activities. In Proceedings of the 2015 acm conference on innovation and technology in computer science education (pp. 248-253). https://doi.org/10.1145/2729094.2742623
• Çam, E. & Kıyıcı, M. (2022). The impact of robotics assisted programming education on academic success, problem solving skills and motivation. Journal of Educational Technology and Online Learning, 5(1), 47-65. https://doi.org/10.31681/jetol.1028825
• Çiftci, S., & Bildiren, A. (2020). The effect of coding courses on the cognitive abilities and problem-solving skills of preschool children. Computer science education, 30(1), 3-21. https://doi.org/10.1080/08993408.2019.1696169
• Dağhan, G., Nuhoğlu Kibar, P., Menzi Çetin, N., Telli, E., & Akkoyunlu, B. (2017). 21st century learners’ and teachers’ charactersistics from ICT preservice teachers’ perspectives. Educational Technology Theory and Practise, 7(2), 215-235. https://doi.org/10.17943/etku.305062
• Da Silva Estácio, B. J., & Prikladnicki, R. (2015). Distributed pair programming: A systematic literature review. Information and Software Technology, 63, 1-10. https://doi.org/10.1016/j.infsof.2015.02.011
• Decker, A., & McGill, M. M. (2017, March). Pre-college computing outreach research: Towards improving the practice. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (pp. 153-158). https://doi.org/10.1145/3017680.3017744
• Durak, H. Y., Yilmaz, F. G. K., & Yilmaz, R. (2019). Computational Thinking, Programming Self-Efficacy, Problem Solving and Experiences in the Programming Process Conducted with Robotic Activities. Contemporary Educational Technology, 10(2), 173-197. https://doi.org/10.30935/cet.554493
• Fagerlund, J., Häkkinen, P., Vesisenaho, M., & Viiri, J. (2021). Computational thinking in programming with Scratch in primary schools: A systematic review. Computer Applications in Engineering Education, 29(1), 12-28. https://doi.org/10.1002/cae.22255
• Garo, E., Kume, V., & Basho, S. (2015). " Programming" an Entrepreneur. Academic Journal of Interdisciplinary Studies, 4(1 S1), 45-45. https://dx.doi.org/10.5901/mjss.2015.v4n1s1p45
• Goktas, Y., Kucuk, S., Aydemir, M., Telli, E., Arpacik, O., Yildirim, G., & Reisoglu, I. (2012). Educational technology research trends in Turkey: A content analysis of the 2000-2009 decade. Educational Sciences: Theory and Practice, 12(1), 191-199.
• Gomes, A., & Mendes, A. J. (2007, September 3-7). Learning to program-difficulties and solutions. In International Conference on Engineering Education–ICEE (Vol. 7). https://www.researchgate.net/publication/228328491_Learning_to_program_-_difficulties_and_solutions
• Grotta, A., & Prado, E. P. V. (2019, July). Benefits of The Project-Based Learning to Cope with Computer Programming Education: A Systematic Literature Review. In PBL2019 Immersive Virtual International Conference, 2019b. Proceedings. 1-10.
• Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field. Educational researcher, 42(1), 38-43.
• Grover, S., Basu, S., Bienkowski, M., Eagle, M., Diana, N., & Stamper, J. (2017). A framework for using hypothesis-driven approaches to support data-driven learning analytics in measuring computational thinking in block-based programming environments. ACM Transactions on Computing Education (TOCE), 17(3), 1-25. https://doi.org/10.1145/3105910
• Gretter, S., & Yadav, A. (2016). Computational thinking and media & information literacy: An integrated approach to teaching twenty-first century skills. TechTrends, 60(5), 510-516. https://doi.org/10.1007/s11528-016-0098-4
• Gurer, D., M., Cetin, I., & Top, E. (2019). Factors affecting students' attitudes toward computer programming. Informatics in Education, 18(2), 281-296. https://doi.org/10.15388/infedu.2019.13
• Guzdial, M. (2016). Bridging Computer Science to US Schools. Communications of the ACM, 59(5), 24-25. https://doi.org/10.1145/2898963
• Gülbahar, Y., & Kalelioğlu, F. (2018). Bilişim Teknolojileri ve Bilgisayar Bilimi: Öğretim Programi Güncelleme Süreci. Millî Eğitim Dergisi, 47(217), 5-23.
• Kelleher, C., & Pausch, R. (2005). Lowering the barriers to programming: A taxonomy of programming environments and languages for novice programmers. ACM Computing Surveys (CSUR), 37(2), 83-137. https://doi.org/10.1145/1089733.1089734
• Kalelioglu, F., & Sentance, S. (2020). Teaching with physical computing in school: the case of the micro: bit. Education and Information Technologies, 25(4), 2577-2603. https://doi.org/10.1007/s10639-019-10080-8
• Kalelioğlu, F., Gülbahar, Y., & Kukul, V. (2016). A framework for computational thinking based on a systematic research review. Baltic Journal of Modern Computing, 4(3), 583-596.
• Hao, Q., Smith IV, D. H., Iriumi, N., Tsikerdekis, M., & Ko, A. J. (2019). A systematic investigation of replications in computing education research. ACM Transactions on Computing Education (TOCE), 19(4), 1-18. https://doi.org/10.1145/3345328
• Hawlitschek, A., Berndt, S., & Schulz, S. (2022). Empirical research on pair programming in higher education: a literature review. Computer Science Education, 1-29. https://doi.org/10.1080/08993408.2022.2039504
• Hughes‐Roberts, T., Brown, D., Standen, P., Desideri, L., Negrini, M., Rouame, A., & Hasson, C. (2019). Examining engagement and achievement in learners with individual needs through robotic‐based teaching sessions. British journal of educational technology, 50(5), 2736-2750. https://doi.org/10.1111/bjet.12722
• Hundt, C., Schlarb, M., & Schmidt, B. (2017). SAUCE: A web application for interactive teaching and learning of parallel programming. Journal of Parallel and Distributed Computing, 105, 163-173. https://doi.org/10.1016/j.jpdc.2016.12.028
• Ioannou, A., & Makridou, E. (2018). Exploring the potentials of educational robotics in the development of computational thinking: A summary of current research and practical proposal for future work. Education and Information Technologies, 23(6), 2531-2544. https://doi.org/10.1007/s10639-018-9729-z
• Kanika, Chakraverty, S., & Chakraborty, P. (2020). Tools and techniques for teaching computer programming: A review. Journal of Educational Technology Systems, 49(2), 170-198. https://doi.org/10.1177/0047239520926971
• Kavitha, R. K., & Ahmed, M. I. (2013). Knowledge sharing through pair programming in learning environments: An empirical study. Education and Information Technologies, 20(2), 319-333. https://doi.org/10.1007/s10639-013-9285-5
• Krippendorff, K. (2004). Content analysis: an introduction to its methodology (2nd Ed.). Thousand Oaks, CA: Sage Publications.
• Korkmaz, Ö. (2018). The effect of scratch-and Lego mindstorms EV3-Based programming activities on academic achievement, problem-solving skills and logical-mathematical thinking skills of students. MOJES: Malaysian Online Journal of Educational Sciences, 4(3), 73-88.
• Law, K. M., Lee, V. C., & Yu, Y. T. (2010). Learning motivation in e-learning facilitated computer programming courses. Computers & Education, 55(1), 218-228. https://doi.org/10.1016/j.compedu.2010.01.007
• Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 58(4), 431-440. https://doi.org/10.1016/j.bushor.2015.03.008
• Lindberg, R. S., Laine, T. H., & Haaranen, L. (2019). Gamifying programming education in K‐12: A review of programming curricula in seven countries and programming games. British Journal of Educational Technology, 50(4), 1979-1995. https://doi.org/10.1111/bjet.12685
• Liu, Z., Zhi, R., Hicks, A., & Barnes, T. (2017). Understanding problem solving behavior of 6–8 graders in a debugging game. Computer Science Education, 27(1), 1-29. https://doi.org/10.1080/08993408.2017.1308651
• Lockwood, J., & Mooney, A. (2017). Computational Thinking in Education: Where does it fit? A systematic literary review. International Journal of Computer Science Education in Schools.(2) 1, 1-20
• Lui, D., Kafai, Y., Litts, B., Walker, J., & Widman, S. (2020). Pair physical computing: high school students’ practices and perceptions of collaborative coding and crafting with electronic textiles. Computer Science Education, 30(1), 72-101.https://doi.org/10.1080/08993408.2019.1682378
• Lukkarinen, A., Malmi, L., & Haaranen, L. (2021). Event-driven Programming in Programming Education: A Mapping Review. ACM Transactions on Computing Education (TOCE), 21(1), 1-31. https://doi.org/10.1145/3423956
• Luxton-Reilly, A., Albluwi, I., Becker, B. A., Giannakos, M., Kumar, A. N., Ott, L. & Szabo, C. (2018, July). Introductory programming: a systematic literature review. In Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education (pp. 55-106). https://doi.org/10.1145/3293881.3295779
• Maia, M. C. O., Serey, D., & Figueiredo, J. (2017, October). Learning styles in programming education: A systematic mapping study. In 2017 IEEE Frontiers in Education Conference (FIE) (pp. 1-7). IEEE. 10.1109/FIE.2017.8190465
• Mason, R., & Cooper, G. (2013). Mindstorms robots and the application of cognitive load theory in introductory programming. Computer Science Education, 23(4), 296-314. https://doi.org/10.1080/08993408.2013.847152
• McMillan, J.H., Schumacher, S. (2001). Research in education: a conceptual introduction. (5th Ed.). New York: Addison Wesley Longman Inc. 660.
• Nikula, U., Gotel, O., & Kasurinen, J. (2011). A motivation guided holistic rehabilitation of the first programming course. ACM Transactions on Computing Education (TOCE), 11(4), 1-38. https://doi.org/10.1145/2048931.2048935
• Noone, M., & Mooney, A. (2018). Visual and textual programming languages: a systematic review of the literature. Journal of Computers in Education, 5(2), 149-174. https://doi.org/10.1007/s40692-018-0101-5
• Omer, U., Farooq, M. S., & Abid, A. (2021). Introductory programming course: review and future implications. PeerJ Computer Science, 7, 1-33. https://doi.org/10.7717/peerj-cs.647
• Othman, M., &, Zain, N. (2015). Online collaboration for programming: Assessing students’ cognitive abilities. Turkish Online Journal of Distance Education, 16(4), 84-97. https://doi.org/10.17718/tojde.88618
• Papamitsiou, Z., Giannakos, M., Simon, & Luxton-Reilly, A. (2020, August). Computing education research landscape through an analysis of keywords. In Proceedings of the 2020 ACM Conference on International Computing Education Research (pp. 102-112). https://doi.org/10.1145/3372782.3406276
• Papastergiou, M. (2009). Digital game-based learning in high school computer science education: Impact on educational effectiveness and student motivation. Computers & education, 52(1), 1-12. https://doi.org/10.1016/j.compedu.2008.06.004
• Peng, Y. C., & Wang, T. I. (2019, December 2-5). The Investigation on Creative Thinking into Projected-Base Programming Course for College Students. In International Conference on Innovative Technologies and Learning (pp. 713-725). Springer, Cham. https://10.1007/978-3-030-35343-8
• Petticrew, M., & Roberts, H. (2008). Systematic reviews in the social sciences: A practical guide. John Wiley & Sons.
• Popat, S., & Starkey, L. (2019). Learning to code or coding to learn? A systematic review. Computers & Education, 128, 365-376. https://doi.org/10.1016/j.compedu.2018.10.005
• Robins, A., Rountree, J., & Rountree, N. (2003). Learning and teaching programming: A review and discussion. Computer science education, 13(2), 137-172. https://doi.org/10.1076/csed.13.2.137.14200
• Salleh, S. M., Shukur, Z., & Judi, H. M. (2013). Analysis of research in programming teaching tools: An initial review. Procedia-Social and Behavioral Sciences, 103, 127-135. https://doi.org/10.1016/j.sbspro.2013.10.317
• Sanders, K., Sheard, J., Becker, B. A., Eckerdal, A., & Hamouda, S. (2019, July). Inferential statistics in computing education research: A methodological review. In Proceedings of the 2019 ACM Conference on International Computing Education Research (pp. 177-185). https://doi.org/10.1145/3291279.3339408
• Santos, S. C., Tedesco, P. A., Borba, M., & Brito, M. (2020). Innovative approaches in teaching programming: A systematic literature review. In Proceedings of the 12th International Conference on Computer Supported Education (Vol. 1, pp. 205-214).
• Saini, J. R., & Chomal, V. S. (2017). Use of Analytical Hierarchy Process for Selection of Elective Subjects by Pre-Final Year Students of Computer Science. International Journal on Recent and Innovation Trends in Computing and Communication, 5(5), 1196-1202.
• Saqr, M., Ng, K., Oyelere, S. S., & Tedre, M. (2021). People, ideas, milestones: a scientometric study of computational thinking. ACM Transactions on Computing Education (TOCE), 21(3), 1-17. https://doi.org/10.1145/3445984
• Scaico, P. D., Scaico, A., & de Queiroz, R. J. B. (2018, October). An Initial Analysis of the Research on Interest and Introductory Programming: A Systematic Review of this Literature. In 2018 IEEE Frontiers in Education Conference (FIE) (pp. 1-9). IEEE. 10.1109/FIE.2018.8659254
• Scherer, R., Siddiq, F., & Sánchez Viveros, B. (2019). The cognitive benefits of learning computer programming: A meta-analysis of transfer effects. Journal of Educational Psychology, 111(5), 764. https://doi.org/10.1037/edu0000314
• Shahid, M., Wajid, A., Haq, K. U., Saleem, I., & Shujja, A. H. (2019, November). A review of gamification for learning programming fundamental. In 2019 International Conference on Innovative Computing (ICIC) (pp. 1-8). IEEE. 10.1109/ICIC48496.2019.8966685
• Sobral, S. R. (2021). Teaching and Learning to Program: Umbrella Review of Introductory Programming in Higher Education. Mathematics, 9(15), 1737. https://doi.org/10.3390/math9151737
• Sol, R., Santos, E. A., Reis, M. C., & Pereira, L. (2021). Computer Supported Collaborative Learning for Programming: A Systematic Review. CSEDU (2), 184-191.
• Sun, L., Guo, Z., & Zhou, D. (2022). Developing K-12 students’ programming ability: A systematic literature review. Education and Information Technologies, 1-39. https://doi.org/10.1007/s10639-022-10891-2
• Szabo, C., Sheard, J., Luxton-Reilly, A., Becker, B. A., & Ott, L. (2019, November). Fifteen years of introductory programming in schools: a global overview of K-12 initiatives. In Proceedings of the 19th Koli Calling International Conference on Computing Education Research (pp. 1-9). https://doi.org/10.1145/3364510.3364513
• Tikva, C., & Tambouris, E. (2021). Mapping computational thinking through programming in K-12 education: A conceptual model based on a systematic literature Review. Computers & Education, 162, 1-23. https://doi.org/10.1016/j.compedu.2020.104083
• Tunga, Y., & Tokel, S. T. (2018). The use of pair programming in education: A systematic review. In 2018 Educcon Education 4.0 Conference. (pp. 19-29).
• Tuparov, G., Tuparova, D., & Jordanov, V. (2014). Teaching sorting and searching algorithms through simulation-based learning objects in an introductory programming course. Procedia-Social and Behavioral Sciences, 116, 2962-2966. https://doi.org/10.1016/j.sbspro.2014.01.688
• Veena, A., & Gowrishankar, S. (2018). Introduction to Python Programming. CRC Press.
• Vihavainen, A., Airaksinen, J., & Watson, C. (2014, July). A systematic review of approaches for teaching introductory programming and their influence on success. In Proceedings of the tenth annual conference on International computing education research (pp. 19-26). https://doi.org/10.1145/2632320.2632349
• Wallen, N. E., & Fraenkel, J. R. (2013). Educational research: A guide to the process. Routledge.
• Webb, M. E., Bell, T., Davis, N., Katz, Y. J., Fluck, A., Sysło, M. M., & Brodnik, A. (2018). Tensions in specifying computing curricula for K-12: Towards a principled approach for objectives. IT-Information Technology, 60(2), 59-68. https://doi.org/10.1515/itit-2017-0017
• Wohl, B. S., Beck, S., & Blair, L. (2017). The Future of the Computing Curriculum: How the Computing Curriculum Instills Values and Subjectivity in Young People. International Journal of Computer Science Education in Schools, 1(1), 1-9.
• Qian, Y., & Lehman, J. (2017). Students’ misconceptions and other difficulties in introductory programming: A literature review. ACM Transactions on Computing Education (TOCE), 18(1), 1-24. https://doi.org/10.1145/3077618
• Qian, Y., Hambrusch, S., Yadav, A., Gretter, S., & Li, Y. (2020). Teachers’ perceptions of student misconceptions in introductory programming. Journal of Educational Computing Research, 58(2), 364-397. https://doi.org/10.1177/0735633119845413
• Yang, T. C., Yang, S. J., & Hwang, G. J. (2014, July 7-10). Development of an interactive test system for students' improving learning outcomes in a computer programming course. In 2014 IEEE 14th International Conference on Advanced Learning Technologies (pp. 637-639). IEEE. https://doi.org/10.1109/ICALT.2014.186
• Yesharim, M. F., & Ben-Ari, M. (2018). Teaching computer science concepts through robotics to elementary school children. International Journal of Computer Science Education in Schools, 2(3), 1-22. https://doi.org/10.21585/ijcses.v2i3.30
• Yu, J., & Roque, R. (2019). A review of computational toys and kits for young children. International Journal of Child-Computer Interaction, 21, 17-36. https://doi.org/10.1016/j.ijcci.2019.04.001