References
- Aho, A. V. (2012). Computation and computational thinking. The Computer Journal, 55(7), 832-835. https://doi.org/10.1093/comjnl/bxs074
- Ala-Mutka, K. M. (2005). A survey of automated assessment approaches for programming assignments. Computer Science Education, 15(2), 83-102. https://doi.org/10.1080/08993400500150747
- Atmatzidou, S., & Demetriadis, S. (2016). Advancing students' computational thinking skills through educational robotics: A study on age and gender relevant differences. Robotics and Autonomous Systems, 75, 661-670. https://doi.org/10.1016/j.robot.2015.10.008
- 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. https://doi.org/10.1145/1929887.1929905
- Bienkowski, M., Snow, E., Rutstein, D., & Grover, S. (2015). Assessment design patterns for computational thinking practices in secondary computer science: A first look. SRI International.
- Boe, B., Hill, C., Len, M., Dreschler, G., Conrad, P., & Franklin, D. (2013, March). Hairball: Lint-inspired static analysis of scratch projects. In Proceeding of the 44th ACM technical symposium on Computer science education (pp. 215-220).
- Brennan, K., & Resnick, M. (2012, April). New frameworks for studying and assessing the development of computational thinking. In Proceedings of the 2012 annual meeting of the American educational research association. (Vol. 1, p. 1-25). Vancouver, Canada.
- Cheang, B., Kurnia, A., Lim, A., & Oon, W. C. (2003). On automated grading of programming assignments in an academic institution. Computers & Education, 41(2), 121-131. https://doi.org/10.1016/S0360-1315(03)00030-7
- Choi, S. (2016). A Study on Teaching-learning for Enhancing Computational Thinking Skill in terms of Problem Solving. The Journal of Korean association of computer education, 19(2), 53-62.
- Choi, S. (2019). Review of Domestic Literature Based on System Mapping for Computational Thinking Assessment. The Journal of Korean association of computer education, 22(6), 19-33. https://doi.org/10.32431/kace.2019.22.6.003
- Computing At School [CAS] (2013). Computing in the National Curriculum : A Guide for Primary Teachers. Retrieved from http://www.computingatschool.org.uk/data/uploads/CASPrimaryComputing.pdf
- Computing At School [CAS] (2015). Computational Thinking : A Guide for teachers. Retrieved from http://community.computingatschool.org.uk/resources/2324
- Dasgupta, S., Hale, W., Monroy-Hernandez, A., & Hill, B. M. (2016, February). Remixing as a pathway to computational thinking. In Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing (pp. 1438-1449).
- Edwards, S. H., & Perez-Quinones, M. A. (2008, June). Web-CAT: automatically grading programming assignments. In Proceedings of the 13th annual conference on Innovation and technology in computer science education (pp. 328-328).
- Foxley, E., Tsintsifas, A., Higgins, C. A., & Symeonidis, P. (1999). Ceilidh, a system for the automatic evaluation of students programming work. Proceedings of CBLISS, 99.
- Gelperin, D., & Hetzel, B. (1988). The growth of software testing. Communications of the ACM, 31(6), 687-695. https://doi.org/10.1145/62959.62965
- Gouda, K., & Hassaan, M. (2016, May). CSI_GED: An efficient approach for graph edit similarity computation. In 2016 IEEE 32nd International Conference on Data Engineering (ICDE) (pp. 265-276).
- Han, Y. (2018). Analysis of Effectiveness of Programming Learning for Non-science Major Preliminary Teachers' Development of Computational Thinking. Journal of the Korean Association of Information Education, 22(1), 41-52. https://doi.org/10.14352/jkaie.2018.22.1.41
- Isaacson, P. C., & Scott, T. A. (1989). Automating the execution of student programs. ACM SIGCSE Bulletin, 21(2), 15-22. https://doi.org/10.1145/65738.65741
- Jackson, D., & Usher, M. (1997, March). Grading student programs using ASSYST. In Proceedings of the twenty-eighth SIGCSE technical symposium on Computer science education (pp. 335-339).
- Jamil, H. M. (2017). Smart assessment of and tutoring for computational thinking MOOC assignments using MindReader. arXiv preprint arXiv:1705.00959.
- Kang, E. (2019). Structural Software Education Model for Non-majors - Focused on Python. Journal of Digital Contents Society, 20(12), 2423-2432. https://doi.org/10.9728/dcs.2019.20.12.2423
- Kim, J. (2017). Development of Rubric for Assessing Computational Thinking Concepts and Programming Ability. The Journal of Korean Association of Computer Education, 20(6), 27-36. https://doi.org/10.32431/KACE.2017.20.6.003
- Kim, S., Ham, S., & Song, K. (2015). Analytic Study on the Effectiveness of Computational Thinking based STEAM Program. The Journal of Korean association of computer education, 18(3), 105-114. https://doi.org/10.32431/KACE.2015.18.3.010
- Kim, T. & Han, S. (2018). Development of Python Education Program for Block Coding Learners. Journnal of the Korean Association of Information Education, 22(1), 53-60. https://doi.org/10.14352/jkaie.2018.22.1.53
- Kitchin, R. (2017). Thinking critically about and researching algorithms. Information, Communication & Society, 20(1), 14-29. https://doi.org/10.1080/1369118X.2016.1154087
- Korea Foundation for the Advancement of Science & Creativity (2014). Research for Introducing Computational Thinking into Primary and Secondary Education.
- Kurnia, A., Lim, A., & Cheang, B. (2001). Online judge. Computers & Education, 36(4), 299-315. https://doi.org/10.1016/S0360-1315(01)00018-5
- Kwon, J. (2019). Research of Computational Thinking based on Analyzed in Each Major Learner. The Journal of Society for e-Business Studies, 24(4), 17-30.
- Lee, Y. (2018). Python-based Software Education Model for Non-Computer Majors. Journal of the Korea Convergence Society, 9(3) 73-78. https://doi.org/10.15207/JKCS.2018.9.3.073
- Lister, R., Adams, E. S., Fitzgerald, S., Fone, W., Hamer, J., Lindholm, M., ... & Simon, B. (2004). A multi-national study of reading and tracing skills in novice programmers. ACM SIGCSE Bulletin, 36(4), 119-150 https://doi.org/10.1145/1041624.1041673
- Marin, V. J., Pereira, T., Sridharan, S., & Rivero, C. R. (2017, April). Automated personalized feedback in introductory Java programming MOOCs. In 2017 IEEE 33rd International Conference on Data Engineering (ICDE) (pp. 1259-1270).
- Ministry of Education, Korea (2015). Software Education Instructional Guidance.
- Moon, M., & Kim, K. (2008). Python programming education for elementary school students. Journnal of the Korean Association of Information Education, 9(1), 33-41.
- Moreno-Leon, J., Robles, G., & Roman-Gonzalez, M. (2015). Dr. Scratch: Automatic analysis of scratch projects to assess and foster computational thinking. RED. Revista de Educacion a Distancia, 1(46), 1-23.
- Myers, G. J., Sandler, C., & Badgett, T. (2011). The art of software testing. John Wiley & Sons.
- Nam, C., & Kim, J. (2019). Development of computational thinking based Coding_Projects using the ARCS model. Journal of the Korean Association of Information Education, 23(4), 355-362. https://doi.org/10.14352/jkaie.2019.23.4.355
- Nygard, S. H. (2016). Automatic self-evaluation system for novice Python developers (Master's thesis, NTNU).
- Ota, G., Morimoto, Y., & Kato, H. (2016, September). Ninja code village for scratch: Function samples/function analyser and automatic assessment of computational thinking concepts. In 2016 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) (pp. 238-239).
- Parsons, D., & Haden, P. (2006, January). Parson's programming puzzles: a fun and effective learning tool for first programming courses. In Proceedings of the 8th Australasian Conference on Computing Education, 52(pp. 157-163).
- Piech, C., Huang, J., Nguyen, A., Phulsuksombati, M., Sahami, M., & Guibas, L. (2015). Learning program embeddings to propagate feedback on student code. arXiv preprint arXiv:1505.05969.
- Reek, K. A. (1989). The TRY system-or-how to avoid testing student programs. In ACM SIGCSE Bulletin, 21(1), 112-116. https://doi.org/10.1145/65294.71198
- Saez-Lopez, J. M., Roman-Gonzalez, M., & Vazquez-Cano, E. (2016). Visual programming languages integrated across the curriculum in elementary school: A two year case study using "Scratch" in five schools. Computers & Education, 97, 129-141. https://doi.org/10.1016/j.compedu.2016.03.003
- Seo, Y., Yeom, M., & Kim, J. (2016). Analysis of Effect that Pair Programming Develope of Computational Thinking and Creativity in Elementary Software Education. Journal of The Korean Assocaition of Information Ecucation. 20(3), 219-234. https://doi.org/10.14352/jkaie.20.3.219
- Shuhidan, S., Hamilton, M., & D'Souza, D. (2010). Instructor perspectives of multiple-choice questions in summative assessment for novice programmers. Computer Science Education, 20(3), 229-259. https://doi.org/10.1080/08993408.2010.509097
- Singh, R., Gulwani, S., & Solar-Lezama, A. (2013). Automated feedback generation for introductory programming assignments. In Proceedings of the 34th ACM SIGPLAN conference on Programming language design and implementation (pp. 15-26).
- Spacco, J., Hovemeyer, D., Pugh, W., Emad, F., Hollingsworth, J. K., & Padua-Perez, N. (2006, June). Experiences with marmoset: designing and using an advanced submission and testing system for programming courses. In ACM Sigcse Bulletin, 38(3), 13-17. https://doi.org/10.1145/1140123.1140131
- Truong, N., Roe, P., & Bancroft, P. (2004, January). Static analysis of students' Java programs. In Proceedings of the Sixth Australasian Conference on Computing Education, 30(pp. 317-325). Australian Computer Society, Inc..
- Von Wangenheim, C. G., Hauck, J. C., Demetrio, M. F., Pelle, R., da Cruz Alves, N., Barbosa, H., & Azevedo, L. F. (2018). CodeMaster--Automatic Assessment and Grading of App Inventor and Snap! Programs. Informatics in Education, 17(1), 117-150. https://doi.org/10.15388/infedu.2018.08
- Vujosevic-Janicic, M., Nikolic, M., Tosic, D., & Kuncak, V. (2013). Software verification and graph similarity for automated evaluation of students' assignments. Information and Software Technology, 55(6), 1004-1016. https://doi.org/10.1016/j.infsof.2012.12.005
- Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215
- Wing, J. M. (2008). Computational thinking and thinking about computing. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 366(1881), 3717-3725. https://doi.org/10.1098/rsta.2008.0118
- Wolz, U., Hallberg, C., & Taylor, B. (2011, March). Scrape: A tool for visualizing the code of Scratch programs. In Poster presented at the 42nd ACM Technical Symposium on Computer Science Education, Dallas, TX.
- Xu, S., & San Chee, Y. (2003). Transformation-based diagnosis of student programs for programming tutoring systems. IEEE Transactions on Software Engineering, 29(4), 360-384. https://doi.org/10.1109/TSE.2003.1191799
- Zhong, B., Wang, Q., Chen, J., & Li, Y. (2016). An exploration of three-dimensional integrated assessment for computational thinking. Journal of Educational Computing Research, 53(4), 562-590. https://doi.org/10.1177/0735633115608444
- Zuleger, F., Radicek, I., & Gulwani, S. (2016). Feedback generation for performance problems in introductory programming assignments. In Software Engineering (pp. 49-50).