Improving Student's Computation Performance: A Systematic Literature Review

References

[1] Aghware, F., Egbuna, E.; Aghware, A. & Ugboh, E. (2010). The implications of the internet and associated information and communication technologies (ICT) on science, technology and mathematics (STM) education in Nigeria. Agbor Journal of Science Education, 163-170.

[2] Aho, A. V. (2012). Computation and Computational Thinking. The Computer Journal, 55(7), 832-835. https://doi.org/10.1093/comjnl/bxs074

[3] Ardito, G., Mosley, P., & Scollins, L. (2014). We, robot: Using robotics to promote Collaborative and mathematics learning in a middle school classroom. (Report). Middle Grades Research Journal, 9(3), 73.

[4] 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(B), 661-670. https://doi.org/10.1016/j.robot.2015.10.008

[5] 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? Inroads, 2(1), 48-54. https://doi.org/10.1145/1929887.1929905

[6] Belanger, C., Christenson, H., & Lopac, K. (2018). Confidence and common challenges: the effects of teaching computational thinking to students ages 10-16. St. Catherine University, MN. https://sophia.stkate.edu/maed/267

[7] Bennedsen, J., & Caspersen, M. E. (2007). Failure rates in introductory programming. ACM

[8] SIGCSE Bulletin, 39(2), 32-36. https://doi.org/10.1145/1272848.1272879

[9] Benton, L., Hoyles, C., Kalas, I., & Noss, R. (2017). Bridging primary programming and mathematics: Some findings of design research in England. Digital Experiences in Mathematics Education, 3(2), 115-138. https://doi.org/10.1007/s40751-017-0028-x

[10] Bornat, R., & Dehnadi, S. (2008). Mental models, consistency and programming aptitude. S. Hamilton & M. Hamilton (Eds.), Proceedings of the Tenth Conference on Australasian Computing Education, 78, 53-61. Australian Computer Society. https://dl.acm.org/doi/epdf/10.5555/1379249.1379253

[11] Borrego, M., & Newswander, L. K. (2010). Definitions of interdisciplinary research: Toward graduate-level interdisciplinary learning outcomes. The Review of Higher Education, 34(1), 61-84. https://doi.org/10.1353/rhe.2010.0006

[12] Bruce, K. B., Drysdale, R. L. S., Kelemen, C., & Tucker, A. (2003). Why math? Communications of the ACM, 46(9), 40-44. https://doi.org/10.1145/903893.903918

[13] Bort, H., & Brylow, D. (2013). CS4Impact: Measuring computational thinking concepts present inCS4HS participant lesson plans. Proceedings of the 44th ACM Technical Symposium on Computer Science Education, 427–432.

[14] Burke, Q., & Kafai, Y. B. (2010). Programming & storytelling: opportunities for learning about coding & composition. In Proceedings of the 9th International Conference on Interaction Design and Children, 348-351. https://doi.org/10.1145/1810543.1810611

[15] Burns, R., Pollock, L., & Harvey, T. (2012). Integrating hard and soft skills: software engineers serving middle school teachers. In Proceedings of the 43rd ACM technical symposium on Computer Science Education, 209-214. ACM.

[16] Cai, W., & Sankaran, G. (2015). Promoting critical thinking through an interdisciplinary study abroad program. Journal of International Students, 5(1), 38-49. https://doi.org/10.32674/jis.v5i1

[17] Cassel, L. N. (2011). Interdisciplinary computing is the answer: now, what was the question?

[18] ACM Inroads, 2(1), 4-6. https://doi.org/10.1145/1929887.1929888

[19] Coenraad, M., Mills, K., Byrne, V. L., & Ketelhut, D. J. (2020). Supporting teachers to integrate computational thinking equitably. Proceedings of 2020 Research on Equity and Sustained Participation in Engineering, Computing, and Technology. https://doi.org/https://doi.org/10.1109/RESPECT49803.2020.9272488

[20] Czerkawski, B. C., & Lyman, E. W., III. (2015). Exploring issues about computational thinking in higher education. TechTrends, 59(2), 57-65. http://dx.doi.org/10.1007/s11528-015-0840-3

[21] Dagdilelis, V., Satratzemi, M., & Evangelidis, G. (2004). Introducing secondary education students to algorithms and programming. Education and Information Technologies, 9(2), 159-173. https://doi.org/10.1023/B:EAIT.0000027928.94039.7b

[22] Davenport, J. H., Wilson, D., Graham, I., Sankaran, G., Spence, A., Blake, J., & Kynaston, S. (2014).

[23] Interdisciplinary teaching of computing to mathematics students: Programming and discrete mathematics. MSOR Connections, 14(1), 1-8. https://doi.org/10.11120/msor.2014.00021

[24] De Raadt, M., Watson, R., & Toleman, M. (2002). Language trends in introductory programming courses. In Proceedings of the 2002 Informing Science+ Information Technology Education Joint Conference, 229-337. Informing Science Institute.

[25] Draganoiu, R., Moldoveanu, A., & Braescu, A. (2017). The Math of Programming-Interdisciplinary Approach. The International Scientific Conference eLearning and Software for Education, Carol National Defense University, 2, 473-481. https://doi.org/10.12753/2066-026X-17-152

[26] Duncan, C., Bell, T., & Tanimoto, S. (2014). Should your 8-year-old learn coding? Schulte (Ed.), Proceedings of the 9th Workshop in Primary and Secondary Computing Education, 60-69. ACM

[27] Feaster, Y., Segars, L., Wahba, S. K., & Hallstrom, J. O. (2011). Teaching CS unplugged in the high school (with limited success). In Proceedings of the 16th Annual Joint Conference on Innovation and Technology in Computer Science Education, 248-252. ACM.

[28] Fofang, J. S., Weintrop, D., Walton, M., Elby, A., & Walkoe, J. (2020). Mutually supportive mathematics and computational thinking in a fourth-grade classroom. In Gresalfi, M. and Horn, I. S. (Eds.), The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS), Nashville, Tennessee: International Society of the Learning Sciences, 3, 1389-1396.

[29] Fojtik, R. (2014). Design patterns in the teaching of programming. Procedia - Social and Behavioral

[30] Sciences, 143, 352-357. https://doi.org/10.1016/j.sbspro.2014.07.493

[31] Gadanidis, G. (2017). Artificial intelligence, computational thinking, and mathematics education.

[32] The International Journal of Information and Learning Technology, 34(2), 133–139. doi:10.1108/ijilt-09-2016-0048

[33] Gadanidis, G., Cendros, R., Floyd, L., & Namukasa, I. (2017). Computational thinking in mathematics teacher education. Contemporary Issues in Technology and Teacher Education, 17(4), 458-477.

[34] Graham, K. J., & Fennell, F. (2001). Principles and standards for school mathematics and teacher education: Preparing and empowering teachers. School Science and Mathematics, 101(6), 319-327. https://doi.org/10.1111/j.1949-8594.2001.tb17963.x

[35] Grover, S., Cooper, S., & Pea, R. (2014). Assessing computational learning in K-12. In Proceedings of the 2014 Conference on Innovation & Technology in Computer Science Education, 57-62. ACM.

[36] Grover, S., & Pea, R. (2013). Computational thinking in K–12: A review of the state of the field.

[37] Educational Researcher, 42(1), 38-43. https://doi.org/10.3102%2F0013189X12463051

[38] Guzdial, M., & DiSalvo, B. (2013). Computing education: Beyond the classroom. Computer, 46(9), 30-31. https://doi.org/10.1109/MC.2013.306

[39] Guzdial, M. (2004). Programming environments for novices. Computer Science Education Research, 127-154. Routledge Falmer.

[40] Halmos, P.R. (2017) Naive Set Theory. Courier Dover Publications, New York. ISBN0387900926, 9780387900926.

[41] Harvie, D. P., Estes, T., & Major, K. (2018). Use of Commercial Online Training to Augment Programming Language Education. In Proceedings of the 19th Annual SIG Conference on Information Technology Education (SIGITE '18) (p. 89). ACM. https://doi.org/10.1145/3241815.3241832

[42] Havill, J. T., & Ludwig, L. D. (2007). Technically speaking: fostering the communication skills of computer science and mathematics students. ACM SIGCSE Bulletin, 39(1), 185-189. https://doi.org/10.1145/1227504.1227375

[43] Herbsleb, J. D. (2005). Beyond computer science. In Proceedings of the 27th International Conference on Software Engineering, 23-27. https://doi.org/10.1145/1062455.1062466

[44] Holmboe, C., McIver, L., & George, C. E. (2001). Research Agenda for Computer Science Education. In Annual Workshop of the Psychology of Programming Interest Group, 13, 207-223. Sheffield Hallam University.

[45] Hurley, P. J. (2012). A Concise Introduction to Logic (11th ed.). Boston, MA: Wadsworth.

[46] Hsu, T. C., Chang, S. C., & Hung, Y. T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers and Education. https://doi.org/10.1016/j.compedu.2018.07.004

[47] Husain, H., Kamal, N., Ibrahim, M. F., Huddin, A. B., & Alim, A. A. (2017). Engendering problem solving skills and mathematical knowledge via programming. Journal of Engineering Science and Technology, 12(12), 1–11.

[48] Ioannidou, A., Bennett, V., Repenning, A., Koh, K. H., & Basawapatna, A. (2011). Computational Thinking Patterns [Paper presentation]. Annual Meeting of the American Educational Research Association, New Orleans, LA.

[49] Israel, M., Pearson, J. N., Tapia, T., Wherfel, Q. M., & Reese, G. (2015). Supporting all learners in school-wide computational thinking: A cross-case qualitative analysis. Computers & Education, 82, 263-279. https://doi.org/10.1016/j.compedu.2014.11.022

[50] Jehlička, V. (2010). Interdisciplinary relations in teaching of programming. In Proceedings of the 2010 International Conference on Applied Computing. World Scientific and Engineering Academy and Society (WSEAS), 33-38.

[51] Jenkins, T. (2002). On the difficulty of learning to program. In Proceedings of the 3rd Annual Conference of the LTSN Centre for Information and Computer Sciences, 4, 53-58.

[52] Jones, C. (2010). Interdisciplinary approach-advantages, disadvantages, and the future benefits of interdisciplinary studies. Essai, 7(1), Article 26. http://dc.cod.edu/essai/vol7/iss1/26

[53] Kafai, Y., & Burke, Q. (2014). Connected code: why children need to learn programming. MIT.

[54] Kale, U., Akcaoglu, M., Cullen, T., Goh, D., Devine, L., Calvert, N., & Grise, K. (2018). Computational what? Relating computational thinking to teaching. TechTrends, 62(6), 574-584. https://doi.org/10.1007/s11528-018-0290-9

[55] Kandel A, Langholz G, Mott J (1998). Foundations Of Digital Logic Design. World Scientific Publishing Company, ISBN 9813105100, 9789813105102.

[56] Kazimoglu, C., Kiernan, M., Bacon, L., & MacKinnon, L. (2012). Learning Programming at the Computational Thinking Level via Digital Game-Play.

[57] Kelleher, C., & Pausch, R. (2007). Using storytelling to motivate programming. Communications of the ACM, 50(7), 58-64. https://doi.org/10.1145/1272516.1272540

[58] Lambic, D. (2011). Presenting practical application of mathematics by the use of programming software with easily available visual components. Teaching Mathematics and Its Applications: An International Journal of the IMA, 30(1), 10–18. doi: 10.1093/teamat/hrq014

[59] LeBlanc, M. D., & Leibowitz, R. (2006). Discrete partnership: a case for a full year of discrete math. ACM SIGCSE Bulletin, 38(1), 313-317. https://doi.org/10.1145/1121341.1121438

[60] Lee, I., Grover, S., Martin, F., Pillai, S., & Malyn-Smith, J. (2019). Computational Thinking from a Disciplinary Perspective: Integrating Computational Thinking in K-12 Science, Technology, Engineering, and Mathematics Education. Journal of Science Education and Technology, 29(1), 1–8. doi:10.1007/s10956-019-09803-w Leonard, J., Buss, A., Gamboa, R., Mitchell, M., Fashola, O., Hubert, T., & Almughyirah, S. (2016). Using robotics and game design to enhance children’s self-efficacy, STEM attitudes, and computational thinking skills. Journal of Science Education and Technology, 25(6), 860–876. doi: 10.1007/s10956-016-9628-2

[61] Lin, Y.-T., Wang, M.-T., & Wu, C.-C. (2019). Design and Implementation of Interdisciplinary STEM Instruction: Teaching Programming by Computational Physics. Asia-Pacific Education Researcher, 28(1), 77-91. https://doi.org/10.1007/s40299-018-0415-0

[62] Lu, J. J., & Fletcher, G. H. (2009). Thinking about computational thinking. ACM SIGCSE Bulletin, 41(1), 260-264. https://doi.org/10.1145/1508865.1508959

[63] Lye, S. Y., & Koh, J. H. L. (2014). Review on teaching and learning of computational thinking through programming: What is next for K-12? Computers in Human Behavior, 41, 51-61. https://doi.org/10.1016/j.chb.2014.09.012

[64] Mahadev, A., & Conner, S. (2014). An interdisciplinary approach to teaching a computer ethics course. Journal of Computing Sciences in Colleges, 29(5), 202-207. https://dl.acm.org/doi/10.5555/2600623.2600663

[65] Malan, D. J., & Leitner, H. H. (2007). Scratch for Budding Computer Scientists. In SIGCSE '07: Proceedings of the 38th SIGCSE Technical Symposium on Computer Science Education, ACM, 223-227. https://doi.org/10.1145/1227504.1227388

[66] Moreno-León, J., Robles, G., & Román-González, M. (2016). Code to learn: Where does it belong in the K-12 curriculum? Journal of Information Technology Education: Research, 15, 283–303. doi: 10.28945/3521

[67] Oliveira Aureliano, V. C. (2013). A methodology for teaching programming for beginners. In Proceedings of the Ninth Annual International ACM Conference on International Computing Education Research, 169-170. ACM.

[68] Olteanu C. (2022). Programming, mathematical reasoning and sense-making. International Journal of Mathematical Education in Science and Technology 53(8), 2046-2064.

[69] Park, J. Y., & Mills, K. A. (2014). Enhancing interdisciplinary learning with a learning management system. Journal of Online Learning and Teaching, 10(2), 299-313. https://jolt.merlot.org/vol10no2/park_0614.pdf

[70] Porter, L., Guzdial, M., McDowell, C., & Simon, B. (2013). Success in introductory programming: What works? Communications of the ACM, 56(8), 34-36.https://doi.org/10.1145/2492007.2492020

[71] Pruski, L., & Friedman, J. (2014). An integrative approach to teaching mathematics, computer science, and Physics with Matlab. Mathematics and Computer Education, 48(1), 6-18.

[72] Rosen K. (2019). Discrete Mathematics and Its Applications. 8th Edition, illustrated Publisher McGraw-Hill, ISBN1260091996, 9781260091991.

[73] 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), 73-88. https://www.ceeol.com/search/article-detail?id=69618

[74] Seng, W. Y., & Yatim, M. H. M. (2014). Computer game as learning and teaching tool for object-oriented programming in higher education institution. Procedia - Social and Behavioral Sciences, 123, 215-224. https://doi.org/10.1016/j.sbspro.2014.01.1417

[75] Sengupta, P., Kinnebrew, J. S., Basu, S., Biswas, G., & Clark, D. (2013). Integrating computational thinking with K-12 science education using agent-based computation: a theoretical framework. Education and Information Technologies, 18, 351-380. https://doi.org/10.1007/s10639-012-9240-x

[76] Sinclair, N., & Patterson, M. (2018). The Dynamic Geometrisation of Computer Programming.

[77] Mathematical Thinking and Learning, 20(1), 54–74. doi: 10.1080/10986065.2018.1403541 Stozhko, N., Bortnik, B., Mironova, L., Tchernysheva, A., & Podshivalova, E. (2015).

[78] Interdisciplinary project-based learning: technology for improving student cognition.

[79] Research in Learning Technology, 23, Article 27577. https://doi.org/10.3402/rlt.v23.27577

[80] Tan, J., Guo, X., & Zheng, W. (2014). Case-based teaching using the Laboratory Animal System for learning C/C++ programming. Computers & Education, 77, 39-49. https://doi.org/10.1016/j.compedu.2014.04.003

[81] Taub, R., Armoni, M., & Ben-Ari, M. (2012). CS unplugged and middle-school students’ views, attitudes, and intentions regarding CS. ACM Transactions on Computing Education (TOCE), 12(2), Article 8. https://doi.org/10.1145/2160547.2160551.

[82] Taylor, M., Harlow, A., & Forret, M. (2010). Using a computer programming environment and an interactive whiteboard to investigate some mathematical thinking. Procedia - Social and Behavioral Sciences, 8, 561–570. doi: 10.1016/j.sbspro.2010.12.078

[83] Thies, R., & Vahrenhold, J. (2013). On plugging unplugged into CS classes. In Proceedings of the 44th ACM Technical Symposium on Computer Science Education, 365-370.

[84] Umar, A., & Musa, S. (2022). ICT and Learning of Mathematics in Nigeria. Journal of Mathematics Instruction, Social Research and Opinion, 1(3), 143-152. ISSN 2962-7842.

[85] Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L., & Wilensky, U. (2016).

[86] Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology, 25, 127-147

[87] Wilson, B. C., & Shrock, S. (2001). Contributing to success in an introductory computer science course: A study of twelve factors. ACM SIGCSE Bulletin, 33(1), 184-188. https://doi.org/10.1145/366413.364581

[88] Wing, J. M. (2008). Computational thinking Communications of the ACM, 49(3), 33-35. https://doi.org/10.1145/1118178.1118215

[89] Yadav, A., Gretter, S., Good, J., & McLean, T. (2017). Computational thinking in teacher education. P. J. Rich & C. B. Hodges (Eds.), Emerging research, practice, and policy on computational thinking, 205-220. Springer.

@article{1709502,
      author = {Nriagu Chukwunonso O, Oketayo Abimbola Mujidat, Bamidele Oluchi Jennie, Oduwole Oluwakemi Omolara},
      title = {Improving Student's Computation Performance: A Systematic Literature Review},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {1},
      pages = {282-293},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1709502.pdf},
      abstract = {The teaching of computer science in schools has been greatly influenced by the rapid development of technology, making Information Technology literacy a priority. Research literatures and experience in classrooms confirm that students have challenges on algorithms, function and programming. To overcome this, there is need to teach the concepts of mathematics in programming. Mathematics in programming constitutes an important role and should be included in the studies. The use of Mathematics in learning of programming offer a range of techniques to train students in computational thinking and programming skills. Foundational mathematical concepts such as logic, functions, and discrete mathematics, provide the cognitive framework for understanding core programming principles. The process of developing and debugging codes require precise and systematic approach similar to constructing a mathematical proof. Furthermore, students with a solid mathematical background tend to understand programming concepts and perform better in programming related tasks with the ability to design efficient solutions. The study reviewed the role of mathematics as the bedrock subject for computing; the integration of mathematical concepts and design of a systematic approach in training of students in problem solving. This comprehensive survey provides an in-depth examination of existing methods on computational thinking and mathematics approach in problem solving. The results showed that teaching programming with mathematics as an interdisciplinary approach increased students? programming and computational thinking skills. Additionally, the integration of mathematics improved the students? learning processes. This survey provide a valuable resource for researchers, teachers, and policymakers seeking to improve students? problem solving skills and to stimulate further research in this critical area.},
      keywords = {Programming, Mathematical Concepts, Computational Thinking Skills, Interdisciplinary, Problem Solving},
      month = {July},
  }