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Quantum Computing Education for Computer Science Students: Bridging the Gap with Layered Learning and Intuitive Analogies (2405.09265v1)

Published 15 May 2024 in cs.ET and math.QA

Abstract: Quantum computing presents a transformative potential for the world of computing. However, integrating this technology into the curriculum for computer science students who lack prior exposure to quantum mechanics and advanced mathematics remains a challenging task. This paper proposes a scaffolded learning approach aimed at equipping computer science students with essential quantum principles. By introducing foundational quantum concepts through relatable analogies and a layered learning approach based on classical computation, this approach seeks to bridge the gap between classical and quantum computing. This differs from previous approaches which build quantum computing fundamentals from the prerequisite of linear algebra and mathematics. The paper offers a considered set of intuitive analogies for foundation quantum concepts including entanglement, superposition, quantum data structures and quantum algorithms. These analogies coupled with a computing-based layered learning approach, lay the groundwork for a comprehensive teaching methodology tailored for undergraduate third level computer science students.

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References (45)
  1. Y. Lu, A. Sigov, L. Ratkin, L. A. Ivanov, and M. Zuo, “Quantum computing and industrial information integration: A review,” Journal of Industrial Information Integration, p. 100511, 2023.
  2. M. Hasanovic, C. Panayiotou, D. Silberman, P. Stimers, and C. Merzbacher, “Quantum technician skills and competencies for the emerging quantum 2.0 industry,” Optical Engineering, vol. 61, no. 8, pp. 081 803–081 803, 2022.
  3. G. P. Temporão, T. B. Guerreiro, P. S. Ripper, and A. M. Pavani, “Teaching quantum computing without prerequisites: a case study,” in 2022 IEEE International Conference on Quantum Computing and Engineering (QCE).   IEEE, 2022, pp. 673–676.
  4. N. Didiş, “The analysis of analogy use in the teaching of introductory quantum theory,” Chemistry Education Research and Practice, vol. 16, no. 2, pp. 355–376, 2015.
  5. M. F. Fox, B. M. Zwickl, and H. Lewandowski, “Preparing for the quantum revolution: What is the role of higher education?” Physical Review Physics Education Research, vol. 16, no. 2, p. 020131, 2020.
  6. M. Kaur and A. Venegas-Gomez, “Defining the quantum workforce landscape: a review of global quantum education initiatives,” Optical Engineering, vol. 61, no. 8, pp. 081 806–081 806, 2022.
  7. G. Carrascal, A. A. Del Barrio, and G. Botella, “First experiences of teaching quantum computing,” The Journal of Supercomputing, vol. 77, no. 3, pp. 2770–2799, 2021.
  8. J. Liu and D. Franklin, “Introduction to quantum computing for everyone: experience report,” in Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1, 2023, pp. 1157–1163.
  9. E. F. Combarro, S. Vallecorsa, L. J. Rodríguez-Muñiz, Á. Aguilar-González, J. Ranilla, and A. Di Meglio, “A report on teaching a series of online lectures on quantum computing from cern,” The Journal of Supercomputing, vol. 77, no. 12, pp. 14 405–14 435, 2021.
  10. T. Kushimo and B. Thacker, “Investigating students’ strengths and difficulties in quantum computing,” in 2023 IEEE International Conference on Quantum Computing and Engineering (QCE), vol. 3.   IEEE, 2023, pp. 33–39.
  11. Ö. Salehi, Z. Seskir, and İ. Tepe, “Teaching quantum computing to an audience beyond physicists: A case study over 22 workshops in 10 countries,” arXiv preprint arXiv:2010.13552, 2020.
  12. M. Mykhailova and K. M. Svore, “Teaching quantum computing through a practical software-driven approach: Experience report,” in Proceedings of the 51st ACM technical symposium on computer science education, 2020, pp. 1019–1025.
  13. S. Khodaeifaal, “Updated and adapted curriculum and pedagogy of physics with the fourth industrial revolution and quantum revolution: From waves principles to quantum mechanics fundamentals,” in 2022 IEEE International Conference on Quantum Computing and Engineering (QCE).   IEEE, 2022, pp. 653–668.
  14. N. A. Davis and B. R. La Cour, “Quantum computing for the faint of heart,” in 2022 IEEE International Conference on Quantum Computing and Engineering (QCE).   IEEE, 2022, pp. 669–672.
  15. S. Chitransh, D. Fischer, N. Kawalek, N. LaRacuente, J. Markman, S. P. Gaunkar, and U. Zvi, “A multidisciplinary, artistic approach to broadening the accessibility of quantum science,” in 2022 IEEE International Conference on Quantum Computing and Engineering (QCE).   IEEE, 2022, pp. 701–708.
  16. S. Aehle, P. Scheiger, and H. Cartarius, “An approach to quantum physics teaching through analog experiments,” Physics, vol. 4, no. 4, pp. 1241–1252, 2022.
  17. S. Seegerer, T. Michaeli, and R. Romeike, “Quantum computing as a topic in computer science education,” in Proceedings of the 16th Workshop in Primary and Secondary Computing Education, 2021, pp. 1–6.
  18. The University of Warwick, “Quantum Computing - CS419-15,” accessed 5 May 2024. [Online]. Available: https://warwick.ac.uk/fac/sci/dcs/teaching/modules/cs419/#description
  19. University of Kent, “Introduction to Quantum Computing & Quantum Cryptography - COMP8220,” accessed 5 May 2024. [Online]. Available: https://www.kent.ac.uk/courses/modules/module/COMP8220
  20. Imperial College London, “Quantum Computing - 70021,” accessed 5 May 2024. [Online]. Available: https://www.imperial.ac.uk/computing/current-students/courses/70021/
  21. Durham University, “Quantum Computing - COMP4117,” accessed 5 May 2024. [Online]. Available: https://apps.dur.ac.uk/faculty.handbook/2022/UG/module/COMP4117
  22. University of Oxford, “Quantum Information: 2023-2024,” accessed 5 May 2024. [Online]. Available: https://www.cs.ox.ac.uk/teaching/courses/2023-2024/qi/#:~:text=The%20aim%20of%20this%20course,is%20divided%20into%20four%20parts
  23. Ludwig Maximilian University of Munich, “Introduction to Quantum Computing,” accessed 5 May 2024. [Online]. Available: https://www.nm.%ifi.lmu.de/teaching/Vorlesungen/2024ss/quantum-computing/
  24. Carnegie Mellon University , “Quantum Computation and Quantum Information 2018 - 15-859BB,” accessed 5 May 2024. [Online]. Available: https://www.cs.cmu.edu/~odonnell/quantum18/
  25. The university of Sydney, “Foundations of Quantum Computing - OLET2610,” accessed 5 May 2024. [Online]. Available: https://www.sydney.edu.au/units/OLET2610
  26. M. I. Núñez-Peña, M. Suárez-Pellicioni, and R. Bono, “Effects of math anxiety on student success in higher education,” International Journal of Educational Research, vol. 58, pp. 36–43, 2013.
  27. H. E. Levy, L. Fares, and O. Rubinsten, “Math anxiety affects females’ vocational interests,” Journal of Experimental Child Psychology, vol. 210, p. 105214, 2021.
  28. F. Neri, “Teaching mathematics to computer scientists: Reflections and a case study,” SN Computer Science, vol. 2, no. 2, p. 75, 2021.
  29. D. Wood, J. S. Bruner, and G. Ross, “The role of tutoring in problem solving,” Journal of child psychology and psychiatry, vol. 17, no. 2, pp. 89–100, 1976.
  30. R. D. Pea, “The social and technological dimensions of scaffolding and related theoretical concepts for learning, education, and human activity,” in Scaffolding.   Psychology Press, 2018, pp. 423–451.
  31. J. C. Richardson, S. Caskurlu, D. Castellanos-Reyes, S. Duan, M. S. U. Duha, H. Fiock, and Y. Long, “Instructors’ conceptualization and implementation of scaffolding in online higher education courses,” Journal of Computing in Higher Education, pp. 1–38, 2022.
  32. B. J. Reiser and I. Tabak, “Scaffolding,” in The Cambridge Handbook of the Learning Sciences, Second Edition.   Cambridge University Press, 2014, pp. 44–62.
  33. S. Shin, T. A. Brush, and K. D. Glazewski, “Designing and implementing web-based scaffolding tools for technology-enhanced socioscientific inquiry,” Journal of Educational Technology & Society, vol. 20, no. 1, pp. 1–12, 2017.
  34. T. A. Brush and J. W. Saye, “A summary of research exploring hard and soft scaffolding for teachers and students using a multimedia supported learning environment,” The Journal of Interactive Online Learning, vol. 1, no. 2, pp. 1–12, 2002.
  35. B. R. Belland, “Scaffolding: Definition, current debates, and future directions,” Handbook of research on educational communications and technology, pp. 505–518, 2014.
  36. J. Van de Pol, M. Volman, and J. Beishuizen, “Scaffolding in teacher–student interaction: A decade of research,” Educational psychology review, vol. 22, pp. 271–296, 2010.
  37. D. Gentner and M. Jeziorski, “The shift from metaphor to analogy in western science,” in Metaphor and Thought, A. Ortony, Ed.   Cambridge: Cambridge University Press, 1993, pp. 447–480.
  38. L. Jonāne, “Analogies in science education,” Pedagogika, vol. 119, no. 3, pp. 116–125, 2015.
  39. S. Glynn, “Analogies, role in science learning. encyclopedia of science education,” 2015.
  40. A. García-Carmona, “The use of analogies in science communication: Effectiveness of an activity in initial primary science teacher education,” International Journal of Science and Mathematics Education, vol. 19, no. 8, pp. 1543–1561, 2021.
  41. Z. Keri and H. S. Elbatarny, “The power of analogy-based learning in science.” HAPS Educator, vol. 25, no. 1, pp. 13–20, 2021.
  42. T. E. o. E. Britannica, “Rutherford model,” Encyclopedia Britannica, Jun. 2023, accessed 15 November 2023. [Online]. Available: https://www.britannica.com/science/Rutherford-model
  43. H. Pedro and E. Edinson, “Use of analogies in science education, asystematic mapping study,” in CS & IT Conference Proceedings, vol. 11, no. 10.   CS & IT Conference Proceedings, 2021.
  44. P. W. Shor, “Algorithms for quantum computation: discrete logarithms and factoring,” in Proceedings 35th annual symposium on foundations of computer science.   Ieee, 1994, pp. 124–134.
  45. L. K. Grover, “A fast quantum mechanical algorithm for database search,” in Proceedings of the twenty-eighth annual ACM symposium on Theory of computing, 1996, pp. 212–219.
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Authors (2)
  1. Anila Mjeda (1 paper)
  2. Hazel Murray (12 papers)

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