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

Anila Mjeda, Hazel Murray

TL;DR

The paper addresses the challenge of teaching quantum computing to computer science students who typically lack physics or advanced mathematics background. It proposes a layered, scaffolded curriculum that grounds quantum concepts in classical computing and employs domain-specific analogies to explain topics such as qubits, superposition, entanglement, data structures, and algorithms. The authors present a two-layer structure (Layer 1: Classical Foundations; Layer 2: Quantum Foundations) supported by curated analogies and teaching materials to create a cohesive, accessible pedagogy. This approach aims to broaden participation in quantum computing education for CS students and foster workforce-ready understanding, with planned evaluation and curriculum expansion in future work.

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.

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

TL;DR

The paper addresses the challenge of teaching quantum computing to computer science students who typically lack physics or advanced mathematics background. It proposes a layered, scaffolded curriculum that grounds quantum concepts in classical computing and employs domain-specific analogies to explain topics such as qubits, superposition, entanglement, data structures, and algorithms. The authors present a two-layer structure (Layer 1: Classical Foundations; Layer 2: Quantum Foundations) supported by curated analogies and teaching materials to create a cohesive, accessible pedagogy. This approach aims to broaden participation in quantum computing education for CS students and foster workforce-ready understanding, with planned evaluation and curriculum expansion in future work.

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.
Paper Structure (17 sections, 3 figures, 5 tables)

This paper contains 17 sections, 3 figures, 5 tables.

Table of Contents

  1. Introduction
  2. Literature review
  3. Teaching Approaches
  4. Current Approaches
  5. "Layered Learning" and Use of Analogies in Education
  6. Layered Learning
  7. Layer 1: Classical Foundations
  8. Algorithms
  9. Complexity Theory
  10. Data Structures
  11. Classical-Quantum Hybrid Nature
  12. Layer 2: Quantum Foundations
  13. Qubits
  14. Superposition and Entanglement
  15. Measurement
  16. ...and 2 more sections

Figures (3)

  • Figure 1: Grover's algorithm amplifies the wave function at the point we are searching for.
  • Figure 2: A representation of the Bloch sphere
  • Figure 3: Ice skater spinning on the Bloch sphere ice rink.