Abstract:

Quantum computing presents significant challenges for higher education due to its abstract mathematical foundations and conceptual difficulty. Students often struggle to translate formal theory into intuitive understanding, which hinders the effective integration of this emerging field into artificial intelligence curricula. This study explores how simulation-based learning can enhance theoretical comprehension and mathematical reasoning in quantum computing education.

The project, conducted within the Master’s in Artificial Intelligence at the University of Alicante, integrates IBM’s Qiskit library and Google Colab as accessible tools for active learning. The first phase focused on the design and implementation of practical sessions centered on fundamental quantum concepts (i.e., superposition, entanglement, and quantum gates). Students developed and simulated simple quantum circuits using only the X and H gates, chosen for their pedagogical clarity. The learning design aimed to connect theoretical lectures on quantum mechanics with concrete experimentation, encouraging students to explore the mathematical structure of qubit transformations through visualization and simulation.

A mixed-methods evaluation was conducted, combining performance data from lab activities with pre- and post-course surveys. Results indicate that hands-on practice with Qiskit simulations improved students’ conceptual and mathematical understanding of quantum principles, particularly among those with weaker backgrounds in formal physics or mathematics. Students reported that simulation-based experimentation helped them grasp the logic behind quantum state evolution, probabilities, and gate operations, thereby transforming abstract equations into observable behavior.

These findings indicate that structured, simulation-centered learning environments can effectively reduce the cognitive barriers inherent to quantum computing education, while simultaneously promoting deeper engagement and theoretical retention. Building on these outcomes, the second phase of the project will expand the instructional framework to include introductory quantum algorithms and the integration of real hardware experimentation through Qiskit API, further reinforcing the connection between simulation, theory, and practical application.

Keywords:

Quantum computing education, Simulation-based learning, Qiskit, Artificial Intelligence education.