Quantum computing education requires students to move beyond classical programming intuitions related to state, determinism, and debugging, and to develop reasoning skills grounded in probability, measurement, and interference. This paper reports on the design and delivery of a combined undergraduate and graduate course at Louisiana State University that employed a lab-integrated learning model to support conceptual change and progressive understanding. The course paired lectures with weekly programming labs that served as environments for experimentation and reflection. These labs enabled students to confront misconceptions and refine their mental models through direct observation and evidence-based reasoning. Instruction began with Quantum Without Linear Algebra (QWLA), which introduced core concepts such as superposition and entanglement through intuitive, dictionary representations. The course then transitioned to IBM Qiskit, which provided a professional framework for circuit design, noise simulation, and algorithm implementation. Analysis of student work and feedback indicated that hands-on experimentation improved confidence, conceptual clarity, and fluency across representations. At the same time, it revealed persistent challenges in debugging, reasoning about measurement, and understanding probabilistic outcomes. This paper presents the course structure, instructional strategies, and lessons learned, and argues that lab-integrated learning offers an effective and accessible approach to teaching quantum computing in computer science education.

翻译：量子计算教育要求学生超越与状态、确定性和调试相关的经典编程直觉，发展基于概率、测量和干涉的推理能力。本文报告了路易斯安那州立大学为本科生和研究生开设的一门融合课程的设计与实施，该课程采用实验整合式学习模式以支持概念转变和渐进式理解。课程将讲座与每周编程实验相结合，这些实验作为学生进行探索和反思的环境。通过直接观察和基于证据的推理，实验环节使学生能够直面错误概念并完善其心智模型。教学从"无需线性代数的量子计算"（QWLA）入门，通过直观的字典表示法介绍叠加态和纠缠等核心概念。随后课程过渡到IBM Qiskit平台，该平台为电路设计、噪声模拟和算法实现提供了专业框架。对学生作业和反馈的分析表明，动手实验提升了学生在不同表征方式间的信心、概念清晰度和运用流畅度。同时，研究也揭示了学生在调试、测量推理及理解概率结果方面持续存在的挑战。本文详细介绍了课程结构、教学策略与实践经验，论证了实验整合式学习为计算机科学教育中的量子计算教学提供了一条高效且易于实施的教学路径。