Quantum computing education is becoming urgent as industry demand and national initiatives grow rapidly. This paper introduces the Quantum Learning Pyramid (QLP), a unified pedagogical framework for undergraduate and graduate education in quantum information and computing. The QLP follows a four-tier structure that integrates phenomenological understanding, computational thinking, hardware-aware development, and societal context. The curriculum is designed using spiral progression, competency-based pathways, and authentic assessment. Instruction is grounded in active and project-based learning, aligned with ACM/IEEE curriculum guidelines. Core topics include quantum mechanics fundamentals, qubit operations, and key algorithms, while advanced modules address error correction, cryptography, and quantum hardware. Hands-on learning is supported through simulation platforms, cloud-accessible quantum processors, and hybrid laboratory environments. Interdisciplinary case studies and real-system experimentation are embedded throughout. The proposed framework bridges theory and practice and provides a scalable roadmap for developing a quantum-ready workforce and scientifically informed citizens.
Quantum computing education is becoming urgent as industry demand and national initiatives grow rapidly. This paper introduces the Quantum Learning Pyramid (QLP), a unified pedagogical framework for undergraduate and graduate education in quantum information and computing. The QLP follows a four-tier structure that integrates phenomenological understanding, computational thinking, hardware-aware development, and societal context. The curriculum is designed using spiral progression, competency-based pathways, and authentic assessment. Instruction is grounded in active and project-based learning, aligned with ACM/IEEE curriculum guidelines. Core topics include quantum mechanics fundamentals, qubit operations, and key algorithms, while advanced modules address error correction, cryptography, and quantum hardware. Hands-on learning is supported through simulation platforms, cloud-accessible quantum processors, and hybrid laboratory environments. Interdisciplinary case studies and real-system experimentation are embedded throughout. The proposed framework bridges theory and practice and provides a scalable roadmap for developing a quantum-ready workforce and scientifically informed citizens.
Quantum information science and engineering (QISE) is advancing rapidly, creating an urgent demand for a quantum-literate, technically proficient workforce. Despite this need, quantum education initiatives remain fragmented across regions, educational levels, and instructional approaches, which constrains their scalability and overall impact. This paper offers a structured analysis of the current quantum education ecosystem by synthesizing global initiatives, pedagogical strategies, and emerging trends. Quantum education is examined through a dual framework that considers both learner progression and instructional methodology, emphasizing the evolution of educational approaches from conceptual exposure to formal reasoning and practical application. Analysis of data from international programs and academic literature reveals key challenges, including inequitable access, absence of standardized curricula, limited empirical evaluation, and discontinuities between educational stages. Quantum education is more accurately conceptualized as a non-linear ecosystem rather than a traditional pipeline, characterized by multiple entry points, feedback mechanisms, and critical transition gaps. Based on this perspective, directions are proposed for developing more coherent, inclusive, and scalable educational frameworks that align with workforce requirements and technological progress. This work presents a unified perspective on the quantum education landscape and outlines actionable strategies to enhance global quantum literacy and workforce preparedness.
Quantum computing promises solutions to problems that are beyond the reach of classical machines; however, current noisy intermediate-scale quantum (NISQ) devices require both theoretical insight and hardware expertise.This paper presents a six-module curriculum designed to bridge that gap for undergraduates from diverse disciplines.The modules progress from Python programming to electronics and circuits, vacuum technology, cryogenic measurements, microwave and RF systems, and culminate with quantum simulations and computations.Implemented at Winston-Salem State University with thirty students across computer science, information technology, mathematics, chemistry, physics, and biology, the program combined lectures, group projects, and presentations.Hands-on activities included resistor network analysis, magnetic levitation, vacuum chamber assembly, cryogenics measurements, RF component analysis, and entanglement experiments, enabling students to connect abstract principles with laboratory practice.Outcomes showed increased confidence, collaboration, critical thinking, and skill set building, even among those with no prior background.Students advanced to research-oriented projects like secure quantum communication protocols and the Quantum Mini Tennis game, which explored gate operations and qubit transformations, demonstrating that hardware-aware quantum education lowers barriers, fosters interdisciplinary participation, and prepares students for NISQ-era challenges.
This paper analyzes extant studies on the teaching of quantum computing within the K-12 education levels.This analysis was necessitated by the limited information on the incorporation of quantum computing in the K-12 curriculum, including the pedagogical approaches, resources utilized, and how quantum computing can be promoted in schools.A systematic literature review approach was adopted to provide answers to the research questions using four reputable academic databases.The databases include ACM, Scopus, IEEE, and Web of Science where articles published between 2012 and March 2023 were retrieved.Fifty articles were found eligible for review from the numerous papers the search yielded.The analysis of the papers indicates that the main teaching methods adopted by researchers were direct instruction, hands-on activity, collaborative learning, inquiry-based learning, participatory learning, game-based learning, project-based learning, and design-oriented learning.The result further showed that the key assessment methods adopted mostly to evaluate the teaching of quantum computing include self-report evaluation, process observation, and knowledge and acquisition questions.The findings were discussed in relation to their implication for promoting quantum computing education in schools.This study offers insight for educators, computing and educational researchers, and education policymakers.
This poster explores strategies for supporting quantum computing education in academic libraries and invites collaborative discussion on building sustainable support models. As quantum computing emerges as a transformative technology with potential to solve complex research questions across disciplines, institutions of higher education must develop effective and scalable support frameworks. Successful integration of quantum computing education and support may position institutions at the forefront of breakthrough computational research and confer benefits such as strengthening the institutional ability to attract top faculty and students, boost workforce development, and deliver a competitive advantage for funding opportunities. We present our initial framework for quantum computing support developed at the University Libraries, University of Alabama. Our instructional model employs backward design principles, emphasizing hands-on engagement with open-source quantum development tools and focusing on transferable computational thinking skills that extend beyond specific tools. Our approach centers on workshops that prioritize achievable learning outcomes tailored to diverse student backgrounds, incorporate active learning strategies, and emphasize real-world applications to build quantum literacy across disciplines. Both our successes and ongoing challenges are shared to inform broader discussions. More broadly, we invite engagement with our framework and discussion across four critical dimensions of emerging technology support including pedagogical approach, assessment strategies, technology platforms and infrastructure, and collaborative support models. Pedagogically, we seek to explore which instructional methods most effectively build quantum computing literacy for students with diverse academic backgrounds as well as strategies to strike the balance between theoretical foundations and hands-on practice. With assessment, we seek meaningful assessment approaches that can address varied student backgrounds and account for steep learning curves accompanying emerging technologies. For technology, we endeavor to discover which platforms will work best within higher education and ensure access and reliability for students and educators on a broad scale. And finally, we seek to examine how academic libraries and other units collaborate to build sustainable, coordinated support infrastructure. As quantum computing and other emerging technologies reshape higher education, academic libraries may be uniquely positioned to lead support for quantum computing by democratizing access to computational resources and bridging gaps between research, instruction, and student success. To that end, we invite discussion on how academic libraries can help to build sustainable, adaptable, and collaborative models to support quantum computing. We seek experiences, challenges, and strategies to inform best practices while aligning with library and other campus computing efforts and meeting the evolving needs of students.
Quantum technologies are increasingly recognized as a strategic priority for economic competitiveness, national security, and technological innovation in the United States. As quantum systems transition from research prototypes to deployable technologies, attention has shifted toward the preparedness of the quantum workforce, particularly the alignment between higher education and industry skill needs. While prior research has examined individual aspects of quantum education or workforce demand, few studies integrate systematic curriculum analysis with documented industry expectations. This study addresses that gap by analyzing primary U.S. masters programs in quantum science and technology, focusing on curriculum structure and skill development. Using a structured coding framework, course offerings were mapped across six quantum-relevant skill categories and aggregated to produce program-level skill profiles. These profiles were then compared with industry-identified competencies reported in recent workforce studies. The findings reveal strong emphasis on quantum theory across programs, alongside substantial variability in technical skills, applied learning opportunities, and professional development components. The results highlight areas of alignment as well as persistent gaps related to workforce readiness, cross-disciplinary integration, and emerging technological demands. This study provides a scalable framework for evaluating quantum education programs and offers evidence-based insights for curriculum design, workforce policy, and the continued development of the U.S. quantum ecosystem.
This paper explores the integration of quantum computing (QC) into STEM curriculum education at higher education institutions, focusing on the dual objectives of workforce training and advancing cutting-edge research into curriculum development and hands-on labs. As the field of quantum computing rapidly evolves, there is a pressing need to equip minority students from diverse backgrounds with the skills necessary to participate in this transformative industry.The paper explores the process of developing a robust QC curriculum that combines theoretical foundations with practical, hands-on learning opportunities in personalized learning environments. It highlights initiatives aimed at equipping students with the skills necessary for conducting groundbreaking research in quantum computing. Through partnerships with academic institutions and industry collaboration, these programs aim to provide students with real-world exposure and mentorship. The findings emphasize the importance of inclusive education in the preparation of a diverse workforce capable of contributing to the future of quantum computing, innovation and application.