Quantum computing is emerging as a key enabler of digital transformation in data science and STEM education. This study investigates how quantum computing can be meaningfully integrated into higher education by combining a dual approach: a structured assessment of the specialized literature and a practical evaluation of educational tools. First, a science mapping study based on 281 peer-reviewed publications indexed in Scopus (2015–2024) identifies growth trends, thematic clusters, and international collaboration networks at the intersection of quantum computing, data science, and education. Second, a comparative analysis of widely used educational platforms—such as Qiskit, Quantum Inspire, QuTiP, and Amazon Braket—is conducted using pedagogical criteria including accessibility, usability, and curriculum integration. The results highlight a growing convergence between quantum technologies, artificial intelligence, and data-driven learning. A strategic framework and roadmap are proposed to support the gradual and scalable adoption of quantum literacy in university-level STEM programs.
Quantum computing is emerging as a key enabler of digital transformation in data science and STEM education. This study investigates how quantum computing can be meaningfully integrated into higher education by combining a dual approach: a structured assessment of the specialized literature and a practical evaluation of educational tools. First, a science mapping study based on 281 peer-reviewed publications indexed in Scopus (2015–2024) identifies growth trends, thematic clusters, and international collaboration networks at the intersection of quantum computing, data science, and education. Second, a comparative analysis of widely used educational platforms—such as Qiskit, Quantum Inspire, QuTiP, and Amazon Braket—is conducted using pedagogical criteria including accessibility, usability, and curriculum integration. The results highlight a growing convergence between quantum technologies, artificial intelligence, and data-driven learning. A strategic framework and roadmap are proposed to support the gradual and scalable adoption of quantum literacy in university-level STEM programs.
A revolutionary technology impacting the field of science, engineering, and education is Quantum computing. Quantum Computing in education is a discipline regarding its application to teaching and learning. The focus of the paper is a bibliometric analysis of academic literature on quantum computing in education to identify the intellectual structure thereof, patterns of growth, and future research perspectives. It is based on the Scopus database as a primary source of data. It covers 104 relevant publications published during 2011-2025. They were sorted and analyzed with the help of Bibliometrix package and its Biblioshiny interface in R to show the annual trends of publications. The findings indicate that quantum computing education is becoming of academic interest, and the number of research materials is growing rapidly since 2020. The highly interdisciplinary nature, with engineering, computer science, physics, and social sciences, respectively, playing the dominant role. There is a transition towards more basic quantum concepts into applied educational concepts, such as curriculum development, engineering education, teaching practices, and student learning. The paper has an important implication for researchers, teachers, and policy formulators. It also outlines the direction of future research that can be used to advance the sustainable development of quantum computing education.
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.
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.
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.
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.
Technological and scientific advancements in recent years have enabled us to manipulate technologies that were once considered unimaginable. Among these, Artificial Intelligence (AI) and quantum physics have emerged as pivotal forces, significantly enhancing our capacity to achieve goals and solve complex problems. Given their growing relevance, a comprehensive review of the scientific output underpinning this new era is both timely and necessary. Such a review allows us to trace the increasing scholarly interest in these domains and to identify emerging trends in the synergy between them. Accordingly, the objective of this article is to present a scientometric analysis of the academic literature related to both AI and quantum science. To achieve this, we examined peerreviewed articles indexed in the Web of Science (WoS) and Scopus databases, focusing on key indicators such as publication volume, citation patterns, and collaboration networks among countries, journals, and authors. The findings reveal a notable increase in interest toward the integration of AI and quantum technologies in recent years, driven by their combined potential to deliver enhanced performance across a wide range of disciplines.