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.
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.
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 a revolutionary field of research in science and technology, which provides sophisticated processing capacity and computation in a finite time frame based on quantum mechanics. It has the great potential to offer more effective and faster solutions to overcome current processing constraints. Therefore, to address the global significance, relevance, and exponential growth, it is imperative to conduct a thorough investigation and promote advancements through rigorous scientometric analysis. The current article presents the knowledge mapping of rapidly expanding quantum computing research using the CiteSpace visualization tool. The foundation of research is the scientific literature on quantum computing extracted from the Scopus database, covering the period of 2008–2022. It provides publication patterns, citation structure, and in-depth keyword co-occurrence network analysis insights to extract emerging research areas. It illustrates a variety of empirical approaches to discover the status quo and evolution. The findings reveal that quantum algorithms serve as the fundamental basis for all research fields, and quantum machine learning is the most active research area nowadays.
This bibliometric study examines the field of quantum computing research from 2014 to 2023, utilizing the Web of Science Core Collection database and the Bibliometrix R package. A total of 1,260 documents from 688 sources were analyzed using bibliometric indicators, network analysis, and text mining techniques to identify research trends, collaboration patterns, and emerging themes. A five-fold increase in publications was observed, with the United States, China, and Germany emerging as the leading contributors to international collaborations. Core research areas were identified as quantum algorithms, error correction, and cryptography, while quantum machine learning and noisy intermediate-scale quantum (NISQ) computing were recognized as emerging trends. Potential research gaps in topological quantum computing and scalable error-correction schemes were identified. The findings underscore the necessity for continued focus on practical applications and interdisciplinary collaboration to advance quantum computing technologies.
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.
Abstract Quantum computing has rapidly emerged as one of the fastest-growing research domains, driven by both technological breakthroughs and the promise of computational advantages over classical systems. This study presents a comprehensive bibliometric analysis of the global quantum computing literature from 1980 to 2025, comprising 31,662 publications indexed in Scopus and accumulating over 800,000 citations. Using advanced bibliometric techniques—including co-authorship mapping, keyword co-occurrence networks, co-citation analysis, and centrality measures—we characterize publication trends, institutional contributions, collaborative structures, and thematic evolution across the field. The results reveal exponential growth in output since 2015, led primarily by the United States, China, and Europe, with key institutions such as MIT, the Chinese Academy of Sciences, CNRS, and the University of Waterloo at the forefront. The intellectual structure exhibits a dual-core configuration, with foundational algorithmic work (e.g. Shor, Grover, Nielsen & Chuang) tightly connected to emerging NISQ-era applications such as quantum machine learning, cryptography, and hybrid algorithms. Keyword analysis reveals the progressive expansion from core quantum algorithms toward increasingly diverse applied domains in healthcare, finance, chemistry, energy, and climate modeling. Public funding bodies (e.g. NSFC, NSF, European Commission, DOE, DoD, MoST) and private-sector investment from major technology firms are jointly driving this translational acceleration. Together, these findings provide an integrated quantitative map of the field’s evolution, offering valuable insight for future scientific policy, international collaboration, and strategic funding initiatives.
This paper presents a comprehensive systematic and bibliometric review of the rapidly expanding literature on quantum computing. The study addresses six research questions concerning prominent themes, temporal evolution, types of key findings, frequently reported research gaps, higher-order gap typologies, and future research directions. Utilizing a researcher-curated database, the final corpus comprises 153 studies compiled from non-Scopus, Scopus and Web of Science. The results demonstrate that quantum hardware and architecture, algorithms, and theoretical foundations dominate the current literature. Furthermore, publication output has risen significantly between 2018 and 2025. Among the reported findings, algorithmic innovations, performance claims, and hardware advancements are the most common. Despite this progress, the field faces substantial barriers; technical, scalability, fault-tolerance, and methodological-standardization gaps are the most frequently reported. Based on these identified gaps, eight actionable future research directions emerge to guide the scientific community. Ultimately, this review concludes that quantum computing is actively transitioning from a purely physics-driven domain into a multidisciplinary, engineering- and application-oriented science. However, its continued advancement is presently constrained by a hardware-methodology-application triad, wherein reporting practices often outpace empirical verification and standardized benchmarking.