Work

Quantum Computing in Data Science and STEM Education: Mapping Academic Trends and Analyzing Practical Tools

Year: 2025

Type: article

Abstract: 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.

Source: Computers

DOI: 10.3390/computers14060235

Authors: Eloy López-Meneses, Jesús Cáceres-Tello, José Javier Galán-Hernández, Luis López-Catalán

Institutions: Universidad Pablo de Olavide, Universidad Complutense de Madrid

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $2,172