Disparities in access to US quantum information education

• URL: http://arxiv.org/abs/2309.08629v3
• Date: Fri, 15 Mar 2024 17:18:22 GMT
• Title: Disparities in access to US quantum information education
• Authors: Josephine C. Meyer, Gina Passante, Bethany R. Wilcox,
• Abstract summary: Quantum information science (QIS) coursework and degree programs are rapidly spreading across US institutions. Yet access to quantum workforce education is unequally distributed, disproportionately benefiting students at private research-focused institutions. We use regression analysis to analyze the distribution of QIS coursework across 456 institutions of higher learning as of fall 2022.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Driven in large part by the National Quantum Initiative Act of 2018, quantum information science (QIS) coursework and degree programs are rapidly spreading across US institutions. Yet prior work suggests that access to quantum workforce education is unequally distributed, disproportionately benefiting students at private research-focused institutions whose student bodies are unrepresentative of US higher education as a whole. We use regression analysis to analyze the distribution of QIS coursework across 456 institutions of higher learning as of fall 2022, identifying statistically significant disparities across institutions in particular along the axes of institution classification, funding, and geographic distribution suggesting today's QIS education programs are largely failing to reach low-income and rural students. We also conduct a brief analysis of the distribution of emerging dedicated QIS degree programs, discovering much the same trends. We conclude with a discussion of implications for educators, policymakers, and education researchers including specific policy recommendations to direct investments in QIS education to schools serving low-income and rural students, leverage existing grassroots diversity and inclusion initiatives that have arisen within the quantum community, and update and modernize procedures for collecting QIS educational data to better track these trends.

Related papers

• Investigating Opportunities for Growth and Increased Diversity in Quantum Information Science and Engineering Education in the U.S. based on an Analysis of the Current Educational Landscape [2.9123029495753934]
  Quantum Information Science and Engineering (QISE) is rapidly gaining interest across a wide range of disciplines. While efforts to characterize introductory QISE courses are underway, a comprehensive understanding of QISE education across the United States remains lacking. This paper presents part of an ongoing effort to characterize the current landscape of QISE courses and degree programs in higher education in the US.
  arXiv  Detail & Related papers  (2025-04-30T18:18:01Z)
• Landscape of Quantum Information Science and Engineering Education: From Physics Foundations to Interdisciplinary Frontiers [5.5326492815055355]
  Quantum Information Science and Engineering (QISE) is rapidly gaining interest from those within many disciplines. There is no holistic picture of the landscape of QISE and quantum-related education in the United States. Across all institutions, we identified over 8,000 courses mentioning 'quantum,' but about one-third of institutions in our study had none.
  arXiv  Detail & Related papers  (2025-04-18T14:41:58Z)
• LLM Agents for Education: Advances and Applications [49.3663528354802]
  Large Language Model (LLM) agents have demonstrated remarkable capabilities in automating tasks and driving innovation across diverse educational applications. This survey aims to provide a comprehensive technological overview of LLM agents for education, fostering further research and collaboration to enhance their impact for the greater good of learners and educators alike.
  arXiv  Detail & Related papers  (2025-03-14T11:53:44Z)
• An Overview of Large Language Models for Statisticians [109.38601458831545]
  Large Language Models (LLMs) have emerged as transformative tools in artificial intelligence (AI) This paper explores potential areas where statisticians can make important contributions to the development of LLMs. We focus on issues such as uncertainty quantification, interpretability, fairness, privacy, watermarking and model adaptation.
  arXiv  Detail & Related papers  (2025-02-25T03:40:36Z)
• From MOOC to MAIC: Reshaping Online Teaching and Learning through LLM-driven Agents [78.15899922698631]
  MAIC (Massive AI-empowered Course) is a new form of online education that leverages LLM-driven multi-agent systems to construct an AI-augmented classroom. We conduct preliminary experiments at Tsinghua University, one of China's leading universities.
  arXiv  Detail & Related papers  (2024-09-05T13:22:51Z)
• Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants [175.9723801486487]
  We evaluate whether two AI assistants, GPT-3.5 and GPT-4, can adequately answer assessment questions. GPT-4 answers an average of 65.8% of questions correctly, and can even produce the correct answer across at least one prompting strategy for 85.1% of questions. Our results call for revising program-level assessment design in higher education in light of advances in generative AI.
  arXiv  Detail & Related papers  (2024-08-07T12:11:49Z)
• Inequalities in Computational Thinking Among Incoming Students in an STEM Chilean University [1.2549535267918006]
  This article characterizes the computational thinking abilities of incoming students at a Chilean university with a strong emphasis on STEM disciplines. Based on more than 500 responses, this study provides evidence of significant inequalities in computational thinking across gender, type of school (private or no), and prior programming knowledge. The findings can enlighten upcoming research endeavors and formulate strategies to create a more equitable field for students entering STEM degrees in nations facing similar circumstances.
  arXiv  Detail & Related papers  (2024-07-22T17:51:15Z)
• Unifying (Quantum) Statistical and Parametrized (Quantum) Algorithms [65.268245109828]
  We take inspiration from Kearns' SQ oracle and Valiant's weak evaluation oracle. We introduce an extensive yet intuitive framework that yields unconditional lower bounds for learning from evaluation queries.
  arXiv  Detail & Related papers  (2023-10-26T18:23:21Z)
• DeSIQ: Towards an Unbiased, Challenging Benchmark for Social Intelligence Understanding [60.84356161106069]
  We study the soundness of Social-IQ, a dataset of multiple-choice questions on videos of complex social interactions. Our analysis reveals that Social-IQ contains substantial biases, which can be exploited by a moderately strong language model. We introduce DeSIQ, a new challenging dataset, constructed by applying simple perturbations to Social-IQ.
  arXiv  Detail & Related papers  (2023-10-24T06:21:34Z)
• Introductory quantum information science coursework at US institutions: Content coverage [0.0]
  We identify content items common across a large fraction of introductory QISE courses that are potentially amenable to research-based curriculum development. As a further guide for curriculum development, we also examine differences in content coverage by level (undergraduate/graduate) and discipline. Finally, we briefly discuss the implications of our findings for the development of a research-based QISE assessment at the postsecondary level.
  arXiv  Detail & Related papers  (2023-08-24T17:06:48Z)
• Framework for understanding quantum computing use cases from a multidisciplinary perspective and future research directions [0.0]
  There has been increasing awareness of the tremendous opportunities inherent in quantum computing (QC) QC will significantly impact the Internet of Things, cryptography, finance, and marketing. However, critical concerns regarding legal, political, and business-related policies germane to QC adoption exist.
  arXiv  Detail & Related papers  (2022-12-19T12:27:12Z)
• Quantum Undergraduate Education and Scientific Training [0.17590081165362778]
  Quantum Undergraduate Education and Scientific Training (QUEST) workshop was held June 3rd and 4th, 2021. This manuscript summarizes the results of workshop discussions with the hope of assisting faculty at PUIs attempting to incorporate quantum information science into their curriculum.
  arXiv  Detail & Related papers  (2021-09-28T16:28:12Z)
• GAEA: Graph Augmentation for Equitable Access via Reinforcement Learning [50.90625274621288]
  Disparate access to resources by different subpopulations is a prevalent issue in societal and sociotechnical networks. We introduce a new class of problems, Graph Augmentation for Equitable Access (GAEA), to enhance equity in networked systems by editing graph edges under budget constraints.
  arXiv  Detail & Related papers  (2020-12-07T18:29:32Z)
• Achieving a quantum smart workforce [38.367466098233315]
  Quantum Information Science and Engineering (QISE) education programs have greatly expanded in recent years. This manuscript not only addresses policy makers and funding agencies (both public and private) but also contains needs identified by industry leaders. We report on the status of eighteen post-secondary education programs in QISE and provide guidance for building new programs.
  arXiv  Detail & Related papers  (2020-10-23T21:24:57Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.