The data science discovery program: A model for data science consulting in higher education

IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY Stat Pub Date : 2024-04-18 DOI:10.1002/sta4.677
C. Taylor Brown, Megan Mehta, Mahathi Ryali, Xiaoran Dong, Iliya Shadfar, Jacqueline Dominquez Davalos, Aaron Culich, Anthony Suen
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Abstract

As one of the largest data science research incubator initiatives in the country, the University of California, Berkeley's Data Science Discovery Program serves as a case study for a scalable and sustainable model of data science consulting in higher education. This case contributes to the broader literature on data science consulting in higher education by analysing the programme's development, institutional influences; staffing and structural model; and defining features, which may prove instructive to similar programmes at other institutions. The programme is characterised by a unique structure of undergraduate consultations led by graduate student mentorship and governance; a streamlined, multidepartmental model that facilitates scalability and sustainability; and diverse modes for undergraduate consulting—including one‐on‐one ad‐hoc data science consultations, extended data science project development and management, peer mentorship and data science workshop instruction. This case demonstrates that universities may be able to initiate a low‐stakes, small‐scale data science consulting initiative and then progressively scale up the project in collaboration with multiple departments and organisations across campus.
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数据科学发现计划:高等教育数据科学咨询模式
作为美国最大的数据科学研究孵化器计划之一,加州大学伯克利分校的数据科学发现计划是高等教育中可扩展、可持续的数据科学咨询模式的案例研究。本案例通过分析该计划的发展、机构影响、人员配备和结构模式,以及可能对其他机构的类似计划具有指导意义的定义特征,为更广泛的高等教育数据科学咨询文献做出了贡献。该计划的特点包括:由研究生指导和管理领导的本科生咨询的独特结构;有利于可扩展性和可持续性的精简的多部门模式;本科生咨询的多样化模式--包括一对一的临时数据科学咨询、扩展的数据科学项目开发和管理、同行指导和数据科学研讨会指导。这个案例表明,大学可以启动一个低风险、小规模的数据科学咨询项目,然后与校园内的多个部门和组织合作,逐步扩大项目规模。
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来源期刊
Stat
Stat Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.10
自引率
0.00%
发文量
85
期刊介绍: Stat is an innovative electronic journal for the rapid publication of novel and topical research results, publishing compact articles of the highest quality in all areas of statistical endeavour. Its purpose is to provide a means of rapid sharing of important new theoretical, methodological and applied research. Stat is a joint venture between the International Statistical Institute and Wiley-Blackwell. Stat is characterised by: • Speed - a high-quality review process that aims to reach a decision within 20 days of submission. • Concision - a maximum article length of 10 pages of text, not including references. • Supporting materials - inclusion of electronic supporting materials including graphs, video, software, data and images. • Scope - addresses all areas of statistics and interdisciplinary areas. Stat is a scientific journal for the international community of statisticians and researchers and practitioners in allied quantitative disciplines.
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