Beyond Normal: Preparing Undergraduates for the Work Force in a Statistical Consulting Capstone

Smucker, Byran J.; Bailer, A. John

doi:10.1080/00031305.2015.1077731

Cited by 18 publications

(18 citation statements)

References 5 publications

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“…In many data science and applied statistics programs, capstone courses, where students undertake open‐ended, authentic tasks, are the primary means by which they can engage in experiential learning to prepare them for the workforce. For example, Lazar et al in 2011 and Smucker and Bailer in 2015 [14,18] describe project‐based capstone courses in which students integrate and synthesize content covered throughout an undergraduate course to develop solutions to problems that require the analysis of real data. In the statistical consulting capstone course described by Smucker and Bailer in 2015 [18], projects are drawn not only from other university faculties but also from the broader community.…”

Section: Preparing Students For Work‐integrated Learningmentioning

confidence: 99%

“…For example, Lazar et al in 2011 and Smucker and Bailer in 2015 [14,18] describe project‐based capstone courses in which students integrate and synthesize content covered throughout an undergraduate course to develop solutions to problems that require the analysis of real data. In the statistical consulting capstone course described by Smucker and Bailer in 2015 [18], projects are drawn not only from other university faculties but also from the broader community. Project teams can be composed of statistics majors and other students.…”

Section: Preparing Students For Work‐integrated Learningmentioning

confidence: 99%

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Building employability capabilities in data science students: An interdisciplinary, industry‐focused approach

Ferns

Phatak

Benson

et al. 2021

Teaching Statistics

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In the contemporary workplace, data scientists who are capable of interdisciplinary collaboration are in high demand. Universities need to provide data science students with a plethora of learning opportunities that involve collaboration in interdisciplinary contexts and engagement with industry partners. Curtin University and Lab Tests Online Australasia (LTOAU) collaborated to provide an interdisciplinary, industry‐focused learning experience for data science students. Upon completing the project, students reported improved understanding of the range of applications for data science skills. The experience delivered opportunities for greater self‐awareness and highlighted the importance of teamwork, decision‐making and leadership skills. This chapter presents Interdisciplinary Project‐based Work‐Integrated Learning (IPjWIL), an educational approach that equips data science students with the necessary skills to navigate the future world of work. The results of the pilot project described demonstrate how interdisciplinary, industry‐focused learning experiences enhance the capabilities of data science students, thereby augmenting employability.

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Section: Preparing Students For Work‐integrated Learningmentioning

confidence: 99%

Section: Preparing Students For Work‐integrated Learningmentioning

confidence: 99%

Building employability capabilities in data science students: An interdisciplinary, industry‐focused approach

Ferns

Phatak

Benson

et al. 2021

Teaching Statistics

View full text Add to dashboard Cite

show abstract

“…While the idea of teaching via applied labs is not new in statistics ( [5,18,33,36,37,38,50]), this style of teaching is less popular in mathematics. When mathematicians teach statistics, theory is often emphasized over applications, and pre-cleaned data (usually, the data that comes with the textbook) is often used instead of real-world data.…”

Section: Applied Statistics Topicsmentioning

confidence: 99%

A Project-Based Approach to Statistics and Data Science

White¹

2019

PRIMUS

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In an increasingly data-driven world, facility with statistics is more important than ever for our students. At institutions without a statistician, it often falls to the mathematics faculty to teach statistics courses. This paper presents a model that a mathematician asked to teach statistics can follow. This model entails connecting with faculty from numerous departments on campus to develop a list of topics, building a repository of real-world datasets from these faculty, and creating projects where students interface with these datasets to write lab reports aimed at consumers of statistics in other disciplines. The end result is students who are well prepared for interdisciplinary research, who are accustomed to coping with the idiosyncrasies of real data, and who have sharpened their technical writing and speaking skills.

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“…One student is selected to be team leader, a position that rotates through the members of the team. The instructor acts as a senior consultant who directs the team to advanced methods as needed (Smucker and Bailer 2015). At the School of Computing and Management Sciences at Sheffield Hallam University in the United Kingdom, the 3-month long standalone capstone project serves as preparation for an off-site capstone experience, in which third-year students spend a full year in industry.…”

Section: Standalone Capstone Projectmentioning

confidence: 99%

“…They advise their clients to avoid entrusting a project on their organization's critical path to the students, both due to the long duration of the project and due to the uncertainty of success, advice which Borrelli (2010) echoed. Smucker and Bailer (2015) pointed out that the instructor responsible for vetting potential projects needs to be confident that the project is of the appropriate level of difficulty for the students without presolving it.…”

Section: Standalone Capstone Projectmentioning

confidence: 99%

A Survey of Statistical Capstone Projects

Martonosi

Williams

2016

Journal of Statistics Education

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In this article, we highlight the advantages of incorporating a statistical capstone experience in the undergraduate curriculum, where students perform an in-depth analysis of real-world data. Capstone experiences develop statistical thinking by allowing students to engage in a consulting-like experience that requires skills outside the scope of traditional courses: defining a complex problem, analyzing data, building a strong team, and communicating effectively. We describe the pedagogical benefits as they relate to improved student outcomes and prospective job and graduate school placement, and we classify statistical capstones into four groups: standalone capstone projects, statistical consultancies, capstone projects embedded in an advanced statistics methodology course, and instruction-focused capstone courses. This article serves as a guide for educators seeking to implement an enriching capstone experience in their undergraduate mathematics or statistics curriculum to better prepare students for industrial and academic careers in data science.

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Beyond Normal: Preparing Undergraduates for the Work Force in a Statistical Consulting Capstone

Cited by 18 publications

References 5 publications

Building employability capabilities in data science students: An interdisciplinary, industry‐focused approach

Building employability capabilities in data science students: An interdisciplinary, industry‐focused approach

A Project-Based Approach to Statistics and Data Science

A Survey of Statistical Capstone Projects

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