Content Analysis of Data Science Graduate Programs in the U.S.

Li, Duo; Milonas, Elizabeth; Zhang, Qiping

doi:10.18260/1-2--36841

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…At the postgraduate level, DS programs have been proliferating across the globe (Hosack and Sagers, 2015;Raj et al, 2019;Li, Milonas & Zhang, 2021). On the other hand, undergraduate DS programs are still being investigated (Zhang, Huang & Wang, 2017;Mikalef et al, 2018;Çetinkaya-Rundel & Ellison, 2021;Davenport & Malone, 2021).…”

Section: Ds Instructional Programsmentioning

confidence: 99%

Instructors' perception of the competencies required to teach DS in HEI

Msweli¹

EPiC Series in Education Science

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While data science education may be a solution in democratising data science, there are challenges towards achieving this. One of the challenges is the shortage of qualified academic staff members, who are able to deliver a multidisciplinary curriculum.Teaching data science is a developing topic and represents a gap in the literature as we embark on the journey of discovering the knowledge required to teach data science. This study aimed to gain insight into instructors’ perceptions on their skills and competencies in teaching data science

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Section: Ds Instructional Programsmentioning

confidence: 99%

Instructors' perception of the competencies required to teach DS in HEI

Msweli¹

EPiC Series in Education Science

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“…Course descriptions offered by a university course catalogue have been used to answer different research questions. Course descriptions have been used to depict the current state of data science education in the U.S. [14], [15]. In the educational data mining area, course recommendation systems have been built that use course descriptions to extract information about concepts or topics covered by each course [16] - [20].…”

Section: Course Descriptions Usagementioning

confidence: 99%