From the classroom to the workplace: How social science students are learning to do data analysis for real

Jacqueline Carter, Mark Brown, Kathryn Simpson

Research output: Contribution to journalArticlepeer-review

165 Downloads (Pure)

Abstract

In British social science degree programmes, methods courses have a bad press, and statistics courses in particular are not well-liked by most students. A nationallycoordinated, strategic investment in quantitative skills training, Q-Step, is an attempt to address the issues affecting the shortage of quantitatively trained humanities and social science graduates. Pedagogic approaches to teaching statistics and data analysis to social science students are starting to indicate positive outcomes. This paper contributes to these debates by focusing on the perspective of the student experience in different learning environments: first, we explain the approach taken at the University of Manchester to teaching a core quantitative research methods module for second-year sociology students; and second, we introduce case studies of three undergraduates who took that training and went on to work as interns with social research organisations, as part of a Manchester Q-Step Centre initiative to take learning from the classroom into the workplace.

Original languageEnglish
Pages (from-to)80-101
Number of pages22
JournalStatistics Education Research Journal
Volume16
Issue number1
Publication statusPublished - 1 May 2017

Keywords

  • Statistics education research; Statistical literacy; Internships; Applied learning

Research Beacons, Institutes and Platforms

  • Cathie Marsh Institute

Fingerprint

Dive into the research topics of 'From the classroom to the workplace: How social science students are learning to do data analysis for real'. Together they form a unique fingerprint.

Cite this