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FROM THE CLASSROOM TO THE WORKPLACE: HOW SOCIAL SCIENCE STUDENTS ARE LEARNING TO DO DATA ANALYSIS FOR REAL
Author(s) -
Jacqueline Carter,
Mark Brown,
Kathryn Simpson
Publication year - 2017
Publication title -
statistics education research journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.538
H-Index - 14
ISSN - 1570-1824
DOI - 10.52041/serj.v16i1.218
Subject(s) - mathematics education , perspective (graphical) , economic shortage , psychology , sociology , pedagogy , computer science , government (linguistics) , philosophy , artificial intelligence , linguistics
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 nationally-coordinated, 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. First published May 2017 at Statistics Education Research Journal Archives

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