Reflections on study abroad: a computational linguistics approach

Peter Grajzl and Cindy Irby ()
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Cindy Irby: Center for International Education, Washington and Lee University

Journal of Computational Social Science, 2019, vol. 2, issue 2, No 4, 181 pages

Abstract: Abstract Study abroad and the associated sociocultural experience has been a subject of substantial interest to social science scholars and university administrators. Shedding novel light on the phenomenon, we draw on a corpus of student-authored reflective essays and apply machine learning methods for analysis of text-as-data to examine the features and the determinants of salient themes emphasized by students in their study abroad reflections. Our analysis identifies 18 different topics spanning the domains of distinctly cultural cognition, interaction with people, physical environment, and personal change. Specifics of the experience such as duration and location, timing of reflections, and observable student characteristics including gender, major, academic performance, extracurricular involvement, and socioeconomic status are all important determinants of student’s reflections. Different factors, however, matter differently with respect to students’ emphases on particular topics, a finding indicative of the complex nature of the study abroad experience.

Keywords: Study abroad; Reflections; Culture; Text-as-data; Machine learning; Structural topic model (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s42001-019-00038-8

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