SOCIOLOGICAL MEDIA: MAXIMIZING STUDENT INTEREST IN QUANTITATIVE METHODS VIA COLLABORATIVE USE OF DIGITAL MEDIA Cover Image

SOCIOLOGICAL MEDIA: MAXIMIZING STUDENT INTEREST IN QUANTITATIVE METHODS VIA COLLABORATIVE USE OF DIGITAL MEDIA
SOCIOLOGICAL MEDIA: MAXIMIZING STUDENT INTEREST IN QUANTITATIVE METHODS VIA COLLABORATIVE USE OF DIGITAL MEDIA

Author(s): Frederick T. Tucker
Subject(s): Education, Media studies, Sociology, School education, ICT Information and Communications Technologies, Sociology of Education
Published by: Scientia Socialis, UAB
Keywords: community college; digital media; sociological methods; transformative pedagogy;

Summary/Abstract: College sociology lecturers are tasked with inspiring student interest in quantitative methods despite widespread student anxiety about the subject, and a tendency for students to relieve classroom anxiety through habitual web browsing. In this paper, the author details the results of a pedagogical program whereby students at a New York City community college used industry-standard software to design, conduct, and analyze sociological surveys of one another, with the aim of inspiring student interest in quantitative methods and enhancing technical literacy. A chi-square test of independence was performed to determine the effect of the pedagogical process on the students’ ability to discuss sociological methods unrelated to their surveys in their final papers, compared with the author’s students from the previous semester who did not undergo the pedagogical program. The relation between these variables was significant, χ 2(3, N=36) = 9.8, p = .02. Findings suggest that community college students, under lecturer supervision, with minimal prior statistical knowledge, and access to digital media can collaborate in small groups to create and conduct sociological surveys, and discuss methods and results in limited classroom time. College sociology lecturers, instead of combatting student desire to use digital media, should harness this desire to advance student mastery of quantitative methods.

  • Issue Year: 73/2016
  • Issue No: 1
  • Page Range: 75-88
  • Page Count: 14
  • Language: English