Kofinas, Alexander and Tsay, Han-Huei (Crystal) ORCID: https://orcid.org/0000-0003-4959-0411 (2021) In favor of large classes: a social networks perspective on experiential learning. Journal of Management Education, 45 (5). pp. 760-785. ISSN 1052-5629 (Print), 1552-6658 (Online) (doi:10.1177/10525629211022819)

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Abstract

Most of the literature has viewed large classes as a problem and a challenge. Furthermore, large classes are often presented to be an obstacle to students’ experiential learning and a multitude of solutions can be found in the literature to manage large classes; solutions that include innovative technologies, alternative assessment designs, or expanding the capacity of delivery. This conceptual paper advocates that large classes, when used intentionally as a pedagogical tool, can be a powerful means for socialized and experiential learning for our students. In this work we connect the phenomenon of large classes with social network theory and concepts to re-conceptualize large classes as a social micro-cosmos consisting of a multitude of interconnected student communities. On this conceptual basis we offer three positive features of large classes: (i) higher levels of freedom for students to learn in their own terms (ii) learning from a diverse body of students and (iii) the provision of meaningful experiences of learning. We conclude with suggestions that should enable educators in large classes shift from an individualistic psychology-based model of experiential learning to a sociological model of experiential learning.

Item Type:	Article
Uncontrolled Keywords:	large classes; social networks; diversity; othering; freedom to learn
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management L Education > L Education (General)
Faculty / School / Research Centre / Research Group:	Faculty of Business Faculty of Business > Department of Human Resources & Organisational Behaviour Greenwich Research into Innovative Pedagogies (GRIP) Greenwich Business School > Centre for Research on Employment and Work (CREW)
Last Modified:	02 Dec 2024 15:46
URI:	http://gala.gre.ac.uk/id/eprint/35791

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