Student Expectations from a cross-cultural virtual collaboration: A qualitative analysis

  • Naresh Kumar Agarwal Graduate School of Library and Information Science, Simmons College, Boston, USA
  • Noor Faridah A Rahim School of Informatics and IT, Temasek Polytechnic, Singapore

Abstract

Peer assessment helps create a learning environment whereby students learn not only from the instructor, but also from one another and each other’s work. The usage of cross-culture collaborations and peer review teaching methodologies in Library and Information Science (LIS) education have shown to benefit student learning. However, LIS students are often made to collaborate with their peers within the same course and from the same discipline. In addition, while social media has been used in education in recent years, the use of social media for cross-culture peer review is not normally seen. In this study, collaboration was carried between out 58 LIS students from Simmons College, Boston and 238 non-LIS students from Temasek Polytechnic, Singapore. Considering that the students were coming from different countries, different types of schools, different cultures and different age-groups, they were asked to answer a question pertaining to their expectations from the virtual collaboration. As expectations form a key basis for the success of any endeavour, the open-ended responses from both sets of students are analyzed. In this paper, we report the results of this qualitative analysis and identify a set of cost and benefit factors for the two sets of students. The study throws light on how LIS and non-LIS students view cross-cultural collaboration for coursework, and what their fears and concerns might be. 

Published
2017-05-19
How to Cite
AGARWAL, Naresh Kumar; RAHIM, Noor Faridah A. Student Expectations from a cross-cultural virtual collaboration: A qualitative analysis. Qualitative and Quantitative Methods in Libraries, [S.l.], v. 3, n. 1, p. 221-234, may 2017. ISSN 2241-1925. Available at: <http://www.qqml.net/index.php/qqml/article/view/132>. Date accessed: 18 aug. 2022.