Abstract

This study combines research methods from student approaches to learning research and social network analysis (SNA) to examine patterns of students’ collaborative learning based on their learning orientations amongst 193 postgraduates enrolled in a blended course. The study identified two distinct learning orientations, namely ‘understanding’ and ‘reproducing’, which differed in approaches to learning through inquiry, approaches to using online learning technologies, perceptions of the online workload, and academic outcomes. On the basis of students’ learning orientations and their choice of whether to collaborate and with whom to collaborate, five networks representing five patterns of collaborative learning were found. From these, two did not reveal any collaboration (Understanding Alone and Reproducing Alone networks); and three revealed collaborations (Understanding Collaboration, Mixed Collaboration, Reproducing Collaboration networks). A range of SNA measures were calculated and revealed different features of the three collaboration networks. Viewed together, the combined methodologies suggest that the Understanding Collaboration network has more desirable features of collaboration, such as the intensity of collaboration, having closely knitted groups who tended to seek out and welcome peers and who tended to engage more often in both face-to-face and online modes. The study suggests that helping students adjust their learning orientations, designing some compulsory collaborative assessment tasks, and configuring the composition of collaborative groups are productive strategies likely to improve students’ experiences of collaborative learning.

Highlights

  • Evaluation of students’ collaborative competence has long been an essential part in higher education quality assurance agenda across countries (Indiana University Center for Postsecondary Research, 2020; Neves & Hewitt, 2020)

  • The hierarchical cluster analysis produced a range of two-cluster to four-cluster solutions

  • The current study investigated features of different patterns of student collaborative learning based on variations of students’ learning orientations amongst a cohort of postgraduate students enrolled in a compulsory blended course using the methods in student approaches to learning (SAL) research and techniques of social network analysis (SNA)

Read more

Summary

Introduction

Evaluation of students’ collaborative competence has long been an essential part in higher education quality assurance agenda across countries (Indiana University Center for Postsecondary Research, 2020; Neves & Hewitt, 2020). While collaborative competence has been continually emphasized and highlighted in the assessment of students’ learning experience in national frameworks in many countries, such as United States (Indiana University Center for Postsecondary Research, 2020), United Kingdom (Neves & Hewitt, 2020), and Australia (Department of Education, Skills & Employment, 2021); there is ongoing evidence that employers are dissatisfied with graduates’ collaborative skills (Harder et al, 2014). Despite its importance, developing students’ collaborative skills and fostering desirable experience of collaborative learning remains a challenging issue in higher education sector partly because collaborative learning is a complex activity, which involves many aspects and the interplay of these aspects in learning, such as the student factor and increasingly complex blended course designs

Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.