Using Social Network Analysisto predict online contributions: The impact of network diversity on cross-cultural collaboration

Jenna MittelmeierInstitute of Educational Technology

The Open University, UKCo-Authors: Yingfei Heliot (University of Surrey)

Bart Rienties (The Open University) Denise Whitelock (The Open University)

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Strijbos & de Laat, 2010Xing, Wadholm & Goggins, 2014Caspi, Gorsky & Chajut, 2003

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Free-rider:‘contributes to the group task when explicitly prompted but minimises the effort as much as possible; often leading to substandard contributions’ (Strijbos & de Laat, 2010)

#1 complaint of students in cross-cultural group work(Popov et al, 2012)

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Cohort-like classrooms(Kimmel & Volet, 2012)

Previous multicultural experiences(Summers & Volet, 2008)

Cultural understanding and respect(Woods, Barker & Hibbins, 2010)

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Research Questions

RQ1: How do users’ social networks within a face-to-face environment influence the quantity of contributions when they collaborate online?

RQ2: To what extent do users’ positions within their social network in a face-to-face setting predict their behaviours when they collaborate online?

Setting118 student classroom92% international students from 24 countriesPhysical class session, optional online synchronous collaborative activities

Research MethodActivity: working anonymously in groups of five for one hour Social Network Analysis surveys compared with data from online collaborative tool

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EI Index

Network Density

# of social connections

total # of possiblesocial connections

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Contribution data analysed

# of posts submitted

summed word count

submitted

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Activity participation – Bivariate Analysis

58 Attendees from 13 countries

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Contribution Quantity – Bivariate Analysis

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Contribution Quantity – Regression Analysis

Number of Posts Submitted

18.9% of variation explained by:

EI Index(β= .388, p = .003)

Social Network Density(β=.252, p = .044)

Summed Word Count Submitted

16.0% of variation explained by:

EI Index(β= .406, p = .002)

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Research Questions

RQ1: How do users’ social networks within a face-to-face environment influence the quantity of contributions when they collaborate online?

RQ2: To what extent do users’ positions within their social network in a face-to-face setting predict their behaviours when they collaborate online?

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What does this mean?

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Implications for Web Science1.) The physical social space has a clear linkage to online behaviours in blended environments

2.) Traditionally ‘quantifiable’ data may not capture all influences on human behaviours

3.) ‘Social agency’ as a factor for participation

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Sources• Caspi, A., Gorsky, P., & Chajut, E. (2003). The influence of group size on nonmandatory

asynchronous instructional disscussion groups. Internet and Higher Education, 6, 227-240.

• Kimmel, K., & Volet, S. (2012). University students' perceptions of and attitudes towards culturally diverse group work: Does context matter? Journal of Studies in International Education, 16(2), 157-181.

• Popov, V., Brinkman, D., Biemans, H. J. A., Mulder, M., Kuznetsov, A., & Noroozi, O. (2012). Multicultural student group work in higher education: An explorative case study on challenges as perceive by students. International Journal of Intercultural Relations, 36, 302-317.

• Strijbos, J.-W., & de Laat, M. F. (2010). Developing the role concept for computer-supported collaborative learning: An explorative synthesis. Computers in Human Behavior, 26, 495-505.

• Summers, M., & Volet, S. (2008). Students' attitudes towards culturally mixed groups on international campuses: Impact of participation in diverse and non-diverse groups. Studies in Higher Education, 33(4), 357-370.

• Woods, P., Barker, M., & Hibbins, R. (2010). Tapping the benefits of multicultural group work: An exploratory study of postgraduate management students. International Journal of Educational Management, 9(2), 59-70.

• Xing, W., Wadholm, B., & Goggins, S. (2014). Learning analytics in CSCL with a focus on assessment: An exploratory study of activity theory-informed cluster analysis. Paper presented at the Fourth International Conference on Learning Analytics and Knowledge, Indianapolis, USA.