Towards a social networks model for understanding teaching and learning in the CPC


In this project, we are interested in understanding the role of social networks (both formal and informal) in learning. Theories in social learning suggest that students learn more through engagement in discussion and articulation of concepts and by way of engaging in activities with peers and teachers than through traditional forms such as large lectures, where engagement is limited. In this project, we look beyond the individual (e.g. IQ, past academic history and socioeconomic background) and to the social personal network of students that has either direct or indirect impact on learning. Motivating questions for this project include: 1. What structures of personal social networks are conducive to social learning and performance? 2. To what extent does properties of social networks of students account for (i) deep learning (where learning is deeply embedded for life/long term) and (ii) surface learning (where learning dilutes over time or even forgotten (e.g. right after the exam))? 3. How does one account for the social network properties of students in order to enhance learning and teaching in organisations such as CPC?  


Dr Kenneth Chung

Research Location

Civil Engineering

Program Type



This project adopts network science thinking for understanding how relational and structural aspects of peer, friendship and work networks affect individuals’ ability to choose deep and/or surface learning approaches which are statistically associated with learning outcomes and performance. In projects, an individual’s learning curve affects one’s ability to perform the task effectively. Individuals generally attempt to relate ideas together and construct their own meaning, possibly in relation to their own experience (deep approach), and/or try to memorise individual details in the form learning material(s) appear for the purpose of achieving short-term objective(s) (surface approach). This study attempts to model the social aspects relating to choice of either or both approaches, which is important and has several significant implications for designing and impacting workflow, organisation structure and project team dynamics.   Students with competencies in statistical modelling, some programming, social science, learning theories & organisational theory, are encouraged to apply. Top-up scholarship opportunities are available also for excellent candidates.

Additional Information

  • Use of research technique / methodology / technology
  • Potential topics of interest for the research opportunity
  • Current PHD and / or Masters topics
  • Eligibility criteria / candidate profile
  • Scholarship(s) / funding available
  • Top up Scholarship Funding available from CPC

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Social network analysis, social learning, deep learning, surface learning, performance, social psychology, weak ties, structural holes

Opportunity ID

The opportunity ID for this research opportunity is: 1914

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