PhD opening: Scaffolding Citizen Science with Learning Analytics

3yr PhD grant: Scaffolding Citizen Science with Learning Analytics

A PhD funded by the UK Open University’s £1M Wolfson OpenScience Laboratory
in collaboration with the Knowledge Media Institute (KMI)

3 year fully-funded PhD (Oct. 2012-Sept.2015)
Stipend: £40,770 (£13,590/year tax free)
Supervisors: Simon Buckingham Shum and Anna De Liddo

This PhD project is a unique opportunity for a highly motivated candidate. The Open University is developing the OpenScience Laboratory, an international virtual laboratory for practical science teaching, funded through a £1m grant awarded by the Wolfson Foundation. You will be working with other OpenScience PhD students on this ground-breaking project, as well joining the wider doctoral communities in learning analytics, knowledge media, educational technology, computing and science education.

The Citizen Science Challenge: Fostering Scientific Communication. A key driver for citizen science is participants’ passion and curiosity to engage with scientific questions. Often, however, citizens are deployed in projects with professional scientists in the roles of simple data gatherers/sensors, and classification. A more ambitious Open Science+Open Learning vision, however, sees citizens learning about and then engaging with other aspects of the scientific ecosystem. The specific focus of this PhD will be to break new ground in learning technologies to promote reflecting, thinking and communicating scientifically in the emerging Science 2.0 landscape.

The Scale Challenge: Timely Feedback. It is widely acknowledged that the global need for learning cannot be met by conventional bricks+mortar educational institutions, with expert mentors providing personal attention. The only way that we can collectively learn fast enough to tackle the planetary-scale challenges facing us is through the judicious use of learning technologies, amplifying and amplified by human interaction. Timely feedback to learners is known to be critical for rapid progress. This makes the use of Learning Analytics that provide automated feedback – to be reflected on, discussed and challenged by learners – a key piece of the strategy for Web-scale deep learning infrastructures.

The Convergence: This PhD will use the world class facilities of the Wolfson OpenScience Lab, coupled with the emerging tools of learning analytics, to tackle a specific aspect of the citizen science challenge introduced above: Can we develop citizen scientists’ everyday language and ways of thinking and writing, into scientific discourse? The strategy here is to help citizens engage firstly in science blogging (a semiformal genre of reflective writing), and then in longer forms of writing, such as a report on their use of the Open Science Lab. Discourse-centric learning analytics will provide feedback on the extent to which they are identifying missing knowledge, and making evidence based arguments and claims, which are the hallmarks of scientific discourse. In order to answer the core question, you will be integrating discourse analytics into the KMI tools, so that the analytics can be rendered back to users in intuitive ways which will be systematically evaluated. An interest in social computing might further focus on how citizens can be helped to share and discuss the analytics they are receiving, building a collective resource for learning about forms of Science 2.0 collaboration and discourse.

Technologies. The PhD will build on existing OU research platforms for collective sensemaking (Cohere, Evidence Hub, SocialLearn, EnquiryBlogger), and the work of Ágnes Sándor at Xerox, on the Xerox Incremental Parser (XIP) whose rhetorical analysis is capable of identifying the forms of writing that are ‘signatures’ of scientific discourse.

The Successful Candidate will bring programming skills enabling rapid Web development  (KMI tools use PHP/JavaScript/SQL). You will ideally already have a solid grounding in one or more relevant disciplines, e.g. HCI, CSCW, Learning Sciences, Web Semantics, Computational Linguistics, Discourse Analysis. Depending on your skillset, in your application you might propose shifting the emphasis to play to your strengths.

Supervision Team. This PhD will be led by Simon Buckingham Shum, who is actively researching Learning Analytics and Computer-Supported Argumentation, Anna De Liddo who works closely with Simon, with computational linguistics input from Ágnes Sándor at Xerox Research Centre Europe (Grenoble). You will also be part of the newly formed global virtual lab for Learning Analytics students, SoLAR Storm.

How to apply: DEADLINE 3 AUGUST

Please submit an outline document (max 2 pages) with your application. You need to demonstrate that you have grasped the challenge, and can relate this to the core ideas in the publications below. If you can add a new perspective from your own or others’ work even better. This is fundamentally a test of your ability to quickly marshall the arguments and write clearly, so don’t worry that this will be cast in stone. You will spend the first 9 months of the PhD developing a detailed proposal that you must defend in order to continue.

Follow the application details on the OpenScience website. You may call Simon on +44 (0)770 212 5734 or Anna De Liddo +44 (0)1908 653591 for an informal chat if you wish, or email s.buckingham.shum <usual sign> gmail dot com or a.deliddo <usual sign> gmail dot com

Key References

Cohere + XIP integration:

De Liddo, A., Sándor, Á. and Buckingham Shum, S. (2012). Contested Collective Intelligence: Rationale, Technologies, and a Human-Machine Annotation Study. Computer Supported Cooperative Work, 21, (4-5), pp. 417-448, DOI: 10.1007/s10606-011-9155-x. Open Access Eprint:

KMI platforms for collective sensemaking:

Buckingham Shum, S. (2008). Cohere: Towards Web 2.0 Argumentation. Proc. COMMA’08: 2nd International Conference on Computational Models of Argument, 28-30 May 2008, Toulouse, France. IOS Press. Open Access Eprint:

De Liddo, A., Sándor, Á. and Buckingham Shum, S., McAndrew, P. and Farrow, R. (2012). The open education evidence hub: a collective intelligence tool for evidence based policy. Proc. Cambridge 2012: Joint OER12 and OpenCourseWare Consortium Global 2012 Conference, 16 – 18 April 2012, Cambridge, UK. Open Access Eprint:

Ferguson, R. and Buckingham Shum, S. (2012). Towards a Social Learning Space for Open Educational Resources. In: Okada, A., Connolly, T. and Scott, P. (Eds.), Collaborative Learning 2.0: Open Educational Resources. Hershey, PA: IGI Global, pp. 309–327. Open Access Eprint:

Ferguson, R., Buckingham Shum, S. and Deakin Crick, R. (2011). EnquiryBlogger – Using widgets to support awareness and reflection in a PLE setting. In W. Reinhardt, & T. D. Ullmann (Eds.), 1st Workshop on Awareness and Reflection in Personal Learning Environments, PLE 2011 Conference, UK. Open Access Eprint:


Lisacek, F., Chichester, C., Kaplan, A. and  Sándor, Á. (2005). Discovering Paradigm Shift Patterns in Biomedical Abstracts: Application to Neurodegenerative Diseases. First International Symposium on Semantic Mining in Biomedicine, Cambridge, UK April 11-13. Open Access Eprint:

Sándor, Á. (2007). Modeling Metadiscourse Conveying the Author’s Rhetorical Strategy in Biomedical Research Abstracts. Revue Française de Linguistique Appliquée, Vol. XII, (2), pp. 97-109. Open Access Eprint:


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