Automated triaging and answering of pupil questions (MRes Scholarship)

Automated triaging and answering of pupil questions

University of South Wales

Project ID: 20183
Annual Stipend: circa £11 k p.a.
Application Deadline:
3rd June 2018

Here is an exciting opportunity to study a technology that could significantly enhance the way schools interface with their pupils.

This is a funded MRes, including a generous stipend and tuition fees, with well-resourced circumstances for a successful scholarship.

The selected candidate will apply their technical and computational skills to develop an automated triaging system based on the Artificial Intelligence techniques associated with Natural Language Processing. This research opportunity, will allow the student to develop transferable knowledge and skills in this most exciting and active field of computational intelligence.

This Knowledge Economy Skills Scholarship (KESS) project will be held in the Faculty of Computing, Engineering and Science at the University of South Wales. KESS is a programme funded by the European Social Fund (ESF) awarded by the Welsh European Funding Office (WEFO) in the Welsh Government.

The project is backed by InterHigh, a forward looking and technology focused school based in Crickhowell, who are keen to ensure that its pupils get a first-class learning experience.

Programme of research:

InterHigh Education Limited provides online education mediated via a synchronous and asynchronous pedagogy. That is, depending on the activity, pupils will work together and with a teacher within a virtual classroom (synchronous) or on their own at a time that suits them (asynchronous). An innovative digital hub is the platform through which courses are made available worldwide. Currently, students study at home and send queries and comments to the InterHigh staff as required.

InterHigh Education Limited has the opportunity to expand its operation both at home and abroad. However, in order to do this they are reviewing the way in which use is made of new technology. One particular avenue of interest is the development of an automated triaging system that will receive queries and comments from students and process them using Natural Language Processing techniques. The triaging system will then direct the communication to the correct response mechanism that might be a teacher or an automated reply.

One of the issues is that the communications will come from a wide range of students – some who might be using English as a second language – and thus understanding their meaning will not be straightforward. A significant amount of automated analysis of communications and the appropriate responses will be required. It is the purpose of this MRes to investigate how the Natural Language Processing techniques developed within the field of Artificial intelligence can help facilitate this.

Studentship:

The studentship will cover the fees for a 1-year full-time MRes programme and pay a stipend of circa £11k p.a. There is also around £3k project support costs available for consumables, travel, minor equipment, training (including the KESS Grad School) and conference attendance.

The position is available from 1st October 2018.

Eligibility of Student:

To be eligible to hold a KESS studentship, you must:

  • have a home address in the Convergence area (details below)* at the time of registration.
  • have the right to take up paid work in the Convergence area* on completion of the scholarship.
  • be classified by the University as ‘home’ or ‘EU’ for tuition fees purposes according to the University’s guidelines.
  • satisfy University of South Wales’s admissions criteria: see below, qualifications and experience and application process

*The Convergence area covers West Wales and the Valleys, and is made up of the following 15 local authorities: Isle of Anglesey, Gwynedd, Conwy, Denbighshire, Ceredigion, Pembrokeshire, Carmarthenshire, Swansea, Neath Port Talbot, Bridgend, Rhondda Cynon Taf, Merthyr Tydfil, Caerphilly, Blaenau Gwent and Torfaen.

Qualifications and experience:

Eligible applicants will:

  • Have a degree (2i or higher) in an appropriate computing or mathematics based subject
  • Possess a reasonable understanding of artificial intelligence techniques
  • Be highly self-motivated, with capacity to design and implement new computational algorithms
  • Have well-developed and positively collaborative interpersonal skills
  • Have an ability to deliver technical reports and communicate findings

Application Process:

To download an application package, please visit:  Participant Application Package

For any queries on eligibility, please contact:  KESS Team at Research and Innovation Services, University of South Wales: kess@southwales.ac.uk  Tel: 01443 482578

For informal enquiries or further programme information, please contact: Prof. Andrew Ware. (andrew.ware@southwales.ac.uk).

Closing date for applications: midnight Sunday 3rd June 2018

(Interviews will be held w/c 11th  June 2018).