Introduction to the Higher Education Statistics Agency (HESA) data from a researcher’s perspective

Details: 

 

Applications for this course are now closed.

26 January 2016 
Edinburgh Training and Conference Venue

This is a one-day hands-on training workshop led by Professor Cristina Iannelli and Dr Adriana Duta from University of Edinburgh.

Course Details

This course will provide an introduction to the use of the Higher Education Statistics Agency (HESA) student data for research purposes. In particular, issues of data availability and supporting material, data coding and analysis will be discussed. The course will include general information on the application process (including sample definition and selection of variables), practical examples of research carried out using the HESA student data and discuss potential for future research. Based on the instructors’ experience, the course will highlight the benefits and limitations in the use of the HESA student data that will guide participants in their own future application and definition of research topic. Furthermore, the course will provide hands-on experience in exploring the HESA student data by using a synthetic version of individual-level data drawn from work conducted within the AQMeN Education research programme. Basic knowledge in STATA or SPSS is needed.

There will also be a lunchtime seminar as part of this event on Social inequalities in graduates' labour market outcomes in the UK: the role of regional job opportunities. Delegates on the training course are automatically registered for this seminar.

Objectives

  • To offer an introduction to the use of the Higher Education Statistics Agency (HESA) student data in research, covering various steps from data application and access to analysis.

Learning Outcomes
By the end of the workshop attendees will be able to:

  • Explore the data collection and variables available in the Higher Education Statistics Agency (HESA) student data
  • Develop a data application
  • Carry out some analyses of the data using a synthetic version of the data generated within the AQMeN Education research programme
  • Identify advantages and disadvantages in using the HESA student data

Criteria for selection
Participants must have a basic knowledge of either STATA or SPSS. This course is addressed to researchers (from academia and beyond) who would like to know more about the process of gaining access to the HESA student data or have an interest in working with these data in the future.

About the Trainers
Cristina Iannelli is Professor of Education and Social Stratification and Co-Director of AQMeN. Within the centre she is also leader of the 'Education and Social Stratification' research strand. Cristina’s research focuses mainly on topics such as social inequalities in education and the labour market, social mobility, youth transitions and her research has been published in top sociological journals in these fields. She has a long-standing interest in applying quantitative methods and she has rich experience with using large-scale surveys and administrative data, including Higher Education Statistics Agency (HESA) Student Records and Destination of Leavers from Higher Education (DLHE) longitudinal data.

Adriana Duta is an AQMeN Research Fellow working in Education and Social Stratification. She received her PhD degree in Social Statistics and Demography from the University of Southampton where she was also involved in teaching introductory quantitative methods. Her PhD was funded through an ESRC/Advanced Quantitative Methods scholarship and she has extensively used various quantitative methods, relying on different large-scale cross-sectional and longitudinal datasets. 'Adriana has a strong research interest in social stratification, particularly in understanding how social inequalities in education, labour market outcomes and family behaviour unfold over the life course. Over the last year she has worked with data from the Higher Education Statistics Agency (HESA) Destination of Leavers from Higher Education (DLHE) longitudinal data.

Course costs:
This training course is offered free of charge to doctoral students registered on a social science degree programme at a Scottish University or to doctoral students studying at an ESRC-funded Doctoral Training Centre.

Remaining places will be open to others for a fee:

Doctoral students studying at a non-DTC institution £30
Academic staff, ESRC funded researchers and UK registered charitable organisations £60
Others £250

Please note that AQMeN can only accept payment for training via the University of Edinburgh ePay system.  We are unable to issue invoices or accept cheques for payment. All payments must be received within 14 days of a place being offered otherwise the place will be released. Payment should not be made until you have received confirmation that you have been allocated a place on the course.

Application process:
There are 18 places available on the course and places will be allocated following a process of application.

To apply for this event, a completed on-line application form should be submitted by 12 noon on 20th January 2017.  Successful applicants will be notified by 23rd January 2017.

Travel and accommodation bursaries:
Doctoral students registered on a social science degree programme at a Scottish university or at an ESRC-funded DTC may be eligible to claim travel and/or accommodation costs to attend.

In order to be eligible for a bursary you must reside outside Edinburgh and attend a university outside Edinburgh. Reimbursement can only take place if you follow the reimbursement process detailed below and bursaries for eligible students will be capped at the following rates:

Travel time (by rail) from Edinburgh Maximum Travel Contribution
Accommodation Contribution
Up to 1 hour (travelling each day)    2 return trips @£25/trip = £50 NIL
Up to 1 hour(with accomodation) 1 return trip @£25/trip = £25 Up to 1 nights accomodation at maximum £60 per night
Up to 2 hours 1 return trip @£50/trip = £50 Up to 1 nights accomodation at maximum £60 per night
Over 2 hours 1 return trip @£100/trip = £100    Up to 1 nights accomodation at maximum £60 per night

Reimbursement process:
Students are responsible for arranging travel and/or accommodation (if applicable) themselves and will only be reimbursed upon presentation of original receipts (no photocopies or credit card receipts will be accepted) and completion of the relevant expense claim form which will be provided post-event.

AQMeN will not reimburse the following costs (unless agreed prior to the event):

  • Mileage
  • First class travel
  • Meals or room service
  • Inter-city travel (e.g. buses to and from event venue)
  • Taxi fares
  • Credit card fees
  • Sundries (e.g.wireless internet access or newspapers at accommodation)

All expense claims and receipts must be received by the AQMeN office no later than 2 weeks following the last day of the event in order to be eligible for reimbursement.

Cancellation and Non-attendance:
By applying for this course, you are expected to attend for the full duration.  Failure to attend all sessions (unless by prior agreement with the AQMeN core team) may result in a charge of £50 per day of the course missed, non-reimbursement of expenses and ineligibility to be  considered for future AQMeN training courses and events.

Non-paying delegates
If after receiving an allocated place on the course you are no longer able to attend, you must notify AQMeN as soon as possible to allow the place to be offered to someone on the waiting list.  Failure to do so may result in a charge of £50 per day of the course, non-reimbursement of expenses and ineligibility to be  considered for future AQMeN training courses and events.

Paying delegates
Course fees are non-refundable.  In exceptional cirumstances a refund may by permitted at the discretion of the AQMeN Research and Development Manager.

Contact:
If you have any questions regarding the course, please feel free to contact events@aqmen.ac.uk or + 44 (0) 131 650 2105

Date: 
Thursday, January 26, 2017 - 09:00 to 17:00
Organiser: 
AQMeN
Location: 
Edinburgh
Venue: 
Edinburgh Training & Conference Venue

Research Strand: