22 January 2018 HEFCE open event “Using data to increase learning gains and teaching excellence”

With the Teaching Excellence Framework being implemented across England, a lot of higher education institutions have started to ask questions about what it means to be “excellent” in teaching. In particular, with the rich and complex data that all educational institutions gather that could potentially capture learning gains, what do we actually know about our students’ learning journeys? What kinds of data could be used to infer whether our students are actually making affective (e.g., motivation), behavioural (e.g., engagement), and/or cognitive learning gains? Please join us on  22 January 2018 in lovely Milton Keynes at a free OU- and HEFCE-supported event on Using data to increase learning gains and teaching excellence.

This open event brings together nearly two and half years of research on learning gains and teaching excellence, across numerous institutions, also including  University of Surrey, Oxford Brookes University, and The Open University (http://abclearninggains.com). This one-day event is a great opportunity to share expertise, research insights, and policy insights. If you want to contribute and share your research or practice in form of a lightning presentation (1-2 minutes quick presentation), please let us know your preliminary title and 100 words summary, and send this to jekaterina.rogaten@open.ac.uk.

You can register for this free event here. Please note that places are limited and will be allocated on a first-come-first-served basis. The live-stream of the event will become available here.

Confirmed agenda

10.30-11.00 Welcome and Coffee

11.00-11.30 Lightning presentations by participants, outlining insights about learning gains

1130-1300 Insights from the ABC-Learning Gains project

  • Dr Jekaterina Rogaten (OU): Reviewing affective, behavioural and cognitive learning gains in higher education of 54 learning gains studies
  • Prof Bart Rienties & Dr Jekaterina Rogaten (OU): Are assessment scores good proxies of estimating learning gains: a large-scale study amongst humanities and science students
  • Prof Rhona Sharpe (University of Surrey) & Dr Simon Cross (OU): Insights from 45 qualitative interviews with different learning gain paths of high and low achievers
  • Dr Ian Scott (Oxford Brookes) & Dr Simon Lygo-Baker (OU): Making sense of learning trajectories: a qualitative perspective

13.00-14.00 Lunch

14.00-15.00 Measuring learning gains with (psychometric) questionnaires

  • Dr Sonia Ilie, Prof Jan Vermunt, Prof Anna Vignoles (University of Cambridge, UK): Learning gain: from concept to measurement
  • Dr Fabio Arico (University of East Anglia): Learning Gain and Confidence Gain Through Peer-instruction: the role of pedagogical design
  • Dr Paul Mcdermott & Dr Robert Jenkins (University of East Anglia): A Methodology that Makes Self-Assessment an Implicit Part of the Answering Process

15.00-15.45 Measuring employability learning gains

  • Dr Heike Behle (University of Warwick): Measuring employability gain in Higher Education. A case study using R2 Strengths
  • Fiona Cobb, Dr Bob Gilworth, David Winter (University of London): Careers Registration Learning Gain project

15.45-16.30 Open discussion how to make data effective for learning gains and teaching excellence


Venue – Milton Keynes: Open University UK, Jennie Lee Building, Meeting Room 1, MK7 6AA, Milton Keynes 

A multi-level longitudinal analysis of 80,000 online learners: Affective-Behaviour-Cognition models of learning gains

Conference of the EARLI SIG 17

Qualitative and Quantitative Approaches to Research on Learning and Instruction 17-19 August 2016 Maastricht University, Maastricht, the Netherlands.

Authors: Jekaterina Rogaten, Bart Rienties, Denise Whitelock, Simon J. Cross and Allison Littlejohn.

Open University, UK

One of the challenges facing higher education is understanding what counts for an excellent educational outcome. Historically academic performance was a variable of choice for measuring ‘excellence’ in education, but more recently a concept of learning gain, which can be defined as change in knowledge, skills and personal development across time (e.g., Andrews et al., 2011; Boyas et al., 2012) gained momentum. Educational research also mainly looked at cognitive gain largely ignoring affective changes (attitude) and behaviour (Tempelaar et al., 2015a). Current research aims to address this gap by developing and testing an Affective-Behaviour-Cognition model of learning gains using longitudinal multilevel modelling. The learner-generated affective-behaviour-cognition data was retrieved from university database for 80,000+ undergraduate students who started their degree in autumn 2013/14. The preliminary multilevel modelling revealed that cognitive and behaviour learning gains are well explained by the hypothesised Affective-Behaviour-Cognition model, whereas the more complex affective learning gains model needs further refinement. The main strength of this research is that approach used is a practical and scalable solution that could be used by teachers, learners, higher education institutions and the sector as a whole in facilitating students’ learning gains by further improving and personalising provision of higher education.