Supporting learners’ successful transitions throughout the health professions education continuum with the meaningful use of technology

Date:                    Sunday 25th August

Half Day:              1330-1630

Level:                    Intermediate


  1. Richard Fuller, Leeds Institute of Medical Education, University of Leeds, UK
  2. Viktoria Joyes, University of Liverpool, UK
  3. Vishna Nadarajah, International Medical University, Malaysia
  4. Jennifer Hallam, Leeds Institute of Medical Education, University of Leeds, UK

Summary of theme and why it is important:  We continue to see major technology breakthroughs in biotechnology, computing, artificial intelligence and the Internet of Things, but what does any of this mean for education?
The possibilities of Universities, their students and faculty, all connected by mobile devices, presents exciting opportunities for educational innovation. New uses of technology (and its’ resultant data) allow design of highly adaptive learning, assessment and feedback. Previously unimaginable possibilities are now on the horizon for increased personalisation of learning experiences, assessment and even curricula.
Yet these opportunities are some of our most challenging ‘threshold concepts’ – with the power to innovate and transform learning, but with complex ethical and academic challenges in avoiding harm to learning through data ‘misuse’ (Lawson et al 2016).
This highly interactive workshop will explore conceptual frameworks of how using technology-captured data can help members of healthcare faculty understand student learning behaviours.  Models of self-regulation will be applied to explore how technology can be used ‘diagnostically’ to track learner growth and development, in both academic and non-academic domains, with implications for practices related to both sustainable assessment and behavioural interventions.
Drawing on examples from different international and cultural perspectives, workshop participants will gain confidence in identifying learners needing extra support (e.g. around key transition points) across complex health care educational programmes.
Participants will have the opportunity to explore interventions that provide differential, personalised support for these learners, and to think about generating potential tailored take-home solutions for their own institutions.
Discussion will focus on the danger that misapplication of collected data could lead to negative consequences for learners and teachers, as education priorities are potentially skewed by ‘predictive’ analytics.

Who should participate in the Pre-Conference Workshop?  This workshop has particular significance for those responsible for the identification of learners in need of additional support, remediation and progression decisions.  The workshop will also support colleagues who wish to make more effective use of technology generated ‘learning data’.

What will they gain from participating?  Participants will be encouraged to focus on how they can use their own existing institutional data to identify learners ‘at risk’ of failing to progress.  The workshop supports participants in gaining confidence in applying the theories of self-regulated learning to understand the behaviours of these learners and apply behaviour change models to design a ‘toolkit’ of interventions

Cost: Euros 90 (includes coffee)

PLEASE NOTE: Pre-conference Workshop participants must also register for AMEE 2019 and pay the conference fee.


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