Highlights from OEB 2016

Monday, 19. December 2016

 

by Neil Peirce, Learnovate, Trinity College Dublin, Ireland

 

Image copyright: ICWE GmbH / OEB.

Image copyright: ICWE GmbH / OEB.

This year’s OEB conference in Berlin was one of the largest with 2,200+ attendees, 100+ parallel sessions, and 73 exhibitors. The conference brings together a healthy mix of educators, researchers, government and industry to discuss the key changes in educational technology.

With so much being discussed there was something for everyone, here are a few themes that stood out:

1. AI and Machine Learning are hot topics

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Nell Watson during the plenary debate (“This House believes artificial intelligence (AI) could, should and will replace teachers”). Image copyright: ICWE GmbH / OEB.

The role of these new technologies in education cropped up in many sessions. As well as a lively discussion in the plenary debate, there was increasing talk on:

  • the ethics of these tools (explaining the black box and the need for qualitative data)
  • the inherent human biases we build into them (consciously and unconsciously)
  • their application as educational assistants (chatbots)
  • their ability to supplements educational approaches such as the flipped classroom model

 

2. Supporting corporate learners in a fast-paced world

Although information overload is nothing new, the speed of change for workers is ever increasing. There are increased demands for:

  • New and constantly evolving technical skills
  • Increased complexity
  • Flattening of hierarchies in organisations
  • Increased demand for teamwork and collaborative working skills
  • Pressure to innovate
  • Volatility in the labour market

There are growing challenges for Learning and Development to cultivate agility, improve efficiency, and develop “Learning Organisations”.

This leads us to question should we be creating technical tools to help these workers, or adapting work practices to relieve the pressure?

Either way, we need evidence to inform and guide this discussion. There is a clear role for Learning Analytics (both quantitative and qualitative) in the workplace that can aid in identifying needs, understanding problem areas, and predicting suitable interventions.

3. Education in an uncertain world

What are the implications for educational technology in a politically uncertain world? The impact of Brexit and the election of Donald Trump were mentioned in numerous sessions.

  • How can technology support learning in a post-truth world?

There were no clear answers but Critical Thinking skills will be increasingly important. As will transferrable competencies that aid workers in adapting in a volatile labour market.

4. Future of workplace learning

Whether you agree with the 70:20:10 model or not, it can’t be denied that the majority of workplace learning takes place in an ad hoc manner with limited objective assessment and debatable consistency and quality. Yet investment in Continuing Professional Development is still predominantly focussed on formal coursework and training.

For this to change there are numerous challenges:

·          Finding the right content

o   Self-directed learning (e.g. through MOOCs) needs to be personalised, the sheer range of content is overwhelming. How can we help learners get what they need when they need it?

·          Variability of quality

o   Without consistent evaluation, quality of both internal and open learning resources is highly variable and unpredictable.

·         Credentials and trust

o   With the value of the traditional college degree being questioned (EY, Penguin Random House), how do you trust and endorse a learning path made up of disparate learning resources? One technical solution may lie in blockchain technology as discussed by Donald Clark (see below). Open Badges are also a disruptive force in this area.

 

There are no simple solutions to these challenges, but acknowledging them is the first step!

 

What does this mean for DEVELOP?

 

The key take-away for the DEVELOP project is that it’s still highly relevant. It aims to address the following challenges:

  • The use of AI/machine learning to support workplace learning, with a strong consideration for the ethical and privacy aspects of doing so.
  • Supporting employee professional development in a changing labour market, and in an evidence-based manner.

  • Focussing on competencies that aid adaptability in an uncertain world.

  • The use of personalisation to identify specific learning needs, and appropriate resources.

 

Acknowledgements:

Images used in this article are copyright ICWE GmbH / OEB.

 

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