Organisers:

Kaska Porayska-Pomsta, Rose Luckin, Manolis Mavrikis, Mutlu Cukurova,  [1]

1 University College London

Introduction

The application of artificial intelligence to education (AIEd) has been the subject of academic research for more than 30 years, a period during which much technical progress has been made, but few in-roads into mainstream education have been achieved. With the upsurge of interest in AI in general and increasingly in AI for education in particular, what role could and should the AIED research community play?

 

In this workshop we will explore ‘how we get to next’ when it comes to AI for education (a phrase borrowed from https://howwegettonext.com). We will discuss the challenges and opportunities and propose some possible ways forward.

Contributors include:

Wayne Holmes and Bart Rienties[2]

Daniel Spikol [3]

Vincent Aleven [4]

Laurie Forcier [5]

2 The Open University, Milton Keynes

3 Malmö University, Sweden

4 Carnegie Mellon University, USA

5 Pearson, UK

The workshop proposers have a wealth of experience and expertise in the field of AIEd and each will present their perspectives on the opportunities, challenges and recommendations for scaling up. In addition, we invite papers from others who are motivated to engage in this agenda. The workshop will be a full day session with short presentations in the morning, followed by an activity to collate all the ideas presented. The afternoon session will consist of a moderated discussion and a writing session to produce a set of recommendations that can be taken forward by the authors. A publication from the workshop will be styled as a public communication piece sponsored by XXX (large corporate OR UCL EDUCATE, to be decided).

The opportunities of AIED

As a community, AIEd researchers have already demonstrated that we can:

  • Assess and tutor one to one accurately and effectively;
  • Build dynamic models of learner cognitive development and non-cognitive development e.g. metacognition, motivation to enable personal scaffolding;
  • Open up the ‘black box’ of learning for students and teachers;
  • Support collaborative learning through facilitating group formation, facilitating the process of collaboration, provide virtual collaborators, provide intelligent moderation
  • Provide cultural modeling;
  • Build intelligent VR and AR for authentic learning environments;
  • Support the development of 21 century skills.

 

In addition to the current state of the Art, we also know that AIEd has the potential to be scaled up and to radically change education, in particular, the way assessment is done; to support social mobility and address the achievement gap. There is enormous potential to support learners holistically and in a context sensitive way, and we can address the chronic and acute teacher shortages across the globe.

 

Next Steps?

So how do we unleash AIEd to the benefit of all teachers and learners?

Suggestions to date include:

  1. Learning from the approach that jump-started driverless cars

In 2005, the US Defense Advanced Research Projects Agency (DARPA) offered $2M for the team that developed a self-driving car that could navigate a 142-mile route. Five vehicles completed the course. The winning team was led by Stanford University’s Sebastian Thrun, who went on to lead Google’s autonomous vehicles team and, when there, began ‘hoovering up’ the best engineers from the DARPA challenges.

Could well-funded, global challenge prizes that pose complex learning problems, and then reward those who provide the most exciting and effective AIEd solutions?

  1. Create centres of independent interdisciplinary expertise in AIEd, funded long term and focused on delivering real-world capabilities. What could we achieve if the improvement of our schools, universities, and community colleges was supported with properly researched and comprehensively evaluated AIEd??
  2. System change: AIEd will need to function effectively in blended learning spaces where digital technologies and traditional classroom activities complement each other. This means addressing the ‘messiness’ of real classrooms, universities, or workplace- learning environments, and involving teachers and learners in a co-design process. What more could we achieve if we focused on designing and describing how AIEd concretely fits within the lived experience of real learners and educators?

If you would like to participate in this workshop please contact Kaska Porayska-Pomsta,  <k.porayska-pomsta@ucl.ac.uk>

 

 

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