A presentation at the Committee of Regions event for the Finnish EU-presidency. Panel discussion "Next Challenge: The Impact of Artificial Intelligence on education and knowledge creation"
1. The European Commission’s
science and knowledge service
Joint Research Centre
Riina Vuorikari, PhD
Unit Human Capital & Employment, Directorate Innovation and Growth
European Commission, DG Joint Research Centre
To thrive in an AI-rich world:
how EU could help building
student and teacher capacities?
3. European Commission: DG JRC (Joint Research Centre)
• Internal science and knowledge service
of the European Commission
• Policy neutral: has no policy agenda of
its own
• JRC mission is to support EU policies
with independent evidence throughout
the whole policy cycle
• Work for more than 20 EC policy
departments
Riina.Vuorikari@ec.europa.eu
@vuorikari
4. AI will change occupations, automate tasks and
processes.
Source: adapted from OECD, 2019 TALIS, Table I.2.27
Average number of hours teachers in EU-22 report having spent on the following activities during the most recent
complete calendar week
What about that of a teacher?
What are the activities
that might be
complemented,
augmented,
substituted or
even made obsolete
by AI?
5. AI in Education: What challenges in education are we solving?
Might we “routinise” old institutional problems or fix them?
The latest OECD data show a worrying trend in teachers’ time
allocation in an average lesson since 2013:
• An overall decline in time spent on actual teaching and learning within
single lessons (16/20 EU countries*)
• Time spent on administrative tasks (including communication,
paperwork and other clerical duties) has gone up in 12 EU countries.
Source: TALIS, OECD, 2019, Table I.2.17
* Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, England (UK), Finland, Flemish Comm.
(Belgium), France, Italy, Latvia, Netherlands, Portugal, Romania, Slovak Republic, Spain
6. What are the real challenges to solve to help learners? Can AI technologies
help teachers and education systems in delivering quality education?
• When teaching larger classes teachers tend to spend less time in teaching
than other tasks
• 30% of teachers have low efficacy in motivating student learning
• 27% teach in classes with more than 10% of special needs students (e.g.
over 50% in BE)
• 20% of teachers have more than 10% of students whose first language is different
from the language of instruction (e.g. over 40% in Austria and Sweden)
BUT only 41% very/well prepared for the use of ICT for teaching (e.g. 20% in FI and AT)
Source: Adapted for EU from OECD (2019), TALIS 2018 Results (Volume I): Teachers and School Leaders as Lifelong Learners
7. AI in Education: Teaching and learning with AI.
Teacher-facing AI can complement/augment/substitute
Teaching methods and delivery, lesson planning
Classroom management
Assessment, evaluation and diagnosis
Learner-facing AI can complement/augment
Individual's learning and development
Affective-motivational disposition (e.g. strategies
to motivate learners, develop socio-emotional skills)
Education System-facing AI complement/substitute/make
obsolete
9. Create a common vision for AI in Education in Europe &
Allocate resources to build AI technologies that help teachers and
learners
A Low hanging fruit driven by supply-side?
AI-based personalised content platforms
& intelligent tutoring systems with a
half-hearted visions of learning & pedagogy
What about a vision of AI in education
for empowering learning and the individual?
10. On-going work at JRC: Co-designing AI empowered tools with
teachers and for teachers
Guidelines on how to involve learners, teachers, school heads and local
education authorities in co-designing of AI-based tools with features t h e y
find useful for their own use.
How to offer training and otherwise support them so that they can
effectively use these tools in their learning and teaching.
Ethics of AI in education
At all levels, policies of ethics and data protection should support
learners, teachers, school principals, etc. to make informed decisions
about the use of their data within their institution but also outside of it
(e.g. game-based learning, informal learning)