Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An AI-based Learning Companion Promoting Lifelong Learning Opportunities
  for All   Artifical Intelligence (AI) in Education has great potential for building
more personalised curricula, as well as democratising education worldwide and
creating a Renaissance of new ways of teaching and learning. We believe this is
a crucial moment for setting the foundations of AI in education in the
beginning of this Fourth Industrial Revolution. This report aims to synthesize
how AI might change (and is already changing) how we learn, as well as what
technological features are crucial for these AI systems in education, with the
end goal of starting this pressing dialogue of how the future of AI in
education should unfold, engaging policy makers, engineers, researchers and
obviously, teachers and learners. This report also presents the advances within
the X5GON project, a European H2020 project aimed at building and deploying a
cross-modal, cross-lingual, cross-cultural, cross-domain and cross-site
personalised learning platform for Open Educational Resources (OER).

30
The categories of this paper are: q-alg
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
14
The categories of this paper are: math-ph
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
16
The categories of this paper are: stat