In this session, students are challenged to design an App which utilises AI and helps to meet a current need in education.

1. Unleashing the Power of
AI in Education
Dr James Stanfield
Tuesday 19th November 2019

2. Plan of Action
Part I: SOLO Taxonomy
Part II: UK & OECD Findings
Part III: AI in education

3. Part I SOLO Taxonomy

4. For additional
materials refer to
Pam Hook’s website

5. Identified the following trends:
• Collaborative use is more effective than individual use
• short but focused use is most effective
• best used as a supplement rather than a
replacement.
• tested gains are greater in maths and science
• Remedial and tutorial use is useful for lower attaining
pupils, those with special educational needs or those
from disadvantaged backgrounds in providing
intensive support to enable them to catch up with
their peers.
The Impact of Digital Technology on Learning: A Summary, Education
Endowment Foundation (2012)
Part II – UK & OECD Findings

6. Recommendations:
• The rationale for the impact of digital technology on teaching
and learning needs to be clear: Will learners work more
efficiently, more effectively, more intensively?
• The role of technology in learning should be identified: Will it
help learners gain access to learning content, to teachers or to
peers?
• Technology should support collaboration and effective
interaction – eg. to support discussion, interaction and
feedback.
• Teachers and/or learners should be supported in developing
their use of digital technology to ensure it improves learning.
On-going professional development and support to evaluate
the impact on learning is likely to be required.

7. In total there are 3,392,100 computers in UK
classrooms in 2017. There are 1,543,700 in
primary schools and 1,848,400 in secondary
schools. The average primary school has 69.8
computers and the average secondary school
has 430.7. Source: BESA/C3 Education (2017).

8. Findings:
• Students who use computers very frequently at school get worse
results
• Students who use computers moderately at school, such as once
or twice a week, have "somewhat better learning outcomes" than
students who use computers rarely
• The results show "no appreciable improvements" in reading,
mathematics or science in the countries that had invested heavily
in information technology
• High achieving school systems such as South Korea and Shanghai in
China have lower levels of computer use in school
• Singapore, with only a moderate use of technology in school, is top
for digital skills.
"One of the most disappointing findings of the report is that the
socio-economic divide between students is not narrowed by
technology, perhaps even amplified," said Mr Schleicher.

10. BIG QUESTION:
Why can algorithms learn
much faster and more
accurately than we can?
Please present your answer without using any
words!
Part III AI In Education

12. Rose Luckin is Professor of Learner Centred
Design at the UCL Knowledge Lab in London.
Her research involves the design and
evaluation of educational technology using
theories from the learning sciences and
techniques from Artificial Intelligence (AI).
She has a particular interest in using AI to
open up the 'black box' of learning to show
teachers and students the detail of their
progress intellectually, emotionally and
socially.

14. ALGORITHM
A defined list of steps for solving a problem. A computer
program can be viewed as an elaborate algorithm. In AI, an
algorithm is usually a small procedure that solves a
recurrent problem.
MACHINE LEARNING
Computer systems that learn from data, enabling them to
make increasingly better predictions.
DECISION THEORY
The mathematical study of strategies for optimal decision
making between options involving different risks or
expectations of gain or loss depending on the outcome.

15. AIEd offers the possibility of learning that is more personalised,
flexible, inclusive, and engaging. It can provide teachers and
learners with the tools that allow us to respond not only to
what is being learnt, but also to how it is being learnt, and how
the student feels.
Drawing on the power of both human and artificial
intelligence, we will lessen achievement gaps, address
teacher retention and development, and equip parents
to better support their children’s (and their own) learning.
we do not see a future in which AIEd replaces teachers. What
we do see is a future in which the role of the teacher continues
to evolve and is eventually transformed; one where their
time is used more effectively and efficiently, and where their
expertise is better deployed, leveraged, and augmented.

16. We define AI as computer systems that have been designed to
interact with the world through capabilities (for example, visual
perception and speech recognition) and intelligent behaviours
(for example, assessing the available information and then
taking the most sensible action to achieve a stated goal) that
we would think of as essentially human.

17. AIEd is a powerful tool to open up the ‘black box of learning,’ giving
us a deeper understanding of how learning happens (for example,
how it is influenced by the learner’s socio-economic and physical
context, or by technology).
These understandings may then be applied to the development of
future AIEd software and, importantly, can also inform approaches
to learning that do not involve technology.
For example, AIEd can help us see and understand the micro-steps
that learners go through in learning physics, or the common
misconceptions that arise. These understandings can then be used
to good effect by classroom teachers.

18. ADAPTIVE LEARNING ENVIRONMENTS
A digital learning environment that
adapts teaching and learning
approaches and materials to the
capabilities and needs of individual
learners.

19. There are three key models at the heart of AIEd:
• the pedagogical model,
• the domain model, and
• the learner model.
Take the example of an AIEd system that is designed to provide
appropriate individualised feedback to a student. Achieving this
requires that the AIEd system knows something about:
• Effective approaches to teaching (which is represented in a
pedagogical model)
• The subject being learned (represented in the domain
model)
• The student (represented in the learner model)
MODELS
These represent
something from
the real world in a
computer system
or process, to assist
calculations and
predictions.

20. In addition to the learner, pedagogical,
and domain models, AIEd researchers
have also developed models that
represent the social, emotional, and
meta-cognitive aspects of learning. This
allows AIEd systems to accommodate
the full range of factors that influence
learning.

21. • an intelligent, personal tutor for
every learner
• intelligent support for
collaborative learning
• Intelligent virtual reality to
support learning in authentic
environments
What AIEd can offer
learning right now?

22. Help learners gain 21st
century skills
Two challenges that need to be addressed:
1 We must develop reliable and valid indicators that will allow
us to track learner progress on all the skills and capabilities
such as creativity and curiosity.
2 We need a better understanding of the most effective
teaching approaches and the learning contexts that allow these
skills to be developed.
The next phase of AIEd

23. AIEd will support a Renaissance in Assessment
AIEd will provide just-in-time assessments to shape learning
AIEd will provide new insights into how learning is progressing
AIEd will help us move beyond ‘stop-and-test’
AIEd will give us lifelong learning partners

24. How AIEd can help us
respond to the biggest
unsolved issues in
education?
• Tackling achievement gaps
• Developing teacher expertise, addressing teacher retention,
and providing respite where teacher shortages are acute

26. BIG CHALLENGE
Taking into account your
own interests in
education, design an App
which utilises AI and
which helps to meet a
current need

27. #edu8213