👂🎴 🕸️
This
How
To
aims
to
demonstrate
how
anyone
''
including
teachers
''
parents
''
and
students
''
can
create
their
own
Personal
Primer
-
a
book
-
like
educational
instrument
that
combines
digital
education
objectives
.<
br
><
br
>
The
session
will
cover
existing
Primer
prototypes
and
off
-
the
-
shelf
components
''
such
as
Raspberry
Pi
Zero
and
e
-
ink
display
''
needed
to
build
the
Primer
.
Participants
will
learn
how
to
design
and
deploy
personalized
educational
instruments
that
differ
from
smartphones
and
tablets
.
The
Goal
is
to
accompany
the
learner
from
the
original
state
of
„
not
-
knowing
“
(
e
.
g
.
analphabetism
)
to
state
where
she
/
he
is
able
to
build
another
copy
of
the
Primer
.<
br
>
<
span
style
=
„
color
:
#
333333
;
font
-
family
:
Lucida
Grande
''
Bitstream
Vera
Sans
''
Verdana
;
“
><
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style
=
„
font
-
size
:
18px
;
background
-
color
:
#
ffe6ee
;
“
>
Education
-
with
-
digital
is
concerned
with
exploitation
and
integration
of
digital
media
and
digital
tools
within
the
framework
of
generic
teaching
''
learning
''
or
cognition
-
enhancing
process
.
span
>
span
>
Education
-
with
digital
:
increase
digital
competences
of
older
students
so
that
they
are
able
to
repair
or
ameliorate
existing
Primers
or
construct
their
new
copies
.<
br
>
AIED
some
text
here
Making
:::
Encounter
0
<
br
>
Can
machines
teach
?<
br
>
Human
–
Machine
Peer
Learning
(
HMPL
)
is
a
proposal
that
is
positioned
at
the
very
frontier
between
educational
''
cognitive
''
and
computer
sciences
.
HMPL
'
s
core
precepts
which
I
introduced
in
my
2022
and
2023
papers
are
simple
:
<
br
/><
br
/><
div
style
=
„
text
-
align
:
center
;
“
>
Humans
and
machines
can
learn
together
.
div
><
div
style
=
„
text
-
align
:
center
;
“
>
Humans
and
machines
can
learn
from
each
other
.
div
>
<
div
style
=
„
text
-
align
:
center
;
“
>
Note
that
HMPL
is
more
than
a
theoretical
concept
.
It
is
happening
.
Here
.
Now
.
div
><
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style
=
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:
center
;
“
> 
div
><
div
style
=
„
text
-
align
:
center
;
“
>
Humanity
teaches
the
big
&
mighty
ones
(
e
.
g
.
GPT4
''
DALL
-
e
3
)
and
big
&
mighty
ones
provide
educational
&
cognitive
services
in
return
. 
div
><
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=
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:
center
;
“
> 
div
><
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style
=
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text
-
align
:
center
;
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>
But
what
about
the
„
small
“
ones
''
the
„
adaptive
“
ones
''
the
„
personalized
“
ones
''
the
embedded
(
or
embooked
?)
ones
?
div
>
<
p
class
=
„
fragment
“
>
0
.
Can
an
entity
E
be
considered
a
„
peer
“
even
if
it
does
not
have
a
physical
body
?
p
><
p
class
=
„
fragment
“
>
1
.
Can
AI
ever
be
a
„
peer
“
to
a
human
being
or
is
it
a
fallacy
to
believe
so
?
p
><
p
class
=
„
fragment
“
>
2
.
Should
an
AI
communicate
what
it
is
doing
(
e
.
g
.
showing
👂
when
listening
)
or
what
it
expects
the
human
peer
to
do
(
e
.
g
.
show
👄
when
H
should
speak
)
?
p
><
p
class
=
„
fragment
“
>
3
.
Can
You
imagine
a
competence
X
which
is
being
simultaneously
acquired
by
a
human
H
and
a
machine
M
within
the
context
of
their
common
mutual
encounter
?
p
><
p
class
=
„
fragment
“
>
4
.
Can
You
imagine
a
competence
A
transmitted
from
H
to
M
during
the
same
encounter
whereby
competence
B
is
transferred
from
M
to
H
?
p
><
p
class
=
„
fragment
“
>
5
.
What
other
question
concerning
the
human
-
machine
education
should
also
be
asked
?
p
>
<
div
style
=
„
text
-
align
:
center
;
“
>
Someone
willing
to
join
me
on
a
journey
towards
div
><
div
style
=
„
text
-
align
:
center
;
“
><
strong
>
„
Encounter
“
:
a
journal
on
human
-
machine
education
strong
>
div
><
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style
=
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:
center
;
“
><
strong
><
br
>
strong
>
div
><
div
style
=
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text
-
align
:
center
;
“
><
strong
>
daniel
@
udk
-
berlin
.
de
<
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>
strong
>
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><
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:
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;
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><
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><
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>
strong
>
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><
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style
=
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align
:
center
;
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><
strong
><
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>
strong
>
div
>
<
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>
In
this
Boardroom
Dialogue
we
will
discuss
the
possibility
of
humans
and
AIs
becoming
„
peers
“
in
helping
each
other
to
acquire
skills
and
competences
. 
div
><
div
><
br
>
div
><
div
>
The
dialogue
will
start
with
introducing
the
concept
of
Human
-
Machine
Peer
Learning
(
HMPL
)
and
exploring
its
potential
to
provide
a
paradigm
for
constructing
human
-
machine
learning
curricula
from
which
both
humans
as
well
as
machines
benefit
. 
div
><
div
><
br
>
div
><
div
>
Participants
will
acquire
both
the
theoretical
concept
of
human
-
machine
peer
learning
and
concrete
insights
into
how
HMPL
is
implemented
through
the
illustration
of
two
prototypical
learning
scenarios
where
HMPL
is
already
deployed
.
div
>
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