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[
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Evaluation Warning : The document was created with Spire.PDF for Python.
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8708
I
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Vo
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8
,
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5
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Octo
b
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2
0
1
8
:
3
3
5
9
–
3
3
6
7
3360
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m
s
c
h
ar
ac
t
er
is
tics
.
I
n
S
ec
tio
n
4
,
w
e
p
r
ese
n
t t
h
e
a
s
s
e
s
s
m
e
n
t a
n
d
d
ata
a
n
a
l
y
s
i
s
m
et
h
o
d
o
lo
g
y
.
Nex
t,
in
S
ec
tio
n
5
w
e
p
r
esen
t
r
esu
l
t
an
d
d
is
cu
tio
n
in
a
r
ea
l
ca
s
e
s
tu
d
y
.
I
n
Sectio
n
6
,
w
e
p
r
esen
t
o
u
r
co
n
clu
s
io
n
s
an
d
p
er
s
p
ec
tiv
es.
2.
RE
L
AT
E
D
WO
RK
S
E
n
co
u
r
ag
i
n
g
lear
n
er
s
to
th
i
n
k
in
m
etac
o
g
n
iti
v
e
ter
m
s
s
h
o
u
ld
h
av
e
a
p
o
s
iti
v
e
i
m
p
ac
t
o
n
lear
n
i
n
g
p
er
f
o
r
m
a
n
ce
,
w
h
ic
h
is
co
n
f
i
r
m
ed
b
y
t
h
e
r
esu
lt
s
o
b
tain
e
d
in
2
0
0
7
b
y
Ma
r
ia
B
an
n
er
t
[
1
1
].
I
n
2
0
0
9
,
a
r
elatio
n
s
h
ip
w
a
s
f
o
u
n
d
b
et
w
e
en
s
el
f
-
a
s
s
e
s
s
m
e
n
t
o
n
th
e
o
n
e
h
an
d
an
d
th
e
ef
f
o
r
t
an
d
p
er
f
o
r
m
a
n
ce
o
f
lear
n
er
s
o
n
th
e
o
th
er
h
a
n
d
b
y
I
za
s
k
u
n
I
b
ab
e
[
5
].
I
n
2
0
1
2
,
Nilg
ü
n
an
d
h
is
tea
m
s
t
u
d
ied
th
e
ef
f
ec
t
o
f
in
te
g
r
ated
co
m
p
u
ter
-
a
s
s
i
s
ted
lear
n
i
n
g
o
n
m
etac
o
g
n
iti
v
e
i
n
ce
n
tiv
e
s
o
n
s
tu
d
en
t
s
'
e
m
o
tio
n
al
s
k
ill
s
[
8
].
I
n
2
0
1
3
,
L
o
n
g
an
d
A
le
v
e
n
ar
g
u
ed
th
at
s
el
f
-
e
v
alu
atio
n
a
n
d
s
tu
d
y
c
h
o
ice
ar
e
t
wo
i
m
p
o
r
tan
t
m
e
taco
g
n
iti
v
e
p
r
o
c
ess
es
in
v
o
lv
ed
in
s
elf
-
r
eg
u
lated
lear
n
in
g
[
17
].
T
h
e
r
elatio
n
s
h
ip
b
et
w
ee
n
ex
ec
u
t
iv
e
f
u
n
ctio
n
s
(
in
h
ib
it
o
r
y
co
n
tr
o
l
an
d
m
e
m
o
r
y
w
o
r
k
)
a
n
d
m
etac
o
g
n
iti
v
e
s
k
i
lls
w
as
s
tu
d
ied
in
2
0
1
4
b
y
Do
n
n
a
B
r
y
ce
[
18
].
I
n
2
0
1
7
,
C
h
r
is
ti
n
a
J
u
lian
e
s
aid
t
h
at
m
o
tiv
a
tio
n
i
s
u
n
d
en
iab
le
f
o
r
th
e
s
u
cc
ess
o
f
e
-
lear
n
i
n
g
p
r
o
ce
s
s
es
[
19
]
.
I
n
th
e
s
a
m
e
y
ea
r
,
a
r
elatio
n
s
h
ip
w
a
s
f
o
u
n
d
b
et
w
ee
n
lear
n
in
g
s
t
y
le
s
an
d
lear
n
er
b
eh
a
v
io
r
in
o
n
lin
e
lear
n
in
g
b
y
B
ah
ar
u
d
in
a
n
d
h
is
tea
m
[
20
]
.
I
n
d
ee
d
,
m
etac
o
g
n
i
tio
n
ca
n
t
ak
e
m
a
n
y
f
o
r
m
s
.
I
t
in
clu
d
e
s
k
n
o
w
led
g
e
o
f
w
h
e
n
an
d
h
o
w
to
u
s
e
lear
n
in
g
s
tr
ateg
ie
s
[
21
].
A
ll
th
e
w
o
r
k
t
h
at
h
as
b
ee
n
d
o
n
e
s
h
o
w
s
th
e
i
m
p
ac
t
o
f
a
m
e
taco
g
n
itio
n
s
k
ill
o
n
t
h
e
lear
n
er
s
'
p
er
f
o
r
m
a
n
ce
o
r
th
e
s
u
cc
es
s
o
f
th
e
tr
ain
in
g
.
Ho
w
e
v
er
,
n
o
w
o
r
k
ad
d
r
ess
es
t
h
e
r
e
latio
n
s
h
ip
b
et
w
ee
n
m
etac
o
g
n
iti
v
e
s
k
ill
s
an
d
lear
n
er
s
tatu
s
.
I
n
th
is
ar
ticle,
w
e
d
eter
m
i
n
e
th
e
p
o
s
s
ib
le
r
elatio
n
s
h
ip
s
b
et
w
ee
n
m
etac
o
g
n
it
iv
e
s
k
ills
an
d
lear
n
er
s
tates.
I
n
d
ee
d
,
w
e
p
r
esen
t
a
n
ag
en
t
m
o
d
el
th
a
t
ca
n
m
o
tiv
a
t
e
a
lear
n
er
to
u
s
e
s
k
i
lls
b
a
s
e
d
o
n
h
is
s
tate.
T
h
e
ag
en
t
u
s
es
a
s
et
o
f
r
u
les
a
n
d
ac
tio
n
s
to
d
ev
e
lo
p
th
e
m
e
taco
g
n
it
iv
e
s
k
ill
s
o
f
t
h
e
lear
n
er
s
.
T
h
e
r
u
les
ar
e
ex
tr
ac
ted
u
s
i
n
g
th
e
d
ec
i
s
io
n
tr
ee
.
3.
M
E
T
ACO
G
NI
T
I
O
N
SK
I
L
L
S
T
h
e
p
o
s
itio
n
in
th
i
s
p
ap
er
is
co
n
s
is
ten
t
w
it
h
t
h
e
w
id
el
y
-
h
el
d
v
ie
w
t
h
at
m
etac
o
g
n
it
io
n
r
e
f
er
s
to
th
e
k
n
o
w
led
g
e,
co
n
tr
o
l
an
d
a
w
ar
en
es
s
th
at
s
t
u
d
en
ts
p
o
s
s
es
s
in
r
elatio
n
to
th
eir
th
in
k
i
n
g
a
n
d
lear
n
in
g
p
r
o
ce
s
s
es
[
2
2
]
.
A
cc
o
r
d
in
g
to
Fla
v
ell
[
22
]
,
m
e
taco
g
n
itio
n
is
d
ef
i
n
ed
as
t
h
e
ab
ilit
y
to
r
ef
lect
o
n
a
n
d
co
n
tr
o
l
o
n
e
'
s
o
w
n
co
g
n
iti
v
e
p
r
o
ce
s
s
e
s
w
h
ic
h
i
n
clu
d
es
k
n
o
w
led
g
e
o
f
t
h
e
'wh
y
'
,
th
e
'
h
o
w
'
a
n
d
t
h
e
'w
h
e
n
'
,
t
h
e
lear
n
er
t
h
u
s
en
g
a
g
i
n
g
i
n
v
ar
io
u
s
co
g
n
it
iv
e
ac
tiv
itie
s
.
Me
taco
g
n
itio
n
h
a
s
t
h
e
f
o
llo
w
i
n
g
th
r
ee
m
ain
p
h
ase
s
:
a.
th
e
p
la
n
n
in
g
p
h
ase
:
allo
w
s
t
h
e
lear
n
er
to
o
r
g
an
ize
h
o
w
h
e
o
r
s
h
e
w
ill
u
s
e
t
h
e
in
f
o
r
m
atio
n
,
ie
d
ef
i
n
e
h
i
s
o
r
h
er
g
o
als,
as
k
h
i
m
s
el
f
q
u
est
io
n
s
b
ef
o
r
e
r
ea
d
in
g
a
le
s
s
o
n
;
b.
th
e
co
n
tr
o
l
p
h
a
s
e
:
allo
w
s
t
h
e
lear
n
er
to
m
a
k
e
d
ec
is
io
n
s
t
h
at
ai
m
to
co
n
tr
o
l
th
e
d
eg
r
ee
o
f
co
m
p
r
e
h
en
s
io
n
an
d
m
a
n
ag
e
t
h
e
lear
n
i
n
g
p
r
o
ce
s
s
,
ie
f
o
c
u
s
atte
n
tio
n
,
e
v
al
u
ate
d
u
r
in
g
r
ea
d
in
g
,
m
ai
n
tai
n
m
o
ti
v
a
tio
n
,
etc
.
;
c.
th
e
s
el
f
-
r
eg
u
latio
n
p
h
a
s
e
:
allo
w
s
t
h
e
lear
n
er
to
f
o
cu
s
o
n
ac
tiv
itie
s
th
at
ar
e
s
tr
o
n
g
l
y
r
elate
d
to
co
n
tr
o
l
s
u
ch
as
d
ec
r
ea
s
in
g
r
ea
d
in
g
s
p
ee
d
,
ch
an
g
i
n
g
t
h
e
lear
n
in
g
s
tr
ate
g
y
ad
o
p
ted
to
ad
j
u
s
t
to
th
e
d
if
f
ic
u
lt
y
o
f
t
h
e
co
u
r
s
e,
etc.
4.
T
H
E
M
E
T
ACO
G
NI
T
I
VE
A
G
E
NT
Ag
e
n
ts
ar
e
s
o
f
t
w
ar
e
o
r
h
ar
d
w
ar
e
e
le
m
e
n
t
s
t
h
at
o
p
er
ate
w
it
h
i
n
a
n
en
v
ir
o
n
m
e
n
t,
ac
t
an
d
s
e
n
s
e,
an
d
co
m
m
u
n
icate
an
d
co
llab
o
r
ate
w
ith
o
th
er
ele
m
e
n
ts
[
23
].
E
v
er
y
a
g
e
n
t
f
o
llo
w
s
g
o
als
o
r
task
s
w
h
ich
ar
e
s
p
ec
if
ied
in
t
h
e
n
ex
t
s
ec
tio
n
[
2
4
]
.
4
.
1
.
T
he
a
g
e
nts’
ro
les
I
n
t
h
is
s
t
u
d
y
,
t
h
e
a
g
e
n
t
d
ea
ls
w
it
h
m
etac
o
g
n
iti
v
e
as
s
is
ta
n
ce
.
I
t
r
ea
cts
ac
co
r
d
in
g
to
lear
n
er
s
’
f
ee
d
b
ac
k
an
d
ass
o
ciat
io
n
r
u
les
ex
tr
ac
ted
b
y
a
n
a
n
al
y
s
is
o
f
d
ata
th
at
w
e
h
a
v
e
p
r
ev
io
u
s
l
y
co
llected
f
r
o
m
s
tu
d
e
n
ts
.
I
n
f
ac
t,
th
e
a
g
en
t
s
t
i
m
u
late
s
lear
n
er
s
w
h
o
n
ee
d
h
elp
a
n
d
o
f
f
er
s
th
e
m
m
etac
o
g
n
it
iv
e
s
u
p
p
o
r
t
in
th
eir
lear
n
i
n
g
t
h
at
s
h
o
w
s
i
n
T
ab
le
1
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
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n
g
I
SS
N:
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-
8708
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mp
r
o
vin
g
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r
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in
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b
y
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lb
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3361
T
ab
le
1
.
T
h
e
Sti
m
u
latio
n
P
er
f
o
r
m
ed
b
y
t
h
e
A
g
e
n
t a
t e
ac
h
L
ea
r
n
in
g
P
h
ase
[
25
]
L
e
a
r
n
i
n
g
P
h
a
se
s
S
t
i
m
u
l
a
t
i
o
n
P
l
a
n
n
i
n
g
Est
a
b
l
i
s
h
t
h
e
p
u
r
p
o
se
,
t
i
me
a
n
d
s
t
r
a
t
e
g
y
o
f
l
e
a
r
n
i
n
g
C
o
n
t
r
o
l
C
o
n
t
r
o
l
t
h
e
t
l
e
a
r
n
i
n
g
a
sse
ssm
e
n
t
R
e
g
u
l
a
t
i
o
n
A
d
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u
st
t
h
e
l
e
a
r
n
i
n
g
p
l
a
n
a
n
d
st
r
a
t
e
g
y
I
n
th
i
s
p
ap
er
,
w
e
p
r
o
p
o
s
e
a
m
o
d
el
o
f
m
etac
o
g
n
iti
v
e
a
g
en
t
th
a
t
co
llects
f
ee
d
b
ac
k
s
[
2
6
]
,
[
27
]
(
q
u
esti
o
n
n
air
e,
in
ter
ac
tio
n
s
)
o
f
lear
n
er
s
to
m
ea
s
u
r
e
an
d
e
v
alu
ate
t
h
eir
ex
p
er
ien
ce
s
an
d
t
h
eir
m
etac
o
g
n
iti
v
e
s
k
il
ls
.
I
n
th
is
r
esp
ec
t,
w
e
o
f
f
e
r
lear
n
er
s
a
s
p
ac
e
to
tak
e
n
o
tes,
k
e
y
w
o
r
d
s
an
d
d
if
f
ic
u
lt
co
n
c
ep
ts
,
as
w
ell
as
w
e
r
eq
u
ir
e
a
f
o
r
m
at
iv
e
e
v
alu
at
io
n
o
n
th
e
ed
u
ca
tio
n
al
s
u
p
p
o
r
t
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Fig
u
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ase
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ig
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Fig
u
r
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2
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n
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m
to
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s
e
th
e
m
etac
o
g
n
i
tiv
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s
k
i
lls
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
2
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8
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3362
Fig
u
r
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2
.
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r
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i
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g
m
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v
ar
iab
l
es:
a.
p
lan
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g
: e
v
al
u
ate
t
h
e
d
eg
r
ee
o
f
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r
g
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izatio
n
o
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t
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,
b.
s
tr
ateg
ie
s
: a
s
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ess
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e
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er
's m
etac
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s
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g
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ter
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u
r
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3
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co
llect
d
ata
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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t J
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lec
&
C
o
m
p
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g
I
SS
N:
2088
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8708
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ata
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o
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l
s
2
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f
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p
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se
o
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me
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o
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n
t
r
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t
i
o
n
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u
r
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4
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se
o
f
t
a
b
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e
s,
d
i
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g
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ms,
e
t
c
.
1
-
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f
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n
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me
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k
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ms
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3
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a
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sh
i
p
s
w
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t
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t
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4
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5
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2
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g
me
t
h
o
d
2
-
U
se
o
f
h
e
l
p
3
-
A
d
a
p
t
a
t
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o
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t
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r
e
q
u
i
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me
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f
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se
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1
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r
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2
-
D
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so
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n
t
a
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3
-
C
o
n
f
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si
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n
4
-
S
u
c
c
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ss
5
.
2
.
T
he
a
s
s
o
cia
t
io
n r
ules
bet
w
ee
n
m
et
a
co
g
nitiv
e
v
a
ri
a
bles
a
nd
t
he
lea
rner
s
perc
ept
io
n
T
h
e
d
ec
is
io
n
tr
ee
th
at
s
h
o
w
s
in
Fi
g
u
r
e
5
,
g
en
er
ated
f
r
o
m
t
h
e
d
ata
co
llected
,
s
h
o
w
s
th
a
t
th
er
e
is
a
g
r
ea
t
d
ea
l
o
f
d
ep
en
d
e
n
ce
b
et
w
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n
t
h
e
u
s
e
o
f
m
etac
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g
n
itiv
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s
tr
ateg
ies
(
p
la
n
n
i
n
g
,
s
e
lf
-
ev
al
u
atio
n
,
s
el
f
-
r
eg
u
lat
io
n
a
n
d
lear
n
i
n
g
s
tr
ate
g
ies)
b
y
a
lear
n
er
a
n
d
h
is
o
r
h
er
p
er
ce
p
tio
n
s
tate
(
d
is
o
r
ien
ted
,
co
n
f
u
s
ed
an
d
i
m
p
r
u
d
en
t
)
.
I
n
d
ee
d
,
w
e
h
a
v
e
e
x
tr
ac
ted
th
e
f
o
llo
w
in
g
r
u
le
s
:
a.
if
n
o
t (
p
lan
n
i
n
g
)
,
t
h
en
t
h
e
lear
n
er
is
d
is
o
r
ien
ted
;
(
1
)
b.
if
n
o
t (
s
el
f
-
e
v
alu
a
tio
n
)
an
d
n
o
t
(
s
elf
-
r
eg
u
latio
n
)
,
t
h
en
t
h
e
lea
r
n
er
is
co
n
f
u
s
ed
;
(
2
)
c.
if
n
o
t (
lear
n
in
g
s
tr
ate
g
ies),
t
h
e
n
th
e
lea
r
n
er
is
i
m
p
r
u
d
en
t.
(
3
)
d.
if
n
o
t (
p
lan
n
i
n
g
)
a
n
d
n
o
t(
s
el
f
-
r
eg
u
la
tio
n
)
an
d
n
o
t (
m
e
m
o
r
izat
io
n
s
tr
ateg
ies)
th
e
n
u
n
s
u
cc
e
s
s
(
4
)
W
e
u
s
ed
th
e
p
r
ev
io
u
s
r
u
les
to
d
ef
in
e
th
e
ac
tio
n
s
to
b
e
tak
en
b
y
th
e
m
etac
o
g
n
iti
v
e
ag
e
n
t
i
n
th
e
ca
s
e
w
h
er
e
a
lear
n
er
h
as a
p
r
o
b
le
m
d
u
r
in
g
h
i
s
lear
n
i
n
g
p
r
o
ce
s
s
th
a
t sh
o
w
s
i
n
T
ab
le
3.
T
ab
le
3
.
A
s
s
o
ciatio
n
b
et
w
ee
n
S
tates a
n
d
A
ct
io
n
s
to
b
e
P
er
f
o
r
m
ed
b
y
t
h
e
M
etac
o
g
n
it
iv
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A
g
en
t
S
t
a
t
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R
e
l
a
t
e
d
i
n
c
e
n
t
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D
i
so
r
i
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n
t
e
d
En
c
o
u
r
a
g
e
p
l
a
n
n
i
n
g
C
o
n
f
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se
d
En
c
o
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r
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g
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t
h
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se
o
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se
l
f
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a
sse
ssm
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n
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st
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a
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n
d
se
l
f
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l
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a
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k
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n
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c
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n
c
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r
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s t
h
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l
e
a
r
n
e
r
t
o
p
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mo
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a
t
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t
r
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t
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g
i
e
s
5
.
3
.
I
nte
g
ra
t
io
n o
f
t
he
lea
rner
s
m
et
a
co
g
nitiv
e
help
W
e
ass
u
m
e
t
h
at
p
ed
ag
o
g
ical
s
u
p
p
o
r
t
is
an
o
r
d
er
l
y
s
eq
u
e
n
c
e
o
f
p
ed
ag
o
g
ical
u
n
it
s
an
d
ea
ch
lear
n
er
m
u
s
t
v
al
id
ate
p
r
ev
io
u
s
u
n
it
to
lear
n
th
e
n
ex
t
o
n
e
t
h
at
s
h
o
w
s
in
Fi
g
u
r
e
4
.
Oth
er
w
is
e,
th
e
ag
en
t
p
er
f
o
r
m
s
th
e
lear
n
er
's
m
etac
o
g
n
i
tiv
e
(
p
lan
n
in
g
,
m
etac
o
g
n
itio
n
s
tr
ate
g
ie
s
,
s
el
f
-
ev
a
lu
at
io
n
a
n
d
s
el
f
-
r
e
g
u
la
tio
n
)
in
ce
n
ti
v
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
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n
g
,
Vo
l.
8
,
No
.
5
,
Octo
b
er
2
0
1
8
:
3
3
5
9
–
3
3
6
7
3364
ac
co
r
d
in
g
to
lear
n
er
’
s
p
er
ce
p
ti
o
n
(
co
n
f
u
s
ed
,
i
m
p
r
u
d
en
t
an
d
d
i
s
o
r
d
er
ly
)
.
T
h
e
a
g
en
t
e
n
co
u
r
ag
es
lear
n
er
s
w
h
o
m
h
av
e
t
h
e
lear
n
in
g
d
is
ab
ilit
ie
s
t
o
u
s
e
m
etac
o
g
n
iti
v
e
s
tr
ateg
ies.
Fig
u
r
e
4
.
Stru
ct
u
r
e
o
f
lear
n
i
n
g
s
u
p
p
o
r
t
5
.
4
.
No
t
a
t
io
n
(u
k
)
k=
1…n
:
a
s
eq
u
e
n
ce
o
f
p
ed
ag
o
g
ical
u
n
it
s
w
h
ich
co
m
p
o
s
es
a
p
ed
ag
o
g
ical
s
u
p
p
o
r
t
S.
E
ac
h
p
ed
ag
o
g
ical
u
n
it
u
k
is
c
h
ar
a
cter
ized
b
y
its
p
ed
ag
o
g
ical
g
o
als,
th
e
m
i
n
i
m
u
m
n
o
te
n
k
t
o
v
alid
ate
an
d
t
h
e
co
n
s
u
ltatio
n
ti
m
e
t
k
an
d
th
e
t
o
ler
an
ce
σ
p
r
ed
ef
in
ed
b
y
th
e
teac
h
er
.
(a
i
)
i=
1…m
:
is
a
co
m
m
u
n
it
y
o
f
lear
n
er
s
co
n
ce
r
n
ed
b
y
th
e
co
n
s
u
ltatio
n
o
f
th
e
s
a
m
e
p
ed
ag
o
g
ica
l
m
ed
i
u
m
S.
T
ik
etN
ik
: th
e
co
n
s
u
ltatio
n
t
i
m
e
o
f
p
ed
ag
o
g
ical
s
u
p
p
o
r
t a
n
d
th
e
s
co
r
e
o
b
tain
ed
b
y
lear
n
er
a
i
i
n
th
e
p
e
d
ag
o
g
ical
u
n
i
t u
k
.
I
n
th
e
ca
s
e
w
h
er
e
t
h
e
lear
n
er
h
as
n
o
t
in
v
ested
s
u
f
f
icien
t
ti
m
e
(T
ik
<t
k
-
σ
)
an
d
co
n
s
eq
u
e
n
tl
y
less
e
f
f
o
r
t,
th
e
ag
e
n
t
e
v
alu
a
tes
t
h
e
m
o
ti
v
a
tio
n
an
d
atte
n
tio
n
o
f
th
e
lear
n
er
b
ased
o
n
th
e
an
s
w
er
s
to
q
u
esti
o
n
s
.
I
f
th
e
le
v
el
o
f
m
o
ti
v
atio
n
is
lo
w
,
th
e
a
g
e
n
t
tr
ig
g
er
s
i
n
ce
n
tiv
e
s
to
m
o
tiv
at
e
an
d
m
a
k
e
t
h
e
lear
n
er
m
o
r
e
a
ctiv
e
a
n
d
ca
u
tio
u
s
.
Oth
er
w
i
s
e,
th
e
ag
e
n
t e
n
co
u
r
a
g
es th
e
lear
n
er
to
r
ev
ie
w
t
h
e
g
o
als
an
d
r
esch
ed
u
le
t
h
e
lear
n
i
n
g
.
I
n
th
e
ca
s
e
w
h
er
e
(
T
ik
>t
k
+σ
)
an
d
th
e
lear
n
er
d
o
esn
’
t
leav
e
t
h
e
lear
n
i
n
g
-
in
o
th
er
w
o
r
d
s
,
t
h
e
lear
n
er
f
i
n
d
s
d
if
f
ic
u
ltie
s
o
r
lo
s
es
m
o
t
iv
atio
n
-
t
h
e
a
g
en
t
as
k
s
t
h
e
le
ar
n
er
:
"
d
o
y
o
u
f
in
d
d
i
f
f
icu
l
tie
s
?
"
.
Dep
en
d
in
g
o
n
th
e
lear
n
er
's
r
esp
o
n
s
e,
t
h
e
a
g
en
t
w
i
ll
tr
i
g
g
er
in
ce
n
ti
v
es
to
m
o
tiv
a
te
a
n
d
m
a
k
e
t
h
e
lear
n
er
m
o
r
e
ac
tiv
e
an
d
ca
u
tio
u
s
if
t
h
e
an
s
w
er
is
n
eg
a
tiv
e.
E
ls
e,
t
h
e
m
etac
o
g
n
i
tiv
e
ag
en
t
p
er
ce
iv
e
s
t
h
e
s
tate
S
ti
o
f
th
e
lear
n
er
a
i
at
a
ti
m
e
t.Sti
ca
n
h
a
v
e
th
e
f
o
llo
w
i
n
g
v
alu
e
s
:
co
n
f
u
s
ed
,
d
is
o
r
ien
ted
or
im
p
r
u
d
e
n
t.
T
h
e
ag
en
t
as
s
o
ciate
s
ea
ch
s
tat
e
w
it
h
an
A
ct
ti
ac
t
io
n
(
i
n
ce
n
ti
v
e
ass
o
ciate
d
w
it
h
th
e
S
ti
s
tate
in
T
ab
le
3
)
.
I
n
th
e
ca
s
e
w
h
er
e
th
e
co
n
s
u
ltatio
n
ti
m
e
is
in
t
h
e
s
ta
n
d
ar
d
s
(
|
T
ik
-
t
k
|
<σ
)
:
a.
if
t
h
e
lear
n
er
h
as
s
u
f
f
icie
n
t
c
o
n
f
id
e
n
ce
in
h
i
m
s
e
lf
/
h
er
s
e
l
f
,
h
e
/
s
h
e
m
a
y
p
as
s
th
e
a
s
s
ess
m
en
t
test
to
v
alid
ate
t
h
e
lear
n
i
n
g
u
n
it
u
k
;
o
th
er
w
is
e
th
e
ag
e
n
t
e
n
co
u
r
a
g
es
h
i
m
/
h
er
to
u
s
e
t
h
e
s
el
f
-
as
s
es
s
m
e
n
t
a
n
d
s
e
lf
-
r
eg
u
lat
io
n
s
tr
ate
g
ies
; (
r
u
le
2
)
;
b.
if
t
h
e
lea
r
n
er
h
as
a
N
ik
r
ati
n
g
h
ig
h
er
th
a
n
th
e
v
a
lid
atio
n
s
co
r
e
n
k
,
h
e
ca
n
m
o
v
e
o
n
to
t
h
e
n
ex
t
p
ed
ag
o
g
ical
u
n
i
t;
o
th
er
w
is
e,
t
h
e
ag
en
t
en
c
o
u
r
ag
es
t
h
e
lear
n
er
to
p
lan
n
in
g
,
s
elf
-
r
e
g
u
la
tio
n
an
d
m
e
m
o
r
i
za
tio
n
s
tr
ateg
ie
s
th
at
p
r
o
m
o
te
s
u
cc
e
s
s
f
u
l
lear
n
i
n
g
.
T
h
ese
s
tr
ate
g
ie
s
a
r
e
ef
f
ec
t
iv
el
y
u
s
ed
b
y
lear
n
er
s
w
h
o
h
a
v
e
p
ass
ed
w
it
h
s
u
cc
e
s
s
f
u
ll
y
t
h
e
u
n
i
t in
q
u
e
s
tio
n
(
r
u
le
4
)
.
6.
RE
SU
L
T
AND
DI
SCUS
SI
O
N
T
h
e
d
ec
is
io
n
tr
ee
s
h
o
w
s
t
h
at
t
h
er
e
is
a
r
elatio
n
s
h
ip
b
et
w
ee
n
th
e
lear
n
er
'
s
s
tate
a
n
d
h
is
m
et
ac
o
g
n
iti
v
e
s
k
il
ls
th
a
t
s
h
o
w
s
i
n
Fi
g
u
r
e
5
.
B
y
ex
p
lo
iti
n
g
th
e
s
tate
o
f
th
e
lear
n
er
,
th
e
ag
e
n
t
g
en
er
ate
s
in
ter
es
tin
g
m
o
tiv
a
tio
n
s
i
n
n
at
u
r
al
la
n
g
u
a
g
e,
w
h
ic
h
'
lead
s
th
e
lear
n
er
to
i
m
p
r
o
v
e
h
i
s
m
etac
o
g
n
it
iv
e
s
k
ills
.
T
o
d
o
th
is
,
o
u
r
s
tu
d
y
f
o
c
u
s
es,
f
ir
s
t,
o
n
m
a
n
a
g
in
g
th
e
d
ialo
g
u
e
b
et
w
ee
n
t
h
e
ag
en
t
a
n
d
t
h
e
lear
n
er
s
f
o
r
n
e
g
o
tiatio
n
an
d
,
t
h
en
,
f
o
cu
s
es
o
n
t
h
e
e
f
f
ec
ts
o
f
o
u
r
ag
en
t
o
n
t
h
e
m
e
taco
g
n
iti
v
e
s
k
ills
o
f
lear
n
er
s
.
W
e
o
b
s
er
v
e
th
at
t
h
e
p
er
ce
n
ta
g
e
o
f
lear
n
er
s
w
h
o
h
av
e
s
u
cc
es
s
f
u
ll
y
co
m
p
leted
th
e
lear
n
i
n
g
is
g
r
ea
ter
(
7
1
%)
w
it
h
t
h
e
in
te
g
r
atio
n
o
f
th
e
m
etac
o
g
n
i
ti
v
e
a
g
en
t
th
a
n
w
it
h
o
u
t
t
h
i
s
ag
e
n
t
(
3
0
%)
th
at
s
h
o
w
s
i
n
T
ab
le
4
.
I
n
d
ee
d
,
th
e
r
esu
lt
s
h
o
w
s
t
h
e
i
m
p
o
r
tan
ce
o
f
t
h
e
m
etac
o
g
n
itiv
e
a
g
e
n
t
in
th
e
lear
n
i
n
g
p
r
o
ce
s
s
.
I
n
d
ee
d
,
m
etac
o
g
n
iti
v
e
in
ce
n
ti
v
es
allo
w
lear
n
er
s
to
b
ec
o
m
e
a
w
ar
e
o
f
th
eir
m
en
ta
l
p
r
o
ce
s
s
es
a
n
d
to
i
m
p
r
o
v
e
t
h
eir
lear
n
i
n
g
m
et
h
o
d
.
T
h
er
ef
o
r
e,
th
e
lear
n
er
w
h
o
h
a
s
th
e
m
etac
o
g
n
i
tiv
e
s
k
ill
s
ea
s
il
y
s
u
cc
ee
d
s
i
n
t
h
e
lear
n
i
n
g
tas
k
th
at
s
h
o
w
s
in
Fig
u
r
e
6
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8708
I
mp
r
o
vin
g
E
-
Lea
r
n
in
g
b
y
I
n
te
g
r
a
tin
g
a
Meta
co
g
n
itive
A
g
en
t
(
Ha
n
a
n
e
E
lb
a
s
r
i
)
3365
Fig
u
r
e
5
.
T
r
ee
in
d
u
ce
d
o
n
r
ea
l d
ata
w
it
h
a
p
r
ed
icted
v
alu
e
"
s
tate"
T
ab
le
4
.
T
h
e
R
u
les o
f
t
h
e
D
ec
is
io
n
T
r
ee
1.
I
f
p
l
a
n
n
i
n
g
=
n
o
,
t
h
e
n
t
h
e
l
e
a
r
n
e
r
is
i
n
a
me
ssy
(
d
i
so
r
i
e
n
t
e
d
)
s
t
a
t
e
.
2.
If
p
l
a
n
n
i
n
g
=
y
e
s a
n
d
se
l
f
-
r
e
g
u
l
a
t
i
o
n
=
n
o
a
n
d
se
l
f
-
a
sse
ssm
e
n
t
=
n
o
,
t
h
e
n
t
h
e
l
e
a
r
n
e
r
i
s
i
n
a
s
t
a
t
e
o
f
c
o
n
f
u
s
i
o
n
.
3.
I
f
(
p
l
a
n
n
i
n
g
=
y
e
s a
n
d
se
l
f
-
r
e
g
u
l
a
t
i
o
n
=
n
o
a
n
d
se
l
f
-
a
sse
ssm
e
n
t
=
y
e
s
)
o
r
(
p
l
a
n
n
i
n
g
=
y
e
s a
n
d
se
l
f
-
r
e
g
u
l
a
t
i
o
n
=
y
e
s a
n
d
st
r
a
t
e
g
y
=
n
o
)
,
t
h
e
n
t
h
e
l
e
a
r
n
e
r
is
i
n
a
st
a
t
e
o
f
r
e
c
k
l
e
ssn
e
ss.
4.
If
(
p
l
a
n
n
i
n
g
=
y
e
s a
n
d
se
l
f
-
r
e
g
u
l
a
t
i
o
n
=
y
e
s a
n
d
s
t
r
a
t
e
g
y
=
y
e
s)
,
t
h
e
n
t
h
e
l
e
a
r
n
e
r
i
s
s
u
c
c
e
ssf
u
l
.
Fig
u
r
e
6
.
C
o
m
p
ar
is
o
n
o
f
lear
n
er
s
'
r
es
u
lt
s
w
it
h
an
d
w
it
h
o
u
t t
h
e
u
s
e
o
f
m
etac
o
g
n
itio
n
7.
CO
NCLU
SI
O
N
AND
P
E
RS
P
E
CT
I
VE
S
T
h
is
s
tu
d
y
w
a
s
co
n
d
u
cted
to
ex
a
m
in
e
t
h
e
ef
f
ec
t
o
f
d
if
f
er
en
t
m
etac
o
g
n
iti
v
e
v
ar
iab
les
o
n
t
h
e
s
u
cc
e
s
s
o
f
th
e
lear
n
in
g
p
r
o
ce
s
s
.
T
h
e
r
esu
lt
o
b
tain
ed
s
h
o
w
s
t
h
at
t
h
e
in
te
g
r
atio
n
o
f
a
m
etac
o
g
n
it
iv
e
ag
e
n
t
i
n
to
th
e
d
is
tan
ce
lear
n
i
n
g
m
a
n
ag
e
m
e
n
t
s
y
s
te
m
ca
n
s
i
g
n
if
ican
t
l
y
i
m
p
r
o
v
e
m
etac
o
g
n
iti
v
e
s
k
il
ls
a
n
d
k
n
o
w
led
g
e.
T
h
e
m
ai
n
g
o
al
o
f
o
u
r
s
t
u
d
y
is
to
e
n
co
u
r
ag
e
t
h
e
lear
n
er
to
u
s
e
m
etac
o
g
n
it
iv
e
s
k
ill
s
i
n
t
h
eir
o
n
l
i
n
e
lear
n
in
g
p
r
o
ce
s
s
.
T
h
e
r
esu
lt
s
h
o
w
s
t
h
at
th
e
i
n
f
lu
en
ce
o
f
th
e
m
etac
o
g
n
iti
v
e
ag
e
n
t
o
n
th
e
e
-
lear
n
i
n
g
p
r
o
ce
s
s
is
i
m
p
o
r
tan
t
b
ec
au
s
e
it
d
ev
elo
p
s
th
e
lear
n
er
's
au
to
n
o
m
y
,
m
ain
tain
s
h
is
o
r
h
er
in
te
n
tio
n
a
n
d
m
o
ti
v
atio
n
,
h
elp
s
h
i
m
o
r
h
er
to
ac
q
u
ir
e
m
etac
o
g
n
iti
v
e
s
k
ill
s
s
u
c
h
as
p
lan
n
in
g
,
s
el
f
-
as
s
ess
m
e
n
t,
s
elf
-
r
eg
u
latio
n
,
tech
n
iq
u
e
s
an
d
m
e
m
o
r
izat
io
n
s
tr
ateg
ie
s
.
I
n
a
f
u
t
u
r
e
w
o
r
k
,
w
e
i
n
te
n
d
to
b
u
ild
a
s
tan
d
ar
d
m
etac
o
g
n
iti
v
e
a
g
en
t
m
o
d
el
t
h
at
ca
n
co
m
m
u
n
icate
w
it
h
th
e
L
MS
s
a
n
d
b
ase
t
h
e
r
u
les
d
y
n
a
m
icall
y
e
x
tr
ac
t.
W
e
w
i
ll
i
m
p
r
o
v
e
it
s
f
u
n
c
tio
n
in
g
s
o
t
h
at
it
ca
n
au
to
m
at
icall
y
d
etec
t t
h
e
s
ta
te
an
d
p
r
o
f
ile
o
f
th
e
lear
n
er
an
d
r
ea
ct
in
r
ea
l
ti
m
e
.
RE
F
E
R
E
NC
E
S
[1
]
F
lav
e
ll
,
J.
H.,
“
M
e
tac
o
g
n
it
iv
e
A
s
p
e
c
ts
o
f
P
ro
b
lem
S
o
lv
in
g
”
,
T
h
e
n
a
tu
re
o
f
in
telli
g
e
n
c
e
,
Ne
w
J
e
rse
y
,
p
p
.
2
3
1
-
2
3
5
,
1
9
7
6
.
[2
]
Bro
w
n
,
A
.
L
.
.
Hill
sd
a
le,
NJ
:
Erl
b
a
u
m
.
,
“
Kn
o
w
in
g
W
h
e
n
,
W
h
e
re
,
a
n
d
H
o
w
to
e
m
e
m
b
e
r
:
A
P
ro
b
lem
o
f
M
e
tac
o
g
n
it
io
n
”
,
Ad
v
a
n
c
e
s
I
n
I
n
st
ru
c
ti
o
n
a
l
Psy
c
h
o
lo
g
y
,
p
p
.
7
7
-
1
6
5
,
1
9
7
8
.
[3
]
M
o
h
d
Ru
m
,
S
.
N.,
a
n
d
Is
m
a
il
,
M
.
A
.
,
“
M
e
to
c
o
g
n
it
iv
e
S
u
p
p
o
rt
A
c
c
e
lera
tes
Co
m
p
u
ter
As
siste
d
L
e
a
r
n
in
g
f
o
r
No
v
ic
e
P
r
o
g
ra
m
m
e
rs”
,
Ed
u
c
a
ti
o
n
a
l
T
e
c
h
n
o
l
o
g
y
&
S
o
c
iety
,
v
o
l.
2
0
,
n
o
.
3
,
p
p
.
1
7
0
-
1
8
1
,
2
0
1
7
.
[4
]
A
n
d
e
rso
n
,
e
t
a
l
.
,
“
C
h
a
n
g
in
g
th
e
M
e
tac
o
g
n
it
iv
e
Orie
n
tatio
n
o
f
a
Clas
sro
o
m
En
v
iro
n
m
e
n
t
to
E
n
h
a
n
c
e
S
tu
d
e
n
ts’
M
e
tac
o
g
n
it
io
n
Re
g
a
rd
in
g
Ch
e
m
is
try
L
e
a
rn
in
g
”
,
L
e
a
rn
in
g
En
v
iro
n
Re
s,
S
p
rin
g
e
r
S
c
ien
c
e
Bu
sin
e
ss
M
e
d
ia
Do
rd
re
c
h
t,
p
p
.
1
3
9
-
1
5
5
,
2
0
1
3
.
[5
]
Ja
u
re
g
iza
r
a
n
d
Iz
a
sk
u
n
Ib
a
b
e
Æ
Jo
a
n
a
,
“
On
li
n
e
S
e
lf
-
a
ss
e
ss
m
e
n
t
w
it
h
F
e
e
d
b
a
c
k
a
n
d
M
e
tac
o
g
n
it
i
v
e
Kn
o
w
led
g
e
”
,
Hig
h
Ed
u
c
,
S
p
r
in
g
e
r
S
c
ien
c
e
+
Bu
sin
e
ss
M
e
d
ia.
2
0
1
0
,
p
p
.
2
4
3
-
2
5
8
,
2
0
1
0
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
5
,
Octo
b
er
2
0
1
8
:
3
3
5
9
–
3
3
6
7
3366
[6
]
R
y
u
,
e
t
a
l
.
,
“
T
h
e
De
v
e
lo
p
m
e
n
t
a
n
d
I
m
p
lem
e
n
tatio
n
o
f
a
W
eb
-
b
a
se
d
F
o
rm
a
ti
v
e
P
e
e
r
A
ss
e
ss
m
e
n
t
S
y
st
e
m
f
o
r
E
n
h
a
n
c
i
n
g
S
t
u
d
e
n
ts’
M
e
tac
o
g
n
it
i
v
e
Aw
a
re
n
e
ss
a
n
d
P
e
rf
o
rm
a
n
c
e
in
I
ll
-
str
u
c
tu
re
d
T
a
sk
s”
,
Ed
u
c
a
ti
o
n
T
e
c
h
Re
se
a
rc
h
De
v
,
p
p
.
5
4
9
-
5
6
1
,
2
0
1
3
.
[7
]
Be
rn
a
rd
,
M
.
,
a
n
d
Ba
c
h
u
,
E.
“
E
n
h
a
n
c
i
n
g
th
e
M
e
tac
o
g
n
it
iv
e
S
k
il
l
o
f
No
v
ice
P
ro
g
ra
m
m
e
r
s
th
ro
u
g
h
C
o
ll
a
b
o
ra
t
iv
e
L
e
a
rn
in
g
”
,
In
M
e
ta
c
o
g
n
i
ti
o
n
:
F
u
n
d
a
me
n
ts
,
A
p
p
li
c
a
ti
o
n
s,
a
n
d
T
re
n
d
s
,
p
p
.
2
7
7
-
2
9
8
,
2
0
1
5
.
[8
]
F
e
y
z
io
g
lu
,
e
t
a
l
.
,
“
T
h
e
Ef
fe
c
t
o
f
Co
m
p
u
ter
-
A
s
siste
d
L
e
a
rn
in
g
In
teg
ra
ted
w
it
h
M
e
tac
o
g
n
it
iv
e
P
ro
m
p
ts
o
n
S
tu
d
e
n
ts’
Aff
e
c
ti
v
e
S
k
il
ls”
,
J
S
c
i
Ed
u
c
T
e
c
h
n
o
l
,
S
p
ri
n
g
e
r
S
c
ien
c
e
Bu
sin
e
ss
M
e
d
ia.
Ne
w
,
2
0
1
2
.
[9
]
A
le
v
e
n
,
e
t
a
l
.,
“
S
u
p
p
o
rti
n
g
S
tu
d
e
n
ts’
S
e
lf
-
Re
g
u
late
d
L
e
a
rn
w
it
h
a
n
Op
e
n
L
e
a
rn
e
r
M
o
d
e
l
in
a
L
in
e
a
r
Eq
u
a
ti
o
n
T
u
to
r”
,
A
IED
,
L
N
A
I
7
9
2
6
,
S
p
r
in
g
e
r
-
V
e
rlag
.
Be
rli
n
He
id
e
lb
e
rg
,
p
p
.
2
1
9
-
2
2
8
,
2
0
1
3
.
[1
0
]
S
z
ű
c
s,
e
t
a
l
.
,
“
T
h
e
R
e
latio
n
sh
ip
s a
m
o
n
g
Ex
e
c
u
ti
v
e
F
u
n
c
ti
o
n
s,
M
e
t
a
c
o
g
n
it
iv
e
S
k
il
ls
a
n
d
Ed
u
c
a
ti
o
n
a
l
Ac
h
iev
e
m
e
n
t
in
5
a
n
d
7
y
e
a
r
-
o
ld
c
h
il
d
re
n
”
,
M
e
tac
o
g
n
it
io
n
L
e
a
rn
in
g
,
S
p
r
in
g
e
r
S
c
ien
c
e
+
Bu
sin
e
ss
,
p
p
.
1
8
1
-
1
9
8
,
2
0
1
4
.
[1
1
]
M
a
ria
Ba
n
n
e
rt
a
n
d
Ch
rist
o
p
h
M
e
n
g
e
lk
a
m
p
,
“
A
ss
e
ss
m
e
n
t
o
f
M
e
ta
c
o
g
n
it
iv
e
S
k
il
ls
b
y
M
e
a
n
s
o
f
I
n
stru
c
ti
o
n
t
o
th
in
k
a
lo
u
d
a
n
d
re
f
lec
t
w
h
e
n
p
ro
m
p
t
e
d
Do
e
s
th
e
V
e
rb
a
li
sa
ti
o
n
M
e
th
o
d
A
ff
e
c
t
Lea
rn
in
g
”
,
M
e
tac
o
g
n
it
io
n
L
e
a
rn
in
g
,
S
p
rin
g
e
r
S
c
ien
c
e
+
Bu
si
n
e
ss
M
e
d
ia,
p
p
.
3
9
-
5
8
,
2
0
0
7
.
[1
2
]
S
teff
e
n
s,
e
t
a
l
.
,
“
Re
se
a
rc
h
o
n
S
e
lf
-
Re
g
u
late
d
L
e
a
rn
in
g
in
T
e
c
h
n
o
l
o
g
y
En
h
a
n
c
e
d
L
e
a
rn
in
g
En
v
iro
n
m
e
n
ts:
Tw
o
Ex
a
m
p
les
f
ro
m
Eu
ro
p
e
”
,
I
n
tern
a
ti
o
n
a
l
Ha
n
d
b
o
o
k
o
f
M
e
tac
o
g
n
it
io
n
a
n
d
L
e
a
rn
in
g
T
e
c
h
n
o
l
o
g
ies
,
S
p
ri
n
g
e
r
In
tern
a
ti
o
n
a
l
Ha
n
d
b
o
o
k
s
o
f
Ed
u
c
a
ti
o
n
2
6
,
Ne
w
Yo
rk
,
2
0
1
3
.
[1
3
]
V
e
e
n
m
a
n
a
n
d
M
a
rc
e
l
V
.
J.,
“
A
s
s
e
ss
in
g
M
e
tac
o
g
n
it
iv
e
S
k
il
ls
in
Co
m
p
u
teriz
e
d
Lea
rn
in
g
”
,
In
tern
a
ti
o
n
a
l
Ha
n
d
b
o
o
k
o
f
M
e
tac
o
g
n
it
io
n
a
n
d
L
e
a
rn
in
g
T
e
c
h
n
o
l
o
g
ies
,
S
p
ri
n
g
e
r
S
c
ien
c
e
Bu
sin
e
ss
M
e
d
ia,
Ne
w
Yo
rk
,
p
p
.
1
5
7
-
1
6
8
,
2
0
1
3
.
[1
4
]
.
Ra
ja
M
.
S
u
le
m
a
n
,
e
t
a
l
.
,
“
A
Ne
w
P
e
rsp
e
c
ti
v
e
o
f
Ne
g
o
ti
a
ti
o
n
-
Ba
s
e
d
Dia
lo
g
to
En
h
a
n
c
e
M
e
tac
o
g
n
i
ti
v
e
S
k
il
ls
in
t
h
e
Co
n
tex
t
o
f
Op
e
n
L
e
a
rn
e
r
M
o
d
e
ls”
,
In
ter
n
a
ti
o
n
a
l
Arti
fi
c
i
a
l
I
n
telli
g
e
n
c
e
in
Ed
u
c
a
ti
o
n
S
o
c
iety
,
p
p
.
1
0
6
9
-
1
1
1
5
,
2
0
1
6
.
[1
5
]
Ha
tzil
y
g
e
ro
u
d
is
,
e
t
a
l
.
,
“
T
h
e
De
sig
n
o
f
a
T
e
a
c
h
e
r
-
Driv
e
n
In
telli
g
e
n
t
Ag
e
n
t
S
y
st
e
m
f
o
r
S
u
p
e
rv
is
in
g
L
e
ss
o
n
s
in
LA
M
”
,
In
telli
g
e
n
t
A
d
a
p
tatio
n
&
P
e
rso
n
a
li
z
a
ti
o
n
T
e
c
h
n
iq
u
e
s,
S
p
r
i
n
g
e
r
-
V
e
rlag
Be
rli
n
He
id
e
lb
e
rg
,
p
p
.
2
1
1
-
2
3
8
,
2
0
1
2
.
[1
6
]
Clé
m
e
n
t
Du
ss
a
rp
s
,
“
L
’a
b
a
n
d
o
n
e
n
f
o
rm
a
ti
o
n
à
d
istan
c
e
”
,
Dista
n
c
e
s
e
t
m
é
d
iatio
n
s
d
e
s
sa
v
o
irs
,
h
tt
p
:/
/
d
m
s.re
v
u
e
s.o
rg
/1
0
3
9
,
2
0
1
7
.
[1
7
]
L
o
n
g
Y
a
n
d
A
le
v
e
n
V
,
“
S
u
p
p
o
rt
in
g
S
tu
d
e
n
ts’
S
e
lf
-
Re
g
u
late
d
L
e
a
rn
in
g
w
it
h
a
n
Op
e
n
L
e
a
rn
e
r
M
o
d
e
l
i
n
a
L
in
e
a
r
Eq
u
a
ti
o
n
T
u
to
r”
,
Arti
f
icia
l
In
tel
li
g
e
n
c
e
in
Ed
u
c
a
ti
o
n
,
1
6
t
h
In
te
rn
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
,
AIE
D
2
0
1
3
,
v
o
l.
7
9
2
6
,
p
p
.
2
1
9
-
2
2
8
,
2
0
1
3
[1
8
]
Br
y
c
e
D,
e
t
a
l
.
,
“
T
h
e
R
e
latio
n
sh
ip
s
a
m
o
n
g
Ex
e
c
u
ti
v
e
F
u
n
c
ti
o
n
s
,
M
e
tac
o
g
n
it
iv
e
S
k
il
ls
a
n
d
Ed
u
c
a
ti
o
n
a
l
A
c
h
iev
e
m
e
n
t
in
5
a
n
d
7
y
e
a
r
-
o
ld
c
h
il
d
re
n
”
,
M
e
t
a
c
o
g
n
it
io
n
L
e
a
rn
in
g
,
2
0
1
4
.
[1
9
]
Ju
li
a
n
e
C,
e
t
a
l
.
,
“
P
re
d
ictin
g
th
e
p
re
se
n
c
e
o
f
lea
rn
in
g
M
o
ti
v
a
ti
o
n
i
n
El
e
c
tro
n
ic
lea
rn
in
g
:
A
Ne
w
R
u
les
to
P
re
d
ict”
,
T
EL
KOM
NIKA
(
T
e
lec
o
mm
u
n
ica
t
io
n
,
Co
mp
u
ti
n
g
,
El
e
c
tro
n
ics
,
a
n
d
Co
n
tro
l)
,
v
o
l
.
1
5
,
n
o
.
3
,
p
p
1
2
2
3
-
1
2
2
9
,
2
0
1
7
.
[2
0
]
Ba
h
a
ru
d
i
n
A
.
F
.
,
e
t
a
l
.
,
“
Be
h
a
v
io
ra
l
trac
k
in
g
in
E
-
lea
rn
in
g
b
y
u
sin
g
L
e
a
rn
in
g
sty
l
e
s
a
p
p
ro
a
c
h
”
,
IJ
EE
CS
,
v
o
l.
8
,
n
o
.
1
,
p
p
.
1
7
-
2
6
,
O
c
to
b
e
r
2
0
1
7
.
[2
1
]
M
e
tca
lfe J.,
a
n
d
S
h
im
a
m
u
ra
A
,
“
M
e
tac
o
g
n
it
io
n
:
Kn
o
w
in
g
A
b
o
u
t
Kn
o
w
in
g
”
,
Bra
d
f
o
rd
Bo
o
k
s,
Ca
m
b
rid
g
e
,
1
9
9
4
.
[2
2
]
F
lav
e
ll
,
J.
H.,
“
M
e
tac
o
g
n
it
io
n
a
n
d
Co
g
n
it
iv
e
M
o
n
it
o
ri
n
g
:
A
N
e
w
A
re
a
o
f
Co
g
n
it
iv
e
–
d
e
v
e
lo
p
m
e
n
tal
In
q
u
iry
”
,
Ame
ric
a
n
P
sy
c
h
o
l
o
g
ist
,
v
o
l.
3
4
,
n
o
.
1
0
,
p
p
.
9
0
6
-
9
1
1
,
1
9
7
9
.
[2
3
]
Ha
m
id
B.
,
e
t
a
l
.,
“
A
r
c
h
it
e
c
tu
ra
l
A
p
p
ro
a
c
h
e
s
f
o
r
S
e
lf
-
H
e
a
li
n
g
S
y
st
e
m
s
B
a
se
d
o
n
M
u
lt
i
A
g
e
n
t
T
e
c
h
n
o
lo
g
ies
”
,
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
E
lec
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l
.
3
,
n
o
.
6
,
p
p
.
7
7
9
-
7
8
3
,
2
0
1
3
.
[2
4
]
L
o
tf
i
E.
,
e
t
a
l
.,
“
T
o
w
a
rd
s
a
S
y
ste
m
o
f
G
u
id
a
n
c
e
,
A
ss
istan
c
e
a
n
d
L
e
a
rn
in
g
A
n
a
l
y
ti
c
s
Ba
s
e
d
o
n
M
u
l
ti
A
g
e
n
t
S
y
ste
m
A
p
p
li
e
d
o
n
S
e
rio
u
sG
a
m
e
s”
,
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
El
e
c
trica
l
a
n
d
Co
m
p
u
ter
En
g
in
e
e
rin
g
(
IJ
EC
E)
,
v
o
l.
5
,
n
o
.
2
,
p
p
.
3
4
4
-
3
5
4
,
2
0
1
5
.
[2
5
]
Ha
m
id
B.
,
e
t
a
l
.,
“
M
u
lt
i
-
A
g
e
n
t
Ap
p
r
o
a
c
h
f
o
r
F
a
c
in
g
Ch
a
ll
e
n
g
e
s in
Ultra
-
L
a
r
g
e
S
c
a
le
s
y
ste
m
s”
,
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
),
v
o
l.
4
,
n
o
.
2
,
p
p
.
1
5
1
-
1
5
4
,
2
0
1
4
.
[2
6
]
G
re
g
g
D
a
w
n
G
,
“
E
-
lea
rn
in
g
A
g
e
n
ts”
,
T
h
e
L
e
a
rn
i
n
g
Or
g
a
n
iza
t
io
n
,
v
o
l.
1
4
,
n
o
.
4
,
p
p
.
3
0
0
-
3
1
2
,
2
0
0
7.
[2
7
]
A
rie
f
Hid
a
y
a
t,
V
icto
r
G
a
y
u
h
Uto
m
o
,
“
A
d
a
p
ti
v
e
On
li
n
e
M
o
d
u
le
P
r
o
to
ty
p
e
f
o
r
L
e
a
rn
in
g
Un
if
ied
M
o
d
e
ll
in
g
L
a
n
g
u
a
g
e
(UML
)”
,
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
(
IJ
ECE
)
,
v
o
l.
6
,
n
o
.
6
,
p
p
.
2
9
3
1
-
2
9
3
8
,
2
0
1
6
.
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
H
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Evaluation Warning : The document was created with Spire.PDF for Python.
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Evaluation Warning : The document was created with Spire.PDF for Python.