I
nte
rna
t
io
na
l J
o
urna
l o
f
E
v
a
lua
t
io
n a
nd
Resea
rc
h in E
du
ca
t
io
n (
I
J
E
RE
)
Vo
l.
15
,
No
.
3
,
J
u
n
e
20
26
,
p
p
.
2690
~
2
6
9
9
I
SS
N:
2
2
5
2
-
8
8
2
2
,
DOI
: 1
0
.
1
1
5
9
1
/
ijer
e
.
v
15
i
3
.
3
7
8
2
2
2690
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ere.
ia
esco
r
e.
co
m
Aca
demic eng
a
g
e
ment and a
r
tif
icia
l int
ellig
en
ce plat
f
o
rm
beha
v
io
rs
in
g
ra
mm
a
r achiev
eme
nt
Wa
ng
Ya
da
n
1
,
So
o
n Sin
g
h B
ik
a
r
Sin
g
h
1
,
Co
nn
ie
Sh
in
1
,
Z
heng
J
un
ca
i
2
,
Z
ha
ng
Q
ia
nq
i
a
n
2
1
F
a
c
u
l
t
y
o
f
Ed
u
c
a
t
i
o
n
a
n
d
S
p
o
r
t
s S
t
u
d
i
e
s,
U
n
i
v
e
r
si
t
i
M
a
l
a
y
si
a
S
a
b
a
h
,
K
o
t
a
K
i
n
a
b
a
l
u
,
M
a
l
a
y
si
a
2
S
c
h
o
o
l
o
f
I
n
t
e
r
n
a
t
i
o
n
a
l
S
t
u
d
i
e
s
,
G
u
a
n
g
z
h
o
u
X
i
n
h
u
a
U
n
i
v
e
r
s
i
t
y
,
G
u
a
n
g
z
h
o
u
,
C
h
i
n
a
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
No
v
23
,
2
0
2
5
R
ev
is
ed
Mar
12
,
2
0
2
6
Acc
ep
ted
Mar
28
,
2
0
2
6
Th
is
stu
d
y
is
a
m
o
n
g
t
h
e
first
to
u
se
a
rc
h
iv
a
l
i
n
stit
u
ti
o
n
a
l
re
c
o
r
d
s
to
tes
t
t
h
e
in
c
re
m
e
n
tal
v
a
li
d
it
y
o
f
a
rti
ficia
l
in
telli
g
e
n
c
e
p
latfo
rm
b
e
h
a
v
i
o
rs
(
AI_
in
d
e
x
)
in
p
re
d
ictin
g
g
ra
m
m
a
r
a
c
h
iev
e
m
e
n
t
(G
A)
.
Us
in
g
d
a
ta
f
ro
m
4
0
5
non
–
E
n
g
li
s
h
-
m
a
jo
r
fre
sh
m
e
n
e
n
r
o
ll
e
d
i
n
a
c
o
m
p
u
lso
r
y
g
ra
m
m
a
r
c
o
u
rse
a
t
a
p
riv
a
te
C
h
in
e
se
u
n
i
v
e
rsity
,
we
e
x
a
m
in
e
d
wh
e
th
e
r
AI
_
in
d
e
x
p
re
d
ict
s
e
n
d
-
of
-
se
m
e
ste
r
g
ra
m
m
a
r
e
x
a
m
p
e
rfo
rm
a
n
c
e
b
e
y
o
n
d
c
o
u
rse
-
e
m
b
e
d
d
e
d
b
e
h
a
v
i
o
ra
l
a
c
a
d
e
m
ic
e
n
g
a
g
e
m
e
n
t
(AE_
in
d
e
x
).
AE_
in
d
e
x
wa
s
d
e
riv
e
d
fro
m
g
ra
d
e
-
b
o
o
k
q
u
izz
e
s
a
n
d
c
las
s
in
tera
c
ti
o
n
s,
wh
e
re
a
s
AI_
i
n
d
e
x
wa
s
c
o
n
stru
c
ted
fr
o
m
in
stit
u
ti
o
n
a
l
p
latfo
rm
lo
g
s
c
a
p
tu
ri
n
g
c
o
u
rse
wo
rk
c
o
m
p
letio
n
a
n
d
a
ss
ig
n
e
d
v
id
e
o
v
iew
in
g
.
In
d
ice
s
we
re
sc
a
led
to
a
0
–
1
0
0
ra
n
g
e
,
a
n
d
GA
wa
s
m
e
a
su
re
d
b
y
a
u
n
ifi
e
d
fi
n
a
l
e
x
a
m
.
De
sc
rip
ti
v
e
sta
ti
stics
,
c
o
rre
latio
n
s,
a
n
d
h
iera
rc
h
ica
l
re
g
r
e
ss
io
n
a
n
a
ly
se
s
s
h
o
we
d
th
a
t
AE
_
i
n
d
e
x
wa
s
a
sm
a
ll
b
u
t
si
g
n
ifi
c
a
n
t
p
re
d
icto
r
o
f
e
x
a
m
p
e
rf
o
rm
a
n
c
e
,
wh
e
re
a
s
AI_
in
d
e
x
wa
s
we
a
k
a
n
d
n
o
n
-
si
g
n
ifi
c
a
n
t
a
n
d
a
d
d
e
d
n
o
in
c
re
m
e
n
tal
p
re
d
ic
ti
v
e
v
a
lu
e
b
e
y
o
n
d
AE
_
in
d
e
x
.
T
o
g
e
t
h
e
r,
th
e
two
in
d
ice
s
e
x
p
lain
e
d
a
m
o
d
e
st
p
ro
p
o
rti
o
n
o
f
v
a
rian
c
e
in
GA
.
Th
e
se
fin
d
in
g
s
su
g
g
e
st
th
a
t
c
o
m
p
leti
o
n
-
b
a
se
d
p
latf
o
rm
m
e
tri
c
s
a
re
u
n
li
k
e
ly
to
re
flec
t
e
ffo
rtfu
l
lea
rn
in
g
u
n
les
s
p
latfo
rm
t
a
sk
s
a
li
g
n
with
su
m
m
a
ti
v
e
a
ss
e
ss
m
e
n
t
d
e
m
a
n
d
s
(e
.
g
.
,
tran
sla
ti
o
n
a
n
d
p
r
o
o
fre
a
d
in
g
).
Th
e
fin
d
in
g
s
c
a
u
ti
o
n
a
g
a
i
n
st
u
sin
g
c
o
m
p
leti
o
n
-
b
a
se
d
AI
m
e
tri
c
s
a
s
h
ig
h
-
sta
k
e
s in
d
ica
to
rs wit
h
o
u
t
d
e
m
o
n
stra
ted
tas
k
–
a
ss
e
ss
m
e
n
t
a
li
g
n
m
e
n
t.
K
ey
w
o
r
d
s
:
Aca
d
em
ic
en
g
ag
e
m
en
t
Ar
tific
ial
in
tellig
en
ce
Gr
am
m
ar
ac
h
iev
e
m
en
t
Hig
h
er
ed
u
ca
tio
n
Platfo
r
m
b
eh
a
v
io
r
s
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
So
o
n
Sin
g
h
B
ik
ar
Sin
g
h
Facu
lty
o
f
E
d
u
ca
tio
n
a
n
d
Sp
o
r
ts
Stu
d
ies,
Un
iv
er
s
iti Ma
lay
s
ia
Sab
ah
Ko
ta
Kin
ab
alu
8
8
4
0
0
,
Sab
ah
,
Ma
lay
s
ia
E
m
ail: so
o
n
b
s
@
u
m
s
.
ed
u
.
m
y
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
r
ev
iew
is
o
r
g
an
ized
ar
o
u
n
d
th
r
ee
th
em
es:
i
)
AI
in
lan
g
u
ag
e
ed
u
ca
tio
n
an
d
lear
n
in
g
an
aly
tics
;
ii
)
en
g
a
g
em
en
t
–
ac
h
iev
em
en
t
lin
k
s
;
an
d
iii
)
g
r
a
m
m
ar
p
e
d
ag
o
g
y
a
n
d
ass
ess
m
en
t
alig
n
m
en
t.
W
ith
in
ea
ch
th
em
e,
e
v
id
en
ce
is
s
y
n
th
esize
d
at
t
h
e
c
o
n
s
tr
u
ct
le
v
el.
T
h
e
r
a
p
id
d
e
v
elo
p
m
en
t o
f
ar
tific
ial
i
n
tellig
en
ce
(
AI
)
h
as
a
m
ajo
r
im
p
ac
t
o
n
ed
u
ca
tio
n
.
As
h
ig
h
lig
h
ted
in
UNE
SC
O
p
o
licy
g
u
id
an
ce
,
b
o
th
o
p
p
o
r
tu
n
ities
an
d
r
is
k
s
ex
is
t,
p
ar
ticu
lar
ly
r
eg
a
r
d
in
g
in
clu
s
io
n
an
d
eq
u
ity
in
th
e
d
e
p
lo
y
m
e
n
t o
f
AI
in
ed
u
ca
tio
n
[
1
]
.
Sp
ec
i
f
ically
,
in
lan
g
u
a
g
e
ed
u
ca
tio
n
,
AI
to
o
ls
ca
n
p
r
o
v
i
d
e
r
ea
l
-
tim
e
f
ee
d
b
ac
k
[
2
]
,
b
u
t
t
h
eir
ef
f
ec
tiv
en
ess
h
in
g
es
o
n
e
d
u
ca
to
r
s
’
ab
ilit
y
to
in
teg
r
ate
th
em
in
t
o
teac
h
in
g
p
r
ac
tices;
o
v
er
-
r
elian
ce
o
n
AI
-
g
en
er
ated
co
r
r
ec
tio
n
s
m
a
y
r
esu
lt
in
p
ass
iv
e
lear
n
in
g
an
d
s
u
r
f
ac
e
-
lev
el
e
n
g
ag
em
e
n
t
[
3
]
.
I
n
p
ar
allel
to
g
en
er
al
d
ev
elo
p
m
en
ts
,
AI
-
m
ed
iated
lan
g
u
ag
e
in
s
tr
u
ctio
n
h
as
b
ee
n
em
p
ir
ica
lly
ex
am
in
ed
with
u
n
iv
e
r
s
ity
E
n
g
lis
h
as
a
f
o
r
ei
g
n
lan
g
u
ag
e
(
E
FL
)
lear
n
er
s
in
C
h
in
a
[
4
]
.
Mo
v
in
g
f
r
o
m
in
d
iv
id
u
al
in
s
tr
u
ctio
n
al
co
n
te
x
ts
to
b
r
o
ad
e
r
ap
p
licatio
n
s
,
r
ec
e
n
t
wo
r
k
o
n
i
n
teg
r
atin
g
co
r
p
o
r
a
an
d
g
en
er
ativ
e
ar
tific
i
al
in
tellig
en
ce
(
Gen
AI
)
with
in
d
ata
-
d
r
iv
e
n
lear
n
in
g
(
DDL
)
h
ig
h
lig
h
ts
b
o
th
n
ew
p
o
s
s
ib
ilit
ies
an
d
lim
itatio
n
s
,
in
clu
d
in
g
lim
ited
tr
ac
k
in
g
in
c
o
r
p
u
s
-
b
ased
ap
p
r
o
ac
h
es
an
d
p
o
ten
tial
in
ac
cu
r
ac
ies
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
E
v
al
&
R
es E
d
u
c
I
SS
N:
2252
-
8
8
2
2
A
ca
d
emic
en
g
a
g
eme
n
t a
n
d
a
r
tifi
cia
l in
tellig
en
ce
p
la
tfo
r
m
b
e
h
a
vio
r
s
in
g
r
a
mma
r
a
ch
ieve
m
en
t
(
Wa
n
g
Ya
d
a
n
)
2691
in
Gen
AI
o
u
tp
u
ts
[
5
]
.
At
th
e
s
y
s
tem
lev
el,
in
f
o
r
m
atio
n
s
y
s
tem
p
latf
o
r
m
s
m
ay
s
u
p
p
o
r
t
lea
r
n
in
g
wh
en
c
o
u
r
s
e
m
an
ag
em
en
t
an
d
p
latf
o
r
m
d
e
s
ig
n
(
e.
g
.
,
g
u
id
an
ce
an
d
r
ea
l
-
tim
e
f
ee
d
b
ac
k
)
ali
g
n
with
l
ea
r
n
er
s
’
n
ee
d
s
an
d
co
u
r
s
e
r
eq
u
ir
em
en
ts
.
Ho
wev
er
,
lim
ited
r
eso
u
r
ce
s
a
n
d
a
d
ap
tab
ilit
y
m
ay
h
in
d
e
r
ac
ad
em
ic
s
u
cc
ess
[
6
]
.
Acc
o
r
d
in
g
ly
,
it
is
im
p
o
r
ta
n
t
to
r
ec
o
g
n
ize
th
at
co
m
p
leti
o
n
-
b
ased
p
latf
o
r
m
r
ec
o
r
d
s
m
ay
u
n
d
er
r
ep
r
esen
t
ef
f
o
r
tf
u
l
lear
n
in
g
.
T
a
k
en
to
g
eth
er
,
th
is
liter
atu
r
e
s
u
g
g
ests
th
at
p
latf
o
r
m
lo
g
s
o
f
te
n
ca
p
tu
r
e
ex
p
o
s
u
r
e
o
r
co
m
p
lian
ce
,
a
n
d
th
eir
in
ter
p
r
et
ab
ilit
y
as lea
r
n
in
g
in
d
icato
r
s
d
ep
en
d
s
o
n
task
–
ass
ess
m
en
t a
li
g
n
m
en
t.
T
u
r
n
in
g
to
th
e
co
n
n
ec
tio
n
b
et
wee
n
en
g
ag
em
e
n
t
an
d
ac
h
ie
v
em
en
t,
s
tu
d
en
ts
’
ac
ad
em
ic
en
g
ag
em
en
t
h
as
b
ee
n
lin
k
ed
to
o
u
tco
m
es
s
u
ch
as
test
s
co
r
es
an
d
g
r
ad
es
in
r
esear
ch
[
7
]
.
E
n
g
a
g
em
en
t
is
wid
ely
r
eg
ar
d
e
d
as
a
m
u
ltid
im
e
n
s
io
n
al
co
n
s
tr
u
c
t
with
b
eh
a
v
io
r
al,
em
o
tio
n
a
l,
an
d
co
g
n
itiv
e
co
m
p
o
n
en
t
s
[
8
]
.
B
eh
av
io
r
al
en
g
ag
em
e
n
t
in
v
o
lv
es
o
n
-
task
atten
tio
n
,
ef
f
o
r
t,
an
d
p
e
r
s
is
ten
ce
;
em
o
tio
n
al
en
g
ag
e
m
en
t
r
ef
lects
task
-
f
ac
ilit
atin
g
em
o
tio
n
s
;
an
d
co
g
n
itiv
e
en
g
ag
em
e
n
t
in
v
o
lv
es
d
ee
p
lear
n
in
g
an
d
s
elf
-
r
eg
u
lat
o
r
y
s
tr
ateg
ies
[
9
]
.
I
n
tech
n
o
lo
g
y
-
e
n
h
an
ce
d
E
FL
c
o
n
te
x
ts
,
s
t
r
u
ct
u
r
e
d
d
ig
ita
l
p
a
r
ti
ci
p
at
io
n
h
as
b
e
e
n
ass
o
ci
at
ed
w
it
h
i
m
p
r
o
v
e
d
lan
g
u
ag
e
lear
n
in
g
o
u
tco
m
es,
in
clu
d
in
g
s
p
ea
k
in
g
p
e
r
f
o
r
m
a
n
ce
in
a
Fli
p
g
r
id
-
b
ased
p
r
o
g
r
am
with
J
o
r
d
an
ian
ad
o
lescen
t
E
FL
lear
n
er
s
[
1
0
]
an
d
g
r
a
m
m
ar
lea
r
n
in
g
o
u
tco
m
es
in
g
a
m
if
ied
o
n
lin
e
E
n
g
li
s
h
co
u
r
s
es
in
T
h
ai
h
ig
h
er
ed
u
ca
tio
n
[
1
1
]
.
Me
ta
-
an
aly
tic
ev
id
en
ce
f
u
r
th
er
s
u
p
p
o
r
ts
p
o
s
itiv
e
en
g
a
g
e
m
en
t
–
ac
h
iev
em
e
n
t
ass
o
ciatio
n
s
in
g
en
er
al
ed
u
c
atio
n
(
r
=
0
.
2
7
)
[
1
2
]
an
d
s
ec
o
n
d
-
lan
g
u
ag
e
lea
r
n
in
g
(
r
=
0
.
2
3
)
,
with
s
tr
o
n
g
er
ass
o
ciatio
n
s
wh
en
en
g
ag
em
e
n
t
is
m
ea
s
u
r
ed
o
v
e
r
a
lear
n
in
g
u
n
it
r
ath
er
th
a
n
as
a
s
in
g
le
task
o
r
g
e
n
er
al
m
ea
s
u
r
e
[
1
3
]
.
Acc
o
r
d
in
g
ly
,
t
h
e
p
r
esen
t
s
tu
d
y
f
o
cu
s
es
o
n
co
u
r
s
e
-
em
b
ed
d
ed
b
e
h
av
io
r
al
ac
a
d
em
ic
en
g
ag
e
m
en
t
(
AE
_
in
d
ex
)
ca
p
tu
r
e
d
in
in
s
titu
tio
n
al
r
ec
o
r
d
s
,
r
ath
er
th
a
n
s
elf
-
r
ep
o
r
ted
em
o
tio
n
al
o
r
co
g
n
i
tiv
e
en
g
ag
em
e
n
t,
to
alig
n
with
th
e
an
aly
tics
p
u
r
p
o
s
e
o
f
m
o
d
elin
g
v
ar
ian
ce
in
th
e
s
am
e
co
u
r
s
e
’
s
s
u
m
m
ativ
e
g
r
a
m
m
ar
ac
h
ie
v
em
en
t
(
GA)
an
d
AI
p
latf
o
r
m
b
e
h
a
v
i
o
r
s
(
A
I
_
i
n
d
ex
)
.
Gr
am
m
ar
r
em
ain
s
a
ce
n
tr
al
is
s
u
e
in
L
2
p
ed
a
g
o
g
y
,
a
n
d
ea
r
ly
f
o
r
m
-
f
o
cu
s
ed
wo
r
k
p
r
o
v
id
es
a
k
n
o
wled
g
e
b
ase
f
o
r
s
u
b
s
eq
u
en
t m
ea
n
in
g
-
f
o
cu
s
ed
lear
n
in
g
[
1
4
]
.
I
n
g
r
am
m
a
r
ass
ess
m
en
t,
test
ta
s
k
s
an
d
s
co
r
e
in
ter
p
r
etatio
n
s
s
h
o
u
ld
b
e
g
u
i
d
ed
b
y
th
e
test
p
u
r
p
o
s
e
an
d
r
ef
lect
r
elev
a
n
t
tar
g
et
lan
g
u
a
g
e
u
s
e
(
T
L
U)
task
s
(
i.e
.
,
test
au
t
h
en
ticity
)
[
1
5
]
.
E
v
id
en
ce
f
r
o
m
a
s
y
s
tem
atic
r
ev
iew
o
f
o
n
lin
e
h
ig
h
er
ed
u
ca
tio
n
s
h
o
ws
th
at
s
elf
-
r
eg
u
lated
lear
n
in
g
(
SR
L
)
s
tr
ateg
ies
—
esp
ec
ially
t
i
m
e
m
an
ag
em
en
t,
m
etac
o
g
n
itio
n
,
an
d
ef
f
o
r
t
r
eg
u
latio
n
—
ar
e
s
ig
n
if
ican
tly
b
u
t
wea
k
ly
ass
o
ciate
d
with
ac
ad
em
ic
ac
h
iev
em
en
t
[
1
6
]
,
an
d
SR
L
is
co
m
m
o
n
ly
f
r
am
ed
as
e
n
co
m
p
ass
in
g
c
o
g
n
itiv
e,
m
etac
o
g
n
itiv
e,
b
e
h
av
io
r
al,
m
o
tiv
atio
n
al,
an
d
em
o
tio
n
al/af
f
ec
tiv
e
p
r
o
ce
s
s
es
[
1
7
]
.
T
h
ese
f
in
d
in
g
s
s
u
g
g
est
th
at
in
teg
r
atin
g
tr
ad
itio
n
al
an
d
AI
-
ass
is
ted
s
tr
at
eg
ies
co
u
ld
s
u
p
p
o
r
t
lan
g
u
ag
e
lear
n
in
g
[
1
8
]
.
Fro
m
a
v
alid
ity
p
er
s
p
ec
tiv
e,
r
esp
o
n
s
e
f
o
r
m
ats
an
d
task
d
em
a
n
d
s
ar
e
ce
n
tr
al
to
wh
at
g
r
am
m
ar
s
co
r
es c
an
m
ea
n
in
g
f
u
lly
r
ep
r
esen
t.
Desp
ite
th
ese
in
s
ig
h
ts
,
th
e
p
r
o
b
lem
r
em
ain
s
t
h
at
ev
id
e
n
ce
is
s
till
lim
ited
o
n
th
e
jo
in
t
a
n
d
in
cr
em
en
tal
co
n
tr
ib
u
tio
n
s
o
f
co
u
r
s
e
-
em
b
e
d
d
ed
b
eh
av
io
r
al
ac
a
d
em
ic
e
n
g
a
g
em
en
t
a
n
d
AI
p
latf
o
r
m
b
e
h
a
v
io
r
s
to
s
u
m
m
ativ
e
GA
in
p
r
iv
ate
C
h
in
ese
u
n
iv
er
s
ities
.
Ad
d
r
ess
in
g
th
is
g
ap
ca
n
in
f
o
r
m
th
e
p
ed
ag
o
g
ical
in
teg
r
atio
n
o
f
AI
-
s
u
p
p
o
r
ted
r
eso
u
r
ce
s
in
g
r
am
m
ar
co
u
r
s
es.
T
h
e
k
e
y
em
p
ir
ical
is
s
u
e
is
wh
eth
er
AI
p
latf
o
r
m
b
eh
av
io
r
al
r
ec
o
r
d
s
(
e.
g
.
,
c
o
m
p
letio
n
-
b
ased
tr
ac
es
)
p
r
o
v
id
e
in
c
r
em
en
tal
p
r
ed
icti
v
e
v
alu
e
f
o
r
g
r
am
m
a
r
ex
am
p
er
f
o
r
m
a
n
ce
b
e
y
o
n
d
co
u
r
s
e
-
em
b
e
d
d
ed
b
eh
av
io
r
al
ac
ad
em
ic
en
g
ag
e
m
en
t
d
er
i
v
e
d
f
r
o
m
in
s
titu
tio
n
al
co
u
r
s
e
r
e
co
r
d
s
.
T
h
is
is
s
u
e
i
s
esp
ec
ially
s
alien
t
wh
en
p
latf
o
r
m
tr
ac
es
p
r
im
ar
ily
r
e
f
lect
task
co
m
p
letio
n
,
w
h
er
ea
s
th
e
s
u
m
m
ativ
e
g
r
a
m
m
ar
ex
am
tar
g
ets
s
p
ec
if
ic
r
esp
o
n
s
e
f
o
r
m
ats
an
d
elicited
a
b
ilit
ies
.
B
ec
au
s
e
ex
p
ec
te
d
r
esp
o
n
s
e
t
y
p
es
ar
e
d
ef
in
e
d
b
y
th
e
task
in
p
u
t
an
d
p
r
o
v
id
e
th
e
b
asis
f
o
r
s
co
r
e
-
b
ased
in
f
e
r
en
ce
s
ab
o
u
t
g
r
am
m
atica
l
k
n
o
wled
g
e,
m
is
m
atch
es
i
n
task
/r
esp
o
n
s
e
f
o
r
m
ats ca
n
wea
k
en
th
e
in
ter
p
r
etab
ilit
y
o
f
p
latf
o
r
m
tr
ac
es a
s
p
r
ed
icto
r
s
o
f
e
x
a
m
o
u
tco
m
es
[
1
5
]
.
I
n
th
is
co
u
r
s
e,
p
latf
o
r
m
lo
g
s
ca
p
tu
r
e
c
o
m
p
letio
n
-
o
r
ie
n
ted
,
au
to
-
s
co
r
e
d
p
r
ac
tice,
wh
ile
th
e
ex
am
r
eq
u
ir
es
co
n
s
tr
u
cted
-
r
esp
o
n
s
e
p
r
o
o
f
r
ea
d
in
g
an
d
tr
an
s
latio
n
;
th
is
m
is
m
atch
i
n
f
o
r
m
at
m
ay
wea
k
en
th
e
r
elatio
n
s
h
ip
b
etwe
en
AI
p
latf
o
r
m
b
e
h
av
io
r
s
a
n
d
GA
.
T
h
e
p
r
esen
t
s
tu
d
y
ex
am
i
n
es
wh
eth
e
r
co
u
r
s
e
-
em
b
ed
d
e
d
b
eh
av
io
r
al
ac
a
d
em
ic
en
g
ag
em
en
t
an
d
AI
p
latf
o
r
m
b
eh
av
i
o
r
s
p
r
ed
ict
GA
in
a
co
m
p
u
ls
o
r
y
g
r
am
m
ar
c
o
u
r
s
e
at
a
p
r
iv
ate
C
h
in
ese
u
n
iv
e
r
s
ity
.
Fig
u
r
e
1
illu
s
tr
ates
th
e
co
n
ce
p
tu
al
m
o
d
el,
s
p
ec
if
y
i
n
g
AE
_
i
n
d
ex
an
d
AI
_
in
d
ex
as
co
n
cu
r
r
en
t
p
r
ed
icto
r
s
o
f
GA
,
with
p
ar
ticu
lar
atten
tio
n
to
th
e
in
cr
em
en
tal
co
n
tr
i
b
u
tio
n
o
f
AI
_
in
d
ex
b
e
y
o
n
d
AE
_
in
d
ex
.
GA
is
m
ea
s
u
r
ed
b
y
th
e
p
er
ce
n
tag
e
s
co
r
e
o
n
a
u
n
if
ied
en
d
-
of
-
s
em
ester
ex
am
;
th
e
ex
am
b
lu
ep
r
in
t
an
d
item
f
o
r
m
ats ar
e
r
ep
o
r
ted
in
th
e
m
eth
o
d
s
s
ec
tio
n
.
Fig
u
r
e
1
.
C
o
n
ce
p
tu
al
m
o
d
el
o
f
AE
_
in
d
ex
a
n
d
AI
_
in
d
ex
p
r
e
d
ictin
g
GA
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
15
,
No
.
3
,
J
u
n
e
20
2
6
:
2
6
9
0
-
2
6
9
9
2692
T
h
e
s
tu
d
y
co
n
tr
ib
u
tes
b
y
:
i)
in
teg
r
atin
g
in
s
titu
tio
n
al
g
r
ad
e
-
b
o
o
k
r
ec
o
r
d
s
with
p
latf
o
r
m
tr
ac
es
in
an
au
th
en
tic
co
u
r
s
e
s
ettin
g
;
ii)
o
p
er
atio
n
alizin
g
AE
_
in
d
ex
a
n
d
AI
_
i
n
d
ex
u
s
e
as
b
eh
a
v
io
r
al
co
m
p
o
s
ites
f
o
r
p
r
ed
ictiv
e
v
alid
ity
test
in
g
;
an
d
iii)
o
f
f
er
in
g
p
r
ac
tical
im
p
licatio
n
s
f
o
r
alig
n
in
g
p
latf
o
r
m
ac
tiv
ities
with
ass
es
s
ed
r
esp
o
n
s
e
f
o
r
m
ats
to
s
u
p
p
o
r
t
s
u
s
tain
ed
,
f
o
r
m
-
f
o
c
u
s
ed
g
r
am
m
ar
p
r
ac
tice.
Acc
o
r
d
in
g
ly
,
two
an
aly
tic
q
u
esti
o
n
s
wer
e
ex
am
in
e
d
:
−
Do
AE
_
in
d
ex
an
d
AI
_
in
d
e
x
jo
in
tly
p
r
ed
ict
GA
?
−
Do
es
AI
_
in
d
ex
e
x
p
lain
ad
d
itio
n
al
v
ar
ian
ce
in
GA
b
ey
o
n
d
AE
_
in
d
ex
(
in
cr
em
e
n
tal
v
alid
ity
)
?
2.
M
E
T
H
O
D
2
.
1
.
Resea
rc
h
des
ig
n
a
nd
pa
rt
icipa
nts
T
h
is
s
tu
d
y
u
s
ed
a
q
u
an
titativ
e
co
r
r
elatio
n
al
d
esig
n
with
ar
ch
iv
al
in
s
titu
tio
n
al
r
ec
o
r
d
s
.
I
n
th
is
co
u
r
s
e,
th
e
in
s
titu
tio
n
ally
m
an
d
ated
weig
h
tin
g
s
ch
em
e
was
p
r
eset
in
th
e
AI
p
latf
o
r
m
;
af
ter
co
n
tin
u
o
u
s
-
ass
ess
m
en
t
co
m
p
o
n
en
t
s
co
r
es
wer
e
r
ec
o
r
d
ed
,
th
e
p
latf
o
r
m
au
to
m
atica
l
ly
co
m
p
u
ted
s
tu
d
en
ts
’
u
s
u
al
p
er
f
o
r
m
an
ce
.
On
ce
th
e
in
s
tr
u
cto
r
s
f
in
is
h
ed
m
ar
k
in
g
th
e
en
d
-
of
-
s
em
ester
ex
a
m
,
th
ey
en
ter
e
d
t
h
e
s
co
r
es
i
n
to
th
e
s
y
s
tem
.
T
h
e
p
latf
o
r
m
th
e
n
ca
lcu
lated
th
e
o
v
er
all
co
u
r
s
e
ev
al
u
atio
n
.
All
v
ar
iab
les
ca
m
e
f
r
o
m
a
r
ch
iv
al
in
s
titu
tio
n
al
r
ec
o
r
d
s
,
in
clu
d
in
g
t
h
e
o
f
f
icial
g
r
ad
e
b
o
o
k
an
d
th
e
in
s
titu
tio
n
al
AI
p
latf
o
r
m
.
Par
ticip
an
ts
wer
e
4
0
5
n
o
n
-
E
n
g
lis
h
m
ajo
r
s
in
a
r
eq
u
ir
e
d
E
n
g
lis
h
g
r
am
m
ar
co
u
r
s
e
at
a
p
r
i
v
ate
u
n
iv
er
s
ity
in
s
o
u
th
er
n
C
h
in
a.
T
h
e
d
ata
ca
m
e
f
r
o
m
s
ix
in
tac
t
class
es,
all
f
o
llo
win
g
a
co
m
m
o
n
s
y
llab
u
s
wit
h
a
ce
n
tr
ally
co
o
r
d
in
ate
d
teac
h
in
g
team
.
E
ac
h
class
co
m
p
leted
th
e
s
am
e
co
n
tin
u
o
u
s
ass
es
s
m
en
t
co
m
p
o
n
en
ts
an
d
to
o
k
th
e
s
am
e
en
d
-
of
-
s
em
ester
ex
am
.
T
h
e
co
u
r
s
e
u
s
e
d
a
b
le
n
d
ed
f
o
r
m
at:
f
ac
e
-
to
-
f
ac
e
in
s
tr
u
ctio
n
p
lu
s
r
eq
u
ir
ed
p
latf
o
r
m
-
b
ased
task
s
.
C
o
n
tin
u
o
u
s
ass
es
s
m
en
t,
ca
ll
ed
“
u
s
u
al
p
er
f
o
r
m
a
n
ce
”
,
co
n
t
r
ib
u
ted
6
0
%
o
f
th
e
co
u
r
s
e
g
r
a
d
e.
T
h
e
en
d
-
of
-
s
em
ester
ex
am
co
n
tr
ib
u
ted
th
e
r
e
m
ain
in
g
4
0
%.
2
.
2
.
M
ea
s
ures
All
v
ar
iab
les
wer
e
d
r
awn
f
r
o
m
b
eh
av
io
r
al
r
ec
o
r
d
s
in
th
e
c
o
u
r
s
e
g
r
ad
e
b
o
o
k
an
d
AI
p
lat
f
o
r
m
lo
g
s
.
AE
_
in
d
ex
an
d
AI
_
in
d
e
x
wer
e
co
n
v
er
ted
to
a
0
–
1
0
0
s
ca
le
f
o
r
an
aly
s
is
,
wh
ile
co
m
p
o
n
en
t
s
co
r
es
r
em
ain
ed
o
n
th
eir
o
r
ig
in
al
s
ca
les.
Fig
u
r
e
2
s
h
o
ws
a
b
r
ea
k
d
o
wn
o
f
th
e
u
s
u
al
p
er
f
o
r
m
a
n
ce
(
co
n
tin
u
o
u
s
ass
es
s
m
en
t;
6
0
%)
r
ec
o
r
d
e
d
o
n
th
e
p
latf
o
r
m
.
I
t
also
illu
s
tr
ates
h
o
w
th
e
s
y
s
te
m
ag
g
r
eg
ates
co
m
p
o
n
en
t
s
co
r
es.
AE
_
in
d
ex
an
d
AI
_
in
d
ex
wer
e
d
ef
in
ed
as
f
o
r
m
ativ
e
c
o
m
p
o
s
ites
o
f
co
u
r
s
e
-
em
b
ed
d
e
d
b
e
h
av
io
r
al
co
m
p
o
n
e
n
ts
.
I
n
ter
n
al
co
n
s
is
ten
cy
in
d
ices
(
α
/ω
)
ar
e
r
ep
o
r
ted
d
escr
ip
tiv
ely
,
n
o
t
as
s
ca
le
r
eliab
ilit
y
.
L
o
w
in
ter
n
al
co
n
s
is
ten
cy
v
alu
es
ar
e
th
er
ef
o
r
e
ex
p
ec
ted
a
n
d
d
o
n
o
t
in
d
icate
m
ea
s
u
r
em
en
t d
ef
i
cien
cy
f
o
r
th
ese
f
o
r
m
ativ
e
in
d
icato
r
s
.
All
r
ec
o
r
d
s
wer
e
an
o
n
y
m
ized
an
d
u
s
ed
wi
th
in
s
titu
tio
n
al
ap
p
r
o
v
al.
Fig
u
r
e
2
.
An
o
n
y
m
ized
s
cr
ee
n
s
h
o
t o
f
t
h
e
in
s
titu
tio
n
al
g
r
a
d
e
r
ep
o
r
t sh
o
win
g
ass
ess
m
en
t c
o
m
p
o
n
e
n
ts
an
d
weig
h
ts
u
s
ed
to
d
er
iv
e
AE
_
in
d
ex
an
d
AI
_
in
d
ex
(
illu
s
tr
ativ
e
v
alu
es o
n
ly
)
AE
_
in
d
ex
was
ca
lcu
lated
f
r
o
m
two
co
u
r
s
e
-
em
b
e
d
d
ed
b
eh
av
io
r
al
co
m
p
o
n
en
ts
in
Fig
u
r
e
2
:
q
u
izze
s
(0
–
3
0
)
an
d
class
in
ter
ac
tio
n
(
0
–
1
0
)
.
C
lass
in
ter
ac
tio
n
in
clu
d
ed
an
s
wer
in
g
q
u
esti
o
n
s
(
0
–
5
)
an
d
p
ar
ticip
atio
n
i
n
ac
tiv
ities
(
0
–
5
)
.
Atten
d
an
ce
a
cc
o
u
n
ted
f
o
r
1
0
%
o
f
th
e
o
f
f
ic
ial
s
ch
em
e
b
u
t
was
ex
clu
d
ed
f
r
o
m
th
e
AE
_
in
d
ex
b
ec
au
s
e
n
ea
r
l
y
all
s
tu
d
en
ts
h
ad
p
er
f
ec
t
atten
d
an
ce
.
T
h
is
r
esu
lted
i
n
litt
le
v
a
r
ian
ce
a
n
d
d
id
n
o
t
h
elp
th
e
an
aly
s
is
o
f
in
d
iv
id
u
al
d
if
f
er
e
n
ce
s
.
Atten
d
an
ce
r
em
ain
e
d
p
ar
t
o
f
th
e
o
f
f
icial
g
r
ad
in
g
.
Qu
izze
s
an
d
class
in
ter
ac
tio
n
wer
e
s
u
m
m
ed
(
0
–
4
0
)
an
d
co
n
v
er
ted
to
a
0
–
1
0
0
s
co
r
e.
AE
_
in
d
ex
was
s
p
ec
if
ied
as
a
f
o
r
m
ativ
e
co
m
p
o
s
ite
b
ec
au
s
e
its
co
m
p
o
n
en
ts
m
ea
s
u
r
e
d
is
tin
ct
asp
ec
ts
o
f
en
g
ag
em
e
n
t.
I
n
ter
n
al
co
n
s
is
ten
cy
is
r
ep
o
r
ted
d
escr
ip
tiv
ely
(
α
=
0
.
5
5
0
; ω
_
to
ta
l=0
.
6
3
4
)
.
C
o
llin
ea
r
ity
am
o
n
g
co
m
p
o
n
en
ts
was n
eg
lig
ib
le
(
al
l
v
ar
ian
ce
in
f
latio
n
f
ac
to
r
(
VI
Fs
)
≤
1
.
4
4
3
)
.
AI
_
in
d
ex
was
co
m
p
u
ted
f
r
o
m
th
e
p
latf
o
r
m
-
lo
g
g
ed
weig
h
ted
co
m
p
o
n
en
ts
in
Fig
u
r
e
2
:
co
u
r
s
ewo
r
k
(0
–
3
0
)
an
d
p
latf
o
r
m
-
tr
ac
k
ed
v
id
eo
v
iewin
g
co
m
p
letio
n
(
0
–
2
0
)
.
T
h
e
s
u
m
m
ed
s
co
r
e
(
0
–
5
0
)
was
co
n
v
er
ted
t
o
a
0
–
1
0
0
s
co
r
e
an
d
is
i
n
ter
p
r
eted
as
a
c
o
u
r
s
e
-
em
b
ed
d
e
d
i
n
d
icat
o
r
o
f
p
latf
o
r
m
p
a
r
ticip
atio
n
r
a
th
er
th
a
n
d
ep
th
o
f
co
g
n
itiv
e
p
r
o
ce
s
s
in
g
.
C
o
u
r
s
e
wo
r
k
co
n
s
is
ted
o
f
u
n
it
-
lev
el
g
r
am
m
ar
d
r
ills
,
au
to
-
s
co
r
ed
q
u
izze
s
,
an
d
s
h
o
r
t
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
E
v
al
&
R
es E
d
u
c
I
SS
N:
2252
-
8
8
2
2
A
ca
d
emic
en
g
a
g
eme
n
t a
n
d
a
r
tifi
cia
l in
tellig
en
ce
p
la
tfo
r
m
b
e
h
a
vio
r
s
in
g
r
a
mma
r
a
ch
ieve
m
en
t
(
Wa
n
g
Ya
d
a
n
)
2693
p
r
ac
tice
test
s
.
Vid
eo
v
iewin
g
ca
p
tu
r
ed
c
o
m
p
letio
n
o
f
ass
ig
n
ed
in
s
tr
u
ctio
n
al
v
id
e
o
s
an
d
em
b
ed
d
e
d
ch
ec
k
s
.
AI
_
in
d
ex
was
tr
ea
ted
as
a
f
o
r
m
ativ
e
co
m
p
o
s
ite
b
ec
au
s
e
co
u
r
s
ewo
r
k
p
er
f
o
r
m
an
ce
an
d
v
id
eo
-
v
iewin
g
co
m
p
letio
n
ca
p
tu
r
e
co
n
ce
p
tu
a
lly
d
is
tin
ct
f
ac
ets
o
f
p
latf
o
r
m
b
eh
av
i
o
r
th
at
jo
in
tly
d
ef
in
e
t
h
e
in
d
icato
r
r
ath
e
r
th
an
r
ef
lectin
g
a
s
in
g
le
laten
t t
r
ait.
I
n
ter
n
al
c
o
n
s
is
ten
cy
is
r
ep
o
r
ted
d
escr
ip
tiv
ely
(
α
=0
.
2
8
3
;
ω
_
to
tal=0
.
2
8
5
)
.
GA
was
m
ea
s
u
r
ed
u
s
in
g
th
e
o
f
f
icial
en
d
-
of
-
s
em
ester
ex
am
(
0
–
1
0
0
)
.
T
est
s
co
r
e
in
ter
p
r
etatio
n
an
d
in
ten
d
ed
u
s
e
f
o
llo
wed
c
o
n
tem
p
o
r
ar
y
v
alid
ity
th
e
o
r
y
,
wh
ich
f
o
cu
s
es
o
n
th
e
a
p
p
r
o
p
r
iaten
es
s
o
f
in
f
er
e
n
ce
s
an
d
u
s
es
f
r
o
m
ass
es
s
m
en
t
o
u
tco
m
es
[
1
9
]
.
T
h
e
clo
s
ed
-
b
o
o
k
,
9
0
-
m
in
u
te
ex
am
was
g
iv
en
to
all
class
e
s
s
im
u
ltan
eo
u
s
ly
.
I
t
was
ce
n
tr
a
lly
p
r
ep
ar
e
d
,
r
ev
iewe
d
b
y
th
e
teac
h
in
g
team
,
an
d
g
r
a
d
ed
with
s
tan
d
ar
d
ized
r
u
b
r
ics.
T
h
e
ex
a
m
was
d
esi
g
n
ed
f
o
r
in
s
titu
tio
n
al
s
u
m
m
ativ
e
u
s
e
an
d
m
atch
ed
th
e
s
y
llab
u
s
o
b
jectiv
es
as
s
p
ec
if
ied
in
th
e
in
s
titu
ti
o
n
al
s
y
llab
u
s
[
2
0
]
.
I
t
co
v
er
ed
co
r
e
g
r
am
m
atica
l
ar
ea
s
(
e.
g
.
,
ten
s
e/asp
ec
t,
ag
r
ee
m
en
t,
cla
u
s
e
s
tr
u
ctu
r
e)
u
s
in
g
s
tan
d
ar
d
f
o
r
m
ats:
m
u
ltip
le
-
ch
o
ice,
e
r
r
o
r
id
en
tific
atio
n
o
r
c
o
r
r
ec
tio
n
,
an
d
C
h
in
ese
–
E
n
g
lis
h
tr
an
s
latio
n
r
eq
u
ir
in
g
g
r
a
m
m
atica
lly
co
r
r
e
ct
r
esp
o
n
s
es.
C
o
n
s
tr
u
cted
-
r
esp
o
n
s
e
f
o
r
m
ats
wer
e
in
clu
d
ed
to
ass
ess
lan
g
u
ag
e
u
s
e,
n
o
t
ju
s
t
r
ec
o
g
n
itio
n
.
T
h
e
m
eth
o
d
s
s
ec
tio
n
r
ep
o
r
ts
th
e
e
x
am
b
lu
ep
r
in
t
an
d
item
f
o
r
m
ats
f
o
r
tr
an
s
p
ar
e
n
c
y
.
T
a
b
le
1
p
r
o
v
id
es
t
h
e
b
lu
e
p
r
in
t
a
n
d
f
o
r
m
ats.
T
h
e
ar
ch
i
v
al
d
ataset
lack
ed
item
-
lev
el
r
esp
o
n
s
es a
n
d
r
ater
d
ata,
s
o
r
eliab
ilit
y
in
d
ices c
o
u
ld
n
o
t b
e
co
m
p
u
ted
.
T
ab
le
1
.
B
lu
ep
r
in
t
o
f
th
e
en
d
-
of
-
s
em
ester
ex
am
o
f
th
e
c
o
m
p
u
ls
o
r
y
g
r
a
m
m
ar
c
o
u
r
s
e
P
a
r
t
S
e
c
t
i
o
n
I
t
e
m t
y
p
e
a
n
d
d
e
scr
i
p
t
i
o
n
N
o
.
o
f
i
t
e
ms
P
o
i
n
t
s
p
e
r
i
t
e
m
S
e
c
t
i
o
n
p
o
i
n
t
s
W
e
i
g
h
t
(
%)
I
V
o
c
a
b
u
l
a
r
y
a
n
d
st
r
u
c
t
u
r
e
M
u
l
t
i
p
l
e
-
c
h
o
i
c
e
q
u
e
st
i
o
n
s
a
ssess
i
n
g
g
r
a
mm
a
t
i
c
a
l
f
o
r
ms
a
n
d
v
o
c
a
b
u
l
a
r
y
u
se
20
1
.
5
30
30
II
P
r
o
o
f
r
e
a
d
i
n
g
Er
r
o
r
i
d
e
n
t
i
f
i
c
a
t
i
o
n
/
c
o
r
r
e
c
t
i
o
n
i
n
s
h
o
r
t
sen
t
e
n
c
e
s
o
r
p
a
ss
a
g
e
s
10
1
.
5
15
15
III
S
e
n
t
e
n
c
e
t
r
a
n
s
l
a
t
i
o
n
C
h
i
n
e
se
–
E
n
g
l
i
s
h
s
e
n
t
e
n
c
e
t
r
a
n
sl
a
t
i
o
n
(
f
o
c
u
s
o
n
g
r
a
mm
a
t
i
c
a
l
a
c
c
u
r
a
c
y
)
5
6
.
0
30
30
IV
P
a
r
a
g
r
a
p
h
t
r
a
n
s
l
a
t
i
o
n
C
h
i
n
e
se
–
E
n
g
l
i
s
h
p
a
r
a
g
r
a
p
h
t
r
a
n
sl
a
t
i
o
n
(
o
n
e
p
a
ssa
g
e
;
5
se
n
t
e
n
c
e
s)
1
p
a
ss
a
g
e
2
5
.
0
(
t
o
t
a
l
)
25
25
To
t
a
l
1
0
0
1
0
0
2
.
3
.
Da
t
a
c
o
llect
io
n a
nd
a
na
ly
s
is
A
t
th
e
en
d
o
f
th
e
s
em
ester
,
th
e
teac
h
in
g
team
ex
p
o
r
ted
co
n
tin
u
o
u
s
ass
ess
m
en
t
s
co
r
es
f
r
o
m
th
e
o
f
f
icial
g
r
a
d
e
b
o
o
k
an
d
p
latf
o
r
m
task
r
ec
o
r
d
s
f
r
o
m
th
e
i
n
s
titu
tio
n
al
AI
p
latf
o
r
m
.
Stu
d
e
n
t
id
en
tifie
r
s
wer
e
r
em
o
v
ed
an
d
r
ep
lace
d
with
an
o
n
y
m
ized
c
o
d
es
b
ef
o
r
e
an
aly
s
is
,
an
d
e
x
p
o
r
ted
v
alu
es
wer
e
ch
ec
k
e
d
f
o
r
p
er
m
is
s
ib
le
r
an
g
es
a
n
d
c
o
n
s
is
ten
cy
with
t
h
e
o
f
f
icial
weig
h
t
in
g
s
ch
em
e.
Of
t
h
e
4
1
0
o
r
ig
i
n
al
co
u
r
s
e
r
ec
o
r
d
s
,
f
iv
e
wer
e
ex
clu
d
ed
d
u
e
to
in
c
o
m
p
lete
GA
r
ec
o
r
d
s
ass
o
ciate
d
with
with
d
r
awa
l
o
r
a
leav
e
o
f
a
b
s
en
ce
,
y
ield
in
g
a
f
in
al
a
n
aly
tic
s
am
p
le
o
f
N=
4
0
5
.
Descr
ip
tiv
e
s
tatis
tics
(
m
ea
n
,
s
tan
d
a
r
d
d
ev
iatio
n
,
m
i
n
im
u
m
,
m
ax
im
u
m
)
wer
e
co
m
p
u
ted
f
o
r
AE
_
i
n
d
ex
,
AI
_
in
d
ex
,
an
d
GA
,
a
n
d
s
co
r
e
d
is
tr
ib
u
tio
n
s
wer
e
in
s
p
ec
te
d
f
o
r
p
lau
s
ib
le
r
a
n
g
es
an
d
p
o
ten
tial
o
u
tlier
s
.
Pear
s
o
n
co
r
r
elatio
n
co
e
f
f
icien
ts
wer
e
t
h
en
ca
lcu
lated
to
ex
am
in
e
b
iv
ar
iate
r
elatio
n
s
h
ip
s
am
o
n
g
ac
a
d
em
ic
en
g
ag
em
en
t,
AI
p
latf
o
r
m
b
eh
a
v
io
r
s
,
an
d
GA
.
T
h
ir
d
,
a
s
tan
d
a
r
d
m
u
ltip
le
r
eg
r
ess
io
n
m
o
d
el
was
s
p
ec
if
ied
with
GA
as
th
e
d
ep
en
d
en
t
v
a
r
iab
le
an
d
b
o
t
h
AE
_
in
d
e
x
an
d
AI
_
in
d
ex
as
p
r
ed
icto
r
s
e
n
ter
ed
s
im
u
ltan
eo
u
s
ly
.
T
o
d
ir
e
ctly
a
s
s
es
s
in
cr
em
en
tal
v
alid
ity
,
h
ie
r
ar
ch
ical
r
e
g
r
ess
io
n
was
co
n
d
u
cted
in
two
s
tep
s
:
in
Step
1
,
o
n
ly
AE
_
in
d
ex
was
en
ter
ed
as
a
p
r
ed
icto
r
;
in
Step
2
,
b
o
th
AE
_
i
n
d
ex
a
n
d
AI
_
i
n
d
ex
wer
e
i
n
clu
d
ed
.
T
h
e
ch
an
g
e
in
e
x
p
lain
ed
v
ar
i
an
ce
(
Δ
R
²)
an
d
F
-
ch
a
n
g
e
s
tatis
tics
wer
e
ex
am
in
ed
af
ter
Step
2
to
d
eter
m
in
e
if
th
e
ad
d
itio
n
o
f
AI
_
i
n
d
ex
s
ig
n
if
ican
tly
im
p
r
o
v
ed
m
o
d
el
p
r
ed
ictio
n
.
T
h
e
r
e
g
r
ess
io
n
m
o
d
el
ca
n
b
e
ex
p
r
ess
ed
as
in
(
1
)
:
G
r
a
mma
r
a
c
hie
ve
me
n
t
=
β₀
+
β₁
(
AE
_
in
de
x
)
+
β₂
(
AI
_
in
de
x
)
+
ε
(
1
)
Ass
u
m
p
tio
n
s
o
f
m
u
ltip
le
r
e
g
r
ess
io
n
wer
e
ev
alu
ated
u
s
in
g
r
esid
u
al
p
lo
ts
an
d
n
o
r
m
al
p
r
o
b
ab
ilit
y
(P
–
P)
p
lo
ts
f
o
r
r
esid
u
al
n
o
r
m
ality
[
2
1
]
.
No
m
ajo
r
v
i
o
latio
n
s
wer
e
o
b
s
er
v
ed
.
Mu
ltico
llin
e
ar
ity
was
ch
ec
k
ed
u
s
in
g
to
ler
an
ce
/VI
F
an
d
was
n
eg
lig
ib
le
(
VI
F_
AE
_
in
d
ex
=1
.
1
8
8
;
VI
F_
AI
_
in
d
ex
=1
.
1
8
8
)
.
Statis
tical
s
ig
n
if
ican
ce
was
ev
alu
ated
at
th
e
0
.
0
5
lev
el.
B
o
th
u
n
s
tan
d
ar
d
ized
c
o
ef
f
icien
ts
(
B
)
an
d
s
tan
d
ar
d
ize
d
co
ef
f
icien
ts
(
β)
wer
e
e
x
am
in
e
d
.
Mo
d
el
R
²
was
also
r
ev
iew
ed
.
As
a
r
o
b
u
s
tn
ess
ch
ec
k
,
th
e
r
eg
r
ess
io
n
m
o
d
el
was
r
e
-
esti
m
ated
with
Atten
d
an
ce
as
an
ad
d
itio
n
al
co
v
ar
iate.
R
esu
lt
s
r
em
ain
ed
s
u
b
s
tan
tiv
ely
u
n
ch
a
n
g
ed
,
co
n
s
is
ten
t w
ith
th
e
m
in
im
al
atten
d
an
ce
v
a
r
ian
ce
in
t
h
is
co
h
o
r
t.
2
.
4
.
E
t
hica
l
c
o
ns
idera
t
io
ns
Seco
n
d
ar
y
u
s
e
o
f
co
u
r
s
e
-
r
elat
ed
r
ec
o
r
d
s
w
as
ap
p
r
o
v
e
d
b
y
th
e
u
n
iv
er
s
ity
’
s
ac
ad
em
ic
af
f
air
s
o
f
f
ice
on
1
3
Sep
tem
b
er
2
0
2
5
.
Stu
d
e
n
ts
wer
e
in
f
o
r
m
e
d
at
th
e
b
e
g
in
n
in
g
o
f
th
e
s
em
ester
th
at
d
e
-
id
en
tifie
d
co
u
r
s
e
an
d
p
latf
o
r
m
r
ec
o
r
d
s
m
ig
h
t
b
e
u
s
ed
f
o
r
r
esear
ch
,
a
n
d
th
e
a
p
p
r
o
v
in
g
o
f
f
ice
g
r
a
n
ted
a
waiv
e
r
o
f
wr
itten
in
f
o
r
m
ed
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
15
,
No
.
3
,
J
u
n
e
20
2
6
:
2
6
9
0
-
2
6
9
9
2694
co
n
s
en
t
f
o
r
th
is
m
i
n
im
al
-
r
is
k
s
ec
o
n
d
a
r
y
a
n
aly
s
is
.
On
ly
v
ar
iab
les
r
eq
u
ir
ed
f
o
r
th
e
p
r
esen
t
s
tu
d
y
wer
e
ex
tr
ac
ted
,
an
d
id
e
n
tifie
r
s
wer
e
r
em
o
v
e
d
p
r
io
r
t
o
an
aly
s
is
.
T
h
e
d
e
-
id
e
n
tifie
d
d
ataset
was
s
to
r
ed
o
n
an
ac
ce
s
s
-
co
n
tr
o
lled
,
p
ass
wo
r
d
-
p
r
o
tecte
d
in
s
titu
tio
n
al
d
r
iv
e
r
estricte
d
to
th
e
r
esear
ch
team
an
d
was
n
o
t
s
h
ar
ed
ex
ter
n
ally
(
in
clu
d
i
n
g
with
th
e
p
latf
o
r
m
p
r
o
v
id
er
)
in
id
en
tifi
ab
le
f
o
r
m
.
Fil
es
wer
e
s
to
r
ed
a
n
d
tr
a
n
s
f
er
r
ed
o
n
ly
th
r
o
u
g
h
s
ec
u
r
e
in
s
titu
tio
n
al
c
h
an
n
els.
T
h
e
d
ataset
will
b
e
r
etain
ed
f
o
r
th
r
ee
y
ea
r
s
a
n
d
t
h
en
s
ec
u
r
ely
d
elete
d
.
B
ec
au
s
e
s
o
m
e
m
ea
s
u
r
es
in
v
o
lv
ed
teac
h
er
s
co
r
i
n
g
(
e.
g
.
,
q
u
esti
o
n
s
an
d
ac
tiv
ity
p
ar
tici
p
atio
n
)
,
p
r
ed
ef
in
e
d
s
co
r
in
g
r
u
les
an
d
s
h
ar
ed
g
u
i
d
a
n
ce
with
in
th
e
teac
h
in
g
team
wer
e
u
s
ed
to
r
ed
u
ce
s
u
b
jectiv
ity
;
r
esid
u
al
s
co
r
in
g
b
ias
an
d
p
o
wer
d
y
n
am
ics
ar
e
ac
k
n
o
wled
g
e
d
as
lim
itatio
n
s
.
T
h
e
r
esear
ch
team
ac
ce
s
s
ed
o
n
ly
d
e
-
id
en
tifie
d
in
s
titu
tio
n
al
ex
p
o
r
ts
p
r
o
v
i
d
ed
b
y
th
e
ac
ad
em
ic
af
f
air
s
o
f
f
ice
an
d
h
ad
n
o
ac
ce
s
s
to
p
r
o
v
id
e
r
-
s
id
e
lo
g
s
b
e
y
o
n
d
th
ese
ex
p
o
r
ts
.
T
h
is
d
e
-
id
en
tifi
ca
tio
n
an
d
ac
ce
s
s
-
co
n
tr
o
l
p
r
o
t
o
co
l
im
p
r
o
v
es
tr
an
s
p
ar
en
cy
a
n
d
r
ed
u
ce
s
th
e
r
is
k
th
at
in
s
titu
tio
n
al
an
aly
tics
o
r
co
m
p
letio
n
in
d
icato
r
s
co
u
ld
b
e
u
s
ed
to
d
if
f
er
en
tially
tr
ea
t
i
d
en
tifia
b
le
s
tu
d
en
ts
o
r
in
f
o
r
m
h
i
g
h
-
s
tak
es d
ec
is
io
n
s
with
o
u
t c
o
n
s
tr
u
ct
-
r
elev
a
n
t v
alid
atio
n
.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
Da
t
a
s
cr
ee
nin
g
a
nd
des
cr
iptiv
e
s
t
a
t
is
t
ics
All
an
aly
s
es
u
s
ed
th
e
f
in
al
an
aly
tic
s
am
p
le
(
N=
4
0
5
)
.
Vis
u
al
in
s
p
ec
tio
n
co
n
f
ir
m
ed
th
at
all
r
em
ain
in
g
v
alu
es
f
o
r
c
o
n
tin
u
o
u
s
ass
ess
m
en
t
co
m
p
o
n
en
ts
,
p
latf
o
r
m
t
ask
s
,
an
d
th
e
en
d
-
of
-
s
em
ester
ex
am
f
ell
with
in
p
lau
s
ib
le
r
an
g
es.
No
ex
tr
em
e
o
u
tlier
s
wer
e
id
en
tifie
d
.
Ou
tlier
s
wer
e
s
cr
ee
n
ed
u
s
in
g
b
o
x
p
lo
ts
an
d
z
-
s
co
r
es
(
|
z|
>3
.
2
9
)
; n
o
n
e
m
et
th
e
cr
iter
i
o
n
.
T
ab
le
2
p
r
esen
ts
d
escr
ip
tiv
e
s
t
atis
tics
f
o
r
AE
_
in
d
ex
,
AI
_
in
d
ex
,
an
d
GA
.
AE
_
in
d
ex
an
d
AI
_
in
d
ex
ar
e
in
ter
p
r
eted
as
co
u
r
s
e
-
em
b
e
d
d
ed
b
eh
a
v
io
r
al
c
o
m
p
o
s
ites
d
er
iv
e
d
f
r
o
m
in
s
titu
tio
n
al
r
ec
o
r
d
s
,
n
o
t
as
co
m
p
r
eh
e
n
s
iv
e
m
ea
s
u
r
es
o
f
m
u
ltid
im
en
s
io
n
al
en
g
ag
em
e
n
t.
Descr
ip
tiv
ely
,
AE
_
in
d
ex
(
M
=7
0
.
3
7
,
SD=2
1
.
8
4
)
an
d
AI
_
in
d
ex
(
M=
8
0
.
5
5
,
SD=
1
6
.
3
2
)
s
u
g
g
est
m
o
d
er
ately
h
ig
h
AE
_
in
d
ex
an
d
r
elativ
ely
h
ig
h
p
latf
o
r
m
-
tr
ac
k
ed
task
co
m
p
letio
n
/activ
ity
.
GA
was a
ls
o
r
elativ
ely
h
ig
h
o
n
av
er
ag
e
(
M=
7
7
.
8
2
,
SD=1
2
.
9
3
)
.
T
h
e
o
b
s
er
v
ed
r
an
g
es
s
u
p
p
o
r
t su
b
s
eq
u
en
t c
o
r
r
elatio
n
al
an
d
r
eg
r
ess
io
n
an
aly
s
es.
T
ab
le
2
.
Descr
ip
tiv
e
s
tatis
tics
f
o
r
AE
_
in
d
ex
,
AI
_
in
d
e
x
,
an
d
GA
(
N=
4
0
5
)
V
a
r
i
a
b
l
e
M
e
a
n
SD
M
i
n
M
a
x
B
e
h
a
v
i
o
r
a
l
a
c
a
d
e
m
i
c
e
n
g
a
g
e
me
n
t
(
A
E_
i
n
d
e
x
)
7
0
.
3
7
2
1
.
8
4
1
.
1
5
1
0
0
.
0
0
A
I
p
l
a
t
f
o
r
m
b
e
h
a
v
i
o
r
s
(
A
I
_
i
n
d
e
x
)
8
0
.
5
5
1
6
.
3
2
0
.
5
5
9
9
.
7
7
GA
7
7
.
8
2
1
2
.
9
3
7
.
5
0
9
8
.
5
0
3
.
2
.
Co
rr
el
a
t
io
ns
a
mo
ng
AE
_
ind
ex
,
AI_
ind
ex
,
a
nd
g
ra
mm
a
r
a
chiev
e
m
ent
Pear
s
o
n
co
r
r
elatio
n
s
am
o
n
g
AE
_
in
d
ex
,
AI
_
in
d
e
x
,
an
d
GA
ar
e
r
ep
o
r
ted
in
T
a
b
le
3
.
A
E
_
in
d
ex
a
n
d
AI
_
in
d
ex
wer
e
m
o
d
e
r
ately
a
n
d
p
o
s
itiv
ely
c
o
r
r
elate
d
(
r
=
0
.
3
9
8
,
p
<
0
.
0
0
1
)
.
T
h
is
in
d
icate
s
th
at
s
tu
d
en
ts
wh
o
o
b
tain
ed
h
i
g
h
er
s
co
r
es
o
n
c
o
u
r
s
e
-
em
b
e
d
d
ed
b
eh
av
i
o
r
al
c
o
m
p
o
n
en
ts
(
q
u
izze
s
an
d
class
in
ter
ac
tio
n
)
also
ten
d
ed
to
s
h
o
w
h
ig
h
er
p
latf
o
r
m
-
tr
ac
k
e
d
co
u
r
s
ewo
r
k
p
e
r
f
o
r
m
an
ce
an
d
o
n
lin
e
r
eso
u
r
c
e
co
m
p
letio
n
.
T
h
is
p
atter
n
m
ay
in
d
icate
th
at
s
tu
d
en
ts
wh
o
en
g
ag
e
m
o
r
e
co
n
s
is
ten
tly
in
o
n
e
co
u
r
s
e
co
m
p
o
n
en
t
also
d
o
s
o
in
o
th
er
r
eq
u
ir
ed
c
o
m
p
o
n
en
ts
.
GA
s
h
o
wed
a
s
m
all
b
u
t
s
tati
s
tically
s
ig
n
if
ican
t
p
o
s
itiv
e
ass
o
ciati
o
n
with
AE
_
in
d
ex
(r=
0
.
2
2
1
,
p
<
0
.
0
0
1
)
.
T
h
is
s
u
g
g
ests
th
at
h
ig
h
er
AE
_
in
d
ex
was
ass
o
ciate
d
with
h
ig
h
er
e
n
d
-
of
-
s
em
ester
ex
am
s
co
r
es.
T
h
e
m
ag
n
itu
d
e
o
f
th
is
ass
o
ciatio
n
is
b
r
o
ad
ly
co
n
s
is
t
en
t
with
m
eta
-
an
aly
tic
ev
id
en
ce
s
h
o
win
g
m
o
d
est
p
o
s
itiv
e
en
g
ag
e
m
en
t
–
ac
h
ie
v
e
m
en
t
co
r
r
elatio
n
s
(
e.
g
.
,
r
≈
0
.
2
7
in
g
en
e
r
al
ed
u
ca
tio
n
an
d
r
≈
0
.
2
3
i
n
L
2
lear
n
in
g
)
[
1
2
]
,
[
1
3
]
.
B
y
co
n
tr
ast,
th
e
ass
o
ciatio
n
b
etwe
en
AI
_
in
d
ex
an
d
GA
was
p
o
s
itiv
e
b
u
t
wea
k
,
an
d
n
o
t
s
tatis
tically
s
ig
n
if
ican
t
(
r
=
0
.
0
6
5
,
p
=
0
.
1
8
8
)
.
AI
_
in
d
ex
p
r
im
ar
ily
r
e
f
lects
p
latf
o
r
m
-
l
o
g
g
e
d
ac
tiv
ity
/co
m
p
letio
n
r
ath
er
th
an
d
ep
th
o
f
p
r
o
ce
s
s
in
g
.
T
h
e
n
u
ll
ass
o
ciatio
n
is
in
ter
p
r
eted
as
an
o
p
er
atio
n
aliza
tio
n
/m
ea
s
u
r
e
m
en
t
co
n
s
id
er
atio
n
,
n
o
t a
s
a
ca
u
s
al
claim
.
T
ab
le
3
.
Pear
s
o
n
c
o
r
r
elatio
n
s
am
o
n
g
AE
_
in
d
ex
,
AI
_
in
d
ex
,
a
n
d
GA
(
N=
4
0
5
)
V
a
r
i
a
b
l
e
1
2
3
B
e
h
a
v
i
o
r
a
l
a
c
a
d
e
m
i
c
e
n
g
a
g
e
me
n
t
(
A
E_
i
n
d
e
x
)
1
.
0
0
A
I
p
l
a
t
f
o
r
m
b
e
h
a
v
i
o
r
s
(
A
I
_
i
n
d
e
x
)
0
.
3
9
8
*
*
*
1
.
0
0
GA
0
.
2
2
1
*
*
*
0
.
0
6
5
1
.
0
0
N
o
t
e
:
P
e
a
r
so
n
c
o
r
r
e
l
a
t
i
o
n
s a
r
e
r
e
p
o
r
t
e
d
.
*
*
*
p
<
0
.
0
0
1
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
E
v
al
&
R
es E
d
u
c
I
SS
N:
2252
-
8
8
2
2
A
ca
d
emic
en
g
a
g
eme
n
t a
n
d
a
r
tifi
cia
l in
tellig
en
ce
p
la
tfo
r
m
b
e
h
a
vio
r
s
in
g
r
a
mma
r
a
ch
ieve
m
en
t
(
Wa
n
g
Ya
d
a
n
)
2695
3.
3
.
Reg
re
s
s
io
n
a
na
ly
s
is
predict
ing
g
ra
mm
a
r
a
chiev
e
m
e
nt
T
o
ad
d
r
ess
wh
eth
er
AE
_
in
d
ex
an
d
AI
_
i
n
d
ex
jo
i
n
tly
p
r
e
d
ict
GA
an
d
wh
eth
er
AI
_
in
d
ex
ad
d
s
in
cr
em
en
tal
p
r
ed
ictiv
e
v
alu
e
b
ey
o
n
d
AE
_
i
n
d
ex
,
m
u
ltip
le
r
eg
r
ess
io
n
an
d
h
ier
ar
ch
ic
al
r
eg
r
ess
io
n
wer
e
co
n
d
u
cte
d
.
Step
1
in
clu
d
ed
A
E
_
in
d
ex
,
a
n
d
Step
2
ad
d
ed
AI
_
in
d
ex
.
An
aly
s
es
u
s
ed
R
²,
Δ
R
²,
an
d
th
e
F
-
ch
an
g
e
test
.
T
h
e
o
v
er
all
m
o
d
el
was
s
tatis
tically
s
ig
n
if
ican
t
(
R
²=
0
.
0
4
9
,
Ad
j
u
s
ted
R
²=
0
.
0
4
5
,
F
(
2
,
4
0
2
)
=
1
0
.
4
1
8
,
p<
0
.
0
0
1
)
.
T
h
is
in
d
icate
s
t
h
at
th
e
two
co
u
r
s
e
-
em
b
e
d
d
ed
b
eh
a
v
io
r
al
p
r
e
d
icto
r
s
to
g
eth
er
ex
p
lai
n
ed
ap
p
r
o
x
im
ately
4
.
9
%
o
f
th
e
v
a
r
ian
ce
in
GA
.
Alth
o
u
g
h
m
o
d
es
t,
th
is
v
ar
ian
ce
ex
p
lain
ed
is
m
ea
n
in
g
f
u
l
in
a
r
ea
l
-
co
u
r
s
e
s
ettin
g
,
wh
er
e
ac
h
iev
e
m
en
t
is
m
u
ltifa
cto
r
ial
an
d
in
f
l
u
en
ce
d
b
y
m
u
ltip
le
lear
n
er
an
d
co
n
tex
tu
al
f
ac
to
r
s
.
I
n
th
e
h
ier
ar
ch
ical
test
,
AE
_
in
d
ex
ac
c
o
u
n
ted
f
o
r
4
.
8
7
%
o
f
th
e
v
ar
ian
ce
(
R
²=
0
.
0
4
8
6
9
,
F
(
1
,
4
0
3
)
=2
0
.
6
3
,
p
=7
.
3
9
×
1
0
⁻⁶)
.
A
d
d
in
g
AI
_
i
n
d
ex
p
r
o
d
u
ce
d
a
n
e
g
lig
ib
l
e
an
d
n
o
n
-
s
ig
n
if
ican
t
in
c
r
ea
s
e
(
R
²=
0
.
0
4
9
2
8
;
Δ
R
²=
0
.
0
0
0
5
9
;
F
-
ch
a
n
g
e
(
1
,
4
0
2
)
=
0
.
2
5
0
,
p
=0
.
6
1
8
)
.
T
h
is
p
atter
n
in
d
icate
s
lim
ited
in
cr
em
en
tal
v
alid
ity
o
f
AI
_
in
d
ex
f
o
r
p
r
ed
ictin
g
ex
a
m
p
er
f
o
r
m
an
ce
b
e
y
o
n
d
AE
_
in
d
ex
.
T
ab
le
4
p
r
esen
ts
th
e
r
eg
r
e
s
s
io
n
co
ef
f
icien
ts
.
AE
_
in
d
ex
was
a
s
ig
n
if
ican
t
p
o
s
itiv
e
p
r
ed
icto
r
o
f
GA
(
B
=0
.
1
3
7
,
SE=
0
.
0
3
1
,
β=0
.
2
3
1
,
t
=4
.
3
6
2
,
p
=1
.
6
×1
0
⁻⁵,
9
5
% C
I
[
0
.
0
7
5
,
0
.
1
9
9
]
)
.
T
ab
le
4
.
Mu
ltip
le
r
e
g
r
ess
io
n
p
r
ed
ictin
g
GA
f
r
o
m
AE
_
in
d
ex
an
d
AI
_
in
d
ex
(
N=
4
0
5
)
P
r
e
d
i
c
t
o
r
B
SE
S
t
d
.
β
t
p
B
e
h
a
v
i
o
r
a
l
a
c
a
d
e
m
i
c
e
n
g
a
g
e
me
n
t
(
A
E_
i
n
d
e
x
)
0
.
1
3
7
0
.
0
3
1
0
.
2
3
1
4
.
3
6
2
<
0
.
0
0
1
A
I
p
l
a
t
f
o
r
m
b
e
h
a
v
i
o
r
s (A
I
_
i
n
d
e
x
)
−
0
.
0
2
1
0
.
0
4
2
−
0
.
0
2
6
−
0
.
5
0
0
0
.
6
1
8
M
o
d
e
l
s
t
a
t
i
s
t
i
c
s:
R
²=
0
.
0
4
9
3
,
F
(
2
,
4
0
2
)
=
1
0
.
4
1
8
,
p
<
0
.
0
0
1
.
C
o
e
f
f
i
c
i
e
n
t
s
c
o
r
r
e
sp
o
n
d
t
o
S
t
e
p
2
(
f
u
l
l
m
o
d
e
l
)
Ho
ld
in
g
AI
_
in
d
ex
co
n
s
tan
t,
a
o
n
e
-
p
o
in
t
in
cr
ea
s
e
in
AE
_
i
n
d
ex
(
0
–
1
0
0
s
ca
le)
co
r
r
esp
o
n
d
ed
to
an
esti
m
ated
0
.
1
4
-
p
o
in
t
in
cr
ea
s
e
in
g
r
am
m
a
r
ex
am
s
co
r
e.
T
o
av
o
id
c
o
n
s
tr
u
ct
o
v
er
r
ea
c
h
,
in
ter
p
r
etatio
n
s
ar
e
r
estricte
d
to
AE
_
in
d
ex
(
q
u
izz
es
an
d
class
in
ter
ac
tio
n
)
r
ath
er
th
an
m
u
ltid
im
en
s
io
n
al
en
g
a
g
em
en
t.
B
y
co
n
tr
ast,
AI
_
in
d
ex
d
id
n
o
t
s
ig
n
if
ican
tly
p
r
ed
ict
GA
af
ter
co
n
tr
o
llin
g
f
o
r
AE
_
in
d
e
x
(
B
=
–
0
.
0
2
1
,
SE=
0
.
0
4
2
,
β=
–
0
.
0
2
6
,
t=
–
0
.
5
0
0
,
p
=0
.
6
1
8
,
9
5
%
C
I
[
–
0
.
1
0
4
,
0
.
0
6
2
]
)
.
R
eg
r
ess
io
n
ass
u
m
p
tio
n
s
wer
e
ch
ec
k
ed
u
s
in
g
r
esid
u
al
d
iag
n
o
s
tics
(
in
clu
d
in
g
n
o
r
m
a
l
p
r
o
b
ab
ilit
y
P
–
P
p
lo
ts
)
an
d
co
llin
ea
r
ity
s
tatis
tic
s
(
to
ler
an
ce
/VI
F).
No
m
ajo
r
v
io
latio
n
s
wer
e
in
d
icate
d
.
Pre
d
icto
r
VI
F
v
alu
es
wer
e
lo
w
(
b
o
th
=
1
.
1
8
8
)
,
i
n
d
icatin
g
n
e
g
lig
ib
le
m
u
ltico
llin
ea
r
ity
.
E
f
f
ec
t
s
izes
wer
e
s
m
all
f
o
r
AE
_
in
d
ex
(
C
o
h
en
’
s
f
²=
0
.
0
4
7
)
an
d
n
eg
li
g
ib
le
f
o
r
AI
_
in
d
ex
(
f
²=
0
.
0
0
1
)
.
Fig
u
r
e
3
v
is
u
alize
s
th
e
s
tan
d
ar
d
ized
p
ath
s
(
β)
an
d
m
o
d
el
R
²(
N=
4
0
5
)
.
Fig
u
r
e
3
.
R
eg
r
ess
io
n
p
at
h
d
iag
r
am
p
r
e
d
ictin
g
GA
f
r
o
m
AE
_
i
n
d
ex
a
n
d
AI
_
i
n
d
ex
(
s
tan
d
ar
d
i
ze
d
co
ef
f
icien
ts
)
3.
4
.
I
nte
g
ra
t
ed
d
is
cus
s
io
n
C
o
n
s
is
ten
t
wi
th
th
e
r
esu
lts
,
co
u
r
s
e
-
em
b
ed
d
ed
b
eh
av
io
r
al
ac
a
d
em
ic
en
g
ag
em
e
n
t
(
AE
_
in
d
ex
)
s
h
o
wed
in
cr
em
en
tal
p
r
ed
ictiv
e
v
alu
e
f
o
r
GA
,
wh
er
ea
s
AI
p
latf
o
r
m
b
eh
a
v
io
r
s
(
AI
_
in
d
e
x
)
d
id
n
o
t
ad
d
e
x
p
lan
ato
r
y
p
o
wer
b
ey
o
n
d
AE
_
in
d
ex
,
s
u
g
g
esti
n
g
lim
ited
cr
iter
io
n
r
elev
an
ce
o
f
co
m
p
letio
n
-
b
ased
p
lat
f
o
r
m
i
n
d
icato
r
s
f
o
r
th
is
en
d
-
of
-
s
em
ester
ex
am
.
O
v
er
all,
th
e
two
in
d
ices
ac
co
u
n
ted
f
o
r
a
m
o
d
est
p
r
o
p
o
r
tio
n
o
f
v
ar
ian
ce
in
ex
am
p
er
f
o
r
m
an
ce
,
in
d
icatin
g
th
at
o
b
s
er
v
ab
le
en
g
ag
em
e
n
t
co
n
tr
ib
u
tes
to
g
r
am
m
ar
o
u
tco
m
es
b
u
t
d
o
es
n
o
t
f
u
lly
ex
p
lain
in
d
iv
id
u
al
d
if
f
er
e
n
ce
s
in
ac
h
iev
e
m
en
t.
W
h
y
d
id
A
E
_
in
d
ex
p
r
e
d
ict
GA
?
T
h
e
ass
o
ciatio
n
alig
n
s
wit
h
b
eh
av
io
r
al
en
g
ag
em
e
n
t
p
er
s
p
ec
tiv
es
in
wh
ich
p
ar
ticip
atio
n
,
ef
f
o
r
t,
a
n
d
p
er
s
is
ten
ce
ar
e
co
r
e
in
d
icato
r
s
o
f
en
g
ag
em
e
n
t
th
at
co
n
s
is
ten
tly
p
r
ed
ict
lear
n
in
g
o
u
tco
m
es
an
d
ac
h
iev
em
en
t
[
7
]
,
[
9
]
.
I
n
th
is
co
u
r
s
e,
q
u
izze
s
an
d
s
tr
u
ctu
r
ed
in
ter
ac
tio
n
lik
ely
c
r
ea
ted
r
ep
ea
te
d
p
r
ac
tice
–
f
ee
d
b
ac
k
o
p
p
o
r
tu
n
ities
th
at
s
u
p
p
o
r
ted
lear
n
er
s
’
er
r
o
r
d
etec
tio
n
an
d
s
elf
-
co
r
r
ec
tio
n
,
co
n
s
is
ten
t
with
f
o
r
m
-
f
o
cu
s
ed
g
r
am
m
ar
lear
n
in
g
p
r
o
ce
s
s
es
[
1
4
]
.
I
n
o
p
p
o
r
tu
n
ity
-
to
-
lear
n
ter
m
s
,
th
ese
b
eh
av
io
r
s
p
r
o
v
id
e
r
ep
ea
te
d
,
f
ee
d
b
ac
k
-
s
u
p
p
o
r
ted
p
r
ac
tice
o
n
ass
ess
ab
le
f
o
r
m
s
th
at
is
clo
s
er
to
th
e
e
x
am
’
s
co
n
s
tr
u
ct
ed
-
r
esp
o
n
s
e
d
em
an
d
s
,
m
ak
in
g
th
em
tem
p
o
r
ally
a
n
d
c
o
g
n
itiv
ely
p
r
o
x
im
al
to
t
h
e
s
u
m
m
ativ
e
ass
ess
m
en
t.
Su
p
p
o
r
tiv
e
co
u
r
s
e
co
n
tex
ts
m
ay
f
ac
i
litate
h
ig
h
er
-
q
u
ality
m
o
tiv
atio
n
an
d
p
e
r
f
o
r
m
an
ce
b
y
s
u
p
p
o
r
tin
g
co
m
p
ete
n
ce
,
au
to
n
o
m
y
,
an
d
r
elate
d
n
ess
,
wh
il
e
p
er
f
o
r
m
an
ce
o
u
tco
m
es
also
r
ef
lect
b
o
th
lea
r
n
er
d
if
f
er
en
ce
s
an
d
co
n
tex
tu
al
s
u
p
p
o
r
ts
[
2
2
]
.
Fro
m
an
ass
ess
m
en
t
v
alid
ity
p
er
s
p
ec
tiv
e,
AI
_
in
d
e
x
’
s
n
o
n
-
s
ig
n
if
ican
t
c
o
n
tr
ib
u
tio
n
m
o
r
e
lik
el
y
r
ef
lects
co
n
s
tr
u
ct
m
is
alig
n
m
e
n
t
b
etwe
en
th
e
p
latf
o
r
m
lo
g
s
an
d
th
e
g
r
am
m
ar
ex
am
th
an
n
u
ll
ef
f
ec
ts
o
f
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
15
,
No
.
3
,
J
u
n
e
20
2
6
:
2
6
9
0
-
2
6
9
9
2696
AI
-
s
u
p
p
o
r
te
d
p
r
ac
tice.
AI
_
in
d
ex
p
r
im
a
r
ily
ca
p
tu
r
ed
c
o
m
p
let
io
n
an
d
au
to
-
s
co
r
ed
e
x
p
o
s
u
r
e,
wh
er
ea
s
th
e
e
x
am
em
p
h
asized
co
n
s
tr
u
cted
-
r
esp
o
n
s
e
p
r
o
o
f
r
ea
d
in
g
a
n
d
tr
a
n
s
latio
n
;
s
u
ch
r
esp
o
n
s
e
-
f
o
r
m
at
d
i
f
f
er
en
ce
s
ca
n
ad
d
f
o
r
m
at
-
r
elate
d
n
o
is
e
an
d
th
r
ea
ten
th
e
v
alid
ity
o
f
lin
k
in
g
s
u
c
h
in
d
icato
r
s
to
co
n
s
tr
u
cted
-
r
esp
o
n
s
e
s
co
r
es
[
1
5
]
.
T
h
is
also
u
n
d
er
s
co
r
es
t
h
at
co
m
p
letio
n
tr
ac
es
m
ay
m
is
s
in
s
tr
u
ctio
n
ally
m
ea
n
in
g
f
u
l
s
u
p
p
o
r
ts
.
Stru
ct
u
r
e
in
v
o
lv
es
clea
r
ex
p
ec
tatio
n
s
an
d
g
o
als,
co
n
s
is
ten
t
r
u
les
an
d
g
u
i
d
elin
es,
an
d
in
f
o
r
m
a
tio
n
al
s
u
p
p
o
r
ts
f
o
r
en
g
ag
em
e
n
t
an
d
e
f
f
icac
y
f
ee
d
b
ac
k
[
2
3
]
.
Acc
o
r
d
in
g
ly
,
c
o
m
p
letio
n
-
b
ased
a
n
aly
tics
s
h
o
u
ld
n
o
t
b
e
u
s
ed
as
lear
n
in
g
p
r
o
x
ies
with
o
u
t
v
a
lid
atio
n
ev
id
en
ce
th
at
th
e
i
n
d
icato
r
is
co
n
s
tr
u
ct
-
r
elev
a
n
t
to
th
e
in
ten
d
ed
ass
es
s
m
en
t
in
f
er
en
ce
s
an
d
o
u
tco
m
es
[
2
4
]
.
T
ec
h
n
o
lo
g
y
-
en
h
an
ce
d
lear
n
in
g
v
alid
i
ty
s
y
n
th
eses
s
tr
es
s
in
ter
p
r
etin
g
ev
i
d
en
ce
in
r
elati
o
n
to
wh
at
is
m
ea
s
u
r
ed
,
h
o
w
it
is
u
s
ed
,
an
d
wh
eth
er
in
d
i
ca
to
r
s
s
u
p
p
o
r
t
th
e
in
ten
d
ed
v
alid
ity
claim
s
an
d
u
s
es
[
2
5
]
.
Fr
o
m
a
clo
s
ed
-
lo
o
p
lear
n
in
g
an
aly
tics
p
er
s
p
ec
ti
v
e,
tr
ac
e
in
d
icato
r
s
s
h
o
u
ld
in
f
o
r
m
iter
ativ
e
r
ef
in
em
en
t
o
f
task
s
,
s
u
p
p
o
r
ts
,
an
d
f
ee
d
b
ac
k
to
im
p
r
o
v
e
co
n
s
t
r
u
ct
alig
n
m
en
t
an
d
in
s
tr
u
ctio
n
al
im
p
ac
t
[
2
6
]
.
T
r
a
ce
-
v
alid
ity
s
ch
o
lar
s
h
ip
s
im
ilar
ly
ca
u
tio
n
s
th
at
tr
ac
e
in
d
icat
o
r
s
r
eq
u
ir
e
th
e
o
r
y
-
d
r
iv
en
alig
n
m
en
t
an
d
v
alid
ati
o
n
,
r
ath
er
th
a
n
ass
u
m
in
g
lo
g
g
ed
ac
tio
n
s
d
ir
ec
tly
r
ep
r
esen
t
lear
n
in
g
p
r
o
ce
s
s
es
[
2
7
]
.
T
r
ac
e
-
b
ased
s
elf
-
r
eg
u
lat
io
n
wo
r
k
s
h
o
ws
th
at
d
ig
ital
tr
ac
es
ca
n
d
iv
er
g
e
f
r
o
m
s
elf
-
r
e
p
o
r
ts
an
d
a
r
e
o
f
ten
o
n
ly
wea
k
ly
alig
n
ed
,
war
r
an
ti
n
g
ca
u
tio
u
s
in
ter
p
r
etatio
n
w
h
e
n
r
elatin
g
tr
ac
es to
lear
n
in
g
o
u
tco
m
es [
2
8
]
.
E
n
g
ag
em
e
n
t
–
ac
h
iev
e
m
en
t
m
e
ta
-
an
aly
s
es
ty
p
ically
s
h
o
w
s
m
all
-
to
-
m
o
d
er
ate
co
r
r
elatio
n
s
th
at
v
ar
y
b
y
en
g
ag
em
e
n
t
o
p
er
atio
n
aliza
tio
n
an
d
s
tu
d
y
c
h
ar
ac
ter
is
tics
(
e
.
g
.
,
m
ea
s
u
r
em
en
t
ch
o
ices
an
d
tim
e
f
r
am
e)
[
1
2
]
.
I
n
L
2
lear
n
in
g
,
th
e
en
g
ag
e
m
e
n
t
–
ac
h
iev
em
e
n
t
lin
k
is
lik
ewi
s
e
m
o
d
est
(
o
v
er
all
r
≈
0
.
2
3
)
an
d
v
ar
ies
b
y
lear
n
in
g
co
n
tex
t/ti
m
e
s
ca
le
[
1
3
]
.
T
h
u
s
,
ef
f
ec
t
s
izes
s
h
o
u
ld
b
e
in
ter
p
r
et
ed
in
lig
h
t
o
f
th
e
s
p
ec
if
ic
e
n
g
a
g
em
en
t d
im
en
s
io
n
an
d
in
d
icato
r
ca
p
tu
r
e
d
b
y
th
e
tr
ac
es,
r
ath
e
r
th
a
n
as
a
g
e
n
er
ic
“
en
g
ag
em
e
n
t
”
ef
f
ec
t
[
2
9
]
.
M
o
r
e
g
en
er
ally
,
ef
f
ec
t
-
s
ize
in
ter
p
r
etatio
n
in
e
d
u
ca
tio
n
is
co
n
tex
t
-
s
en
s
itiv
e,
an
d
ev
e
n
s
m
all
ef
f
ec
ts
m
ay
b
e
m
ea
n
in
g
f
u
l
wh
en
f
in
d
in
g
s
h
a
v
e
s
ca
lab
le,
co
s
t
-
ef
f
ec
tiv
e
in
s
tr
u
ctio
n
al
im
p
licatio
n
s
[
3
0
]
.
Pra
ctica
l
im
p
licatio
n
s
o
p
er
ate
at
th
r
ee
lev
els.
I
n
s
tr
u
ctio
n
ally
,
f
r
eq
u
en
t
lo
w
-
s
tak
es
q
u
izze
s
an
d
s
tr
u
ctu
r
ed
in
ter
ac
tio
n
s
h
o
u
l
d
r
em
ain
ce
n
tr
al
in
g
r
am
m
ar
tea
ch
in
g
,
s
u
s
tain
in
g
ac
tiv
e
p
r
o
ce
s
s
in
g
an
d
f
ee
d
b
ac
k
f
o
r
er
r
o
r
d
etec
tio
n
an
d
c
o
r
r
e
ctio
n
in
co
n
s
tr
ain
ed
p
r
o
d
u
cti
o
n
task
s
.
At
th
e
p
latf
o
r
m
-
tas
k
lev
el,
in
s
titu
tio
n
s
s
h
o
u
ld
r
ed
esig
n
AI
-
m
ed
iated
task
s
to
b
etter
m
atch
ex
am
-
r
elev
an
t
r
esp
o
n
s
e
f
o
r
m
ats
(
e.
g
.
,
co
n
s
tr
u
cte
d
-
r
esp
o
n
s
e
er
r
o
r
d
etec
tio
n
a
n
d
c
o
n
tr
o
lled
tr
a
n
s
latio
n
)
an
d
t
o
e
m
p
h
asize
f
ee
d
b
ac
k
u
p
ta
k
e
r
at
h
er
th
an
c
o
m
p
letio
n
.
Fro
m
a
task
–
tech
n
o
lo
g
y
f
it
p
er
s
p
ec
tiv
e,
e
f
f
ec
tiv
e
u
s
e
d
ep
en
d
s
o
n
alig
n
m
e
n
t
a
m
o
n
g
tech
n
o
l
o
g
ical
f
u
n
ctio
n
ality
,
lear
n
er
ca
p
a
b
ilit
ies,
an
d
task
r
eq
u
ir
e
m
en
ts
[
3
1
]
.
At
th
e
p
o
licy
lev
el,
t
h
e
f
in
d
i
n
g
s
ca
u
tio
n
ag
ain
s
t
u
s
in
g
co
m
p
letio
n
-
b
ased
A
I
m
etr
ics
as
h
ig
h
-
s
tak
es
lear
n
in
g
in
d
icato
r
s
with
o
u
t
d
o
cu
m
en
ted
co
n
s
tr
u
ct
alig
n
m
en
t a
n
d
v
alid
ity
ev
id
en
ce
lin
k
in
g
tr
ac
es to
ass
ess
m
en
t o
u
tco
m
es; lea
r
n
in
g
an
al
y
tics
s
h
o
u
ld
b
e
v
alid
ate
d
f
o
r
m
o
n
ito
r
in
g
a
n
d
ac
co
u
n
tab
i
lity
p
u
r
p
o
s
es,
as d
ash
b
o
ar
d
-
b
a
s
ed
p
r
ed
ictio
n
s
ar
e
n
o
t n
ec
ess
ar
ily
tr
an
s
lated
in
to
p
ed
ag
o
g
ical
ac
tio
n
s
[
3
2
]
.
L
im
itatio
n
s
in
clu
d
e
r
elian
ce
o
n
ar
ch
iv
al
in
d
icato
r
s
th
at
u
n
d
er
-
r
e
p
r
esen
t
co
g
n
itiv
e/st
r
ateg
ic
en
g
ag
em
e
n
t
[
3
3
]
,
lac
k
o
f
m
u
lti
-
s
o
u
r
c
e
ass
ess
m
en
t/p
r
o
ce
s
s
ev
id
en
ce
f
o
r
f
in
er
-
g
r
ain
e
d
alig
n
m
en
t
an
aly
s
es
[
3
4
]
,
an
d
s
in
g
le
-
in
s
titu
tio
n
s
co
p
e.
Fu
t
u
r
e
r
esear
ch
s
h
o
u
ld
co
m
b
in
e
cr
o
s
s
-
in
s
titu
tio
n
al
r
ep
licatio
n
with
r
ic
h
er
tr
ac
es
(
e.
g
.
,
tim
e
-
on
-
task
an
d
f
ee
d
b
ac
k
-
u
p
tak
e
p
atter
n
s
)
an
d
ex
p
l
icit
p
latf
o
r
m
–
e
x
am
alig
n
m
en
t m
ap
p
in
g
t
o
clar
if
y
wh
en
AI
-
s
u
p
p
o
r
ted
b
eh
av
i
o
r
s
p
r
ed
ict
GA
.
4.
CO
NCLU
SI
O
N
U
s
in
g
ar
ch
iv
al
i
n
s
titu
tio
n
al
r
e
co
r
d
s
f
r
o
m
4
0
5
n
o
n
–
E
n
g
lis
h
-
m
ajo
r
u
n
d
er
g
r
ad
u
ates,
th
is
s
tu
d
y
f
o
u
n
d
th
at
co
u
r
s
e
-
em
b
ed
d
e
d
b
e
h
av
i
o
r
al
ac
ad
em
ic
en
g
a
g
em
en
t
w
as
a
s
m
all
b
u
t
s
ig
n
if
ican
t
p
r
e
d
icto
r
o
f
g
r
a
m
m
ar
ex
am
p
e
r
f
o
r
m
an
ce
,
wh
er
ea
s
AI
p
latf
o
r
m
b
eh
a
v
io
r
s
we
r
e
wea
k
an
d
n
o
n
-
s
ig
n
if
ican
t
an
d
p
r
o
v
id
e
d
n
o
in
cr
em
en
tal
p
r
ed
ictiv
e
v
alu
e.
T
h
e
o
v
er
all
en
g
a
g
em
en
t
–
ac
h
iev
em
en
t
ass
o
ciatio
n
was
m
o
d
est.
C
o
m
p
letio
n
-
b
ased
p
latf
o
r
m
m
etr
ics
m
a
y
h
av
e
lim
ited
i
n
ter
p
r
eta
b
ilit
y
f
o
r
g
r
am
m
ar
ac
h
iev
em
e
n
t
u
n
l
ess
p
latf
o
r
m
task
s
alig
n
with
th
e
ex
am
’
s
r
esp
o
n
s
e
f
o
r
m
ats
a
n
d
task
d
em
a
n
d
s
;
i
m
p
r
o
v
i
n
g
task
–
e
x
am
ali
g
n
m
e
n
t
m
ay
en
h
a
n
ce
th
e
in
ter
p
r
etab
ilit
y
o
f
s
co
r
e
-
b
ased
in
f
er
en
ce
s
.
I
n
s
titu
tio
n
s
s
h
o
u
ld
th
er
ef
o
r
e
tr
ea
t
co
m
p
letio
n
-
b
ased
p
latf
o
r
m
in
d
icato
r
s
as
p
ar
ticip
atio
n
m
e
tr
ics
r
ath
er
th
an
h
ig
h
-
s
tak
es
p
r
o
x
ies
in
th
e
a
b
s
en
ce
o
f
c
o
n
s
tr
u
ct
alig
n
m
en
t
a
n
d
v
alid
ity
ev
id
en
ce
.
Fu
tu
r
e
r
ese
ar
ch
s
h
o
u
ld
ex
ten
d
t
h
is
wo
r
k
th
r
o
u
g
h
lo
n
g
itu
d
in
al
d
esig
n
s
,
cr
o
s
s
-
in
s
titu
tio
n
al
r
ep
licatio
n
,
item
-
lev
el
ex
am
an
aly
s
is
,
an
d
th
e
in
te
g
r
atio
n
o
f
m
o
tiv
atio
n
al,
s
elf
-
r
eg
u
lat
o
r
y
,
a
n
d
AI
liter
ac
y
m
ea
s
u
r
es.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
Au
th
o
r
s
s
tate
n
o
f
u
n
d
in
g
in
v
o
lv
ed
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
E
v
al
&
R
es E
d
u
c
I
SS
N:
2252
-
8
8
2
2
A
ca
d
emic
en
g
a
g
eme
n
t a
n
d
a
r
tifi
cia
l in
tellig
en
ce
p
la
tfo
r
m
b
e
h
a
vio
r
s
in
g
r
a
mma
r
a
ch
ieve
m
en
t
(
Wa
n
g
Ya
d
a
n
)
2697
AUTHO
R
CO
NT
RI
B
UT
I
O
NS ST
A
T
E
M
E
N
T
T
h
is
jo
u
r
n
al
u
s
es
th
e
C
o
n
t
r
ib
u
to
r
R
o
les
T
a
x
o
n
o
m
y
(
C
R
ed
iT)
to
r
ec
o
g
n
ize
in
d
iv
i
d
u
al
au
th
o
r
co
n
tr
ib
u
tio
n
s
,
r
ed
u
ce
au
th
o
r
s
h
ip
d
is
p
u
tes,
an
d
f
ac
ilit
ate
co
llab
o
r
atio
n
.
Na
m
e
o
f
Aut
ho
r
C
M
So
Va
Fo
I
R
D
O
E
Vi
Su
P
Fu
W
an
g
Yad
an
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
So
o
n
Sin
g
h
B
ik
ar
Sin
g
h
✓
✓
✓
✓
✓
C
o
n
n
ie
Sh
in
✓
✓
✓
Z
h
en
g
J
u
n
c
ai
✓
✓
✓
Z
h
an
g
Qian
q
ian
✓
✓
✓
C
:
C
o
n
c
e
p
t
u
a
l
i
z
a
t
i
o
n
M
:
M
e
t
h
o
d
o
l
o
g
y
So
:
So
f
t
w
a
r
e
Va
:
Va
l
i
d
a
t
i
o
n
Fo
:
Fo
r
mal
a
n
a
l
y
s
i
s
I
:
I
n
v
e
s
t
i
g
a
t
i
o
n
R
:
R
e
so
u
r
c
e
s
D
:
D
a
t
a
C
u
r
a
t
i
o
n
O
:
W
r
i
t
i
n
g
-
O
r
i
g
i
n
a
l
D
r
a
f
t
E
:
W
r
i
t
i
n
g
-
R
e
v
i
e
w
&
E
d
i
t
i
n
g
Vi
:
Vi
su
a
l
i
z
a
t
i
o
n
Su
:
Su
p
e
r
v
i
s
i
o
n
P
:
P
r
o
j
e
c
t
a
d
mi
n
i
st
r
a
t
i
o
n
Fu
:
Fu
n
d
i
n
g
a
c
q
u
i
si
t
i
o
n
CO
NF
L
I
C
T
O
F
I
N
T
E
R
E
S
T
ST
A
T
E
M
E
NT
Au
th
o
r
s
s
tate
n
o
co
n
f
lict o
f
in
t
er
est.
DATA AV
AI
L
AB
I
L
I
T
Y
Data
wer
e
d
er
iv
ed
f
r
o
m
in
te
r
n
al
co
u
r
s
e
r
ec
o
r
d
s
o
f
Gu
an
g
z
h
o
u
Xin
h
u
a
Un
iv
er
s
ity
an
d
ar
e
av
ailab
le
f
r
o
m
th
e
co
r
r
esp
o
n
d
in
g
au
th
o
r
,
[
SS
B
S],
u
p
o
n
r
ea
s
o
n
ab
le
r
eq
u
est.
RE
F
E
R
E
NC
E
S
[
1
]
U
N
ESCO
,
AI
a
n
d
E
d
u
c
a
t
i
o
n
:
G
u
i
d
a
n
c
e
f
o
r
P
o
l
i
c
y
-
m
a
k
e
rs
.
P
a
r
i
s
:
U
N
ESC
O
,
2
0
2
1
,
d
o
i
:
1
0
.
5
4
6
7
5
/
P
C
S
P
7
3
5
0
.
[
2
]
L.
W
e
i
,
“
A
r
t
i
f
i
c
i
a
l
i
n
t
e
l
l
i
g
e
n
c
e
i
n
l
a
n
g
u
a
g
e
i
n
st
r
u
c
t
i
o
n
:
i
m
p
a
c
t
o
n
E
n
g
l
i
sh
l
e
a
r
n
i
n
g
a
c
h
i
e
v
e
m
e
n
t
,
L2
mo
t
i
v
a
t
i
o
n
,
a
n
d
sel
f
-
r
e
g
u
l
a
t
e
d
l
e
a
r
n
i
n
g
,
”
Fr
o
n
t
i
e
rs
i
n
Psy
c
h
o
l
o
g
y
,
v
o
l
.
1
4
,
p
.
1
2
6
1
9
5
5
,
N
o
v
.
2
0
2
3
,
d
o
i
:
1
0
.
3
3
8
9
/
f
p
s
y
g
.
2
0
2
3
.
1
2
6
1
9
5
5
.
[
3
]
J.
J.
J
a
r
a
m
i
l
l
o
,
A
.
C
h
i
a
p
p
e
,
a
n
d
F
.
S
.
D
e
l
g
a
d
o
,
“
F
r
o
m
st
r
u
g
g
l
e
t
o
mas
t
e
r
y
:
A
I
-
p
o
w
e
r
e
d
w
r
i
t
i
n
g
s
k
i
l
l
s
i
n
ESL
e
d
u
c
a
t
i
o
n
,
”
A
p
p
l
i
e
d
S
c
i
e
n
c
e
s
,
v
o
l
.
1
5
,
n
o
.
1
4
,
p
.
8
0
7
9
,
J
u
l
.
2
0
2
5
,
d
o
i
:
1
0
.
3
3
9
0
/
a
p
p
1
5
1
4
8
0
7
9
.
[
4
]
A
.
M
o
h
e
b
b
i
,
“
E
n
a
b
l
i
n
g
l
e
a
r
n
e
r
i
n
d
e
p
e
n
d
e
n
c
e
a
n
d
s
e
l
f
-
r
e
g
u
l
a
t
i
o
n
i
n
l
a
n
g
u
a
g
e
e
d
u
c
a
t
i
o
n
u
s
i
n
g
A
I
t
o
o
l
s
:
a
sy
st
e
ma
t
i
c
r
e
v
i
e
w
,
”
C
o
g
e
n
t
E
d
u
c
a
t
i
o
n
,
v
o
l
.
1
2
,
n
o
.
1
,
p
.
2
4
3
3
8
1
4
,
D
e
c
.
2
0
2
5
,
d
o
i
:
1
0
.
1
0
8
0
/
2
3
3
1
1
8
6
X
.
2
0
2
4
.
2
4
3
3
8
1
4
.
[
5
]
C
.
L
u
,
“
A
I
-
g
e
n
e
r
a
t
e
d
c
o
r
p
u
s
l
e
a
r
n
i
n
g
a
n
d
EFL
l
e
a
r
n
e
r
s’
l
e
a
r
n
i
n
g
o
f
g
r
a
m
mat
i
c
a
l
st
r
u
c
t
u
r
e
s
,
l
e
x
i
c
a
l
b
u
n
d
l
e
s
,
a
n
d
w
i
l
l
i
n
g
n
e
ss
t
o
w
r
i
t
e
,
”
PLO
S
O
n
e
,
v
o
l
.
2
0
,
n
o
.
7
,
p
.
e
0
3
2
1
5
4
4
,
J
u
l
.
2
0
2
5
,
d
o
i
:
1
0
.
1
3
7
1
/
j
o
u
r
n
a
l
.
p
o
n
e
.
0
3
2
1
5
4
4
.
[
6
]
C
.
Y
a
n
g
a
n
d
S
.
S
.
B
.
S
i
n
g
h
,
“
U
se
r
e
x
p
e
r
i
e
n
c
e
i
n
i
n
f
o
r
ma
t
i
o
n
sy
s
t
e
m
p
l
a
t
f
o
r
ms
:
a
st
u
d
y
o
n
l
e
a
r
n
i
n
g
s
t
y
l
e
s
a
n
d
a
c
a
d
e
m
i
c
c
h
a
l
l
e
n
g
e
s,”
J
o
u
rn
a
l
o
f
I
n
t
e
r
n
e
t
S
e
rv
i
c
e
s
a
n
d
I
n
f
o
rm
a
t
i
o
n
S
e
c
u
ri
t
y
,
v
o
l
.
1
4
,
n
o
.
4
,
p
p
.
2
0
9
–
2
2
3
,
N
o
v
.
2
0
2
4
,
d
o
i
:
1
0
.
5
8
3
4
6
/
JI
S
I
S
.
2
0
2
4
.
I
4
.
0
1
2
.
[
7
]
J.
A
.
F
r
e
d
r
i
c
k
s,
P
.
C
.
B
l
u
me
n
f
e
l
d
,
a
n
d
A
.
H
.
P
a
r
i
s
,
“
S
c
h
o
o
l
e
n
g
a
g
e
m
e
n
t
:
p
o
t
e
n
t
i
a
l
o
f
t
h
e
c
o
n
c
e
p
t
,
st
a
t
e
o
f
t
h
e
e
v
i
d
e
n
c
e
,”
Re
v
i
e
w
o
f
Ed
u
c
a
t
i
o
n
a
l
R
e
se
a
rc
h
,
v
o
l
.
7
4
,
n
o
.
1
,
p
p
.
5
9
–
1
0
9
,
M
a
r
.
2
0
0
4
,
d
o
i
:
1
0
.
3
1
0
2
/
0
0
3
4
6
5
4
3
0
7
4
0
0
1
0
5
9
.
[
8
]
J.
A
.
F
r
e
d
r
i
c
k
s
,
M
.
F
i
l
s
e
c
k
e
r
,
a
n
d
M
.
A
.
L
a
w
so
n
,
“
S
t
u
d
e
n
t
e
n
g
a
g
e
me
n
t
,
c
o
n
t
e
x
t
,
a
n
d
a
d
j
u
st
m
e
n
t
:
a
d
d
r
e
s
s
i
n
g
d
e
f
i
n
i
t
i
o
n
a
l
,
mea
s
u
r
e
me
n
t
,
a
n
d
me
t
h
o
d
o
l
o
g
i
c
a
l
i
ss
u
e
s,
”
L
e
a
r
n
i
n
g
a
n
d
I
n
st
ru
c
t
i
o
n
,
v
o
l
.
4
3
,
p
p
.
1
–
4
,
Ju
n
.
2
0
1
6
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
l
e
a
r
n
i
n
s
t
r
u
c
.
2
0
1
6
.
0
2
.
0
0
2
.
[
9
]
J.
R
e
e
v
e
,
“
A
sel
f
-
d
e
t
e
r
mi
n
a
t
i
o
n
t
h
e
o
r
y
p
e
r
sp
e
c
t
i
v
e
o
n
st
u
d
e
n
t
e
n
g
a
g
e
m
e
n
t
,
”
i
n
H
a
n
d
b
o
o
k
o
f
Re
s
e
a
r
c
h
o
n
S
t
u
d
e
n
t
E
n
g
a
g
e
m
e
n
t
,
1
st
e
d
.
,
S
.
L.
C
h
r
i
st
e
n
so
n
,
A
.
L.
R
e
s
c
h
l
y
,
a
n
d
C
.
W
y
l
i
e
,
E
d
s.,
B
o
st
o
n
,
M
A
:
S
p
r
i
n
g
e
r
U
S
,
2
0
1
2
,
p
p
.
1
4
9
–
172
,
d
o
i
:
1
0
.
1
0
0
7
/
9
7
8
-
1
-
4
6
1
4
-
2
0
1
8
-
7
_
7
.
[
1
0
]
W
.
M
.
Z
g
h
o
u
l
a
n
d
R
.
F
.
B
a
t
a
i
n
e
h
,
“
F
l
i
p
g
r
i
d
:
u
n
l
o
c
k
i
n
g
t
h
e
En
g
l
i
s
h
s
p
e
a
k
i
n
g
p
o
t
e
n
t
i
a
l
o
f
Jo
r
d
a
n
i
a
n
a
d
o
l
e
sce
n
t
EFL
l
e
a
r
n
e
r
s,
”
J
o
u
rn
a
l
o
f
I
n
f
o
rm
a
t
i
o
n
T
e
c
h
n
o
l
o
g
y
E
d
u
c
a
t
i
o
n
:
I
n
n
o
v
a
t
i
o
n
s
i
n
Pr
a
c
t
i
c
e
,
v
o
l
.
2
3
,
p
.
1
7
,
2
0
2
4
,
d
o
i
:
1
0
.
2
8
9
4
5
/
5
4
0
7
.
[
1
1
]
B
.
W
a
l
u
y
o
,
S
.
P
h
a
n
r
a
n
g
s
e
e
,
a
n
d
W
.
W
h
a
n
c
h
i
t
,
“
G
a
mi
f
i
e
d
g
r
a
mm
a
r
l
e
a
r
n
i
n
g
i
n
o
n
l
i
n
e
E
n
g
l
i
s
h
c
o
u
r
ses
i
n
T
h
a
i
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
,
”
O
n
l
i
n
e
J
o
u
rn
a
l
o
f
C
o
m
m
u
n
i
c
a
t
i
o
n
a
n
d
M
e
d
i
a
T
e
c
h
n
o
l
o
g
i
e
s
,
v
o
l
.
1
3
,
n
o
.
4
,
p
.
e
2
0
2
3
5
4
,
O
c
t
.
2
0
2
3
,
d
o
i
:
1
0
.
3
0
9
3
5
/
o
j
c
mt
/
1
3
7
5
2
.
[
1
2
]
H
.
Le
i
,
Y
.
C
u
i
,
a
n
d
W
.
Zh
o
u
,
“
R
e
l
a
t
i
o
n
s
h
i
p
s
b
e
t
w
e
e
n
s
t
u
d
e
n
t
e
n
g
a
g
e
me
n
t
a
n
d
a
c
a
d
e
m
i
c
a
c
h
i
e
v
e
m
e
n
t
:
a
me
t
a
-
a
n
a
l
y
si
s
,
”
S
o
c
i
a
l
Be
h
a
v
i
o
r
a
n
d
Pe
rs
o
n
a
l
i
t
y
:
An
I
n
t
e
rn
a
t
i
o
n
a
l
J
o
u
rn
a
l
,
v
o
l
.
4
6
,
n
o
.
3
,
p
p
.
5
1
7
–
5
2
8
,
M
a
r
.
2
0
1
8
,
d
o
i
:
1
0
.
2
2
2
4
/
sb
p
.
7
0
5
4
.
[
1
3
]
A
.
O
k
u
n
u
k
i
a
n
d
Y
.
K
a
s
h
i
m
u
r
a
,
“
S
t
u
d
e
n
t
e
n
g
a
g
e
m
e
n
t
a
n
d
a
c
a
d
e
mi
c
a
c
h
i
e
v
e
m
e
n
t
i
n
s
e
c
o
n
d
l
a
n
g
u
a
g
e
l
e
a
r
n
i
n
g
:
a
m
e
t
a
-
a
n
a
l
y
s
i
s,”
J
AC
ET
J
o
u
rn
a
l
,
v
o
l
.
6
8
,
p
p
.
7
1
–
9
0
,
2
0
2
4
.
[
1
4
]
R
.
E
l
l
i
s,
“
C
u
r
r
e
n
t
i
ssu
e
s
i
n
t
h
e
t
e
a
c
h
i
n
g
o
f
g
r
a
mm
a
r
:
a
n
S
LA
p
e
r
sp
e
c
t
i
v
e
,
”
T
ES
O
L
Q
u
a
rt
e
rl
y
,
v
o
l
.
4
0
,
n
o
.
1
,
p
p
.
8
3
–
1
0
7
,
M
a
r
.
2
0
0
6
,
d
o
i
:
1
0
.
2
3
0
7
/
4
0
2
6
4
5
1
2
.
[
1
5
]
J.
E.
P
u
r
p
u
r
a
,
“
A
ss
e
ssi
n
g
g
r
a
mm
a
r
,
”
i
n
T
h
e
C
o
m
p
a
n
i
o
n
t
o
L
a
n
g
u
a
g
e
Assessm
e
n
t
,
A
.
J
.
K
u
n
n
a
n
,
E
d
.
,
H
o
b
o
k
e
n
,
N
J:
W
i
l
e
y
-
B
l
a
c
k
w
e
l
l
,
2
0
1
3
,
p
p
.
1
0
0
–
1
2
4
,
d
o
i
:
1
0
.
1
0
0
2
/
9
7
8
1
1
1
8
4
1
1
3
6
0
.
w
b
c
l
a
1
4
7
.
[
1
6
]
J.
B
r
o
a
d
b
e
n
t
a
n
d
W
.
L.
P
o
o
n
,
“
S
e
l
f
-
r
e
g
u
l
a
t
e
d
l
e
a
r
n
i
n
g
s
t
r
a
t
e
g
i
e
s
&
a
c
a
d
e
mi
c
a
c
h
i
e
v
e
me
n
t
i
n
o
n
l
i
n
e
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
l
e
a
r
n
i
n
g
e
n
v
i
r
o
n
m
e
n
t
s
:
a
s
y
st
e
ma
t
i
c
r
e
v
i
e
w
,
”
T
h
e
I
n
t
e
rn
e
t
a
n
d
H
i
g
h
e
r
Ed
u
c
a
t
i
o
n
,
v
o
l
.
2
7
,
p
p
.
1
–
1
3
,
O
c
t
.
2
0
1
5
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
i
h
e
d
u
c
.
2
0
1
5
.
0
4
.
0
0
7
.
[
1
7
]
E.
P
a
n
a
d
e
r
o
,
“
A
r
e
v
i
e
w
o
f
s
e
l
f
-
r
e
g
u
l
a
t
e
d
l
e
a
r
n
i
n
g
:
s
i
x
m
o
d
e
l
s
a
n
d
f
o
u
r
d
i
r
e
c
t
i
o
n
s
f
o
r
r
e
s
e
a
r
c
h
,
”
Fr
o
n
t
i
e
rs
i
n
P
syc
h
o
l
o
g
y
,
v
o
l
.
8
,
p
.
4
2
2
,
A
p
r
.
2
0
1
7
,
d
o
i
:
1
0
.
3
3
8
9
/
f
p
s
y
g
.
2
0
1
7
.
0
0
4
2
2
.
[
1
8
]
N
.
J
o
ma
a
,
B
.
A
.
M
u
d
h
s
h
,
a
n
d
K
.
A
l
G
h
a
f
r
i
,
“
Tr
a
d
i
t
i
o
n
a
l
s
t
r
a
t
e
g
i
e
s
a
n
d
A
I
-
i
n
t
e
g
r
a
t
e
d
st
r
a
t
e
g
i
e
s
i
n
l
e
a
r
n
i
n
g
E
n
g
l
i
sh
a
mo
n
g
EFL
O
man
i
st
u
d
e
n
t
s
,”
J
u
rn
a
l
Ar
b
i
t
rer
,
v
o
l
.
1
2
,
n
o
.
3
,
p
p
.
3
6
8
–
3
8
2
,
S
e
p
.
2
0
2
5
,
d
o
i
:
1
0
.
2
5
0
7
7
/
a
r
.
1
2
.
3
.
3
6
8
-
3
8
2
.
2
0
2
5
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
15
,
No
.
3
,
J
u
n
e
20
2
6
:
2
6
9
0
-
2
6
9
9
2698
[
1
9
]
S
.
S
h
a
w
a
n
d
V
.
C
r
i
sp
,
“
Tr
a
c
i
n
g
t
h
e
e
v
o
l
u
t
i
o
n
o
f
v
a
l
i
d
i
t
y
i
n
e
d
u
c
a
t
i
o
n
a
l
m
e
a
su
r
e
m
e
n
t
:
p
a
st
i
ss
u
e
s
a
n
d
c
o
n
t
e
m
p
o
r
a
r
y
c
h
a
l
l
e
n
g
e
s,”
Re
se
a
rc
h
Ma
t
t
e
rs
,
n
o
.
1
1
,
p
p
.
1
4
–
1
9
,
2
0
1
1
.
[
2
0
]
G
u
a
n
g
z
h
o
u
X
i
n
h
u
a
U
n
i
v
e
r
si
t
y
,
“
U
n
i
v
e
r
s
i
t
y
f
o
r
e
i
g
n
l
a
n
g
u
a
g
e
s
—
g
r
a
m
mar
t
e
a
c
h
i
n
g
s
y
l
l
a
b
u
s
c
o
m
p
i
l
a
t
i
o
n
(
R
e
v
i
se
d
2
0
2
4
)
,
”
U
n
p
u
b
l
i
sh
e
d
i
n
st
i
t
u
t
i
o
n
a
l
d
o
c
u
me
n
t
,
2
0
2
4
.
[
2
1
]
R
.
W
.
O
sb
o
r
n
e
a
n
d
E
.
W
a
t
e
r
s,
“
F
o
u
r
a
ss
u
mp
t
i
o
n
s
o
f
mu
l
t
i
p
l
e
r
e
g
r
e
s
si
o
n
t
h
a
t
r
e
sea
r
c
h
e
r
s
s
h
o
u
l
d
a
l
w
a
y
s
t
e
s
t
,
”
Pr
a
c
t
i
c
a
l
Assessm
e
n
t
,
R
e
se
a
rc
h
a
n
d
Ev
a
l
u
a
t
i
o
n
,
v
o
l
.
8
,
n
o
.
2
,
p
p
.
1
–
9
,
2
0
0
2
.
[
2
2
]
E.
L.
D
e
c
i
a
n
d
R
.
M
.
R
y
a
n
,
“
T
h
e
‘
w
h
a
t
’
a
n
d
‘
w
h
y
’
o
f
g
o
a
l
p
u
r
su
i
t
s
:
h
u
ma
n
n
e
e
d
s
a
n
d
t
h
e
s
e
l
f
-
d
e
t
e
r
mi
n
a
t
i
o
n
o
f
b
e
h
a
v
i
o
r
,”
Psy
c
h
o
l
o
g
i
c
a
l
I
n
q
u
i
ry
,
v
o
l
.
1
1
,
n
o
.
4
,
p
p
.
2
2
7
–
2
6
8
,
O
c
t
.
2
0
0
0
,
d
o
i
:
1
0
.
1
2
0
7
/
S
1
5
3
2
7
9
6
5
P
LI
1
1
0
4
_
0
1
.
[
2
3
]
R
.
M
.
R
y
a
n
a
n
d
E.
L.
D
e
c
i
,
“
I
n
t
r
i
n
si
c
a
n
d
e
x
t
r
i
n
si
c
mo
t
i
v
a
t
i
o
n
f
r
o
m
a
s
e
l
f
-
d
e
t
e
r
mi
n
a
t
i
o
n
t
h
e
o
r
y
p
e
r
s
p
e
c
t
i
v
e
:
d
e
f
i
n
i
t
i
o
n
s,
t
h
e
o
r
y
,
p
r
a
c
t
i
c
e
s,
a
n
d
f
u
t
u
r
e
d
i
r
e
c
t
i
o
n
s,
”
C
o
n
t
e
m
p
o
r
a
ry
E
d
u
c
a
t
i
o
n
a
l
P
syc
h
o
l
o
g
y
,
v
o
l
.
6
1
,
p
.
1
0
1
8
6
0
,
A
p
r
.
2
0
2
0
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
c
e
d
p
s
y
c
h
.
2
0
2
0
.
1
0
1
8
6
0
.
[
2
4
]
P
.
G
.
d
e
B
a
r
b
a
,
E
.
A
.
O
l
i
v
e
i
r
a
,
a
n
d
N
.
En
g
l
i
s
h
,
“
D
e
v
e
l
o
p
me
n
t
a
n
d
v
a
l
i
d
a
t
i
o
n
o
f
a
l
e
a
r
n
i
n
g
a
n
a
l
y
t
i
c
s
r
u
b
r
i
c
f
o
r
sel
f
-
r
e
g
u
l
a
t
e
d
l
e
a
r
n
i
n
g
,
”
Ed
u
c
a
t
i
o
n
a
l
T
e
c
h
n
o
l
o
g
y
R
e
se
a
rc
h
a
n
d
D
e
v
e
l
o
p
m
e
n
t
,
v
o
l
.
7
3
,
n
o
.
5
,
p
p
.
3
2
2
3
–
3
2
4
5
,
O
c
t
.
2
0
2
5
,
d
o
i
:
1
0
.
1
0
0
7
/
s
1
1
4
2
3
-
0
2
5
-
1
0
5
2
1
-
x.
[
2
5
]
M
.
v
a
n
H
a
a
st
r
e
c
h
t
,
M
.
H
a
a
s
,
M
.
B
r
i
n
k
h
u
i
s
,
a
n
d
M
.
S
p
r
u
i
t
,
“
U
n
d
e
r
st
a
n
d
i
n
g
v
a
l
i
d
i
t
y
c
r
i
t
e
r
i
a
i
n
t
e
c
h
n
o
l
o
g
y
-
e
n
h
a
n
c
e
d
l
e
a
r
n
i
n
g
:
a
sy
st
e
mat
i
c
l
i
t
e
r
a
t
u
r
e
r
e
v
i
e
w
,
”
C
o
m
p
u
t
e
rs &
Ed
u
c
a
t
i
o
n
,
v
o
l
.
2
2
0
,
p
.
1
0
5
1
2
8
,
O
c
t
.
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
c
o
m
p
e
d
u
.
2
0
2
4
.
1
0
5
1
2
8
.
[
2
6
]
M
.
S
a
i
l
e
r
,
M
.
N
i
n
a
u
s,
S
.
E.
H
u
b
e
r
,
E
.
B
a
u
e
r
,
a
n
d
S
.
G
r
e
i
f
f
,
“
T
h
e
e
n
d
i
s t
h
e
b
e
g
i
n
n
i
n
g
i
s
t
h
e
e
n
d
:
t
h
e
c
l
o
se
d
-
l
o
o
p
l
e
a
r
n
i
n
g
a
n
a
l
y
t
i
c
s
f
r
a
mew
o
r
k
,
”
C
o
m
p
u
t
e
rs
i
n
H
u
m
a
n
Be
h
a
v
i
o
r
,
v
o
l
.
1
5
8
,
p
.
1
0
8
3
0
5
,
S
e
p
.
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
c
h
b
.
2
0
2
4
.
1
0
8
3
0
5
.
[
2
7
]
Y
.
F
a
n
e
t
a
l
.
,
“
To
w
a
r
d
s
i
n
v
e
st
i
g
a
t
i
n
g
t
h
e
v
a
l
i
d
i
t
y
o
f
mea
s
u
r
e
m
e
n
t
o
f
s
e
l
f
-
r
e
g
u
l
a
t
e
d
l
e
a
r
n
i
n
g
b
a
se
d
o
n
t
r
a
c
e
d
a
t
a
,
”
M
e
t
a
c
o
g
n
i
t
i
o
n
a
n
d
L
e
a
r
n
i
n
g
,
v
o
l
.
1
7
,
n
o
.
3
,
p
p
.
9
4
9
–
9
8
7
,
D
e
c
.
2
0
2
2
,
d
o
i
:
1
0
.
1
0
0
7
/
s1
1
4
0
9
-
0
2
2
-
0
9
2
9
1
-
1.
[
2
8
]
F
.
H
a
n
a
n
d
R
.
A
.
E
l
l
i
s,
“
S
e
l
f
-
r
e
p
o
r
t
e
d
a
n
d
d
i
g
i
t
a
l
-
t
r
a
c
e
mea
s
u
r
e
s
o
f
c
o
mp
u
t
e
r
sci
e
n
c
e
st
u
d
e
n
t
s’
s
e
l
f
-
r
e
g
u
l
a
t
e
d
l
e
a
r
n
i
n
g
i
n
b
l
e
n
d
e
d
c
o
u
r
se
d
e
si
g
n
s,”
E
d
u
c
a
t
i
o
n
a
n
d
I
n
f
o
rm
a
t
i
o
n
T
e
c
h
n
o
l
o
g
i
e
s
,
v
o
l
.
2
8
,
n
o
.
1
0
,
p
p
.
1
3
2
5
3
–
1
3
2
6
8
,
O
c
t
.
2
0
2
3
,
d
o
i
:
1
0
.
1
0
0
7
/
s1
0
6
3
9
-
0
2
3
-
1
1
6
9
8
-
5.
[
2
9
]
N
.
B
e
r
g
d
a
h
l
,
M
.
B
o
n
d
,
J
.
S
j
ö
b
e
r
g
,
M
.
D
o
u
g
h
e
r
t
y
,
a
n
d
E
.
O
x
l
e
y
,
“
U
n
p
a
c
k
i
n
g
st
u
d
e
n
t
e
n
g
a
g
e
me
n
t
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
l
e
a
r
n
i
n
g
a
n
a
l
y
t
i
c
s
:
a
sy
s
t
e
mat
i
c
r
e
v
i
e
w
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
E
d
u
c
a
t
i
o
n
a
l
T
e
c
h
n
o
l
o
g
y
i
n
H
i
g
h
e
r
E
d
u
c
a
t
i
o
n
,
v
o
l
.
2
1
,
n
o
.
1
,
p
.
6
3
,
D
e
c
.
2
0
2
4
,
d
o
i
:
1
0
.
1
1
8
6
/
s4
1
2
3
9
-
0
2
4
-
0
0
4
9
3
-
y.
[
3
0
]
S
.
To
b
l
e
r
,
“
C
o
n
t
e
x
t
mat
t
e
r
s
:
i
n
t
e
r
p
r
e
t
i
n
g
e
f
f
e
c
t
s
i
z
e
s
i
n
e
d
u
c
a
t
i
o
n
me
a
n
i
n
g
f
u
l
l
y
,
”
M
e
t
h
o
d
sX
,
v
o
l
.
1
3
,
p
.
1
0
3
0
2
3
,
D
e
c
.
2
0
2
4
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
m
e
x
.
2
0
2
4
.
1
0
3
0
2
3
.
[
3
1
]
W
.
M
.
A
l
-
R
a
h
m
i
e
t
a
l
.
,
“
I
n
t
e
g
r
a
t
i
n
g
c
o
mm
u
n
i
c
a
t
i
o
n
a
n
d
t
a
sk
–
t
e
c
h
n
o
l
o
g
y
f
i
t
t
h
e
o
r
i
e
s
:
t
h
e
a
d
o
p
t
i
o
n
o
f
d
i
g
i
t
a
l
m
e
d
i
a
i
n
l
e
a
r
n
i
n
g
,
”
S
u
s
t
a
i
n
a
b
i
l
i
t
y
,
v
o
l
.
1
5
,
n
o
.
1
0
,
p
.
8
1
4
4
,
M
a
y
2
0
2
3
,
d
o
i
:
1
0
.
3
3
9
0
/
su
1
5
1
0
8
1
4
4
.
[
3
2
]
I
.
M
a
si
e
l
l
o
,
Z
.
(
A
r
t
e
mi
s)
M
o
h
se
n
i
,
F
.
P
a
l
m
a
,
S
.
N
o
r
d
m
a
r
k
,
H
.
A
u
g
u
st
ss
o
n
,
a
n
d
R
.
R
u
n
d
q
u
i
s
t
,
“
A
c
u
r
r
e
n
t
o
v
e
r
v
i
e
w
o
f
t
h
e
u
s
e
o
f
l
e
a
r
n
i
n
g
a
n
a
l
y
t
i
c
s
d
a
s
h
b
o
a
r
d
s
,
”
Ed
u
c
a
t
i
o
n
S
c
i
e
n
c
e
s
,
v
o
l
.
1
4
,
n
o
.
1
,
p
.
8
2
,
Ja
n
.
2
0
2
4
,
d
o
i
:
1
0
.
3
3
9
0
/
e
d
u
c
s
c
i
1
4
0
1
0
0
8
2
.
[
3
3
]
E.
M
a
z
z
u
l
l
o
,
O
.
B
u
l
u
t
,
T.
W
o
n
g
v
o
r
a
c
h
a
n
,
a
n
d
B
.
T
a
n
,
“
L
e
a
r
n
i
n
g
a
n
a
l
y
t
i
c
s i
n
t
h
e
e
r
a
o
f
l
a
r
g
e
l
a
n
g
u
a
g
e
m
o
d
e
l
s
,”
An
a
l
y
t
i
c
s
,
v
o
l
.
2
,
n
o
.
4
,
p
p
.
8
7
7
–
8
9
8
,
N
o
v
.
2
0
2
3
,
d
o
i
:
1
0
.
3
3
9
0
/
a
n
a
l
y
t
i
c
s
2
0
4
0
0
4
6
.
[
3
4
]
P
.
K
a
n
n
a
n
a
n
d
D
.
Z
a
p
a
t
a
-
R
i
v
e
r
a
,
“
F
a
c
i
l
i
t
a
t
i
n
g
t
h
e
u
se
o
f
d
a
t
a
f
r
o
m
mu
l
t
i
p
l
e
so
u
r
c
e
s
f
o
r
f
o
r
mat
i
v
e
l
e
a
r
n
i
n
g
i
n
t
h
e
c
o
n
t
e
x
t
o
f
d
i
g
i
t
a
l
a
ss
e
ssm
e
n
t
s:
i
n
f
o
r
mi
n
g
t
h
e
d
e
si
g
n
a
n
d
d
e
v
e
l
o
p
m
e
n
t
o
f
l
e
a
r
n
i
n
g
a
n
a
l
y
t
i
c
d
a
s
h
b
o
a
r
d
s
,
”
Fr
o
n
t
i
e
rs
i
n
E
d
u
c
a
t
i
o
n
,
v
o
l
.
7
,
p
.
9
1
3
5
9
4
,
J
u
n
.
2
0
2
2
,
d
o
i
:
1
0
.
3
3
8
9
/
f
e
d
u
c
.
2
0
2
2
.
9
1
3
5
9
4
.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
Wa
n
g
Ya
d
a
n
is
a
P
h
.
D
.
c
a
n
d
i
d
a
te
a
t
th
e
F
a
c
u
lt
y
o
f
Ed
u
c
a
ti
o
n
a
n
d
S
p
o
rt
s
S
tu
d
ies
,
Un
i
v
e
rsiti
M
a
la
y
sia
S
a
b
a
h
(UMS
),
M
a
lay
sia
,
a
n
d
a
n
a
ss
istan
t
p
ro
fe
ss
o
r
a
t
G
u
a
n
g
z
h
o
u
Xi
n
h
u
a
Un
iv
e
rsit
y
,
Ch
in
a
.
S
h
e
re
c
e
iv
e
d
h
e
r
M
.
A
.
i
n
F
o
re
i
g
n
L
in
g
u
isti
c
s
a
n
d
Ap
p
li
e
d
L
in
g
u
isti
c
s
fro
m
He
n
a
n
Un
iv
e
rsity
,
Ch
i
n
a
.
He
r
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
tec
h
n
o
l
o
g
y
-
e
n
h
a
n
c
e
d
En
g
li
sh
i
n
s
tru
c
ti
o
n
a
n
d
lea
rn
in
g
a
n
a
ly
ti
c
s
i
n
EF
L
c
o
n
tex
ts.
S
h
e
h
a
s
p
u
b
li
sh
e
d
jo
u
rn
a
l
a
rti
c
les
,
i
n
c
lu
d
in
g
a
n
EI
-
i
n
d
e
x
e
d
p
a
p
e
r,
a
n
d
h
a
s
led
fo
u
r
p
ro
v
in
c
ial/mu
n
icip
a
l
re
se
a
rc
h
p
ro
jec
ts
wh
il
e
p
a
rti
c
i
p
a
ti
n
g
in
m
o
re
th
a
n
fi
v
e
a
d
d
it
i
o
n
a
l
fu
n
d
e
d
p
r
o
je
c
ts.
S
h
e
c
a
n
b
e
c
o
n
ta
c
ted
a
t
e
m
a
il
:
wa
n
g
y
a
d
a
n
2
0
2
5
@g
m
a
il
.
c
o
m
.
S
o
o
n
S
i
n
g
h
Bik
a
r
S
in
g
h
is
th
e
d
e
a
n
o
f
th
e
F
a
c
u
lt
y
o
f
E
d
u
c
a
ti
o
n
a
n
d
S
p
o
rt
s
S
tu
d
ies
a
t
Un
iv
e
rsiti
M
a
lay
sia
S
a
b
a
h
(UMS
)
,
M
a
la
y
sia
,
a
n
d
a
Ph
.
D
.
s
u
p
e
rv
iso
r
.
He
h
o
ld
s
a
P
h
.
D
.
i
n
G
e
o
g
ra
p
h
y
Ed
u
c
a
ti
o
n
fro
m
M
a
c
q
u
a
rie
U
n
iv
e
rsit
y
,
S
y
d
n
e
y
,
a
n
M
.
E
d
.
in
Ed
u
c
a
ti
o
n
a
l
P
sy
c
h
o
l
o
g
y
,
a
n
d
a
B.
A.
(Ho
n
s)
i
n
G
e
o
g
ra
p
h
y
fro
m
th
e
Un
iv
e
rsit
y
o
f
M
a
lay
a
.
His
m
a
in
re
se
a
rc
h
in
tere
sts
a
re
in
e
d
u
c
a
ti
o
n
a
l
p
s
y
c
h
o
l
o
g
y
,
g
e
o
g
ra
p
h
y
e
d
u
c
a
ti
o
n
,
a
n
d
c
u
rricu
lu
m
stu
d
ies
,
wit
h
p
a
rti
c
u
lar
a
tt
e
n
t
io
n
t
o
m
i
x
e
d
m
e
th
o
d
s
re
se
a
rc
h
,
t
h
e
u
se
o
f
g
e
o
g
ra
p
h
ica
l
i
n
fo
rm
a
ti
o
n
s
y
ste
m
s
(G
IS
)
in
tea
c
h
in
g
.
He
h
a
s
p
u
b
li
sh
e
d
b
o
o
k
c
h
a
p
ters
a
n
d
jo
u
r
n
a
l
a
rti
c
les
o
n
G
IS
in
teg
ra
ti
o
n
a
n
d
g
e
o
g
ra
p
h
y
s
k
il
ls
i
n
M
a
lay
si
a
n
sc
h
o
o
ls
a
n
d
is
a
c
ti
v
e
i
n
p
ro
fe
ss
io
n
a
l
a
ss
o
c
iatio
n
s
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
s
o
o
n
b
s@
u
m
s.e
d
u
.
m
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
E
v
al
&
R
es E
d
u
c
I
SS
N:
2252
-
8
8
2
2
A
ca
d
emic
en
g
a
g
eme
n
t a
n
d
a
r
tifi
cia
l in
tellig
en
ce
p
la
tfo
r
m
b
e
h
a
vio
r
s
in
g
r
a
mma
r
a
ch
ieve
m
en
t
(
Wa
n
g
Ya
d
a
n
)
2699
Co
n
n
ie
S
h
in
is
a
n
a
c
a
d
e
m
ic
a
t
Un
iv
e
rsiti
M
a
lay
sia
S
a
b
a
h
(
UMS
),
M
a
lay
sia
,
a
n
d
a
P
h
D
c
o
-
su
p
e
rv
iso
r
.
S
h
e
h
o
ld
s
a
P
h
D
i
n
Cu
rricu
l
u
m
a
n
d
I
n
stru
c
ti
o
n
fro
m
UMS
a
n
d
c
u
rre
n
tl
y
se
rv
e
s
a
s
th
e
He
a
d
o
f
t
h
e
Ru
ra
l
Ed
u
c
a
ti
o
n
Re
se
a
rc
h
Un
i
t.
S
h
e
is
a
lso
a
M
a
lay
sia
n
Qu
a
li
fica
ti
o
n
s
A
g
e
n
c
y
(M
QA
)
a
u
d
it
o
r.
He
r
m
a
in
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
ru
ra
l
e
d
u
c
a
ti
o
n
,
e
a
rly
c
h
il
d
h
o
o
d
e
d
u
c
a
ti
o
n
,
e
d
u
c
a
ti
o
n
a
l
m
a
n
a
g
e
m
e
n
t
a
n
d
lea
d
e
rsh
i
p
,
tea
c
h
in
g
a
n
d
lea
rn
in
g
,
S
TE
M
e
d
u
c
a
ti
o
n
i
n
e
a
rly
c
h
il
d
h
o
o
d
e
d
u
c
a
ti
o
n
,
a
n
d
in
terv
e
n
ti
o
n
d
e
sig
n
a
n
d
e
v
a
lu
a
ti
o
n
.
S
h
e
h
a
s
c
o
n
tri
b
u
te
d
to
c
u
rricu
l
u
m
d
e
v
e
lo
p
m
e
n
t
,
tea
c
h
e
r
e
d
u
c
a
ti
o
n
,
a
n
d
e
d
u
c
a
ti
o
n
a
l
i
n
n
o
v
a
ti
o
n
,
p
a
rti
c
u
larly
fo
r
ru
ra
l
a
n
d
u
n
d
e
rse
rv
e
d
c
o
m
m
u
n
i
ti
e
s.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
c
o
n
n
ie
o
m
p
o
k
@u
m
s.e
d
u
.
m
y
.
Zh
e
n
g
J
u
n
c
a
i
is
a
Ch
i
n
e
se
–
E
n
g
li
s
h
tran
sla
t
o
r
a
n
d
lo
c
a
li
z
a
ti
o
n
sp
e
c
ialist
b
a
se
d
in
S
h
e
n
z
h
e
n
,
Ch
in
a
.
He
h
o
l
d
s
a
n
M
A
in
Tran
sla
ti
o
n
a
n
d
I
n
terp
re
t
in
g
a
n
d
is
CATTI
Lev
e
l
2
c
e
rti
fied
.
S
i
n
c
e
2
0
1
3
,
h
e
h
a
s
wo
rk
e
d
a
s
a
p
a
rt
-
ti
m
e
Lo
c
a
li
z
a
ti
o
n
En
g
i
n
e
e
r
a
t
Re
a
d
d
le
I
n
c
.
,
fo
c
u
sin
g
o
n
UI
l
o
c
a
li
z
a
ti
o
n
,
term
in
o
l
o
g
y
m
a
n
a
g
e
m
e
n
t,
M
TP
E,
a
n
d
c
ro
ss
-
p
latf
o
rm
c
o
n
siste
n
c
y
fo
r
iOS
a
n
d
m
a
c
OS
p
ro
d
u
c
ts.
He
a
lso
w
o
rk
s
a
s
a
f
re
e
lan
c
e
tran
sla
to
r
i
n
li
fe
sc
ien
c
e
s a
n
d
g
a
m
e
lo
c
a
li
z
a
ti
o
n
,
a
n
d
h
a
s c
o
n
tr
ib
u
ted
to
M
TP
E/
LQ
A an
d
AI d
a
ta p
ro
jec
ts wi
th
g
lo
b
a
l
p
latf
o
rm
s.
He
c
a
n
b
e
c
o
n
ta
c
ted
a
t
e
m
a
il
:
ij
a
y
c
i@g
m
a
il
.
c
o
m
.
Zh
a
n
g
Q
ia
n
q
i
a
n
is
a
tea
c
h
in
g
a
ss
istan
t
a
t
G
u
a
n
g
z
h
o
u
Xi
n
h
u
a
Un
i
v
e
rsity
,
Ch
in
a
.
S
h
e
h
o
l
d
s
a
m
a
ste
r
’
s
d
e
g
re
e
in
F
o
re
ig
n
Li
n
g
u
isti
c
s
a
n
d
Ap
p
li
e
d
Li
n
g
u
isti
c
s.
He
r
re
se
a
rc
h
in
tere
sts
fo
c
u
s
o
n
th
e
p
sy
c
h
o
lo
g
ica
l
d
e
v
e
lo
p
m
e
n
t
m
e
c
h
a
n
ism
s
o
f
ES
P
tea
c
h
e
rs,
stu
d
e
n
ts
’
lea
rn
i
n
g
m
o
ti
v
a
ti
o
n
,
a
n
d
t
h
e
d
e
v
e
lo
p
m
e
n
t
a
n
d
re
fo
rm
o
f
c
o
ll
e
g
e
fo
re
i
g
n
lan
g
u
a
g
e
c
u
rricu
la.
S
h
e
h
a
s
p
u
b
li
sh
e
d
se
v
e
ra
l
sin
g
le
-
a
u
t
h
o
re
d
a
rti
c
les
in
n
a
ti
o
n
a
l
a
n
d
in
tern
a
ti
o
n
a
l
jo
u
r
n
a
ls
a
n
d
d
e
v
e
l
o
p
e
d
t
h
e
E
S
P
c
o
u
rse
.
S
h
e
h
a
s
led
tw
o
n
a
ti
o
n
a
l
re
se
a
rc
h
p
ro
jec
ts
a
n
d
p
a
rti
c
ip
a
ted
in
th
re
e
a
d
d
it
io
n
a
l
p
r
o
v
i
n
c
ial
-
a
n
d
u
n
iv
e
rsit
y
-
lev
e
l
p
r
o
j
e
c
ts.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
z
1
2
4
6
9
1
9
1
6
1
@g
m
a
il
.
c
o
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.