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Artif
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and writi
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R
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Mar
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2
0
2
6
Acc
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ted
Mar
28
,
2
0
2
6
Artifi
c
ial
in
telli
g
e
n
c
e
(AI)
is
in
c
re
a
sin
g
ly
a
d
o
p
ted
i
n
Ch
i
n
e
se
En
g
li
s
h
a
s
a
fo
re
ig
n
lan
g
u
a
g
e
(EF
L)
c
las
sro
o
m
s,
y
e
t
it
s
lea
rn
in
g
b
e
n
e
fi
ts
re
m
a
in
u
n
c
e
rtain
i
n
a
n
e
x
a
m
in
a
ti
o
n
-
o
ri
e
n
ted
c
o
n
te
x
t
wh
e
re
re
a
d
in
g
a
n
d
writi
n
g
p
ro
ficie
n
c
y
a
re
o
f
ten
c
o
n
stra
in
e
d
.
Th
is
stu
d
y
e
m
p
lo
y
e
d
a
q
u
a
n
ti
tati
v
e
q
u
a
si
-
e
x
p
e
rime
n
tal
d
e
sig
n
wit
h
p
re
-
a
n
d
p
o
st
-
tes
ts,
i
n
v
o
lv
i
n
g
6
7
n
o
n
-
En
g
li
sh
-
m
a
jo
r
u
n
d
e
rg
ra
d
u
a
tes
a
ss
ig
n
e
d
to
a
c
o
n
tro
l
g
r
o
u
p
a
n
d
a
n
AI
-
in
teg
ra
ted
g
ro
u
p
,
to
e
x
a
m
in
e
AI
-
su
p
p
o
rte
d
lea
rn
in
g
e
ffe
c
ts
o
n
re
a
d
i
n
g
a
n
d
writi
n
g
with
in
a
c
o
n
str
u
c
ti
v
e
a
li
g
n
m
e
n
t
(CA)
fra
m
e
wo
rk
.
Bo
th
g
ro
u
p
s
imp
ro
v
e
d
a
fter
th
e
in
te
rv
e
n
t
io
n
,
wh
i
le
th
e
AI
-
in
teg
ra
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g
ro
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p
d
e
m
o
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stra
te
d
a
n
o
ta
b
ly
g
re
a
ter
g
a
in
in
re
a
d
i
n
g
p
e
rfo
rm
a
n
c
e
.
Th
e
fin
d
in
g
s
su
g
g
e
st
th
a
t
CA
c
a
n
stre
n
g
th
e
n
th
e
e
ffe
c
ti
v
e
n
e
ss
o
f
AI
in
teg
ra
ti
o
n
b
y
a
li
g
n
in
g
lea
rn
in
g
o
u
tco
m
e
s,
a
c
ti
v
it
ies
,
a
n
d
a
ss
e
ss
m
e
n
t,
a
n
d
th
a
t
AI
u
se
,
in
tu
r
n
,
c
a
n
re
in
f
o
rc
e
a
li
g
n
m
e
n
t
d
u
ri
n
g
th
e
lea
rn
in
g
p
ro
c
e
ss
.
P
e
d
a
g
o
g
ica
l
imp
l
ica
ti
o
n
s
a
re
d
isc
u
ss
e
d
re
g
a
rd
in
g
p
e
rfo
rm
a
n
c
e
d
isp
a
rit
y
,
th
e
e
x
ten
sio
n
o
f
CA
-
g
u
id
e
d
AI
u
s
e
to
o
th
e
r
EF
L
d
o
m
a
in
s,
a
n
d
f
u
tu
re
i
n
stru
c
t
i
o
n
a
l
re
se
a
rc
h
.
K
ey
w
o
r
d
s
:
Ar
tific
ial
in
tellig
en
ce
C
o
n
s
tr
u
ctiv
e
alig
n
m
en
t
E
FL
R
ea
d
in
g
W
r
itin
g
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
:
Haz
r
u
l
Ab
d
u
l H
am
id
Sch
o
o
l o
f
Dis
tan
ce
E
d
u
ca
tio
n
,
Un
iv
er
s
iti Sain
s
Ma
lay
s
ia
1
1
8
0
0
,
Geo
r
g
e
T
o
wn
,
Pen
an
g
,
Ma
lay
s
ia
E
m
ail:
h
az
r
u
l@
u
s
m
.
m
y
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
ap
p
licatio
n
a
n
d
d
ev
el
o
p
m
en
t
o
f
ar
tific
ial
in
tellig
en
ce
(
AI
)
h
av
e
ar
is
en
in
e
d
u
ca
ti
o
n
al
f
ield
,
tr
ig
g
er
in
g
wid
e
in
ter
est
an
d
at
ten
tio
n
in
ac
ad
em
ia.
I
m
p
lem
e
n
tin
g
g
en
er
ativ
e
AI
in
ed
u
ca
tio
n
r
eq
u
ir
es
d
ig
ital
co
m
p
eten
cies
an
d
p
ed
a
g
o
g
ica
l
k
n
o
wled
g
e
f
r
o
m
in
s
tr
u
cto
r
s
[
1
]
,
s
u
ch
as
tailo
r
in
g
lea
r
n
in
g
co
n
ten
t
to
lear
n
er
s
’
n
ee
d
s
,
en
h
a
n
cin
g
lea
r
n
in
g
ac
tiv
ities
,
o
r
in
ten
s
if
y
in
g
lear
n
in
g
ex
p
er
ien
ce
s
[
2
]
,
[
3
]
.
I
n
th
e
E
n
g
lis
h
as
a
f
o
r
ei
g
n
lan
g
u
ag
e
(
E
FL)
c
o
n
tex
t,
E
n
g
l
is
h
teac
h
er
s
h
av
e
r
eso
r
ted
to
d
iv
er
s
e
AI
to
o
ls
,
s
u
ch
as
AI
ch
atb
o
ts
,
au
to
m
ated
wr
itin
g
ev
alu
ati
o
n
(
AW
E
)
,
an
d
au
to
m
ated
s
p
ee
c
h
r
ec
o
g
n
itio
n
(
ASR
)
,
in
ten
d
in
g
to
f
ac
ilit
ate
s
tu
d
en
ts
’
E
n
g
lis
h
p
r
o
f
icien
c
y
[
4
]
–
[
6
]
,
m
o
tiv
atio
n
an
d
co
n
f
id
e
n
ce
[
7
]
,
[
8
]
.
Ag
a
in
s
t
th
is
b
ac
k
d
r
o
p
,
r
esear
ch
o
n
AI
-
s
u
p
p
o
r
ted
E
FL
lear
n
in
g
h
as
ex
p
a
n
d
ed
co
n
s
id
er
ab
ly
,
a
n
d
r
ea
d
in
g
an
d
wr
itin
g
r
em
ai
n
in
d
is
p
e
n
s
ab
le
co
m
p
o
n
en
ts
o
f
o
v
er
all
E
FL
p
r
o
f
icien
c
y
[
9
]
.
T
h
e
r
ea
d
in
g
s
p
ee
d
o
f
E
n
g
lis
h
lear
n
er
s
in
C
h
in
a
i
s
s
ig
n
if
ica
n
tly
s
lo
wer
th
an
th
at
o
f
co
lleg
e
s
tu
d
en
ts
in
th
e
Un
ited
States
an
d
Gr
ea
t
B
r
itain
,
p
ar
tly
b
ec
au
s
e
m
an
y
lear
n
er
s
p
r
o
ce
s
s
E
n
g
lis
h
wo
r
d
b
y
wo
r
d
[
1
0
]
.
T
h
is
ten
d
en
cy
is
r
ein
f
o
r
ce
d
b
y
r
e
ad
in
g
p
r
ac
tices
s
h
ap
ed
b
y
ex
am
-
o
r
ien
ted
in
s
tr
u
ctio
n
,
wh
er
e
r
ea
d
in
g
al
o
u
d
is
wid
ely
u
s
ed
f
o
r
m
em
o
r
izatio
n
th
r
o
u
g
h
o
u
t
p
r
e
-
te
r
tiar
y
a
n
d
ter
tiar
y
ed
u
ca
tio
n
[
1
1
]
.
I
n
p
ar
allel,
lear
n
er
s
’
wr
itin
g
is
o
f
ten
ch
ar
ac
ter
ized
b
y
wea
k
s
en
ten
ce
-
lev
el
e
x
p
r
ess
io
n
,
with
lim
ited
s
y
n
tactic
f
lex
ib
ilit
y
an
d
a
n
u
n
d
er
d
ev
elo
p
e
d
ab
ilit
y
to
f
o
r
m
u
late
co
h
er
en
t
wr
itten
s
tatem
en
ts
[
1
2
]
.
As
a
r
esu
lt,
s
tu
d
en
ts
o
f
ten
s
tr
u
g
g
le
to
attain
th
e
ex
p
ec
ted
le
v
el
o
f
la
n
g
u
ag
e
c
o
m
p
eten
ce
.
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
r
tifi
cia
l in
tellig
en
ce
in
a
ctio
n
:
en
h
a
n
cin
g
r
ea
d
in
g
a
n
d
w
r
it
in
g
p
r
o
ficien
cy
in
C
h
in
ese
… (
Jin
g
d
a
n
Liu
)
1817
Stu
d
ies o
n
AI
-
s
u
p
p
o
r
te
d
r
ea
d
i
n
g
in
E
FL
h
av
e
r
ep
o
r
ted
g
ai
n
s
in
r
ea
d
in
g
co
m
p
r
eh
e
n
s
io
n
ac
r
o
s
s
v
ar
ied
ap
p
r
o
ac
h
es,
in
clu
d
in
g
m
o
b
ile
ap
p
licatio
n
s
,
v
id
eo
g
a
m
es
[
1
3
]
,
ex
ec
u
tiv
e
-
f
u
n
ctio
n
t
r
ain
i
n
g
[
1
4
]
,
in
te
n
s
iv
e
r
ea
d
in
g
[
1
5
]
,
b
len
d
ed
lear
n
in
g
[
1
6
]
,
an
d
s
to
r
y
tellin
g
ch
atb
o
ts
[
4
]
.
R
ea
d
in
g
co
m
p
r
eh
en
s
io
n
i
n
ef
f
ec
tiv
e
r
ea
d
er
s
r
elies
o
n
co
n
s
tr
u
ctin
g
s
em
an
tic
r
elate
d
n
ess
f
r
o
m
tex
tu
al
cu
es
[
1
7
]
.
Nev
e
r
th
eless
,
AI
-
in
teg
r
ated
r
ea
d
i
n
g
r
esear
ch
h
as
h
ig
h
lig
h
te
d
to
o
l
-
r
elate
d
co
n
s
tr
ain
ts
,
p
ar
ticu
lar
l
y
th
e
tim
e
-
ef
f
o
r
t
b
u
r
d
e
n
th
at
ca
lls
f
o
r
ca
lib
r
atio
n
in
s
tu
d
y
d
esig
n
an
d
ca
p
ac
ity
t
o
s
u
p
p
o
r
t
r
ea
d
in
g
m
an
ag
e
m
e
n
t
[
18
]
,
[
19
]
.
Acc
o
r
d
in
g
ly
,
AI
-
s
u
p
p
o
r
te
d
r
ea
d
in
g
m
ay
b
en
ef
it
f
r
o
m
r
ec
o
m
m
e
n
d
in
g
m
ater
ials
th
at
b
etter
alig
n
with
lear
n
er
s
’
ab
ilit
ies
an
d
p
r
ef
er
e
n
ce
s
[
2
0
]
.
On
th
e
o
th
er
h
an
d
,
ac
ad
e
m
ic
wr
itin
g
in
h
ig
h
er
e
d
u
ca
tio
n
r
eq
u
ir
es
s
tu
d
en
ts
to
s
tr
u
ct
u
r
e
id
ea
s
an
d
r
ef
in
e
th
in
k
in
g
[
2
1
]
.
Stu
d
en
ts
o
f
ten
r
ep
o
r
t
p
o
s
itiv
e
attitu
d
es
to
war
d
C
h
atGPT
-
ass
i
s
ted
wr
itin
g
[
2
2
]
an
d
p
er
ce
iv
ed
im
p
r
o
v
em
e
n
t
wh
en
u
s
in
g
AI
f
ee
d
b
ac
k
s
y
s
tem
s
[
5
]
,
au
to
m
a
ted
f
ee
d
b
ac
k
p
latf
o
r
m
s
,
an
d
AW
E
to
o
ls
s
u
ch
as
Gr
am
m
ar
ly
[
2
3
]
.
Ho
wev
e
r
,
A
I
s
u
p
p
o
r
t
m
a
y
n
o
t
f
it
d
iv
e
r
s
e
lear
n
in
g
s
ty
les
an
d
ca
n
s
h
o
w
li
m
ited
in
f
lu
en
ce
o
n
ar
g
u
m
en
tativ
e
wr
itin
g
s
elf
-
ef
f
icac
y
[
2
4
]
,
with
s
o
m
e
s
tu
d
i
es
r
ep
o
r
tin
g
n
o
clea
r
g
ain
s
f
r
o
m
AI
-
g
e
n
er
ated
f
ee
d
b
ac
k
[
12
]
o
r
n
o
s
ig
n
if
ica
n
t e
f
f
ec
t o
n
c
o
n
tin
u
a
n
ce
in
ten
ti
o
n
d
esp
ite
m
u
ltip
le
to
o
ls
b
ein
g
av
ailab
le
[
8
]
.
C
o
n
s
tr
u
ctiv
e
alig
n
m
en
t
(
C
A)
is
a
co
n
s
tr
u
ctiv
is
t
f
r
am
ewo
r
k
th
at
alig
n
s
in
ten
d
ed
lear
n
in
g
o
u
tco
m
es,
ac
tiv
ities
,
an
d
ass
ess
m
en
t
to
p
r
o
v
id
e
a
co
h
er
en
t
b
asis
f
o
r
ad
d
r
ess
in
g
im
p
lem
en
tatio
n
co
n
s
tr
ain
ts
,
as
s
h
o
wn
in
Fig
u
r
e
1
.
I
t
s
h
if
ts
in
s
tr
u
ctio
n
f
r
o
m
teac
h
er
-
ce
n
ter
ed
d
eliv
er
y
to
s
tu
d
e
n
t
-
ce
n
ter
ed
lear
n
in
g
[
2
5
]
,
[
2
6
]
,
s
o
th
at
wh
at
s
tu
d
en
ts
ar
e
ex
p
ec
ted
t
o
ac
h
iev
e
is
co
n
s
is
ten
tly
s
u
p
p
o
r
ted
b
y
wh
at
th
e
y
d
o
an
d
h
o
w
th
ey
ar
e
ev
al
u
ated
.
C
A
p
r
io
r
itizes
h
o
w
s
tu
d
en
ts
l
ea
r
n
o
v
er
wh
at
teac
h
er
s
p
r
esen
t,
th
er
e
b
y
in
cr
ea
s
in
g
th
e
lik
e
lih
o
o
d
o
f
ac
h
iev
i
n
g
th
e
in
ten
d
e
d
o
u
tc
o
m
es.
E
m
p
i
r
ical
wo
r
k
h
as
s
h
o
w
n
th
at
C
A
-
in
f
o
r
m
e
d
d
esig
n
,
ev
e
n
with
o
u
t
tech
n
o
l
o
g
y
,
ca
n
s
tr
en
g
th
en
lear
n
in
g
e
x
p
er
ie
n
c
es
b
y
an
c
h
o
r
in
g
in
s
tr
u
ctio
n
in
ex
p
licit
lear
n
in
g
o
b
jectiv
es
an
d
p
r
o
m
o
tin
g
d
ee
p
e
r
lear
n
in
g
[
27
]
.
I
n
tech
n
o
lo
g
y
-
en
h
an
ce
d
a
n
d
b
le
n
d
ed
c
o
n
te
x
ts
,
C
A
ad
d
itio
n
ally
h
elp
s
d
iag
n
o
s
e
m
is
m
atch
es
b
etwe
en
m
ater
ials
,
cu
r
r
icu
l
u
m
r
eq
u
ir
em
e
n
ts
,
an
d
s
tu
d
e
n
ts
’
n
ee
d
s
,
s
u
p
p
o
r
tin
g
m
o
r
e
co
h
e
r
e
n
t
d
esig
n
d
ec
is
io
n
s
in
b
len
d
e
d
teac
h
in
g
[
28
].
Fig
u
r
e
1
.
E
lem
e
n
ts
o
f
C
A
E
m
er
g
in
g
s
tu
d
ies
s
u
g
g
est
th
at
AI
to
o
ls
ca
n
h
elp
s
tr
en
g
th
en
alig
n
m
en
t
b
y
s
u
p
p
o
r
tin
g
c
o
u
r
s
e
d
esig
n
an
d
th
e
im
p
lem
en
tatio
n
o
f
e
f
f
ec
tiv
e
teac
h
in
g
-
lea
r
n
in
g
ac
t
iv
ities
[
22
]
,
[
29
]
,
co
n
s
is
ten
t
with
th
e
v
iew
th
at
lear
n
in
g
is
an
ac
tiv
e
c
o
n
s
tr
u
ct
io
n
p
r
o
ce
s
s
[
3
0
]
.
AI
ca
n
also
en
r
ich
lea
r
n
in
g
ex
p
er
ien
ce
s
th
r
o
u
g
h
p
er
s
o
n
alize
d
m
ater
ials
th
at
b
etter
m
atch
le
ar
n
er
s
’
n
ee
d
s
an
d
ca
p
a
b
ilit
ies
[
3
1
]
.
Nev
e
r
th
eless
,
alig
n
m
en
t
s
h
o
u
ld
r
em
ain
th
e
s
tar
tin
g
p
o
in
t:
in
ten
d
ed
o
u
tco
m
es
m
u
s
t
b
e
s
p
ec
if
ied
f
ir
s
t
,
af
ter
wh
ich
AI
to
o
ls
s
h
o
u
ld
b
e
s
elec
ted
an
d
co
n
f
ig
u
r
ed
to
s
er
v
e
th
o
s
e
o
u
t
co
m
es,
en
s
u
r
in
g
p
u
r
p
o
s
ef
u
l
a
n
d
ef
f
ec
tiv
e
in
teg
r
atio
n
[
3
2
]
.
I
n
E
FL
co
n
tex
ts
,
in
s
tr
u
cto
r
s
th
er
ef
o
r
e
n
ee
d
to
in
teg
r
ate
AI
cr
ea
tiv
ely
wh
ile
m
ain
tain
in
g
alig
n
m
en
t
b
etwe
en
o
u
tco
m
es,
ac
tiv
ities
,
an
d
ass
ess
m
en
t.
Ho
wev
er
,
r
esear
ch
th
at
ex
a
m
in
es
AI
-
s
u
p
p
o
r
ted
d
ev
elo
p
m
e
n
t
o
f
r
ea
d
in
g
an
d
wr
itin
g
u
n
d
er
a
C
A
f
r
am
ewo
r
k
r
em
ai
n
s
lim
ited
.
T
h
er
ef
o
r
e,
wh
e
n
C
A
p
r
o
v
id
es
a
s
o
lid
f
o
u
n
d
atio
n
f
o
r
ef
f
ec
tiv
e
lear
n
in
g
a
n
d
A
I
s
u
p
p
o
r
t
is
b
o
th
r
ele
v
an
t
a
n
d
im
p
ac
tf
u
l,
th
is
s
tu
d
y
aim
s
to
ap
p
l
y
C
A
f
r
am
ewo
r
k
in
in
v
esti
g
atin
g
h
o
w
AI
-
in
teg
r
ated
lear
n
i
n
g
af
f
ec
ts
lear
n
er
s
’
ac
ad
em
ic
p
er
f
o
r
m
a
n
ce
in
th
eir
r
ea
d
in
g
a
n
d
wr
itin
g
s
k
ills
.
T
h
u
s
,
t
wo
r
esear
ch
q
u
esti
o
n
s
ar
e
as
:
−
I
s
th
er
e
an
y
s
ig
n
if
ican
t
e
f
f
ec
t
o
f
n
o
n
-
AI
lea
r
n
in
g
an
d
AI
-
in
t
eg
r
ated
lear
n
in
g
o
n
ac
a
d
em
ic
ac
h
iev
em
en
t
in
r
ea
d
in
g
a
n
d
wr
itin
g
?
−
I
s
th
er
e
an
y
s
ig
n
if
ican
t
co
r
r
ela
tio
n
b
etwe
en
r
ea
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in
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d
wr
itin
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n
d
er
AI
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n
teg
r
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lear
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i
n
g
co
m
p
ar
e
d
to
non
-
AI
lea
r
n
in
g
?
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
2
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I
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J
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&
R
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Vo
l
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15
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No
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2
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2
6
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1
8
1
6
-
1
8
2
4
1818
2.
M
E
T
H
O
D
I
n
co
n
s
id
er
in
g
CA
as
th
e
in
s
tr
u
ctio
n
al
f
r
am
ewo
r
k
,
th
is
s
tu
d
y
d
iv
id
ed
all
6
7
p
ar
ticip
a
n
ts
in
to
two
g
r
o
u
p
s
,
with
o
n
e
e
x
p
er
ien
ci
n
g
n
o
n
-
AI
lear
n
in
g
an
d
th
e
o
t
h
er
u
n
d
er
g
o
in
g
an
AI
-
in
teg
r
ate
d
lear
n
in
g
p
r
o
ce
s
s
,
in
p
u
r
s
u
it
o
f
ex
p
lo
r
in
g
t
h
e
ef
f
ec
ts
o
f
AI
o
n
p
r
o
m
o
tin
g
lear
n
er
s
’
r
ea
d
i
n
g
an
d
wr
itin
g
s
k
ills
.
A
q
u
asi
-
ex
p
er
im
en
tal
r
esear
ch
m
et
h
o
d
was
ad
o
p
ted
an
d
im
p
lem
e
n
ted
th
r
o
u
g
h
o
u
t
a
1
7
-
wee
k
e
x
p
er
im
en
t,
as
s
h
o
wn
in
T
ab
le
1
.
Stu
d
en
ts
in
th
e
co
n
t
r
o
l
g
r
o
u
p
an
d
th
e
e
x
p
er
im
e
n
tal
g
r
o
u
p
wer
e
r
esp
ec
tiv
ely
s
u
b
j
ec
ted
to
n
o
n
-
AI
an
d
AI
-
in
teg
r
ated
lear
n
in
g
.
R
ea
d
i
n
g
an
d
wr
itin
g
test
s
wer
e
ad
m
in
is
ter
ed
to
b
o
th
g
r
o
u
p
s
b
e
f
o
r
e
a
n
d
a
f
ter
th
e
ex
p
er
im
en
t.
T
h
e
p
r
e
-
test
s
ev
alu
ated
s
tu
d
en
ts
’
p
r
elim
in
ar
y
le
v
els
o
f
lan
g
u
ag
e
p
r
o
f
icien
cy
f
o
r
co
m
p
ar
is
o
n
with
p
o
s
t
-
test
s
,
aim
in
g
to
g
au
g
e
th
e
ef
f
ec
t o
f
d
if
f
er
e
n
t le
ar
n
in
g
o
n
r
ea
d
in
g
a
n
d
wr
itin
g
s
k
ills
.
T
ab
le
1
.
R
esear
ch
d
esig
n
Q
u
a
si
-
e
x
p
e
r
i
me
n
t
a
l
r
e
se
a
r
c
h
Pre
-
t
e
st
4
m
o
n
t
h
s e
x
p
e
r
i
me
n
t
P
o
st
-
t
e
st
D
V
s:
r
e
a
d
i
n
g
a
n
d
w
r
i
t
i
n
g
I
V
s:
n
on
-
A
I
l
e
a
r
n
i
n
g
a
n
d
AI
-
i
n
t
e
g
r
a
t
e
d
l
e
a
r
n
i
n
g
D
V
s:
r
e
a
d
i
n
g
a
n
d
w
r
i
t
i
n
g
2
.
1
.
Sa
m
ples
a
nd
ins
t
ruct
io
n
s
T
h
is
s
tu
d
y
i
n
v
o
l
v
ed
a
co
h
o
r
t
o
f
6
7
s
ec
o
n
d
-
y
ea
r
u
n
d
er
g
r
a
d
u
ates
f
r
o
m
a
s
ec
o
n
d
-
tier
u
n
iv
er
s
ity
in
Hu
n
an
Pro
v
i
n
ce
,
C
h
in
a.
All p
ar
ticip
an
ts
wer
e
n
o
n
-
E
n
g
lis
h
m
ajo
r
s
an
d
wer
e
ass
ess
ed
as h
av
in
g
a
f
o
u
n
d
atio
n
al
lev
el
o
f
E
n
g
lis
h
p
r
o
f
icien
c
y
.
T
h
e
in
ter
v
en
tio
n
was
im
p
lem
en
ted
in
th
e
s
ec
o
n
d
s
em
ester
o
f
th
e
s
o
p
h
o
m
o
r
e
y
ea
r
with
in
an
E
n
g
lis
h
f
o
r
s
p
e
cif
ic
p
u
r
p
o
s
es
(
E
SP
)
co
u
r
s
e.
T
h
e
co
u
r
s
e
c
o
m
p
r
is
ed
3
2
s
ess
io
n
s
o
r
g
an
ize
d
in
to
1
6
wee
k
ly
less
o
n
s
.
T
h
e
in
s
tr
u
ctio
n
al
d
esig
n
f
o
r
th
e
two
g
r
o
u
p
s
is
p
r
esen
ted
in
T
a
b
le
2
.
T
h
e
co
n
tr
o
l
g
r
o
u
p
(
n
=3
3
)
lear
n
e
d
th
r
o
u
g
h
tex
tb
o
o
k
s
,
Po
wer
Po
in
t
s
lid
es,
an
d
o
n
lin
e
m
ater
ials
.
T
h
e
ex
p
er
im
en
tal
g
r
o
u
p
(
n
=3
4
)
ad
d
itio
n
ally
u
s
ed
D
o
u
B
ao
as a
n
AI
to
o
l o
n
ce
p
er
wee
k
to
e
n
r
ich
lear
n
in
g
.
T
h
e
in
ten
d
ed
lear
n
in
g
o
u
tco
m
es f
o
r
r
ea
d
in
g
a
n
d
wr
itin
g
wer
e
s
p
ec
if
ied
with
r
ef
er
en
ce
to
th
e
r
ev
is
ed
B
lo
o
m
’
s
tax
o
n
o
m
y
,
ad
o
p
tin
g
lev
el
4
(
a
n
aly
ze
)
as
th
e
tar
g
et
co
g
n
i
tiv
e
d
em
an
d
f
o
r
th
is
co
h
o
r
t
[
3
3
]
.
B
y
th
e
e
n
d
o
f
th
e
co
u
r
s
e,
s
tu
d
en
ts
wer
e
ex
p
ec
ted
to
ac
cu
r
ately
d
is
tin
g
u
is
h
m
ain
id
ea
s
f
r
o
m
s
u
p
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o
r
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etails
wh
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i
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ticle
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d
to
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d
ep
en
d
en
tly
p
r
o
d
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ce
a
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s
tr
u
ctu
r
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ay
with
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r
a
m
m
atica
lly
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r
ate
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en
ten
ce
s
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ese
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ilit
ies
ar
e
co
m
m
o
n
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y
ch
allen
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g
f
o
r
C
h
in
ese
s
tu
d
en
ts
[
3
4
]
,
[
3
5
]
.
Stu
d
en
ts
’
p
er
f
o
r
m
an
ce
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d
m
aster
y
o
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k
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y
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o
r
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al
ac
a
d
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m
ic
ex
am
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atio
n
.
T
ab
le
2
.
I
n
s
tr
u
ctio
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d
esig
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r
o
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p
s
No
CA
Le
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n
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n
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o
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t
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me
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t
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v
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t
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s
A
ssessme
n
t
C
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n
t
r
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l
g
r
o
u
p
33
−
R
e
a
d
i
n
g
:
t
o
d
i
s
t
i
n
g
u
i
sh
t
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−
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t
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g
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d
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v
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p
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w
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st
r
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d
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ssa
y
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−
To
e
x
a
mi
n
e
g
r
a
mm
a
r
r
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l
e
s
c
o
r
r
e
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t
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o
n
-
A
I
l
e
a
r
n
i
n
g
Te
x
t
b
o
o
k
s
;
P
P
T
s
;
o
n
l
i
n
e
mat
e
r
i
a
l
s
P
a
p
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r
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c
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m
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me
n
t
t
e
st
s
Ex
p
e
r
i
m
e
n
t
a
l
g
r
o
u
p
34
AI
-
i
n
t
e
g
r
a
t
e
d
l
e
a
r
n
i
n
g
Te
x
t
b
o
o
k
s
;
P
P
T
s
;
o
n
l
i
n
e
mat
e
r
i
a
l
s
;
D
o
u
B
a
o
A
I
2
.
2
.
I
ns
t
rum
ent
s
Un
d
er
th
e
C
A
f
r
am
ewo
r
k
,
ac
a
d
em
ic
r
ea
d
in
g
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n
d
wr
itin
g
test
s
wer
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u
s
ed
as
th
e
r
esear
ch
in
s
tr
u
m
en
ts
an
d
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ad
m
i
n
is
ter
ed
to
b
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th
g
r
o
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p
s
as p
r
e
-
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d
p
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t
-
test
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as
s
h
o
wn
in
T
ab
le
3
.
T
h
e
r
ea
d
in
g
test
(
3
0
p
o
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ts
)
in
clu
d
ed
two
p
ass
ag
es
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es
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ab
ilit
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tify
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tific
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h
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1
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ts
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r
e
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u
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ar
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ay
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ater
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I
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DV
Ty
p
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1
15
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8
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r
tifi
cia
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tellig
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:
en
h
a
n
cin
g
r
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in
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d
w
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it
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p
r
o
ficien
cy
in
C
h
in
ese
… (
Jin
g
d
a
n
Liu
)
1819
2
.
3
.
Da
t
a
a
na
ly
s
is
T
h
e
d
ata
wer
e
a
n
aly
ze
d
u
s
in
g
d
escr
ip
ti
v
e
an
d
in
f
er
en
ti
al
s
tatis
tic
s
in
SP
SS
v
er
s
io
n
2
9
,
with
s
tatis
t
ical
s
ig
n
if
ican
ce
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ted
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th
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ef
o
r
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th
e
m
ain
ex
p
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elim
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cted
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ased
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ad
m
in
is
ter
ed
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class
o
f
3
1
s
tu
d
en
ts
.
As s
h
o
wn
in
T
ab
le
4
,
th
e
m
ea
n
s
co
r
es f
o
r
th
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two
ad
m
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is
tr
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icate
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s
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5
p
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les
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test
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e
s
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ity
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izes
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est
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at
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y
ield
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s
tab
le
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s
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r
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ac
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tim
e,
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u
p
p
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r
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g
th
eir
r
eliab
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y
f
o
r
as
s
ess
in
g
th
e
tar
g
eted
co
n
s
tr
u
cts
in
th
is
s
tu
d
y
.
T
ab
le
4
.
Descr
ip
tiv
e
an
al
y
s
is
o
f
p
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elim
in
a
r
y
s
tu
d
y
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sp
e
c
t
s
No
M
i
n
M
a
x
M
e
a
n
SD
S
k
e
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ss
K
u
r
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R
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1
31
2
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1
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1
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3
.
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2
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c
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M
e
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9
5
%
C
I
(
d
i
f
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)
t
SD
C
o
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n
’
s
d
P
v
a
l
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e
Lo
w
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p
p
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R
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d
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1
5
3
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4
0
0
3.
RE
SU
L
T
S
As
p
r
esen
ted
i
n
T
a
b
le
6
,
wh
i
le
b
o
th
g
r
o
u
p
s
s
tar
ted
with
s
im
ilar
p
r
e
-
test
av
er
ag
es
(
ap
p
r
o
x
im
ately
1
1
.
7
)
i
n
r
ea
d
in
g
,
th
e
p
o
s
t
-
test
o
u
tco
m
es
d
iv
er
g
ed
m
ar
k
ed
ly
.
T
h
e
AI
-
in
teg
r
ated
g
r
o
u
p
ac
h
ie
v
ed
a
h
ig
h
e
r
m
ea
n
s
co
r
e
(
1
9
.
5
9
)
co
m
p
a
r
ed
to
th
e
co
n
tr
o
l
g
r
o
u
p
(
1
5
.
7
9
)
.
N
o
tab
ly
,
th
e
g
r
ea
ter
r
e
d
u
ctio
n
in
s
tan
d
ar
d
d
e
v
iatio
n
f
r
o
m
6
.
2
6
9
t
o
4
.
6
0
6
s
u
g
g
e
s
ts
m
o
r
e
co
n
s
is
ten
t
p
er
f
o
r
m
an
ce
am
o
n
g
s
tu
d
en
ts
af
ter
th
e
AI
-
in
teg
r
ate
d
in
ter
v
en
tio
n
.
T
h
e
s
h
if
t
in
s
k
ew
n
ess
also
in
d
icate
s
th
at
th
e
s
co
r
e
d
is
tr
ib
u
tio
n
b
ec
am
e
m
o
r
e
c
en
ter
ed
a
r
o
u
n
d
t
h
e
m
ea
n
,
with
f
ewe
r
lo
w
-
p
e
r
f
o
r
m
in
g
o
u
tlier
s
in
th
e
ex
p
er
im
e
n
tal
g
r
o
u
p
.
Ov
er
all,
AI
-
in
te
g
r
ated
lear
n
in
g
le
d
to
a
s
u
b
s
tan
tial im
p
r
o
v
em
e
n
t in
r
ea
d
in
g
s
k
ills
r
elativ
e
to
th
e
n
o
n
-
AI
ap
p
r
o
ac
h
.
T
ab
le
7
s
h
o
ws
th
at
b
o
th
g
r
o
u
p
s
im
p
r
o
v
ed
in
wr
itin
g
.
T
h
e
ex
p
er
im
en
tal
g
r
o
u
p
ex
h
ib
it
ed
a
lar
g
er
in
cr
ea
s
e
in
m
ea
n
s
co
r
e
f
r
o
m
7
.
5
5
9
to
9
.
0
0
0
a
n
d
a
clea
r
er
r
ed
u
ctio
n
i
n
s
co
r
e
v
ar
iab
ilit
y
f
r
o
m
2
.
9
4
6
to
2
.
0
1
5
,
wh
er
ea
s
th
e
co
n
tr
o
l
g
r
o
u
p
s
h
o
wed
r
elativ
ely
litt
le
ch
an
g
e
in
d
is
p
er
s
io
n
.
Sk
ewn
ess
in
cr
ea
s
ed
in
b
o
th
g
r
o
u
p
s
,
in
d
icatin
g
a
s
tr
o
n
g
er
co
n
ce
n
tr
atio
n
o
f
h
ig
h
er
p
o
s
t
-
test
s
co
r
e
s
,
an
d
th
e
r
is
e
in
k
u
r
to
s
is
s
u
g
g
ests
a
m
o
r
e
p
ea
k
ed
d
is
tr
ib
u
tio
n
.
Ov
er
all,
th
e
wr
itin
g
s
co
r
es
s
h
if
ted
u
p
war
d
in
b
o
th
g
r
o
u
p
s
,
with
m
o
r
e
p
r
o
n
o
u
n
ce
d
g
ain
s
an
d
g
r
ea
ter
co
n
s
is
ten
cy
in
th
e
AI
-
i
n
teg
r
ated
g
r
o
u
p
.
T
ab
le
6
.
Descr
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DIS
CU
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I
O
N
B
o
th
g
r
o
u
p
s
s
h
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wed
s
ig
n
if
ica
n
t
g
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s
in
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ea
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wr
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,
b
u
t
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p
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o
v
em
e
n
ts
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e
lar
g
er
u
n
d
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th
e
AI
-
in
teg
r
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in
s
tr
u
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.
T
h
is
s
u
g
g
ests
th
at
wh
en
AI
u
s
e
is
d
esig
n
ed
with
in
a
C
A
f
r
a
m
ewo
r
k
,
it c
an
m
o
r
e
ef
f
ec
tiv
ely
s
u
p
p
o
r
t
tar
g
eted
an
d
ass
ess
ab
le
o
u
tco
m
es.
Natu
r
al
lan
g
u
ag
e
p
r
o
ce
s
s
in
g
to
o
ls
ca
n
g
en
er
ate
lev
el
-
ap
p
r
o
p
r
iate
co
n
ten
t
f
o
r
lear
n
er
s
with
d
if
f
er
en
t
p
r
o
f
icien
c
y
lev
els
[
3
6
]
.
I
n
wr
itin
g
,
Do
u
B
ao
s
u
p
p
o
r
ted
id
ea
d
ev
elo
p
m
e
n
t
an
d
a
r
g
u
m
e
n
t
p
lan
n
in
g
b
y
o
f
f
er
in
g
m
u
ltip
l
e,
ex
p
lain
ed
lin
es
o
f
r
ea
s
o
n
i
n
g
in
r
esp
o
n
s
e
to
s
tu
d
en
ts
’
p
r
o
m
p
ts
,
wh
ich
alig
n
s
with
ev
id
en
ce
th
at
AI
-
ass
is
ted
to
o
ls
ca
n
h
el
p
wr
iter
s
allo
ca
te
m
o
r
e
ef
f
o
r
t
to
co
m
p
o
s
in
g
id
ea
s
an
d
o
r
g
an
izi
n
g
co
n
ten
t
[
2
3
]
.
I
n
ad
d
itio
n
,
D
o
u
B
ao
’
s
r
ap
id
g
en
er
atio
n
o
f
v
ar
ied
p
r
ac
tice
task
s
ca
n
r
ed
u
ce
tim
e
a
n
d
r
eso
u
r
ce
co
n
s
tr
ain
ts
ass
o
ciate
d
with
tea
ch
er
-
p
r
e
p
ar
ed
m
ater
ials
[
37
]
.
Fo
r
r
ea
d
in
g
,
AI
ca
n
p
r
o
v
id
e
s
en
ten
ce
-
lev
el
co
m
p
ar
is
o
n
an
d
ex
p
lan
atio
n
[
38
]
,
wh
ich
m
a
y
f
ac
ilit
ate
s
em
an
tic
in
teg
r
atio
n
an
d
g
r
am
m
atica
l a
n
aly
s
is
d
u
r
in
g
c
o
m
p
r
eh
e
n
s
io
n
[
8
].
AI
-
in
teg
r
ated
in
s
tr
u
ctio
n
ap
p
ea
r
ed
to
n
ar
r
o
w
ac
h
iev
em
en
t
g
ap
s
b
ec
au
s
e
it
p
r
o
v
id
ed
m
o
r
e
u
n
i
f
o
r
m
ac
ce
s
s
to
s
ca
f
f
o
ld
in
g
a
n
d
p
r
ac
tice.
I
n
a
r
eso
u
r
ce
-
s
atu
r
ate
d
o
n
lin
e
e
n
v
ir
o
n
m
en
t,
lear
n
e
r
s
ca
n
e
x
p
er
ien
ce
co
g
n
itiv
e
o
v
er
lo
a
d
an
d
s
ele
ctiv
ely
s
k
ip
k
e
y
m
ater
ials
,
wh
ich
cr
ea
tes
u
n
e
v
en
lea
r
n
i
n
g
an
d
o
m
is
s
io
n
s
[
18
]
,
[
39
]
.
B
y
c
o
n
tr
ast,
Do
u
B
ao
o
f
f
e
r
ed
o
n
-
d
em
an
d
an
d
lev
el
-
ap
p
r
o
p
r
iate
ex
p
lan
atio
n
s
an
d
p
r
ac
tice,
allo
win
g
lo
wer
-
p
r
o
f
icien
cy
s
tu
d
e
n
ts
to
o
b
tain
im
m
ed
iate
s
u
p
p
o
r
t
w
h
ile
h
ig
h
er
-
p
r
o
f
icien
cy
s
tu
d
e
n
ts
co
u
ld
m
o
v
e
t
o
m
o
r
e
ch
allen
g
i
n
g
task
s
.
T
h
is
ju
s
t
-
in
-
tim
e
s
u
p
p
o
r
t
r
ed
u
ce
d
r
elian
ce
o
n
teac
h
er
-
lim
ited
f
ee
d
b
ac
k
,
t
h
er
eb
y
im
p
r
o
v
in
g
c
o
n
s
is
ten
cy
o
f
e
n
g
ag
em
en
t
a
n
d
co
m
p
r
ess
in
g
s
co
r
e
d
is
p
er
s
io
n
.
T
h
is
is
co
n
s
is
ten
t
with
s
ca
f
f
o
ld
ed
lear
n
in
g
,
wh
er
e
b
y
tailo
r
ed
s
u
p
p
o
r
t
en
a
b
les
lear
n
e
r
s
to
c
r
itically
p
r
o
ce
s
s
in
p
u
t
an
d
b
u
ild
u
n
d
er
s
tan
d
i
n
g
,
th
er
eb
y
r
ed
u
cin
g
p
er
f
o
r
m
a
n
ce
d
is
p
er
s
io
n
[
4
0
].
T
h
e
lar
g
er
g
ain
in
r
ea
d
in
g
u
n
d
er
AI
-
in
teg
r
ated
in
s
tr
u
ctio
n
m
ay
b
e
ex
p
lain
ed
b
y
AI
’
s
ca
p
ac
ity
to
s
tr
en
g
th
en
au
t
o
n
o
m
y
,
m
o
tiv
atio
n
,
an
d
s
elf
-
ef
f
icac
y
,
wh
ich
ar
e
clo
s
ely
lin
k
e
d
to
s
u
s
tain
ed
r
ea
d
in
g
en
g
ag
em
e
n
t.
AI
-
s
u
p
p
o
r
ted
e
n
v
ir
o
n
m
e
n
ts
ca
n
s
tim
u
late
lear
n
er
s
’
m
o
tiv
atio
n
t
o
r
ea
d
a
n
d
e
n
h
an
ce
in
ter
est
an
d
s
elf
-
ef
f
icac
y
[
4
1
]
.
R
elate
d
w
o
r
k
o
n
au
to
m
ated
s
to
r
y
b
o
ts
s
im
ilar
ly
s
u
g
g
ests
th
at
in
ter
ac
t
iv
e
AI
ca
n
b
r
o
ad
e
n
ac
ce
s
s
to
r
ea
d
in
g
g
en
r
es
an
d
s
u
p
p
o
r
t
h
ig
h
er
s
elf
-
e
f
f
icac
y
,
wi
th
p
ar
ticu
lar
ly
s
tr
o
n
g
b
en
ef
its
f
o
r
m
o
r
e
ad
v
an
ce
d
lear
n
er
s
[
4
]
.
I
n
a
d
d
itio
n
,
r
ea
d
i
n
g
im
p
r
o
v
em
en
t
in
h
ig
h
er
ed
u
ca
tio
n
is
o
f
ten
tied
to
th
e
d
ev
elo
p
m
en
t
o
f
cr
itical
th
in
k
in
g
an
d
p
r
o
b
lem
-
s
o
lv
in
g
,
wh
ich
en
ab
les
s
tu
d
en
ts
to
g
r
asp
m
ain
p
o
in
ts
m
o
r
e
ef
f
icien
tly
[
4
2
]
.
W
ith
in
a
C
A
-
o
r
ien
ted
d
esig
n
,
well
-
d
ef
in
ed
o
u
tco
m
es f
u
r
th
er
h
elp
le
ar
n
er
s
f
o
r
m
u
late
f
o
cu
s
ed
q
u
es
tio
n
s
an
d
en
g
ag
e
in
g
o
al
-
d
ir
ec
ted
r
ea
d
in
g
p
r
ac
tice,
wh
ile
also
r
ed
u
cin
g
lear
n
in
g
o
m
is
s
io
n
s
b
y
k
ee
p
in
g
m
ater
ials
an
d
task
s
an
ch
o
r
e
d
to
th
e
i
n
ten
d
ed
o
b
jec
tiv
es.
AI
e
f
f
ec
ts
w
er
e
d
r
i
v
e
n
b
y
h
o
w
AI
u
s
e
was
c
o
n
s
t
r
ai
n
ed
a
n
d
o
r
g
a
n
i
ze
d
th
r
o
u
g
h
C
A.
C
A
o
p
e
r
ati
o
n
ali
ze
s
a
c
o
n
t
r
o
lla
b
l
e
i
n
s
t
r
u
ct
io
n
al
c
h
ai
n
f
r
o
m
i
n
te
n
d
e
d
o
u
tc
o
m
e
s
to
le
ar
n
i
n
g
ac
t
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a
n
d
ass
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m
e
n
t,
t
h
e
r
e
b
y
r
e
d
u
ci
n
g
th
e
c
o
m
m
o
n
r
is
k
th
a
t
tec
h
n
o
l
o
g
y
u
s
e
b
ec
o
m
e
s
a
d
d
iti
v
e
r
a
th
er
t
h
a
n
o
u
tc
o
m
e
-
d
i
r
ec
t
ed
[
2
6
]
.
T
h
e
i
n
t
en
d
ed
o
u
t
co
m
es
we
r
e
s
p
e
ci
f
ie
d
at
an
“a
n
al
y
ze
”
l
e
v
e
l,
an
d
A
I
-
i
n
t
eg
r
a
te
d
t
ask
s
we
r
e
t
h
e
n
s
ele
cte
d
to
s
er
v
e
t
h
o
s
e
ta
r
g
ets
,
w
h
i
c
h
l
ik
e
ly
s
tr
e
n
g
th
en
e
d
t
h
e
r
el
e
v
a
n
c
e
o
f
p
r
ac
t
ic
es.
T
h
is
is
co
n
s
is
te
n
t
wit
h
p
r
i
o
r
e
v
i
d
en
ce
th
a
t
C
A
ca
n
p
r
o
m
o
t
e
d
e
ep
er
l
ea
r
n
in
g
a
n
d
s
t
r
o
n
g
e
r
lea
r
n
i
n
g
en
g
a
g
em
en
t
w
h
e
n
ac
ti
v
iti
es
ar
e
e
x
p
li
citl
y
ti
ed
t
o
in
t
en
d
ed
o
u
tc
o
m
es
an
d
ass
ess
m
e
n
ts
[
28
]
.
I
n
ad
d
i
ti
o
n
,
C
A
c
an
s
t
r
e
n
g
th
e
n
g
o
al
o
r
i
e
n
ta
ti
o
n
b
y
cl
ar
i
f
y
i
n
g
w
h
y
s
p
e
ci
f
ic
ac
t
iv
iti
es m
att
er
,
w
h
i
c
h
s
u
p
p
o
r
ts
s
e
lf
-
d
i
r
ec
te
d
l
ea
r
n
i
n
g
[
4
3
]
a
n
d
m
a
y
m
iti
g
a
te
u
n
p
r
o
d
u
cti
v
e
r
eli
a
n
ce
o
n
AI
b
y
m
a
k
i
n
g
s
u
c
ce
s
s
cr
i
te
r
i
a
ex
p
li
cit
an
d
ass
ess
a
b
l
e
[
4
4
]
.
I
n
t
h
is
s
e
n
s
e
,
C
A
m
ax
im
izes
t
h
e
i
n
s
t
r
u
cti
o
n
a
l
v
al
u
e
o
f
A
I
a
n
d
c
o
n
s
t
r
a
in
s
AI
u
s
e
wit
h
i
n
p
ed
a
g
o
g
i
ca
l
ly
m
ea
n
in
g
f
u
l
b
o
u
n
d
a
r
ies
,
a
li
g
n
i
n
g
wit
h
t
h
e
v
i
ew
th
at
p
r
io
r
i
tiz
in
g
al
ig
n
m
e
n
t
is
ess
e
n
t
ial
f
o
r
p
u
r
p
o
s
e
f
u
l
a
n
d
e
f
f
e
cti
v
e
AI
i
n
t
e
g
r
ati
o
n
[
2
2
]
,
[
3
2
].
Ov
er
all,
th
e
s
tu
d
y
i
n
d
icate
s
th
at
AI
-
in
teg
r
ated
in
s
tr
u
ctio
n
,
wh
en
g
u
id
e
d
b
y
C
A,
ca
n
p
r
o
d
u
c
e
m
ea
n
in
g
f
u
l
g
ain
s
in
E
FL
liter
ac
y
o
u
tco
m
es
wh
ile
im
p
r
o
v
i
n
g
c
o
n
s
is
ten
cy
o
f
lear
n
i
n
g
ac
r
o
s
s
s
tu
d
en
ts
.
B
o
th
g
r
o
u
p
s
im
p
r
o
v
ed
,
s
u
g
g
esti
n
g
th
at
well
-
s
tr
u
ctu
r
ed
in
s
tr
u
ct
io
n
alo
n
e
ca
n
s
u
p
p
o
r
t
p
r
o
g
r
ess
;
h
o
wev
er
,
th
e
AI
-
in
teg
r
ated
in
s
tr
u
ctio
n
s
h
o
wed
lar
g
er
o
v
er
all
g
ain
s
,
a
c
lear
er
r
ed
u
ctio
n
in
p
e
r
f
o
r
m
a
n
ce
d
is
p
er
s
io
n
,
an
d
a
m
o
r
e
p
r
o
n
o
u
n
ce
d
a
d
v
an
ta
g
e
f
o
r
r
ea
d
in
g
.
T
h
ese
im
p
ly
th
a
t
AI
is
m
o
s
t
in
s
tr
u
ctio
n
ally
im
p
ac
tf
u
l
wh
en
it
is
u
s
ed
to
d
eliv
er
ju
s
t
-
in
-
tim
e
s
ca
f
f
o
ld
in
g
an
d
tar
g
eted
p
r
ac
tice
th
at
d
ir
ec
tly
s
er
v
es
clea
r
ly
s
p
ec
if
ied
o
u
tco
m
es,
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
r
tifi
cia
l in
tellig
en
ce
in
a
ctio
n
:
en
h
a
n
cin
g
r
ea
d
in
g
a
n
d
w
r
it
in
g
p
r
o
ficien
cy
in
C
h
in
ese
… (
Jin
g
d
a
n
Liu
)
1821
r
ath
er
th
an
as
a
g
en
er
al
-
p
u
r
p
o
s
e
ad
d
-
o
n
.
At
th
e
s
am
e
tim
e,
th
e
m
o
r
e
m
o
d
est
ad
v
an
tag
e
in
wr
itin
g
in
d
icate
s
th
at
s
h
o
r
t
-
ter
m
AI
i
n
teg
r
atio
n
m
ay
n
o
t
a
u
to
m
atica
lly
tr
an
s
lat
e
in
to
s
u
p
er
io
r
wr
itin
g
p
e
r
f
o
r
m
an
ce
,
h
ig
h
lig
h
tin
g
th
e
n
ee
d
f
o
r
tig
h
te
r
alig
n
m
en
t
b
etwe
en
wr
itin
g
task
s
,
f
ee
d
b
ac
k
u
s
e,
an
d
ass
ess
m
en
t
cr
iter
ia.
T
ak
en
to
g
eth
er
,
C
A
p
r
o
v
id
es
a
p
r
in
cip
led
way
to
m
ak
e
AI
u
s
e
ac
co
u
n
tab
le
to
lear
n
in
g
g
o
als
an
d
ass
ess
m
e
n
t,
s
u
p
p
o
r
tin
g
b
o
th
ef
f
ec
tiv
en
ess
an
d
r
esp
o
n
s
ib
le
im
p
lem
en
tatio
n
in
class
r
o
o
m
s
ettin
g
s
,
wh
ich
is
in
cr
ea
s
in
g
ly
im
p
o
r
tan
t
f
o
r
estab
lis
h
in
g
wo
r
k
ab
le
g
u
id
elin
es f
o
r
AI
ad
o
p
tio
n
ac
r
o
s
s
ed
u
c
ato
r
s
,
in
s
titu
tio
n
s
,
an
d
to
o
l d
e
v
elo
p
er
s
[
4
5
].
4
.
1
.
F
uture
i
m
pli
ca
t
io
ns
a
nd
l
im
it
a
t
io
ns
T
h
e
r
e
d
u
ce
d
p
er
f
o
r
m
a
n
ce
d
is
p
er
s
io
n
u
n
d
er
AI
-
i
n
teg
r
ated
i
n
s
tr
u
ctio
n
in
d
icate
s
th
at
AI
m
ay
f
u
n
ctio
n
as
an
eq
u
alizin
g
s
ca
f
f
o
ld
wh
e
n
it
is
d
ep
lo
y
ed
with
in
a
C
A
-
o
r
ien
ted
d
esig
n
.
Fu
tu
r
e
s
tu
d
ie
s
s
h
o
u
ld
th
er
ef
o
r
e
ex
am
in
e
wh
y
d
is
p
er
s
io
n
d
ec
r
e
ases
b
y
test
in
g
p
lau
s
ib
le
m
ec
h
an
is
m
s
s
u
ch
as d
if
f
er
en
tial u
p
tak
e
o
f
s
ca
f
f
o
ld
in
g
,
ch
an
g
es
in
tim
e
-
on
-
task
,
an
d
s
h
if
ts
in
s
elf
-
r
eg
u
latio
n
an
d
s
elf
-
ef
f
icac
y
ac
r
o
s
s
p
r
o
f
icien
c
y
lev
els.
I
d
en
tify
in
g
th
ese
m
ec
h
an
is
m
s
wo
u
ld
p
r
o
v
id
e
ev
id
e
n
ce
-
b
ased
cr
iter
ia
f
o
r
s
elec
tin
g
an
d
c
o
n
f
ig
u
r
in
g
AI
to
o
ls
with
in
C
A
f
o
r
co
h
o
r
ts
with
h
eter
o
g
en
e
o
u
s
lan
g
u
ag
e
p
r
o
f
icien
cy
.
Seco
n
d
,
th
e
C
A
-
f
ir
s
t
ap
p
r
o
ac
h
u
s
ed
in
th
is
s
tu
d
y
o
f
f
er
s
a
tr
an
s
f
er
ab
le
d
esig
n
lo
g
ic
f
o
r
ex
ten
d
i
n
g
AI
in
teg
r
atio
n
b
ey
o
n
d
r
ea
d
in
g
an
d
wr
itin
g
.
I
n
p
a
r
ticu
lar
,
C
A
ca
n
b
e
ap
p
lied
to
lis
ten
in
g
an
d
s
p
ea
k
in
g
b
y
s
p
ec
if
y
in
g
o
u
tco
m
e
lev
els,
d
esig
n
in
g
alig
n
ed
AI
-
m
ed
iated
p
r
ac
tice
task
s
,
an
d
b
u
ild
in
g
ass
ess
m
en
ts
.
Fo
r
ex
am
p
le,
p
r
o
f
icien
c
y
-
ca
lib
r
ated
lis
ten
in
g
p
r
ac
t
ice
with
r
ea
l
-
tim
e
co
m
p
r
eh
e
n
s
io
n
ch
ec
k
s
an
d
f
e
ed
b
ac
k
c
o
u
ld
b
e
d
ev
el
o
p
ed
an
d
ev
alu
ated
u
n
d
e
r
alig
n
e
d
ass
ess
m
en
t
co
n
d
itio
n
s
.
T
h
ir
d
,
th
e
in
s
tr
u
ctio
n
al
m
o
d
el
is
lik
ely
to
m
o
d
er
ate
AI
ef
f
ec
ts
.
AI
f
ee
d
b
ac
k
m
ay
o
p
er
ate
d
if
f
er
en
tly
in
b
len
d
ed
lea
r
n
in
g
th
an
in
tr
ad
it
io
n
al
class
r
o
o
m
s
ettin
g
s
.
Fu
tu
r
e
r
esear
ch
s
h
o
u
ld
th
er
e
f
o
r
e
c
o
m
p
ar
e
C
A
-
g
u
i
d
ed
AI
in
teg
r
atio
n
ac
r
o
s
s
d
eliv
er
y
f
o
r
m
ats,
s
u
ch
as
f
ac
e
-
to
-
f
ac
e
,
b
len
d
ed
,
an
d
f
u
lly
o
n
lin
e
in
s
tr
u
ctio
n
,
to
clar
if
y
wh
ich
alig
n
m
en
t c
o
n
f
ig
u
r
atio
n
s
b
est s
u
p
p
o
r
t le
ar
n
in
g
.
Sev
er
al
lim
itatio
n
s
s
h
o
u
ld
b
e
ac
k
n
o
wled
g
e
d
.
First,
th
e
s
tu
d
y
was
co
n
d
u
cted
with
a
r
elati
v
ely
s
m
all
s
am
p
le
d
r
awn
f
r
o
m
a
s
in
g
le
in
s
titu
tio
n
an
d
co
h
o
r
t.
R
ep
licatio
n
with
lar
g
er
s
am
p
les
ac
r
o
s
s
m
u
ltip
le
s
ite
s
,
p
r
o
g
r
a
m
ty
p
es,
an
d
r
eg
io
n
s
is
n
ee
d
ed
t
o
test
wh
eth
er
t
h
e
o
b
s
er
v
ed
e
f
f
ec
ts
g
en
e
r
alize
to
d
i
v
er
s
e
E
FL
co
n
tex
ts
an
d
lear
n
er
p
r
o
f
iles
.
Seco
n
d
,
i
m
p
lem
en
tatio
n
was
em
b
ed
d
ed
in
o
n
e
co
u
r
s
e
s
ettin
g
,
an
d
in
s
tr
u
ctio
n
al
d
eliv
er
y
was
lar
g
ely
s
h
ap
ed
b
y
a
s
in
g
le
teac
h
er
a
n
d
th
e
lo
ca
l
tea
ch
in
g
team
.
T
h
is
lim
its
in
f
er
en
ce
ab
o
u
t
teac
h
er
ef
f
ec
ts
.
Fu
tu
r
e
wo
r
k
s
h
o
u
l
d
in
v
o
lv
e
m
u
ltip
le
in
s
tr
u
cto
r
s
an
d
ex
am
in
e
f
id
elity
o
f
im
p
lem
en
tatio
n
,
f
o
r
e
x
am
p
l
e
th
r
o
u
g
h
s
tan
d
ar
d
ized
less
o
n
p
l
an
s
,
class
r
o
o
m
o
b
s
er
v
atio
n
s
,
o
r
cr
o
s
s
-
teac
h
er
ca
lib
r
atio
n
,
to
d
eter
m
in
e
wh
eth
er
o
u
tco
m
es
d
e
p
en
d
o
n
in
d
iv
id
u
al
teac
h
in
g
s
ty
le
o
r
o
n
th
e
C
A
-
g
u
id
ed
AI
d
esig
n
its
elf
.
T
h
ir
d
,
th
e
in
ter
v
e
n
tio
n
r
elied
o
n
a
s
in
g
le
AI
to
o
l
(
D
o
u
B
ao
)
an
d
a
s
p
ec
if
ic
p
atter
n
o
f
u
s
e.
T
o
o
l
af
f
o
r
d
an
ce
s
,
r
esp
o
n
s
e
q
u
ality
,
an
d
g
u
ar
d
r
ails
d
if
f
er
ac
r
o
s
s
p
latf
o
r
m
s
,
an
d
th
ese
d
if
f
e
r
en
ce
s
m
ay
in
f
lu
en
ce
lear
n
in
g
.
Fu
t
u
r
e
r
esear
ch
s
h
o
u
ld
co
m
p
ar
e
m
u
ltip
le
AI
to
o
ls
o
r
co
n
f
ig
u
r
atio
n
s
u
n
d
e
r
th
e
s
am
e
C
A
d
esig
n
an
d
r
ep
o
r
t
to
o
l
s
ettin
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s
,
u
s
ag
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r
u
les,
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d
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ter
ac
tio
n
p
atter
n
s
to
i
m
p
r
o
v
e
r
ep
r
o
d
u
ci
b
ilit
y
.
Fin
a
lly
,
th
e
s
tu
d
y
r
elied
p
r
im
a
r
i
ly
o
n
p
ap
er
-
b
ased
p
r
e/p
o
s
t
test
s
,
wh
ich
m
ay
n
o
t
ca
p
tu
r
e
p
r
o
ce
s
s
-
lev
el
ch
a
n
g
es,
s
u
ch
as
h
o
w
s
tu
d
en
ts
u
s
ed
AI
,
tim
e
-
on
-
task
,
o
r
r
ev
is
io
n
b
e
h
av
io
r
s
.
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n
co
r
p
o
r
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tin
g
lear
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in
g
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al
y
tics
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ter
ac
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,
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n
d
l
o
n
g
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in
al
f
o
llo
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u
p
s
wo
u
ld
en
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le
s
tr
o
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e
r
claim
s
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o
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t
m
ec
h
an
is
m
s
an
d
th
e
d
u
r
a
b
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o
f
ef
f
ec
ts
.
5.
CO
NCLU
SI
O
N
T
h
is
s
tu
d
y
e
x
am
in
ed
th
e
e
f
f
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ts
o
f
AI
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in
te
g
r
ated
in
s
tr
u
ct
io
n
,
r
elativ
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to
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n
o
n
-
AI
ap
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r
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n
non
-
E
n
g
lis
h
-
m
ajo
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u
n
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er
g
r
ad
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ates
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ea
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g
an
d
wr
itin
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p
e
r
f
o
r
m
a
n
ce
with
in
a
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f
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am
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k
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o
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r
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u
p
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im
p
r
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v
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d
f
r
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p
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t
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test
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at
s
tr
u
ctu
r
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d
in
s
tr
u
ctio
n
s
u
p
p
o
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ted
p
r
o
g
r
ess
;
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o
wev
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,
t
h
e
AI
-
in
teg
r
ated
g
r
o
u
p
s
h
o
wed
lar
g
er
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ain
s
o
v
e
r
all,
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clea
r
er
r
ed
u
ctio
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in
s
co
r
e
d
is
p
e
r
s
io
n
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d
a
m
o
r
e
p
r
o
n
o
u
n
ce
d
ad
v
an
tag
e
f
o
r
r
ea
d
in
g
.
T
h
ese
r
esu
lts
s
u
g
g
est
th
at
AI
is
m
o
s
t
b
e
n
ef
icial
wh
en
its
u
s
e
is
g
u
id
ed
b
y
C
A,
s
tar
tin
g
f
r
o
m
clea
r
ly
s
p
ec
if
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lear
n
in
g
o
b
jectiv
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an
d
th
en
alig
n
in
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n
g
ac
tiv
it
ies
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d
ass
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m
en
t,
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o
th
at
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ated
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p
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s
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ir
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tly
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th
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k
ills
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u
ch
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en
tify
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g
m
ain
id
ea
s
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d
s
u
p
p
o
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tin
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d
etails an
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d
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elo
p
in
g
m
o
r
e
o
r
g
an
ized
wr
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r
esp
o
n
s
es.
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th
e
s
am
e
tim
e,
AI
to
o
ls
ar
e
n
o
t
a
s
tan
d
-
alo
n
e
s
o
lu
tio
n
.
T
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ca
tio
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v
alu
e
d
ep
en
d
s
o
n
p
u
r
p
o
s
ef
u
l
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teg
r
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,
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r
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ask
co
n
s
tr
ain
ts
,
an
d
ap
p
r
o
p
r
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te
teac
h
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o
r
ch
estra
tio
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to
p
r
e
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en
t
m
is
alig
n
m
en
t,
o
v
er
r
elian
ce
,
o
r
o
f
f
-
task
u
s
e.
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tu
r
e
r
esear
ch
s
h
o
u
ld
test
th
e
g
en
er
aliza
b
ilit
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o
f
th
ese
f
in
d
i
n
g
s
ac
r
o
s
s
s
ites
an
d
in
s
tr
u
cto
r
s
,
co
m
p
ar
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d
if
f
er
en
t
AI
to
o
ls
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d
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s
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d
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s
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n
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e
s
am
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C
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p
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p
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lo
g
y
wh
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to
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k
p
ar
t in
th
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s
tu
d
y
.
Evaluation Warning : The document was created with Spire.PDF for Python.
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DATA AV
AI
L
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[
HAH
]
,
u
p
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n
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ea
s
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ab
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r
eq
u
est.
RE
F
E
R
E
NC
E
S
[
1
]
L.
K
o
h
n
k
e
,
B
.
L
.
M
o
o
r
h
o
u
se
,
a
n
d
D
.
Zo
u
,
“
E
x
p
l
o
r
i
n
g
g
e
n
e
r
a
t
i
v
e
a
r
t
i
f
i
c
i
a
l
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n
t
e
l
l
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g
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n
c
e
p
r
e
p
a
r
e
d
n
e
ss
a
m
o
n
g
u
n
i
v
e
r
si
t
y
l
a
n
g
u
a
g
e
i
n
s
t
r
u
c
t
o
r
s:
a
c
a
s
e
s
t
u
d
y
,
”
C
o
m
p
u
t
e
rs
a
n
d
E
d
u
c
a
t
i
o
n
:
Art
i
f
i
c
i
a
l
I
n
t
e
l
l
i
g
e
n
c
e
,
v
o
l
.
5
,
p
.
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0
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6
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,
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o
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:
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/
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.
c
a
e
a
i
.
2
0
2
3
.
1
0
0
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5
6
.
[
2
]
A
.
Jo
k
h
a
n
,
A
.
A
.
C
h
a
n
d
,
V
.
S
i
n
g
h
,
a
n
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K
.
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.
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mu
n
,
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[
3
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H
.
Y
a
n
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a
n
d
S
.
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y
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n
,
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T
h
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:
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