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I
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N
Ar
tific
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tellig
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AI
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h
as
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ican
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m
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s
asp
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f
m
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s
o
ciety
[
1
]
,
[
2
]
.
Ov
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th
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ad
es,
AI
h
as p
r
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d
tech
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lo
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[
1
]
–
[
3
]
.
T
h
is
ev
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lu
tio
n
h
as
le
d
to
th
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Mid
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u
m
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[
4
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.
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en
t
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as
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s
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in
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in
d
u
s
tr
ies,
in
clu
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in
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ed
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ca
tio
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[
2
]
,
[
3
]
.
As
em
er
g
in
g
tec
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n
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l
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ies
s
u
ch
as
Gen
AI
co
n
tin
u
e
to
s
h
a
p
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v
ar
i
o
u
s
in
d
u
s
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ies
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d
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s
,
it
is
cr
u
cial
f
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r
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n
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s
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to
cu
ltiv
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lear
n
er
s
’
r
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i
n
ess
to
en
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ag
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with
Gen
AI
ef
f
ec
tiv
el
y
an
d
r
esp
o
n
s
ib
ly
[
5
]
–
[
7
]
.
T
h
i
s
r
ea
d
in
ess
in
v
o
lv
es
h
av
i
n
g
te
ch
n
ical
p
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o
f
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an
d
ab
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,
co
g
n
itiv
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u
n
d
er
s
tan
d
in
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,
eth
ical
awa
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an
d
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war
d
-
th
in
k
in
g
v
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r
eg
ar
d
in
g
Gen
AI
ap
p
licatio
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s
.
W
h
en
Gen
AI
r
ea
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in
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p
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lear
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ten
tio
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Ho
wev
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r
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,
p
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ticu
lar
ly
am
o
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ad
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f
ac
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to
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ter
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m
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ay
p
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Evaluation Warning : The document was created with Spire.PDF for Python.
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I
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J
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R
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Vo
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14
,
No
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2
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Ap
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20
25
:
1
0
6
5
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7
4
1066
d
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Gen
AI
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am
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ODL
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lear
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s
[
8
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.
Fo
r
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b
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ab
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p
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Gen
AI
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T
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tial
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ap
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AI
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W
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ter
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p
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t
f
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m
th
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u
n
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s
ities
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u
lt
lear
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ay
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allen
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lly
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m
b
r
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Gen
AI
a
n
d
lev
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ag
in
g
its
p
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ten
tial
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an
ce
th
eir
lear
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in
g
ex
p
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ce
s
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d
f
u
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u
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r
k
.
T
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x
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eh
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am
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s
t
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v
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s
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v
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r
a
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s
ig
n
i
f
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a
n
t
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a
p
s
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F
ir
s
t,
t
h
er
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is
a
la
ck
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f
c
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p
r
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h
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f
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g
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w
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f
lu
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s
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f
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Ge
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tec
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[
5
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.
R
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[
7
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,
[
9
]
,
[
1
0
]
.
Se
co
n
d
,
d
es
p
i
te
t
h
e
g
r
o
w
in
g
p
r
o
m
i
n
e
n
c
e
o
f
Ge
n
A
I
in
th
e
e
d
u
ca
ti
o
n
al
co
n
t
ex
t,
t
h
e
r
e
a
r
e
r
el
ati
v
el
y
f
e
w
s
t
u
d
ies
t
h
at
h
a
v
e
e
x
p
l
o
r
ed
p
er
ce
p
ti
o
n
s
an
d
i
n
te
n
t
io
n
s
o
f
s
t
u
d
e
n
ts
to
u
s
e
Ge
n
A
I
tec
h
n
o
lo
g
i
es
s
u
c
h
as
C
h
atGP
T
t
o
e
n
h
a
n
ce
le
ar
n
i
n
g
en
v
i
r
o
n
m
en
ts
t
h
a
t c
r
ea
t
e
ef
f
e
cti
v
e
l
ea
r
n
i
n
g
e
x
p
e
r
i
en
ce
s
[
2
]
.
Fin
all
y
,
t
h
e
s
l
o
w
u
p
ta
k
e
o
f
A
I
tec
h
n
o
l
o
g
ies
i
n
c
u
r
r
e
n
t
ed
u
c
ati
o
n
al
s
et
ti
n
g
s
m
a
y
b
e
d
u
e
t
o
n
eg
lec
ti
n
g
s
o
c
io
-
tec
h
n
o
f
a
ct
o
r
s
.
F
o
r
i
n
s
t
a
n
ce
,
e
x
t
an
t
s
t
u
d
ies
e
m
p
h
asiz
e
t
h
e
s
i
g
n
i
f
ic
a
n
ce
o
f
u
n
d
e
r
s
ta
n
d
i
n
g
s
tu
d
en
ts
’
a
n
d
ed
u
c
at
o
r
s
’
p
r
ef
e
r
e
n
c
es,
s
o
ci
al
d
y
n
a
m
i
cs,
an
d
e
th
ica
l
c
o
n
s
i
d
e
r
a
ti
o
n
s
;
h
o
w
ev
er
,
t
h
es
e
f
ac
to
r
s
a
r
e
o
f
te
n
n
o
t
p
r
io
r
i
tiz
ed
i
n
t
h
e
d
ev
el
o
p
m
e
n
t
an
d
d
e
p
l
o
y
m
e
n
t
o
f
A
I
te
c
h
n
o
lo
g
ies
i
n
t
h
e
ed
u
ca
t
io
n
al
s
y
s
te
m
s
[
3
]
,
[
1
1
]
.
T
h
ese
g
a
p
s
s
u
g
g
est
f
u
r
th
e
r
r
ese
ar
c
h
i
s
n
e
e
d
e
d
t
o
in
f
o
r
m
d
is
cu
s
s
io
n
s
o
n
l
ea
r
n
e
r
s
’
r
ea
d
i
n
ess
a
n
d
b
eh
av
io
r
a
l
i
n
t
en
ti
o
n
s
to
w
ar
d
s
A
I
o
r
G
en
AI
to
o
ls
.
A
g
ai
n
s
t
t
h
is
b
a
ck
d
r
o
p
,
w
e
i
n
t
en
d
t
o
ex
am
in
e
a
d
u
lt
le
ar
n
e
r
s
’
r
ea
d
i
n
ess
f
o
r
Ge
n
A
I
an
d
th
ei
r
b
e
h
av
io
r
a
l
i
n
t
e
n
ti
o
n
wit
h
i
n
t
h
e
s
p
e
cif
ic
c
o
n
te
x
t
o
f
ODL
e
d
u
ca
t
i
o
n
.
I
n
s
i
g
h
ts
g
a
in
e
d
f
r
o
m
th
e
f
i
n
d
i
n
g
s
o
f
t
h
e
s
t
u
d
y
s
h
o
u
l
d
b
e
a
b
l
e
t
o
in
f
o
r
m
t
h
e
d
esi
g
n
o
f
a
p
p
r
o
p
r
iate
i
n
t
er
v
e
n
t
io
n
s
a
n
d
p
o
lic
ies
to
e
n
h
a
n
c
e
G
e
n
A
I
p
r
e
p
a
r
e
d
n
ess
a
m
o
n
g
a
d
u
lt
le
ar
n
e
r
s
in
t
h
e
u
n
i
v
e
r
s
it
y
.
T
h
e
s
tu
d
y
is
b
as
ed
o
n
t
wo
r
ese
a
r
c
h
q
u
e
s
tio
n
s
:
i)
W
h
at
is
t
h
e
r
ela
ti
o
n
s
h
i
p
b
etw
e
en
Ge
n
A
I
r
ea
d
i
n
ess
a
n
d
b
eh
av
io
r
al
i
n
t
en
ti
o
n
o
f
a
d
u
lt
l
ea
r
n
e
r
s
?
ii)
W
h
at
is
t
h
e
m
o
s
t
s
i
g
n
if
ic
an
t G
en
A
I
r
ea
d
i
n
ess
f
ac
to
r
p
r
ed
icti
n
g
b
eh
av
io
r
al
in
te
n
ti
o
n
o
f
a
d
u
lt
lea
r
n
e
r
s
?
2.
RE
L
E
VA
NT
S
T
UD
I
E
S AN
D
H
YP
O
T
H
E
S
E
S D
E
VE
L
O
P
M
E
N
T
T
ec
h
n
o
lo
g
y
r
ea
d
in
ess
an
d
ac
ce
p
tan
ce
m
o
d
el
(
T
R
AM
)
was
d
er
iv
ed
f
r
o
m
t
h
e
in
t
eg
r
atio
n
o
f
tech
n
o
lo
g
y
r
ea
d
in
ess
in
d
ex
(
T
R
I
)
an
d
tech
n
o
l
o
g
y
ac
ce
p
ta
n
ce
m
o
d
el
(
T
AM
)
to
p
r
o
v
id
e
a
r
o
b
u
s
t
f
r
a
m
ewo
r
k
f
o
r
u
n
d
er
s
tan
d
in
g
u
s
er
ac
ce
p
t
an
ce
o
f
n
ew
tech
n
o
lo
g
ies
[
1
2
]
.
Acc
o
r
d
in
g
t
o
T
AM
,
as
p
o
s
ited
b
y
Dav
is
[
1
3
]
,
p
er
ce
iv
ed
u
s
ef
u
ln
ess
an
d
p
e
r
ce
iv
ed
ea
s
e
o
f
u
s
e
ar
e
f
u
n
d
a
m
en
tal
d
eter
m
in
a
n
ts
o
f
b
e
h
av
io
r
al
in
ten
tio
n
.
T
h
is
m
o
d
el
h
as
b
ee
n
em
p
ir
ically
v
alid
ated
ac
r
o
s
s
s
tu
d
ies.
Fo
r
ex
am
p
le,
E
s
tr
ieg
an
a
et
a
l.
[
1
4
]
r
ep
o
r
ted
t
h
at
s
tu
d
en
ts
ar
e
m
o
r
e
in
clin
e
d
to
ad
o
p
t
th
e
tec
h
n
o
lo
g
y
i
f
th
ey
f
in
d
it
u
s
ef
u
l
in
e
n
h
a
n
cin
g
th
ei
r
wr
itin
g
p
er
f
o
r
m
an
ce
.
Similar
ly
,
Yan
g
an
d
W
an
g
[
1
5
]
o
b
s
er
v
ed
th
at
t
h
e
p
er
ce
i
v
ed
ea
s
e
o
f
u
s
e
is
a
c
r
itical
an
d
p
o
s
itiv
e
in
f
lu
en
ce
o
n
s
tu
d
en
ts
’
in
te
n
tio
n
to
u
s
e
m
ac
h
i
n
e
tr
an
s
latio
n
.
T
ec
h
n
o
lo
g
y
r
ea
d
i
n
ess
r
ef
er
s
to
“p
eo
p
le’
s
p
r
o
p
en
s
ity
to
em
b
r
ac
e
an
d
u
s
e
n
ew
tech
n
o
lo
g
ies
to
ac
co
m
p
lis
h
g
o
als
in
h
o
m
e
lif
e
an
d
at
wo
r
k
”
[
1
6
]
.
I
t
m
ea
s
u
r
es
wh
eth
er
an
in
d
i
v
id
u
al
is
r
ea
d
y
to
u
s
e
a
n
ew
tech
n
o
lo
g
y
[
1
7
]
.
L
in
et
a
l.
[
1
2
]
in
teg
r
ated
th
e
T
R
I
in
to
T
AM
,
p
r
o
p
o
s
in
g
th
e
T
R
AM
.
B
ased
o
n
th
eir
an
aly
s
is
,
p
er
ce
iv
ed
ea
s
e
o
f
u
s
e
a
n
d
p
e
r
ce
iv
ed
u
s
ef
u
ln
ess
m
ed
iate
th
e
r
elatio
n
s
h
ip
b
etwe
en
r
ea
d
in
ess
an
d
in
ten
tio
n
.
Su
p
p
o
r
tin
g
th
ese
f
i
n
d
in
g
s
,
B
a
g
ze
[
1
8
]
r
ep
o
r
te
d
th
at
tech
n
o
lo
g
y
r
ea
d
in
ess
’
s
im
p
ac
t
o
n
m
o
b
ile
s
h
o
p
p
in
g
in
ten
tio
n
is
m
ed
iated
b
y
b
o
t
h
p
er
ce
iv
ed
u
s
ef
u
ln
ess
an
d
ea
s
e
o
f
u
s
e.
L
ik
ewise,
C
h
en
an
d
L
in
[
1
9
]
f
o
u
n
d
th
at
tech
n
o
lo
g
y
r
ea
d
i
n
ess
s
ig
n
if
ican
tly
an
d
p
o
s
itiv
ely
af
f
ec
ts
th
e
p
er
ce
iv
ed
ea
s
e
o
f
u
s
e
an
d
u
s
ef
u
ln
ess
o
f
d
ietar
y
an
d
f
itn
ess
ap
p
s
.
W
ith
th
is
r
ea
d
in
ess
,
it is
also
ab
le
to
p
r
ed
ic
t th
e
in
ten
tio
n
to
d
o
wn
l
o
ad
an
d
u
s
e
th
e
ap
p
s
.
As L
in
et
a
l.
[
1
2
]
ar
ticu
lated
,
t
ec
h
n
o
lo
g
y
r
ea
d
i
n
ess
is
a
co
n
s
t
r
u
ct
th
at
is
s
p
ec
if
ic
to
th
e
in
d
iv
id
u
al
an
d
n
o
t
tied
to
an
y
p
ar
ticu
lar
s
y
s
tem
.
T
h
is
m
ea
n
s
it
en
co
m
p
ass
es
f
ac
to
r
s
th
at
ar
e
in
h
er
en
t
to
th
e
in
d
iv
id
u
al,
wh
er
ea
s
p
er
ce
iv
ed
u
s
ef
u
ln
ess
an
d
p
er
ce
i
v
ed
ea
s
e
o
f
u
s
e
ar
e
co
n
s
tr
u
cts
lin
k
ed
to
th
e
c
h
ar
ac
ter
is
tics
o
f
a
g
iv
en
s
y
s
tem
.
T
h
e
cu
r
r
en
t
s
tu
d
y
is
s
et
to
in
v
esti
g
ate
h
o
w
th
e
p
er
s
o
n
al
f
ac
to
r
s
o
f
ad
u
lt
lear
n
er
s
co
n
tr
ib
u
te
to
th
eir
b
eh
av
io
r
al
in
ten
tio
n
s
r
eg
ar
d
in
g
Gen
AI
u
s
e.
C
o
n
s
id
er
in
g
th
e
r
an
g
e
o
f
Gen
AI
to
o
ls
a
v
ailab
le,
wh
ich
v
ar
y
in
ea
s
e
o
f
u
s
e
an
d
u
s
ef
u
ln
ess
,
it
is
p
o
s
s
ib
le
th
at
lear
n
er
s
a
r
e
ev
alu
atin
g
d
if
f
er
e
n
t
Gen
AI
to
o
ls
b
ased
o
n
t
h
ese
v
ar
y
in
g
s
y
s
tem
-
s
p
ec
if
ic
f
ac
t
o
r
s
.
T
h
er
ef
o
r
e,
th
is
s
tu
d
y
ex
cl
u
d
es
p
er
ce
iv
ed
u
s
ef
u
ln
ess
an
d
p
er
ce
iv
e
d
ea
s
e
o
f
u
s
e,
f
o
cu
s
in
g
i
n
s
tead
o
n
th
e
in
d
iv
id
u
al
f
ac
to
r
s
’
r
ea
d
in
ess
,
th
a
t d
r
iv
e
b
e
h
av
io
r
al
i
n
ten
tio
n
.
Stu
d
ies
h
av
e
also
d
o
cu
m
en
te
d
th
e
d
ir
ec
t
im
p
ac
t
o
f
r
ea
d
i
n
ess
o
n
b
eh
av
io
r
al
in
ten
tio
n
.
Stu
d
y
b
y
Om
ar
et
a
l.
[
2
0
]
h
ig
h
lig
h
ted
th
at
f
ar
m
er
s
’
tech
n
o
l
o
g
y
r
ea
d
i
n
ess
p
r
ed
icted
th
eir
b
eh
a
v
io
r
a
l
in
ten
tio
n
to
ad
o
p
t
th
e
e
-
Ag
r
iFi
n
an
ce
ap
p
.
R
ah
im
et
a
l.
[
8
]
d
is
co
v
er
ed
th
at
ac
ad
em
ic
s
taf
f
’
s
tech
n
o
lo
g
y
r
ea
d
i
n
ess
d
ir
ec
tly
af
f
ec
ts
th
eir
b
eh
av
io
r
al
in
ten
tio
n
to
u
s
e
ODL
tech
n
o
lo
g
y
d
u
r
in
g
th
e
C
OVI
D
-
1
9
p
an
d
em
ic.
Simila
r
ly
,
An
h
et
a
l.
[
2
1
]
n
o
ted
th
at
tech
n
o
lo
g
y
r
ea
d
i
n
e
s
s
p
o
s
itiv
ely
in
f
lu
en
ce
s
th
e
in
t
en
tio
n
to
ap
p
l
y
AI
in
th
e
ac
co
u
n
tin
g
a
n
d
au
d
itin
g
f
ield
s
.
I
n
th
e
co
n
te
x
t
o
f
th
is
s
tu
d
y
,
we
ex
p
l
o
r
e
th
e
in
f
lu
e
n
ce
o
f
Gen
AI
r
ea
d
in
ess
am
o
n
g
a
d
u
lt
lear
n
er
s
o
n
th
eir
b
eh
av
io
r
al
i
n
ten
tio
n
t
o
u
s
e
Ge
n
AI
.
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
E
xa
min
in
g
Gen
A
I
r
ea
d
in
ess
a
n
d
b
eh
a
vio
u
r
a
l
in
te
n
tio
n
o
f
a
d
u
lt lea
r
n
ers
…
(
Jo
s
ep
h
in
e
I
e
L
yn
C
h
a
n
)
1067
Sev
er
al
r
esear
ch
[
6
]
,
[
7
]
p
r
o
p
o
s
ed
th
e
co
n
ce
p
t
o
f
AI
r
ea
d
in
ess
th
at
h
as
b
ee
n
r
ed
ef
in
ed
f
o
r
m
ed
ical
s
tu
d
en
ts
an
d
ed
u
ca
to
r
s
,
r
esp
ec
tiv
ely
.
Acc
o
r
d
i
n
g
to
th
em
,
AI
r
ea
d
in
ess
co
n
s
is
ts
o
f
f
o
u
r
co
n
s
tr
u
cts:
co
g
n
itio
n
,
ab
ilit
y
,
v
is
io
n
,
a
n
d
eth
ics.
C
o
g
n
itiv
e
r
ea
d
i
n
ess
r
ef
er
s
to
a
n
in
d
iv
id
u
al’
s
u
n
d
er
s
tan
d
in
g
o
f
th
e
im
p
o
r
ta
n
ce
an
d
f
u
n
ctio
n
o
f
AI
in
ed
u
ca
tio
n
,
a
n
d
th
e
r
elatio
n
s
h
ip
b
etwe
en
h
u
m
an
an
d
AI
.
T
h
e
ab
ilit
y
asp
ec
t
is
r
elate
d
to
an
in
d
iv
id
u
al’
s
s
k
ills
an
d
co
m
p
e
ten
ce
in
s
elec
tin
g
an
d
u
s
in
g
AI
f
o
r
lear
n
in
g
.
Vis
io
n
r
elate
s
to
an
in
d
iv
id
u
al’
s
r
ec
o
g
n
itio
n
o
f
AI
’
s
p
o
ten
tial a
n
d
lim
itatio
n
s
in
th
e
ed
u
ca
tio
n
al
s
ec
to
r
.
L
astl
y
,
th
e
eth
ics co
n
s
tr
u
ct
r
ef
er
s
to
th
e
ad
h
er
en
ce
to
eth
ical
an
d
le
g
al
n
o
r
m
s
an
d
r
e
g
u
latio
n
s
in
AI
’
s
ed
u
ca
tio
n
al
u
s
ag
e.
As s
u
ch
,
we
h
y
p
o
th
esize
th
at:
i)
Gen
AI
r
ea
d
in
ess
h
as
a
p
o
s
itiv
e
s
ig
n
if
ican
t
in
f
lu
e
n
ce
o
n
b
e
h
av
io
r
al
in
ten
tio
n
(
H1
)
;
ii)
a
b
i
lity
h
as
a
p
o
s
itiv
e
s
ig
n
if
ican
t
in
f
lu
en
ce
o
n
b
eh
a
v
io
r
al
in
ten
tio
n
(
H
1
a
)
;
iii)
c
o
g
n
itio
n
h
as
a
p
o
s
itiv
e
s
ig
n
if
ican
t
in
f
lu
en
ce
o
n
b
eh
av
io
r
al
i
n
ten
tio
n
(
H1
b
)
;
iv
)
e
th
ics
h
as
a
p
o
s
itiv
e
s
ig
n
if
ic
an
t
in
f
lu
en
ce
o
n
b
eh
av
io
r
al
in
ten
tio
n
(
H1
c
)
;
a
n
d
v)
v
is
io
n
h
as a
p
o
s
itiv
e
s
ig
n
if
i
ca
n
t in
f
lu
en
ce
o
n
b
eh
av
io
r
al
i
n
ten
tio
n
(
H1
d
)
.
3.
M
E
T
H
O
D
T
h
e
cu
r
r
en
t
s
tu
d
y
is
a
q
u
an
ti
tativ
e
s
elf
-
ad
m
in
is
ter
ed
s
u
r
v
ey
b
ased
o
n
p
u
r
p
o
s
iv
ely
s
am
p
lin
g
.
T
h
e
r
eq
u
ir
ed
s
am
p
lin
g
s
ize
f
o
llo
wed
Hair
et
a
l.
[
2
2
]
r
u
le
o
f
th
u
m
b
o
f
“
1
0
-
tim
es
t
h
e
m
a
x
im
u
m
n
u
m
b
er
o
f
ar
r
o
wh
ea
d
s
”
t
o
war
d
s
th
e
d
ep
en
d
en
t
v
ar
iab
le.
Sin
ce
th
er
e
ar
e
f
o
u
r
a
r
r
o
wh
ea
d
s
o
f
th
e
c
o
n
s
tr
u
cts
o
f
ab
ilit
y
,
co
g
n
itio
n
,
eth
ics,
an
d
v
is
io
n
p
o
in
tin
g
to
war
d
s
b
eh
av
io
r
al
in
ten
tio
n
,
th
e
m
in
im
u
m
s
am
p
l
e
s
ize
s
h
o
u
ld
b
e
4
0
.
T
h
e
p
ar
ticip
an
ts
s
elec
ted
ar
e
all
u
n
d
er
g
r
ad
u
ate
an
d
p
o
s
tg
r
ad
u
ate
s
tu
d
en
ts
at
an
ODL
in
s
titu
tio
n
wh
o
ar
e
ac
tiv
e
d
u
r
i
n
g
th
e
Ma
y
2
0
2
3
,
Sep
tem
b
er
2
0
2
3
,
an
d
J
an
u
ar
y
2
0
2
4
ter
m
s
.
T
h
e
s
u
r
v
ey
c
o
n
tain
s
d
em
o
g
r
a
p
h
ic
item
s
an
d
th
e
m
ea
s
u
r
em
en
t
item
s
u
s
ed
to
o
p
er
atio
n
alize
th
e
co
n
s
tr
u
ct
wer
e
ad
ap
ted
f
r
o
m
ex
tan
t
s
tu
d
ies
o
n
tech
n
o
lo
g
y
r
ea
d
in
ess
an
d
b
eh
av
io
r
al
in
te
n
tio
n
.
Sp
ec
if
ic
ally
,
we
ad
ap
ted
item
s
f
o
r
Gen
AI
r
ea
d
in
ess
co
m
p
r
is
in
g
o
f
ab
ilit
y
(
6
item
s
)
,
co
g
n
itio
n
(
5
item
s
)
,
eth
ics
(
4
item
s
)
,
an
d
v
is
io
n
(
3
item
s
)
f
r
o
m
[
6
]
,
[
7
]
,
wh
ile
item
s
f
o
r
b
e
h
av
io
r
al
in
ten
tio
n
(
3
item
s
)
wer
e
ad
a
p
ted
f
r
o
m
L
ai
an
d
L
ee
[
2
3
]
.
All
ite
m
s
wer
e
r
ated
o
n
a
5
-
p
o
in
t
L
ik
er
t
s
ca
le
f
r
o
m
1
(
s
tr
o
n
g
ly
d
is
ag
r
ee
)
t
o
5
(
s
tr
o
n
g
l
y
ag
r
ee
)
.
Fig
u
r
e
1
illu
s
tr
ates
all
th
e
h
y
p
o
th
esized
r
elatio
n
s
h
ip
s
ex
am
in
ed
in
t
h
e
s
tu
d
y
.
Ap
p
r
o
v
al
was
g
iv
en
b
y
th
e
u
n
iv
er
s
ity
’
s
eth
ics
co
m
m
i
ttee
to
co
n
d
u
ct
th
e
s
tu
d
y
.
R
esp
o
n
d
en
ts
’
p
ar
ticip
at
io
n
was
o
n
a
v
o
lu
n
tar
y
b
asis
wh
er
e
th
ey
wer
e
in
f
o
r
m
ed
o
f
th
e
p
u
r
p
o
s
e
o
f
th
e
s
tu
d
y
an
d
ass
u
r
ed
o
f
c
o
n
f
id
e
n
t
iality
an
d
an
o
n
y
m
ity
as th
e
d
a
ta
co
llected
will b
e
ag
g
r
e
g
ated
.
Prio
r
to
d
ata
co
llectio
n
,
a
f
ac
e
an
d
co
n
ten
t
v
alid
ity
wer
e
c
o
n
d
u
cte
d
o
n
t
h
e
s
u
r
v
e
y
item
s
an
d
lay
o
u
t
wh
er
e
f
o
u
r
ex
p
er
ts
p
r
o
v
id
ed
f
ee
d
b
ac
k
.
T
h
e
s
u
r
v
ey
was
th
e
n
r
ev
is
ed
ac
c
o
r
d
in
g
ly
.
I
n
to
tal
,
4
8
4
s
u
r
v
ey
s
wer
e
co
m
p
leted
;
h
o
wev
e
r
,
2
4
h
ad
t
o
b
e
d
elete
d
d
u
e
t
o
s
tr
aig
h
t
-
lin
in
g
o
r
o
u
tlier
is
s
u
es.
T
h
u
s
,
4
6
0
r
esp
o
n
s
es
wer
e
u
s
ed
in
t
h
is
s
tu
d
y
.
T
h
e
r
esp
o
n
s
es
co
llected
m
et
th
e
r
eq
u
ir
ed
m
in
im
u
m
s
am
p
le
s
ize
o
f
4
0
.
T
ab
le
1
s
h
o
ws
th
e
r
esp
o
n
d
en
ts
’
p
r
o
f
ile
s
u
m
m
ar
y
.
I
n
g
e
n
er
al,
t
h
er
e
is
n
ea
r
l
y
eq
u
al
m
ale
a
n
d
f
em
ale
r
e
s
p
o
n
d
en
ts
,
with
an
ap
p
r
o
x
im
ate
av
e
r
ag
e
a
g
e
o
f
3
4
y
e
ar
s
;
th
e
m
ajo
r
ity
o
f
r
esp
o
n
d
e
n
ts
ar
e
f
r
o
m
th
e
Sch
o
o
l
o
f
B
u
s
in
ess
an
d
Ad
m
in
is
tr
atio
n
(
5
4
.
1
3
%)
an
d
m
o
s
tly
en
ter
i
n
g
t
h
e
u
n
iv
er
s
ity
th
r
o
u
g
h
r
e
g
u
lar
t
y
p
e
o
f
e
n
t
r
y
.
Ad
d
itio
n
ally
,
a
h
ig
h
p
e
r
ce
n
tag
e
(
6
8
.
0
4
%)
o
f
t
h
e
r
esp
o
n
d
en
ts
h
av
e
lim
ited
e
x
p
er
ien
ce
in
u
s
in
g
Gen
AI
.
Fig
u
r
e
1
.
R
esear
ch
m
o
d
el
G
e
n
A
I
r
e
a
d
i
n
e
ss
H
1
c
H
1
a
H
1
b
H
1
d
C
o
g
n
i
t
i
o
n
A
b
i
l
i
t
y
Et
h
i
c
s
V
i
si
o
n
B
e
h
a
v
i
o
u
r
a
l
i
n
t
e
n
t
i
o
n
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
.
14
,
No
.
2
,
Ap
r
il
20
25
:
1
0
6
5
-
1
0
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4
1068
T
ab
le
1
.
Dem
o
g
r
ap
h
ic
p
r
o
f
ile
o
f
r
esp
o
n
d
en
ts
(
n
=
4
6
0
)
P
r
o
f
i
l
e
i
t
e
ms
F
r
e
q
u
e
n
c
y
P
e
r
c
e
n
t
a
g
e
(
%)
G
e
n
d
e
r
M
a
l
e
1
9
8
4
3
.
0
4
F
e
mal
e
2
6
2
5
6
.
9
6
S
c
h
o
o
l
S
c
h
o
o
l
o
f
B
u
s
i
n
e
ss
a
n
d
A
d
mi
n
i
s
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r
a
t
i
o
n
2
4
9
5
4
.
1
3
S
c
h
o
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f
T
e
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h
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o
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o
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y
a
n
d
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c
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e
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c
e
1
0
6
2
3
.
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S
c
h
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o
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E
d
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c
a
t
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o
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,
H
u
ma
n
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t
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e
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a
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o
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i
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l
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e
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1
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9
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c
h
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o
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e
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t
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y
R
e
g
u
l
a
r
2
7
1
5
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9
1
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P
EL
1
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9
4
1
.
0
9
G
e
n
A
I
u
sa
g
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e
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p
e
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p
e
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e
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3
3
.
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1
Li
t
t
l
e
e
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p
e
r
i
e
n
c
e
1
5
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3
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.
1
3
S
o
me
e
x
p
e
r
i
e
n
c
e
1
0
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2
2
.
1
7
G
o
o
d
e
x
p
e
r
i
e
n
c
e
41
8
.
9
1
Ex
t
e
n
si
v
e
e
x
p
e
r
i
e
n
c
e
4
0
.
8
8
A
g
e
M
e
a
n
S
t
a
n
d
a
r
d
d
e
v
i
a
t
i
o
n
3
4
.
3
2
9
.
3
0
Data
was
f
ir
s
t
an
aly
ze
d
u
s
in
g
SP
SS
v
er
s
io
n
2
8
(
f
o
r
d
ata
cl
ea
n
in
g
an
d
d
escr
ip
tiv
e
s
tatis
tics
)
.
Nex
t,
Sm
ar
tPLS
4
was
u
s
ed
to
ass
e
s
s
th
e
m
ea
s
u
r
em
en
t
(
v
alid
ity
an
d
r
eliab
ilit
y
)
an
d
s
tr
u
ctu
r
al
m
o
d
els
(
h
y
p
o
th
eses
test
in
g
)
,
an
d
co
n
d
u
ctin
g
im
p
o
r
tan
ce
-
p
e
r
f
o
r
m
an
ce
m
atr
ix
a
n
aly
s
is
(
I
PMA)
.
Acc
o
r
d
in
g
to
Hair
et
a
l.
[
2
2
]
,
I
PMA
ex
ten
d
s
th
e
b
asic
PLS
-
SEM
f
in
d
in
g
s
as
it
co
n
tr
asts
th
e
to
tal
ef
f
ec
ts
(
im
p
o
r
tan
ce
)
o
f
th
e
s
tr
u
ctu
r
al
m
o
d
el
a
n
d
av
er
ag
e
v
al
u
es
o
f
th
e
laten
t
v
a
r
iab
le
s
co
r
es
(
p
er
f
o
r
m
an
ce
)
o
f
th
e
d
ep
e
n
d
e
n
t
co
n
s
tr
u
ct,
th
u
s
,
h
ig
h
lig
h
tin
g
s
ig
n
if
ican
t a
r
ea
s
o
f
im
p
r
o
v
em
e
n
t.
I
PMA
ca
n
al
s
o
b
e
u
s
ed
f
o
r
co
n
s
tr
u
cts an
d
i
n
d
icato
r
s
.
4.
RE
SU
L
T
S
4
.
1
.
M
ea
s
urem
ent
mo
del
W
e
u
s
ed
Sm
ar
tPLS
4
to
co
n
d
u
ct
th
e
p
ar
tial
least
s
q
u
ar
es
s
tr
u
ctu
r
al
e
q
u
atio
n
m
o
d
ellin
g
(
PLS
-
SEM
)
o
n
th
e
r
esear
ch
m
o
d
el.
W
e
f
o
llo
wed
th
e
two
-
s
tag
e
an
aly
s
is
p
r
o
ce
d
u
r
es
r
ec
o
m
m
en
d
e
d
by
Hair
et
a
l.
[2
2
]
.
First,
we
te
s
ted
th
e
m
ea
s
u
r
em
en
t
m
o
d
el
f
o
r
v
alid
ity
an
d
r
eliab
ilit
y
.
Acc
o
r
d
in
g
t
o
Hair
et
a
l.
[2
2
]
,
c
o
n
v
er
g
en
t
v
alid
ity
en
s
u
r
es
m
u
ltip
le
item
s
th
at
m
ea
s
u
r
e
th
e
s
am
e
c
o
n
ce
p
t
ar
e
n
o
t
co
n
tr
ad
ictin
g
o
n
e
an
o
th
er
.
I
t
is
d
eter
m
in
ed
with
lo
ad
in
g
s
,
av
e
r
ag
e
v
ar
ian
ce
ex
tr
ac
ted
(
AVE
)
,
an
d
co
m
p
o
s
ite
r
eliab
ilit
y
.
T
h
e
lo
ad
in
g
s
wer
e
all
m
o
r
e
th
an
th
e
th
r
esh
o
ld
v
alu
e
o
f
0
.
7
,
wh
ile
b
o
th
th
e
co
m
p
o
s
ite
r
eliab
ilit
ies an
d
AVE
wer
e
all
also
h
ig
h
er
th
an
th
e
r
eq
u
ir
ed
v
alu
es
o
f
0
.
7
an
d
0
.
5
r
esp
ec
tiv
ely
,
as
p
r
esen
ted
in
T
a
b
le
2
.
Ad
d
itio
n
ally
,
d
is
cr
im
in
an
t
v
alid
ity
was
also
e
s
tab
lis
h
ed
b
etwe
en
th
e
co
n
s
tr
u
cts
(
T
ab
le
2
)
as
th
e
h
eter
o
tr
ait
-
m
o
n
o
tr
ait
(
HT
MT
)
v
alu
es
wer
e
less
th
an
th
e
0
.
9
0
[
2
4
]
.
T
ab
le
2
.
R
esu
lts
o
f
m
ea
s
u
r
em
en
t m
o
d
el
M
o
d
e
l
c
o
n
s
t
r
u
c
t
R
e
l
i
a
b
i
l
i
t
y
a
n
d
c
o
n
v
e
r
g
e
n
t
v
a
l
i
d
i
t
y
D
i
scri
m
i
n
a
n
t
v
a
l
i
d
i
t
y
-
H
TM
T
F
a
c
t
o
r
l
o
a
d
i
n
g
r
a
n
g
e
C
R
(
>
0
.
7
)
A
V
E
(
>
0
.
5
)
BI
AB
CO
ET
VI
B
e
h
a
v
i
o
r
a
l
i
n
t
e
n
t
i
o
n
(
B
I
)
0
.
9
2
3
–
0
.
9
4
2
0
.
9
5
2
0
.
8
6
8
*
*
*
A
b
i
l
i
t
y
(
AB
)
0
.
8
6
2
–
0
.
9
1
7
0
.
9
6
2
0
.
8
0
8
0
.
6
3
5
*
*
*
C
o
g
n
i
t
i
o
n
(
CO
)
0
.
8
4
1
–
0
.
8
8
7
0
.
9
3
6
0
.
7
4
5
0
.
5
1
4
0
.
8
0
0
*
*
*
Et
h
i
c
s
(
ET
)
0
.
8
0
0
–
0
.
8
9
7
0
.
9
2
1
0
.
7
4
5
0
.
5
8
4
0
.
7
1
8
0
.
6
6
3
*
*
*
V
i
si
o
n
(
VI
)
0
.
8
4
8
–
0
.
8
9
5
0
.
9
1
1
0
.
7
7
3
0
.
5
6
6
0
.
8
1
5
0
.
7
4
6
0
.
8
2
7
*
*
*
N
o
t
e
:
C
R
=
c
o
m
p
o
s
i
t
e
r
e
l
i
a
b
i
l
i
t
y
;
A
V
E
=
a
v
e
r
a
g
e
v
a
r
i
a
n
c
e
e
x
t
r
a
c
t
e
d
4
.
2
.
Str
uct
ura
l
m
o
del
As
th
e
m
ea
s
u
r
em
en
t
m
o
d
el
was
ass
u
r
ed
o
f
co
n
s
tr
u
ct
v
ali
d
ity
an
d
r
elia
b
ilit
y
,
we
co
n
ti
n
u
ed
with
test
in
g
th
e
s
tr
u
ctu
r
al
m
o
d
el
a
cc
o
r
d
in
g
to
Hair
et
a
l.
p
r
o
ce
d
u
r
es
[2
2
]
.
T
h
e
s
tr
u
ctu
r
al
m
o
d
el
ca
p
tu
r
es
all
th
e
h
y
p
o
th
esized
r
elatio
n
s
h
ip
s
b
etwe
en
th
e
c
o
n
s
tr
u
cts
ex
am
in
e
d
in
th
is
s
tu
d
y
.
W
e
also
test
ed
co
llin
ea
r
ity
is
s
u
es
am
o
n
g
th
e
co
n
s
tr
u
cts.
T
h
e
co
n
s
tr
u
cts
m
et
th
e
co
llin
ea
r
ity
o
u
ter
m
o
d
el
th
r
esh
o
ld
v
al
u
e
o
f
less
th
an
5
.
0
.
I
n
th
e
s
tr
u
ctu
r
al
m
o
d
el,
we
an
aly
ze
d
th
e
p
ath
co
ef
f
icien
ts
,
th
e
t
-
v
a
lu
es
an
d
th
eir
s
ig
n
if
ican
ce
le
v
els,
an
d
c
o
n
f
i
d
en
ce
in
ter
v
als,
th
r
o
u
g
h
a
5
,
0
0
0
r
esa
m
p
lin
g
b
o
o
ts
tr
ap
p
in
g
p
r
o
ce
s
s
,
as
th
ey
in
d
icate
h
o
w
well
th
e
d
ata
s
u
p
p
o
r
ted
th
e
h
y
p
o
th
esized
r
elatio
n
s
h
ip
s
o
f
t
h
e
r
esear
ch
m
o
d
el
,
as sh
o
wn
i
n
T
ab
le
3
a
n
d
Fig
u
r
e
2
.
T
wo
h
y
p
o
th
eses
(
H1
a
a
n
d
H1
c)
wer
e
s
u
p
p
o
r
ted
as
Gen
AI
r
ea
d
in
ess
o
f
ab
ilit
y
(
β=0
.
4
3
8
,
p
<0
.
0
1
)
an
d
eth
ics
(
β=0
.
2
4
1
,
p
<0
.
0
1
)
wer
e
p
o
s
itiv
ely
s
ig
n
if
ican
t
to
b
eh
a
v
io
r
al
in
ten
tio
n
.
T
h
e
o
th
er
tw
o
h
y
p
o
th
eses
(
H1
b
an
d
H1
d
)
we
r
e
n
o
t
s
u
p
p
o
r
te
d
as
Gen
AI
r
ea
d
in
ess
o
f
co
g
n
itio
n
(
(
β=0
.
6
0
4
,
p
<0
.
0
1
)
an
d
v
is
io
n
(
β=0
.
0
2
5
,
p
>0
.
0
5
)
wer
e
f
o
u
n
d
n
o
t
s
ig
n
if
ican
t
to
b
eh
av
io
r
al
in
te
n
tio
n
.
T
h
e
R
2
o
f
b
eh
av
io
r
al
in
te
n
tio
n
is
0
.
3
9
2
m
ea
n
i
n
g
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xa
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in
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Gen
A
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r
ea
d
in
ess
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n
d
b
eh
a
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u
r
a
l
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tio
n
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d
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lt lea
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(
Jo
s
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h
in
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I
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h
a
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)
1069
th
at
3
9
.
2
%
o
f
th
e
v
ar
ian
ce
in
b
eh
av
io
r
al
in
ten
tio
n
ca
n
b
e
ex
p
lain
ed
b
y
Ge
n
AI
r
ea
d
in
ess
o
f
ab
ilit
y
a
n
d
eth
ics.
Fo
llo
win
g
Hair
et
a
l.
[
2
2
]
,
f
o
r
ass
ess
in
g
th
e
ef
f
ec
t
s
ize
(
f
2
)
,
th
e
f
in
d
in
g
s
in
d
icate
s
m
all
ef
f
ec
t
s
ize
f
o
r
ab
ilit
y
an
d
eth
ics as th
e
v
alu
es a
r
e
m
o
r
e
th
an
0
.
0
2
(
s
m
all
ef
f
ec
t)
b
u
t le
s
s
th
an
0
.
1
5
(
m
ed
iu
m
e
f
f
ec
t)
.
T
h
e
Q
2
v
alu
e
f
o
r
th
e
en
d
o
g
en
o
u
s
co
n
s
tr
u
ct
(
b
e
h
av
io
r
al
in
ten
tio
n
)
is
at
0
.
3
7
0
wh
ich
is
m
o
r
e
th
an
t
h
e
cr
iter
i
a
o
f
m
o
r
e
th
an
ze
r
o
.
Hen
ce
,
p
r
ed
ictiv
e
r
elev
an
ce
o
f
th
e
r
esear
ch
m
o
d
el
was e
s
tab
lis
h
ed
.
T
ab
le
3
.
R
esu
lts
o
f
s
tr
u
ctu
r
al
m
o
d
el
R
e
l
a
t
i
o
n
s
h
i
p
S
t
d
b
e
t
a
(
β)
t
-
v
a
l
u
e
9
5
%
C
o
n
f
i
d
e
n
c
e
i
n
t
e
r
v
a
l
Ef
f
e
c
t
si
z
e
(
f
2
)
D
e
c
i
s
i
o
n
H
1
a
.
A
b
i
l
i
t
y
→
b
e
h
a
v
i
o
r
a
l
i
n
t
e
n
t
i
o
n
0
.
4
2
7
5
.
7
4
9
*
*
[
0
.
2
7
7
,
0
.
5
6
5
]
0
.
0
9
6
S
u
p
p
o
r
t
e
d
H
1
b
.
C
o
g
n
i
t
i
o
n
→
b
e
h
a
v
i
o
r
a
l
i
n
t
e
n
t
i
o
n
0
.
0
0
6
0
.
0
9
1
[
-
0
.
1
2
4
,
0
.
1
3
5
]
0
.
0
0
0
N
o
t
s
u
p
p
o
r
t
e
d
H
1
c
.
Et
h
i
c
s
→
b
e
h
a
v
i
o
r
a
l
i
n
t
e
n
t
i
o
n
0
.
2
2
7
3
.
1
9
9
*
*
[
0
.
0
8
8
,
0
.
3
6
4
]
0
.
0
3
7
S
u
p
p
o
r
t
e
d
H
1
d
.
V
i
s
i
o
n
→
b
e
h
a
v
i
o
r
a
l
i
n
t
e
n
t
i
o
n
0
.
0
2
4
0
.
3
6
5
[
-
0
.
1
0
3
,
0
.
1
5
4
]
0
.
0
0
0
N
o
t
s
u
p
p
o
r
t
e
d
N
o
t
e
:
*
*
p
<
0
.
0
1
;
*
p
<
0
.
0
5
Fig
u
r
e
2
.
R
esu
lts
o
f
s
tr
u
ctu
r
al
m
o
d
el
b
o
o
ts
tr
ap
p
in
g
4
.
3
.
I
m
po
r
t
a
nce
-
perf
o
r
m
a
n
ce
m
a
t
ri
x
a
na
ly
s
is
Nex
t,
we
c
o
n
d
u
cted
t
h
e
I
PM
A
an
aly
s
is
.
As
m
en
tio
n
ed
ea
r
l
ier
,
I
PMA
is
u
s
ef
u
l
as
it
is
ab
l
e
to
e
x
ten
d
th
e
f
in
d
i
n
g
s
o
f
PLS
-
SEM
.
An
I
PMA
m
ap
was
c
o
n
s
tr
u
cted
f
o
r
th
e
Gen
AI
r
ea
d
in
ess
co
n
s
tr
u
cts
as
p
r
esen
ted
in
Fig
u
r
e
3
u
s
in
g
th
e
p
er
f
o
r
m
an
ce
an
d
im
p
o
r
tan
ce
m
ea
s
u
r
es
an
d
d
ata
o
f
t
h
is
s
tu
d
y
.
T
ab
le
4
s
h
o
ws
th
e
I
PMA
r
esu
lts
b
ased
o
n
to
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ased
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r
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im
p
r
o
v
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e
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ts
m
ay
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e
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ee
d
e
d
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
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8
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I
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5.
DIS
CU
SS
I
O
N
T
h
e
PLS
-
SEM
an
aly
s
is
r
e
v
e
aled
m
ix
e
d
f
i
n
d
in
g
s
f
o
r
th
e
r
elatio
n
s
h
ip
b
etwe
en
Gen
AI
r
ea
d
in
ess
(
ab
ilit
y
,
co
g
n
itio
n
,
eth
ics,
an
d
v
is
io
n
)
an
d
b
e
h
av
io
r
al
in
t
en
tio
n
to
ad
o
p
t
Gen
AI
.
Firstl
y
,
n
eith
er
Gen
AI
r
ea
d
in
ess
o
f
c
o
g
n
itio
n
n
o
r
v
is
i
o
n
s
ig
n
if
ican
tly
af
f
ec
ts
th
e
in
t
en
tio
n
to
u
s
e
Gen
AI
.
T
h
is
in
s
ig
n
if
ican
ce
m
ay
b
e
d
u
e
to
th
eo
r
etica
l
k
n
o
wled
g
e
o
f
Gen
AI
d
o
es
n
o
t
n
ec
ess
ar
ily
lead
to
an
in
ten
tio
n
to
u
s
e
Gen
AI
[
2
5
]
.
Sp
ec
if
ically
,
ad
u
lt
lear
n
er
s
m
ay
u
n
d
er
s
tan
d
th
e
im
p
o
r
tan
ce
o
f
Gen
AI
f
o
r
ed
u
ca
tio
n
;
h
o
wev
er
,
th
is
d
o
es
n
o
t
au
to
m
atica
lly
m
ea
n
th
e
y
will
in
ten
d
t
o
u
s
e
th
e
Gen
AI
i
n
th
eir
lear
n
in
g
.
Acc
o
r
d
in
g
t
o
C
h
an
an
d
Z
h
o
u
[
2
5
]
,
k
n
o
win
g
Gen
AI
’
s
d
ef
in
itio
n
,
s
tr
en
g
th
s
an
d
wea
k
n
ess
es
ar
e
n
o
t
en
o
u
g
h
f
o
r
s
tu
d
en
ts
to
wan
t
to
u
s
e
Gen
AI
.
W
h
at
is
m
o
r
e
im
p
o
r
tan
t
is
f
o
r
th
e
s
tu
d
en
ts
to
h
av
e
AI
liter
ac
y
an
d
g
u
i
d
in
g
th
em
to
u
s
e
A
I
in
a
p
r
ac
tical
an
d
ef
f
ec
tiv
e
m
an
n
er
.
Dah
lk
em
p
e
r
et
a
l.
[
2
6
]
r
ev
ea
led
th
at
s
tu
d
e
n
ts
with
p
r
io
r
ex
p
er
ien
ce
s
u
s
in
g
AI
will
b
e
m
o
r
e
p
o
s
itiv
e
to
war
d
s
AI
,
th
u
s
,
u
s
e
it
m
o
r
e
o
f
te
n
.
I
n
o
u
r
s
tu
d
y
,
t
h
e
ad
u
lt
lear
n
er
s
’
d
em
o
g
r
ap
h
i
c
p
r
o
f
ile
in
d
icate
d
th
at
a
h
ig
h
p
er
ce
n
tag
e
o
f
th
e
m
h
av
e
litt
le
o
r
n
o
ex
p
e
r
ien
ce
u
s
in
g
Gen
AI
.
T
h
is
co
u
ld
ex
p
lain
th
e
in
s
ig
n
if
ican
ce
o
f
co
g
n
itio
n
to
war
d
s
th
e
in
ten
tio
n
to
u
s
e
Gen
AI
.
As
s
tu
d
e
n
ts
’
co
g
n
itiv
e
r
ea
d
in
ess
in
cr
ea
s
e
s
,
th
ey
will
b
e
ab
le
to
u
n
d
er
s
tan
d
AI
’
s
r
o
le
an
d
s
ig
n
if
ican
ce
in
e
d
u
ca
tio
n
a
n
d
h
a
v
e
awa
r
en
ess
o
f
th
e
co
llab
o
r
at
iv
e
n
atu
r
e
b
etwe
en
h
u
m
an
s
an
d
AI
[
6
]
,
[
7
]
.
C
h
an
an
d
Hu
[
2
7
]
ar
g
u
e
th
at
f
r
eq
u
e
n
cy
o
f
u
s
in
g
Gen
AI
ca
n
in
cr
e
ase
th
e
in
ten
tio
n
t
o
u
s
e
AI
.
Per
h
ap
s
if
th
e
u
n
iv
er
s
ity
en
co
u
r
a
g
es
o
r
in
co
r
p
o
r
ates
th
e
u
s
e
o
f
Gen
AI
in
t
h
e
ad
u
lt
lear
n
e
r
s
’
ass
ig
n
m
en
ts
o
r
in
th
e
cu
r
r
ic
u
lu
m
will
th
e
c
o
g
n
itiv
e
r
ea
d
i
n
ess
in
cr
ea
s
e
[
3
]
.
B
esid
es,
Gen
AI
g
a
r
n
er
ed
m
o
r
e
in
ter
est
s
in
ce
th
e
p
o
p
u
lar
ity
o
f
C
h
atGPT
at
th
e
en
d
o
f
No
v
em
b
er
2
0
2
2
[
2
8
]
,
an
d
ad
u
lt
lear
n
er
s
m
ay
s
till
b
e
u
n
ce
r
tain
r
e
g
ar
d
in
g
th
e
b
en
ef
i
ts
an
d
p
o
ten
tial o
f
Gen
AI
in
t
h
eir
lear
n
in
g
p
r
o
ce
s
s
.
As
f
o
r
v
is
io
n
,
b
ein
g
o
n
e
o
f
Gen
AI
r
ea
d
in
ess
co
n
s
tr
u
cts,
it
r
elate
s
to
h
av
in
g
a
f
o
r
wa
r
d
-
lo
o
k
i
n
g
o
u
tlo
o
k
o
n
Gen
AI
’
s
p
o
ten
tia
l
r
o
le
in
tr
an
s
f
o
r
m
in
g
ed
u
ca
t
io
n
[
6
]
,
[
7
]
.
Vis
io
n
m
ay
b
e
in
f
lu
en
ce
d
b
y
th
e
s
tr
ateg
ic
g
o
als
o
f
th
e
in
s
titu
tio
n
an
d
th
e
b
r
o
a
d
er
e
d
u
ca
tio
n
al
p
o
licies
at
p
lay
.
Fo
r
in
s
ta
n
ce
,
Ar
izo
n
a
State
Un
iv
er
s
ity
,
wh
ich
h
av
e
a
clea
r
s
tr
ateg
ic
v
is
io
n
f
o
r
AI
,
ar
e
cu
r
r
en
tly
wo
r
k
in
g
with
Op
e
n
AI
to
en
h
a
n
ce
s
tu
d
en
t
ac
h
iev
em
en
ts
,
cr
ea
te
n
ew
in
n
o
v
ativ
e
r
esear
ch
o
p
p
o
r
tu
n
iti
es,
an
d
in
cr
ea
s
e
o
r
g
a
n
izatio
n
al
ef
f
icien
cy
[
2
9
]
.
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
E
xa
min
in
g
Gen
A
I
r
ea
d
in
ess
a
n
d
b
eh
a
vio
u
r
a
l
in
te
n
tio
n
o
f
a
d
u
lt lea
r
n
ers
…
(
Jo
s
ep
h
in
e
I
e
L
yn
C
h
a
n
)
1071
T
h
r
o
u
g
h
th
is
s
tr
ateg
ic
m
o
v
e
,
f
ac
u
lty
an
d
s
tu
d
en
ts
m
ay
b
e
m
o
r
e
lik
ely
to
alig
n
th
eir
o
wn
v
is
io
n
with
th
at
o
f
th
e
in
s
titu
tio
n
,
th
e
r
eb
y
en
h
a
n
c
in
g
th
eir
r
ea
d
in
ess
to
ad
o
p
t
AI
[
2
9
]
.
Ho
wev
e
r
,
th
e
ODL
in
s
titu
tio
n
in
th
is
s
tu
d
y
h
as
y
et
to
h
av
e
s
u
ch
s
tr
ateg
ic
v
is
io
n
,
th
u
s
,
it
is
n
o
t
s
u
r
p
r
is
in
g
th
at
th
e
v
is
io
n
was
f
o
u
n
d
in
s
ig
n
if
ican
t
to
war
d
s
in
ten
tio
n
to
a
d
o
p
t G
en
AI
.
Seco
n
d
ly
,
Gen
AI
r
ea
d
in
ess
o
f
ab
ilit
y
an
d
eth
ics
h
av
e
a
s
ig
n
if
ican
t
p
o
s
itiv
e
r
elatio
n
s
h
ip
with
b
eh
av
io
r
al
in
ten
tio
n
,
in
d
icatin
g
th
at
th
ey
ar
e
s
tr
o
n
g
p
r
ed
icto
r
s
o
f
b
eh
av
io
r
al
in
ten
tio
n
to
w
ar
d
s
Gen
AI
.
Ad
u
lt
lear
n
er
s
’
ab
ilit
y
in
th
is
s
tu
d
y
is
a
s
ig
n
if
ican
t
p
r
ed
icto
r
o
f
th
e
ir
in
ten
tio
n
to
u
s
e
Gen
AI
.
Her
e,
th
e
ab
ilit
y
asp
ec
t
in
v
o
lv
es
th
e
lear
n
e
r
s
’
s
k
ills
an
d
co
m
p
eten
ce
to
s
elec
t
an
d
u
s
e
AI
f
o
r
lear
n
in
g
[
6
]
,
[
7
]
.
I
t
i
s
im
p
o
r
tan
t
to
n
o
te
th
at
th
e
m
ea
s
u
r
e
o
f
ab
ilit
y
in
t
h
is
s
tu
d
y
d
o
es
n
o
t
ca
p
tu
r
e
th
e
ac
tu
al
s
k
ill
s
in
u
s
in
g
Gen
AI
b
u
t
r
ath
er
th
e
ad
u
lt
lear
n
er
s
’
p
er
ce
p
tio
n
o
f
th
eir
c
ap
ab
ilit
y
.
T
h
is
co
n
ce
p
t
is
s
im
ilar
to
th
e
co
n
ce
p
t
o
f
p
er
ce
iv
e
d
co
m
p
eten
ce
in
th
e
s
elf
-
d
eter
m
in
atio
n
t
h
eo
r
y
[
3
0
]
,
s
elf
-
ef
f
icac
y
[
3
1
]
,
a
n
d
p
er
ce
iv
ed
k
n
o
wled
g
e
[
3
2
]
.
Kwa
k
e
t
a
l.
[
3
3
]
r
ep
o
r
ted
th
at
s
elf
-
ef
f
icac
y
p
r
e
d
icts
n
u
r
s
in
g
s
tu
d
en
ts
’
b
eh
av
io
r
al
in
te
n
tio
n
in
u
s
in
g
AI
-
b
ased
h
ea
lt
h
ca
r
e
tech
n
o
lo
g
y
.
I
n
r
esear
c
h
b
y
L
u
ik
an
d
T
ai
m
alu
[
3
2
]
,
it
was
f
o
u
n
d
th
at
s
tu
d
en
t
teac
h
er
s
’
p
er
ce
iv
e
d
k
n
o
wled
g
e
ab
o
u
t
in
teg
r
atin
g
tech
n
o
lo
g
y
h
a
d
an
in
d
ir
ec
t
ef
f
ec
t
o
n
th
e
in
ten
tio
n
to
u
s
e
it.
I
n
th
e
co
n
tex
t
o
f
th
is
s
tu
d
y
,
th
e
p
er
ce
iv
ed
a
b
ilit
y
to
u
s
e
Gen
AI
in
an
ODL
in
s
titu
tio
n
ca
n
b
e
s
ig
n
if
ican
tly
in
f
lu
en
ce
d
b
y
th
e
av
ailab
ilit
y
o
f
r
eso
u
r
ce
s
,
tr
ain
in
g
,
an
d
in
s
titu
tio
n
al
s
u
p
p
o
r
t.
I
n
h
ig
h
er
lea
r
n
in
g
in
s
titu
tio
n
s
th
at
p
r
o
v
i
d
e
r
o
b
u
s
t
s
u
p
p
o
r
t
f
o
r
Gen
AI
in
teg
r
atio
n
s
u
ch
as
th
r
o
u
g
h
wo
r
k
s
h
o
p
s
,
AI
-
p
o
wer
ed
to
o
ls
,
an
d
ac
ce
s
s
ib
le
tech
n
o
l
o
g
y
in
f
r
astru
ctu
r
e
,
f
ac
u
lty
an
d
s
tu
d
en
ts
ar
e
m
o
r
e
lik
ely
to
f
ee
l
c
o
n
f
id
e
n
t
in
th
eir
ab
ilit
y
to
u
s
e
AI
.
Fo
r
ex
a
m
p
le,
Mu
d
awy
[
3
4
]
co
n
f
ir
m
ed
th
at
f
am
iliar
ity
to
AI
ap
p
licatio
n
s
ca
n
b
e
s
tr
en
g
t
h
en
ed
th
r
o
u
g
h
tr
ain
in
g
a
n
d
s
u
p
p
o
r
t w
h
ich
ca
n
h
elp
f
ac
ilit
ate
b
etter
in
teg
r
atio
n
o
f
n
ew
AI
to
o
ls
.
T
h
er
e
f
o
r
e,
in
o
r
d
er
t
o
in
c
r
ea
s
e
th
e
ad
u
lt
l
ea
r
n
er
s
’
b
eh
av
io
r
al
in
ten
tio
n
to
u
s
e
Gen
AI
in
th
ei
r
lear
n
in
g
,
h
an
d
s
-
o
n
wo
r
k
s
h
o
p
s
s
h
o
u
ld
b
e
p
r
o
v
id
ed
t
o
th
e
m
s
o
th
at
th
ey
h
av
e
th
e
k
n
o
wled
g
e
an
d
s
k
ills
to
u
s
e
Gen
AI
in
th
eir
lear
n
in
g
.
T
h
e
eth
ics
co
n
s
tr
u
ct
r
elate
s
to
co
m
p
ly
i
n
g
with
eth
ical
an
d
l
eg
al
n
o
r
m
s
an
d
r
eg
u
latio
n
s
w
h
en
u
s
in
g
AI
[
6
]
,
[
7
]
.
Data
an
aly
s
is
s
h
o
ws
th
at
eth
ics
p
o
s
itiv
ely
af
f
ec
ts
ad
u
lt
lear
n
er
s
’
b
e
h
av
io
r
al
in
ten
tio
n
to
u
s
e
Gen
AI
.
T
h
is
f
in
d
in
g
s
u
g
g
ests
th
at
s
tu
d
en
ts
wh
o
u
n
d
er
s
tan
d
d
ig
ital
eth
ics
an
d
eth
ical
r
esp
o
n
s
ib
ilit
ies
ten
d
to
f
ee
l
a
g
r
ea
ter
s
en
s
e
o
f
ac
co
u
n
tab
ilit
y
wh
en
u
s
in
g
Gen
AI
in
th
eir
lear
n
in
g
wh
ich
in
t
u
r
n
in
cr
ea
s
es
th
eir
in
ten
tio
n
to
u
s
e
Gen
AI
.
B
esid
es,
th
ey
s
h
o
w
a
g
r
ea
ter
in
clin
atio
n
to
war
d
s
its
u
s
e
wh
en
eq
u
ip
p
ed
with
k
n
o
wled
g
e
o
n
h
o
w
to
p
r
o
tect
th
eir
p
er
s
o
n
al
in
f
o
r
m
atio
n
.
Ho
wev
er
,
ex
tan
t
s
tu
d
ies
wer
e
u
n
ab
le
to
d
eter
m
in
e
if
h
av
in
g
eth
ics
awa
r
en
ess
in
f
l
u
en
ce
b
e
h
av
io
r
al
in
ten
tio
n
to
u
s
e
Gen
AI
am
o
n
g
s
tu
d
en
ts
[
3
3
]
,
[
3
5
]
.
Desp
ite
Gen
AI
’
s
b
en
ef
its
in
ed
u
ca
tio
n
,
th
er
e
is
a
n
ee
d
f
o
r
clea
r
er
et
h
ics
g
u
id
elin
e
an
d
t
r
an
s
p
ar
en
c
y
f
o
r
a
d
u
lt
lear
n
er
s
to
en
s
u
r
e
r
esp
o
n
s
ib
le
an
d
eth
i
ca
l u
s
e
o
f
Gen
AI
[
3
6
]
,
[
3
7
]
.
A
s
s
u
ch
,
Gen
AI
eth
ics s
h
o
u
ld
b
e
in
teg
r
ated
in
to
th
e
cu
r
r
icu
la
a
n
d
eth
ical
f
r
a
m
ewo
r
k
s
estab
lis
h
ed
to
p
r
ev
e
n
t
tr
a
n
s
p
ar
en
cy
,
s
ec
u
r
ity
a
n
d
ac
c
o
u
n
tab
ilit
y
is
s
u
es
wh
en
u
s
in
g
Gen
AI
[
3
7
]
.
T
h
e
d
is
cu
s
s
io
n
o
f
Gen
A
I
eth
ics
h
as
in
t
en
s
if
ied
with
th
e
r
ap
i
d
a
d
v
an
ce
m
en
t
o
f
Gen
AI
.
Ho
wev
er
,
m
o
s
t
o
f
th
e
s
tu
d
ies
ex
am
in
ed
th
e
eth
ical
ch
all
en
g
es
[
3
8
]
a
n
d
d
if
f
e
r
en
t
f
ac
ets
o
f
eth
ics
[
3
9
]
.
R
esear
ch
ex
p
lo
r
in
g
t
h
e
r
elatio
n
s
h
ip
b
etwe
en
eth
ics
an
d
u
s
er
b
eh
av
io
r
al
in
ten
tio
n
is
s
till
in
th
e
in
f
an
c
y
s
tag
e.
T
h
u
s
,
th
is
s
tu
d
y
co
n
tr
i
b
u
tes
t
o
th
e
em
e
r
g
en
t
b
o
d
y
o
f
k
n
o
wled
g
e
b
y
d
em
o
n
s
tr
atin
g
h
o
w
u
n
d
er
s
tan
d
in
g
a
n
d
ad
h
er
in
g
to
eth
ical
n
o
r
m
s
s
h
ap
es a
d
u
lt lea
r
n
er
s
’
in
ten
tio
n
s
to
u
s
e
Gen
AI
in
th
eir
lea
r
n
in
g
.
Fin
ally
,
b
ased
o
n
th
e
I
PMA
r
esu
lts
,
th
er
e
is
a
m
is
alig
n
m
en
t
b
etwe
en
th
e
p
er
ce
iv
ed
im
p
o
r
tan
ce
an
d
ac
tu
al
p
er
f
o
r
m
an
ce
o
f
Gen
AI
r
ea
d
in
ess
co
n
s
tr
u
cts
am
o
n
g
ad
u
lt
lear
n
er
s
.
Ab
ilit
y
an
d
eth
ics
em
er
g
e
as
th
e
tw
o
m
o
s
t
ess
en
tial
co
n
s
tr
u
cts
o
f
Gen
AI
r
ea
d
in
ess
.
Hav
in
g
th
e
h
ig
h
est
im
p
o
r
tan
ce
,
ab
ilit
y
i
s
a
cr
itical
f
ac
to
r
in
p
r
ed
ictin
g
b
eh
a
v
io
r
al
i
n
ten
tio
n
to
ad
o
p
t
Gen
AI
am
o
n
g
a
d
u
lt
lear
n
er
s
.
T
h
e
p
er
f
o
r
m
an
ce
lev
el
is
m
o
d
er
ate,
in
d
icatin
g
th
at
lear
n
e
r
s
p
er
ce
i
v
e
th
em
s
elv
es
as
s
o
m
ewh
at
c
ap
ab
le
o
f
u
s
in
g
Gen
AI
,
b
u
t
t
h
er
e
m
ig
h
t
s
till
b
e
r
o
o
m
f
o
r
im
p
r
o
v
e
m
en
t.
Un
d
e
r
th
e
ODL
co
n
tex
t,
a
d
u
lt
lea
r
n
er
s
ar
e
ex
p
o
s
ed
m
o
r
e
to
t
h
e
d
ig
ital
o
n
lin
e
r
ea
lm
th
an
f
ac
e
-
to
-
f
ac
e
in
ter
ac
tio
n
s
[
8
]
.
B
esid
es
th
at,
th
ey
h
av
e
to
b
alan
ce
wo
r
k
,
f
a
m
ily
,
a
n
d
e
d
u
ca
tio
n
[
4
0
]
.
T
h
u
s
,
h
av
in
g
th
e
ab
ilit
y
r
ea
d
i
n
ess
to
ad
o
p
t
Gen
AI
is
d
ef
in
itely
n
ee
d
ed
.
I
n
s
titu
tio
n
s
o
f
h
ig
h
er
lear
n
in
g
s
h
o
u
l
d
s
u
p
p
o
r
t
an
d
en
h
a
n
ce
ad
u
lt
le
ar
n
er
s
’
ab
ilit
ies
th
r
o
u
g
h
f
o
cu
s
ed
tr
ain
in
g
p
r
o
g
r
am
m
e
r
s
,
u
s
er
-
f
r
ien
d
ly
Gen
AI
to
o
ls
,
an
d
o
n
-
g
o
i
n
g
tech
n
ical
s
u
p
p
o
r
t
[
3
4
]
.
E
t
h
ics,
b
ein
g
r
an
k
ed
s
ec
o
n
d
in
ter
m
s
o
f
i
m
p
o
r
tan
ce
,
is
also
d
ee
m
ed
im
p
o
r
tan
t
in
in
f
l
u
en
cin
g
b
eh
a
v
io
r
al
in
ten
tio
n
to
ad
o
p
t
Gen
AI
.
Hav
i
n
g
th
e
h
i
g
h
est
p
er
f
o
r
m
an
ce
in
d
icate
s
th
at
eth
ical
co
n
ce
r
n
s
ab
o
u
t
p
r
iv
ac
y
,
d
ata
s
ec
u
r
ity
,
an
d
f
air
n
ess
in
Gen
AI
u
s
ag
e
ar
e
b
ein
g
ad
eq
u
ately
ad
d
r
ess
ed
.
E
th
ical
co
n
s
id
er
ati
o
n
s
ar
e
im
p
o
r
tan
t,
esp
ec
ially
f
o
r
ad
u
lt
lear
n
e
r
s
wh
o
m
ay
b
e
war
y
o
f
u
s
in
g
Gen
AI
d
u
e
to
d
ata
p
r
iv
ac
y
is
s
u
es
o
r
b
iased
alg
o
r
ith
m
s
.
Hen
ce
,
in
s
titu
tio
n
s
s
h
o
u
ld
co
n
tin
u
e
to
em
p
h
asize
an
d
co
m
m
u
n
icate
eth
ical
AI
u
s
ag
e
an
d
g
u
id
elin
es th
at
r
ea
s
s
u
r
e
a
d
u
lt lea
r
n
er
s
[
3
6
]
,
[
3
7
].
C
o
g
n
itio
n
a
n
d
v
is
io
n
,
o
n
th
e
o
th
er
h
an
d
,
ar
e
p
e
r
ce
iv
ed
as
l
ess
cr
itical,
alth
o
u
g
h
th
eir
p
e
r
f
o
r
m
an
ce
lev
els
v
ar
y
.
C
o
g
n
itio
n
p
lace
d
lo
west
in
im
p
o
r
tan
ce
as
well
as
in
p
er
f
o
r
m
a
n
ce
.
T
h
is
r
e
s
u
lt
r
ein
f
o
r
ce
s
t
h
e
in
s
ig
n
if
ican
ce
o
f
c
o
g
n
itio
n
a
n
d
th
at
it
h
as
m
in
im
al
im
p
a
ct
o
n
b
eh
a
v
io
r
al
in
ten
tio
n
,
s
u
g
g
esti
n
g
th
at
ad
u
lt
lear
n
er
s
m
ay
n
o
t
h
a
v
e
a
d
ee
p
u
n
d
e
r
s
tan
d
in
g
o
f
Gen
AI
,
its
f
u
n
ctio
n
s
,
a
n
d
f
ea
tu
r
es.
Ad
u
lt
lear
n
er
s
co
u
ld
b
e
m
o
r
e
in
ter
ested
in
th
e
p
r
ac
tica
l
asp
ec
ts
o
f
Gen
AI
[
3
]
,
[
2
5
]
in
s
tead
o
f
in
-
d
ep
t
h
co
g
n
itiv
e
u
n
d
er
s
tan
d
in
g
.
W
h
ile
it
m
ay
n
o
t
b
e
n
ec
ess
ar
y
to
en
h
an
ce
th
e
c
o
g
n
itiv
e
Gen
AI
r
ea
d
in
ess
o
f
ad
u
lt
lea
r
n
er
s
,
in
s
titu
t
io
n
s
co
u
ld
p
r
o
v
id
e
o
p
tio
n
al
r
eso
u
r
ce
s
f
o
r
t
h
o
s
e
in
ter
ested
to
lear
n
m
o
r
e
a
b
o
u
t
AI
o
r
Gen
AI
,
with
o
u
t
m
ak
in
g
it
a
co
r
e
co
m
p
o
n
en
t
o
f
th
e
Gen
AI
ad
o
p
tio
n
s
tr
ateg
y
.
Desp
ite
its
lo
w
im
p
o
r
tan
ce
,
th
e
p
e
r
f
o
r
m
an
ce
le
v
el
o
f
v
is
io
n
is
m
o
d
e
r
ate.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
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2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
14
,
No
.
2
,
Ap
r
il
20
25
:
1
0
6
5
-
1
0
7
4
1072
T
h
e
f
in
d
in
g
i
n
d
icate
s
th
at
f
o
r
ad
u
lt
lear
n
er
s
,
im
m
e
d
iate
b
en
ef
its
an
d
p
r
ac
tical
ap
p
licati
o
n
s
o
f
Gen
AI
ar
e
lik
ely
to
b
e
d
ee
m
ed
m
o
r
e
im
p
o
r
tan
t
th
a
n
lo
n
g
-
ter
m
v
is
io
n
s
o
f
Gen
AI
’
s
r
o
le
in
ODL
.
Ad
u
lt
lear
n
er
s
m
a
y
f
o
cu
s
o
n
Gen
AI
to
o
ls
th
at
p
r
o
v
id
e
d
i
r
ec
t
s
u
p
p
o
r
t
in
th
eir
cu
r
r
en
t
lear
n
in
g
co
n
tex
t
o
v
e
r
b
r
o
a
d
er
v
is
io
n
a
r
y
id
ea
s
[
2
7
]
,
[
3
4
]
.
Pro
m
o
tio
n
o
f
p
o
ten
tial
f
u
t
u
r
e
Gen
AI
b
en
ef
its
is
in
ev
itab
le
d
u
e
to
its
r
ap
i
d
in
f
lu
en
ce
in
th
e
ed
u
ca
tio
n
s
ec
to
r
[
4
]
,
[
2
8
]
.
I
n
s
titu
tio
n
s
m
ay
wan
t to
c
o
n
s
id
er
d
is
cu
s
s
io
n
s
o
n
AI
in
th
eir
lo
n
g
-
ter
m
s
tr
ateg
y
.
6.
I
M
P
L
I
CA
T
I
O
N
6
.
1
.
T
heo
re
t
ica
l i
m
pli
ca
t
io
ns
On
a
th
eo
r
etica
l b
asis
,
th
e
cu
r
r
en
t stu
d
y
’
s
f
in
d
in
g
s
co
n
f
ir
m
t
h
at
th
e
r
esear
ch
m
o
d
el
an
d
m
e
asu
r
em
en
t
s
ca
les
ad
ap
ted
f
r
o
m
s
ev
er
al
s
tu
d
ies
[
6
]
,
[
7
]
,
[
2
3
]
ar
e
v
alid
a
n
d
r
eliab
le
f
o
r
m
ea
s
u
r
in
g
Gen
AI
r
ea
d
in
ess
am
o
n
g
ad
u
lt
lear
n
er
s
f
r
o
m
an
ODL
u
n
iv
er
s
ity
.
T
h
is
ex
p
a
n
d
s
th
e
s
c
o
p
e
o
f
th
e
liter
atu
r
e,
w
h
ich
h
a
s
lar
g
ely
f
o
cu
s
ed
o
n
ed
u
ca
to
r
s
,
m
e
d
ical
s
tu
d
en
ts
,
an
d
b
u
ild
in
g
in
f
o
r
m
atio
n
m
o
d
elin
g
(
B
I
M
)
u
s
er
s
.
Ad
d
itio
n
ally
,
th
e
s
tu
d
y
also
p
r
o
v
id
es
e
v
id
en
ce
th
at
o
u
t
o
f
t
h
e
f
o
u
r
Gen
AI
r
ea
d
in
ess
co
n
s
tr
u
cts,
ab
ilit
y
an
d
et
h
ics
ar
e
s
ig
n
if
ican
t
p
r
e
d
icto
r
s
o
f
ad
u
lt
lear
n
e
r
s
’
b
e
h
av
io
r
al
in
ten
tio
n
to
u
s
e
Gen
AI
.
B
etwe
en
th
ese
two
co
n
s
tr
u
cts,
a
b
ilit
y
is
th
e
s
tr
o
n
g
er
p
r
ed
icto
r
o
f
b
eh
av
i
o
r
al
in
ten
ti
o
n
.
As
s
u
ch
,
th
e
s
tu
d
y
co
n
tr
ib
u
tes
to
war
d
s
n
ew
in
s
ig
h
ts
in
t
o
a
d
if
f
er
en
t
s
et
o
f
Gen
AI
r
ea
d
i
n
ess
co
n
s
tr
u
cts
(
ab
ilit
y
,
co
g
n
itio
n
,
eth
ics,
a
n
d
v
is
io
n
)
th
at
in
f
lu
e
n
ce
t
h
e
b
eh
av
io
r
al
in
te
n
tio
n
o
f
Gen
AI
am
o
n
g
ad
u
lt
lear
n
er
s
,
in
s
tead
o
f
co
n
s
tr
u
cts
o
f
o
p
ti
m
is
m
,
in
n
o
v
ativ
en
ess
,
d
is
co
m
f
o
r
t,
an
d
in
s
ec
u
r
ity
wh
ich
ar
e
co
m
m
o
n
ly
u
s
ed
in
e
x
tan
t stu
d
ies
[
8
]
,
[
1
6
]
–
[
1
9
]
,
[
2
3
]
.
6
.
2
.
P
r
a
ct
ica
l i
m
pli
ca
t
io
ns
T
h
e
PLS
-
SEM
f
in
d
in
g
s
an
d
I
PMA
d
ata
r
ev
ea
l
s
ev
er
al
p
r
ac
tical
im
p
licatio
n
s
f
o
r
ea
ch
Gen
AI
r
ea
d
in
ess
co
n
s
tr
u
ct
o
f
ad
u
lt lea
r
n
er
s
in
an
ODL
u
n
iv
e
r
s
ity
.
I
n
g
en
er
al,
a
d
u
lt lea
r
n
er
s
in
th
e
ODL
co
n
tex
t o
f
ten
ju
g
g
le
with
v
ar
io
u
s
wo
r
k
co
m
m
itm
en
ts
an
d
f
am
ily
r
esp
o
n
s
ib
ilit
ies
[
4
0
]
.
T
h
ey
m
ay
p
r
ef
er
s
tr
aig
h
tf
o
r
war
d
,
p
r
ac
tical
to
o
ls
th
at
en
h
an
ce
th
eir
lear
n
in
g
ex
p
er
ien
ce
wi
th
o
u
t
r
eq
u
ir
in
g
d
ee
p
co
g
n
itiv
e
en
g
ag
em
e
n
t
o
r
v
is
io
n
ar
y
th
i
n
k
in
g
.
T
h
ese
ad
u
lt
lear
n
er
s
ar
e
lik
ely
m
o
r
e
co
n
ce
r
n
with
h
o
w
Ge
n
AI
ca
n
s
o
l
v
e
th
eir
im
m
ed
iate
ch
allen
g
es
s
u
ch
as
tim
e
m
a
n
ag
em
en
t
[
2
7
]
,
ac
ce
s
s
to
r
eso
u
r
ce
s
[
2
7
]
,
[
3
4
]
,
an
d
eth
ical
co
n
ce
r
n
s
[
3
7
]
,
[
3
8
]
r
ath
er
th
an
h
o
w
Gen
AI
m
ig
h
t
tr
an
s
f
o
r
m
e
d
u
ca
tio
n
in
th
e
lo
n
g
r
u
n
.
M
o
r
e
s
p
ec
if
ically
,
t
h
e
Gen
AI
r
ea
d
i
n
ess
co
n
s
tr
u
cts
o
f
ab
ilit
y
an
d
eth
ics
ar
e
th
e
m
o
s
t
cr
it
ical
in
in
f
lu
en
cin
g
ad
u
lt
lear
n
er
s
’
b
eh
av
io
r
al
in
ten
tio
n
to
ad
o
p
t
Gen
AI
.
I
n
s
titu
tio
n
s
o
f
h
ig
h
er
lear
n
i
n
g
s
h
o
u
ld
p
r
i
o
r
itize
m
ain
tain
in
g
a
n
d
en
h
an
cin
g
th
ese
two
ar
ea
s
.
Fo
r
ab
ilit
y
,
it
co
u
l
d
m
ea
n
o
f
f
er
in
g
m
o
r
e
h
an
d
s
-
o
n
tr
ain
i
n
g
,
s
im
p
l
if
ied
in
ter
f
ac
es,
a
n
d
u
s
er
s
u
p
p
o
r
t.
Fo
r
eth
ics,
it
is
k
ey
to
co
n
tin
u
e
b
u
ild
in
g
tr
u
s
t
th
r
o
u
g
h
tr
an
s
p
ar
e
n
t A
I
p
o
licies an
d
eth
ical
p
r
ac
tices.
C
o
g
n
it
io
n
an
d
v
is
io
n
h
av
e
lo
w
im
p
o
r
ta
n
ce
.
T
h
is
f
in
d
in
g
s
u
g
g
ests
th
at
wh
ile
th
ese
two
co
n
s
tr
u
cts
m
ay
co
n
t
r
ib
u
te
to
a
d
ee
p
er
u
n
d
er
s
tan
d
i
n
g
an
d
lo
n
g
-
ter
m
en
g
ag
em
e
n
t
with
AI
,
th
ey
ar
e
n
o
t
im
m
ed
iately
im
p
ac
tf
u
l
o
n
th
e
d
ec
is
io
n
to
ad
o
p
t
Gen
AI
.
I
n
s
titu
tio
n
s
o
f
h
ig
h
er
lear
n
in
g
c
o
u
ld
c
o
n
s
i
d
er
th
em
as
lo
wer
p
r
io
r
ities
an
d
f
o
cu
s
m
o
r
e
o
n
p
r
ac
tical
asp
ec
ts
th
at
d
ir
ec
tly
en
h
an
ce
th
e
lear
n
in
g
ex
p
e
r
ien
ce
o
f
ad
u
lt lea
r
n
er
s
.
7.
CO
NCLU
SI
O
N
T
h
e
s
tu
d
y
ex
am
i
n
ed
th
e
b
eh
a
v
io
r
al
in
te
n
tio
n
o
f
ad
u
lt
lea
r
n
er
s
to
war
d
s
Gen
AI
ad
o
p
tio
n
with
in
an
ODL
h
ig
h
er
lear
n
i
n
g
i
n
s
titu
tio
n
.
T
h
e
n
o
v
elty
o
f
th
is
s
tu
d
y
is
its
ex
p
lo
r
ati
o
n
o
f
th
e
d
im
en
s
io
n
s
o
f
Gen
AI
r
ea
d
in
ess
–
ab
ilit
y
,
co
g
n
itio
n
,
e
th
ics,
an
d
v
is
io
n
–
r
ath
er
th
an
t
h
e
co
m
m
o
n
l
y
u
s
ed
d
im
e
n
s
io
n
s
o
f
i
n
n
o
v
ativ
en
ess
,
o
p
tim
is
m
,
d
is
co
m
f
o
r
t
an
d
in
s
ec
u
r
ity
.
Mo
r
eo
v
er
,
its
co
n
tex
t
is
b
ased
o
n
a
m
o
r
e
s
p
ec
if
i
c
co
n
tex
t
o
f
ad
u
lt
lear
n
er
s
an
d
ODL
.
Ad
d
itio
n
all
y
,
d
ata
an
aly
s
is
was
ex
ten
d
ed
to
in
clu
d
e
th
e
I
PMA
ap
p
r
o
ac
h
,
o
f
f
er
in
g
v
alu
a
b
le
in
s
ig
h
ts
in
th
e
d
im
en
s
io
n
s
o
f
Gen
AI
r
ea
d
in
ess
.
Ov
er
all,
th
e
s
tu
d
y
’
s
f
in
d
in
g
s
co
n
tr
i
b
u
te
s
ig
n
if
ican
tly
to
th
e
tech
n
o
lo
g
y
/AI
r
ea
d
i
n
ess
liter
atu
r
e,
h
ig
h
lig
h
tin
g
ar
ea
s
f
o
r
i
m
p
r
o
v
e
m
en
t
an
d
p
r
o
v
id
i
n
g
r
ec
o
m
m
en
d
atio
n
s
to
u
n
iv
er
s
ity
m
an
a
g
er
s
an
d
p
o
li
cy
m
ak
er
s
.
Sp
ec
if
ically
,
th
e
PLS
-
SEM
r
esu
lts
in
d
icate
th
at
ab
ilit
y
an
d
eth
ical
r
ea
d
in
ess
s
ig
n
if
ican
tly
p
r
ed
i
ct
ad
u
lt
lear
n
e
r
s
’
in
ten
tio
n
to
ad
o
p
t
Gen
AI
,
alig
n
in
g
with
I
PMA
r
esu
lts
.
Ho
wev
er
,
th
e
in
s
ig
n
if
ica
n
ce
an
d
r
elativ
ely
lo
w
p
er
f
o
r
m
an
ce
o
f
co
g
n
itio
n
an
d
v
is
io
n
s
u
g
g
ests
a
n
ee
d
f
o
r
f
u
r
th
er
e
x
p
lo
r
atio
n
o
f
th
ese
co
n
s
tr
u
cts in
f
u
tu
r
e
r
esear
ch
.
Ad
d
itio
n
ally
,
alth
o
u
g
h
s
tatis
tically
s
ig
n
if
ican
t,
th
e
s
m
all
ef
f
ec
t
s
izes
o
f
ab
ilit
y
an
d
eth
ics
h
ig
h
lig
h
t
a
n
ee
d
f
o
r
f
u
r
t
h
er
i
n
v
esti
g
atio
n
to
b
etter
u
n
d
e
r
s
tan
d
th
e
r
e
latio
n
s
h
ip
b
etwe
en
th
ese
f
ac
t
o
r
s
an
d
b
e
h
av
io
r
al
in
ten
tio
n
.
T
h
e
s
tu
d
y
’
s
s
co
p
e
wh
ich
is
lim
ited
to
o
n
e
ODL
in
s
titu
tio
n
,
r
estricts
g
en
er
aliza
tio
n
.
Su
b
s
eq
u
en
t
s
tu
d
ies
s
h
o
u
ld
co
n
s
id
er
ex
p
an
d
in
g
th
e
s
am
p
le
to
in
clu
d
e
d
i
v
er
s
e
lear
n
in
g
en
v
i
r
o
n
m
e
n
ts
s
u
ch
as
o
th
er
p
r
iv
at
e
h
ig
h
er
lea
r
n
in
g
in
s
titu
tio
n
s
an
d
p
u
b
lic
u
n
i
v
er
s
ities
.
E
x
p
lo
r
in
g
an
tece
d
e
n
ts
o
f
Ge
n
AI
r
ea
d
in
ess
an
d
ex
am
i
n
in
g
d
ee
p
er
in
to
t
h
e
eth
ics
-
b
eh
a
v
io
r
r
elatio
n
s
h
ip
ar
e
r
ec
o
m
m
e
n
d
ed
.
T
h
ese
f
u
tu
r
e
r
esear
ch
a
v
e
n
u
es
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1
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R
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7
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O
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K
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.
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8
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N
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N
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[
9
]
G
.
Ö
.
G
ü
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,
Ş
.
Y
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l
ma
z
,
a
n
d
F
.
I
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c
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ğ
l
u
,
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mi
n
i
n
g
me
d
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a
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x
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a
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d
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a
d
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l
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A
.
Y
.
Z.
T
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W
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“
M
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.
B
.
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h
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R
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F
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1
2
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C
.
L
i
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H
.
S
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,
a
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P
.
J
.
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1
3
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F
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D
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