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tellig
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I
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tr
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Per
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CC B
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SA
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C
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s
p
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A
uth
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:
Yg
n
ac
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Facu
lty
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Ph
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m
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Sch
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San
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Per
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1.
I
NT
RO
D
UCT
I
O
N
W
ith
in
r
ec
en
t
y
ea
r
s
,
th
e
p
o
s
itio
n
o
f
a
r
tific
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in
tellig
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ce
(
AI
)
is
elev
atin
g
in
th
e
ed
u
ca
t
io
n
s
ec
to
r
.
T
h
e
em
er
g
en
ce
an
d
ac
ce
p
tan
ce
o
f
AI
is
f
o
s
ter
in
g
ch
an
g
e
s
to
d
y
n
am
ics
o
f
teac
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in
g
an
d
lear
n
in
g
in
th
e
p
r
ac
tices
o
f
k
n
o
wled
g
e
p
r
o
d
u
ctio
n
[
1
]
.
T
h
e
f
ac
to
r
s
ass
o
ciate
d
with
th
e
ad
o
p
tio
n
a
n
d
ac
ce
p
tan
ce
o
f
AI
ar
e
b
ein
g
s
tu
d
ied
th
r
o
u
g
h
th
e
len
s
o
f
s
ev
er
al
ad
d
itio
n
al
f
ac
to
r
s
[
2
]
.
T
h
ese
s
tu
d
ies
h
av
e
e
n
co
m
p
ass
ed
co
n
s
is
ten
t
u
s
e,
m
o
tiv
atio
n
,
a
n
d
p
er
ce
iv
e
d
u
s
ef
u
l
n
ess
an
d
in
th
is
in
v
est
ig
atio
n
,
we
r
eg
a
r
d
AI
u
s
ag
e
(
i
.
e.
,
u
s
ag
e
o
f
AI
b
y
s
tu
d
en
ts
)
,
in
tr
in
s
ic
m
o
tiv
atio
n
(
I
M)
(
i.e
.
,
p
er
s
o
n
al
m
o
tiv
atio
n
s
)
,
an
d
ex
tr
in
s
ic
m
o
tiv
atio
n
(
E
M)
with
r
esp
ec
t to
p
er
ce
iv
ed
u
s
ef
u
ln
ess
o
f
AI
f
r
o
m
th
e
p
er
s
p
ec
tiv
e
o
f
u
n
iv
er
s
ity
s
tu
d
en
ts
,
wh
o
ar
e
p
ar
tici
p
atin
g
in
u
n
iv
e
r
s
ity
ac
ad
em
ic
p
r
ac
tice
an
d
d
ev
e
lo
p
in
g
d
esig
n
an
d
m
u
ltime
d
ia
p
r
o
jects.
R
ec
en
t
ev
i
d
en
ce
s
h
o
ws
th
at
th
e
ac
ce
p
tan
ce
o
f
A
I
in
ed
u
ca
tio
n
is
s
tr
o
n
g
ly
s
h
ap
ed
b
y
attitu
d
e,
tr
u
s
t,
ea
s
e
o
f
u
s
e,
an
d
p
er
ce
i
v
e
d
v
alu
e
[
3
]
.
T
h
e
ad
o
p
tio
n
an
d
u
s
e
o
f
AI
(
USE)
-
b
ased
s
y
s
tem
s
is
as
s
o
ciate
d
with
p
er
ce
iv
ed
u
s
ef
u
ln
ess
an
d
p
er
ce
iv
ed
ea
s
e
o
f
u
s
e
o
f
s
tu
d
e
n
ts
[
4
]
.
Gen
er
ativ
e
ar
tific
ial
in
tellig
en
ce
(
Gen
AI
)
r
ef
e
r
s
to
a
d
v
an
ce
d
AI
m
o
d
els
ca
p
ab
le
o
f
p
r
o
d
u
cin
g
o
r
i
g
in
al
o
u
tp
u
ts
s
u
ch
as
im
ag
es,
v
id
e
o
s
,
tex
ts
,
an
d
d
esig
n
s
b
y
lear
n
in
g
p
atter
n
s
f
r
o
m
lar
g
e
d
atasets
,
th
er
eb
y
ex
p
an
d
in
g
cr
ea
tiv
e
an
d
ed
u
ca
tio
n
al
p
o
s
s
ib
ilit
ies.
R
ec
en
t
ev
id
en
ce
s
h
o
ws
th
at
Gen
AI
n
o
t o
n
l
y
en
h
a
n
ce
s
ef
f
icien
cy
b
u
t a
ls
o
f
o
s
ter
s
m
o
tiv
atio
n
a
n
d
cr
ea
tiv
ity
in
h
ig
h
er
ed
u
ca
tio
n
co
n
tex
ts
[
5
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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J
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&
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I
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2252
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Mo
tiva
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l in
tellig
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:
p
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a
mo
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…
(
Yg
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To
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Qu
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p
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)
545
W
ith
r
esp
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t
to
ed
u
ca
tio
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,
g
en
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v
is
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al
AI
to
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as
L
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AI
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Stab
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Dif
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Mid
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cr
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in
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v
ir
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n
m
en
ts
.
T
h
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is
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n
ew
f
o
r
m
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f
v
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cr
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-
g
en
er
ated
im
ag
e
r
y
t
o
o
ls
as
v
er
y
u
s
ef
u
l
to
o
ls
in
ea
r
ly
s
tag
es
o
f
d
esig
n
,
an
d
i
d
ea
s
f
o
r
cr
ea
tiv
ity
[
6
]
.
Hav
in
g
p
r
ev
i
o
u
s
tech
n
o
l
o
g
ical
ex
p
er
ien
ce
s
h
as
b
ee
n
p
o
s
itiv
ely
ass
o
ciate
d
with
s
tu
d
en
t
ac
ce
p
tan
ce
o
f
Gen
AI
to
o
ls
r
elev
an
t
to
cr
e
ativ
e
p
r
o
d
u
cts
an
d
lear
n
in
g
e
n
v
ir
o
n
m
en
ts
.
Stu
d
ie
s
o
n
d
esig
n
-
b
ased
lear
n
i
n
g
in
ar
t
an
d
d
esig
n
e
d
u
ca
tio
n
s
h
o
w
h
o
w
th
e
u
s
e
o
f
d
esig
n
-
ce
n
ter
ed
lear
n
in
g
tech
n
o
lo
g
ies en
h
an
ce
s
s
tu
d
e
n
ts
’
m
o
tiv
atio
n
,
cr
ea
tiv
ity
,
a
n
d
s
k
ills
[
7
]
.
Gen
AI
in
v
is
u
al
ed
u
ca
tio
n
h
as
im
p
licatio
n
s
f
o
r
s
tu
d
e
n
t
m
o
tiv
atio
n
.
Ma
k
in
g
c
o
m
p
l
ex
v
is
u
al
co
m
p
o
s
itio
n
s
,
o
r
v
id
eo
s
,
r
ap
i
d
ly
with
to
o
ls
s
u
ch
as
Hey
Gen
AI
,
o
r
R
u
n
way
ML
(
A
I
v
id
eo
g
en
er
at
o
r
)
,
in
cr
ea
s
es
ef
f
icac
y
p
e
r
ce
p
tio
n
s
,
s
elf
-
d
ir
ec
tio
n
,
an
d
IM
.
R
esear
ch
b
y
W
ei
et
a
l
.
[
8
]
co
m
p
le
x
p
r
o
b
lem
-
s
o
lv
in
g
,
an
d
ad
v
an
ce
d
v
is
u
al
s
k
ill
ac
q
u
is
itio
n
,
wh
ile
also
co
n
s
id
er
in
g
im
p
o
r
ta
n
t
eth
ical
ch
allen
g
es
s
u
ch
as
au
th
o
r
s
h
ip
,
tech
n
o
lo
g
y
d
e
p
en
d
e
n
ce
,
an
d
t
r
ain
in
g
d
ata
q
u
ality
,
p
ar
ticu
la
r
ly
in
a
d
o
m
ain
wh
e
r
e
th
e
v
is
u
al
is
s
o
ce
n
tr
al
to
m
ea
n
in
g
-
m
a
k
in
g
b
ac
k
ed
b
y
r
ec
en
t
f
in
d
in
g
s
s
h
o
win
g
th
at
Gen
AI
e
n
h
an
ce
s
cr
ea
tiv
ity
,
p
r
o
d
u
ctiv
ity
,
an
d
s
tu
d
en
t
m
o
tiv
atio
n
,
esp
ec
ially
wh
en
in
teg
r
ated
in
to
v
is
u
al
d
e
s
ig
n
p
r
o
ce
s
s
es
[
9
]
.
I
n
ed
u
ca
tio
n
,
Gen
AI
n
o
t
o
n
ly
p
er
s
o
n
alize
s
lear
n
in
g
a
n
d
p
r
o
v
id
es
ad
ap
tiv
e
f
ee
d
b
ac
k
,
b
u
t
a
ls
o
en
h
an
ce
s
s
tu
d
en
ts
’
m
o
tiv
a
tio
n
,
cr
ea
tiv
ity
,
a
n
d
p
r
o
d
u
ctiv
ity
b
y
en
ab
lin
g
r
ap
i
d
v
is
u
al
ex
p
er
im
e
n
tatio
n
an
d
p
r
o
b
lem
-
s
o
lv
in
g
in
d
esig
n
co
n
te
x
ts
[
1
0
]
.
Usi
n
g
to
o
ls
lik
e
Stab
le
Dif
f
u
s
io
n
o
r
Kaib
e
r
AI
lets
s
tu
d
en
ts
tr
y
o
u
t
d
if
f
er
e
n
t
v
is
u
al
s
ty
les
an
d
tu
r
n
th
eir
s
k
etch
es
o
r
wr
itten
id
ea
s
in
to
a
n
im
atio
n
s
.
T
h
is
h
elp
s
t
h
em
m
ak
e
s
ch
o
o
l
p
r
o
jects
m
o
r
e
en
g
a
g
in
g
an
d
f
ee
l
m
o
r
e
i
n
v
o
lv
e
d
a
n
d
co
n
f
i
d
en
t
i
n
th
e
cr
ea
tiv
e
p
r
o
ce
s
s
.
M
o
tiv
a
tio
n
an
d
th
e
s
en
s
e
o
f
b
e
n
ef
it
a
r
e
two
k
ey
f
ac
to
r
s
th
at
in
f
lu
en
ce
wh
eth
e
r
s
o
m
eo
n
e
d
ec
id
es
to
tr
y
o
u
t
n
ew
tec
h
to
o
ls
.
Acc
o
r
d
in
g
to
s
elf
-
d
et
er
m
in
atio
n
th
e
o
r
y
[
1
1
]
,
I
M
ass
o
ciate
d
with
th
e
i
n
tr
in
s
ic
d
esire
to
lear
n
,
an
d
E
M
ass
o
ciate
d
with
ex
ter
n
al
r
e
war
d
s
o
r
d
em
a
n
d
s
,
ar
e
b
o
th
d
eter
m
in
an
ts
in
th
e
ad
o
p
tio
n
o
f
to
o
ls
s
u
ch
as
v
is
u
al
Gen
AI
.
L
i
et
a
l
.
[
1
2
]
an
a
ly
ze
d
th
e
n
etwo
r
k
s
tr
u
ctu
r
e
o
f
s
tu
d
e
n
ts
’
m
o
tiv
at
io
n
to
lear
n
AI
,
s
h
o
win
g
th
at
s
o
m
e
f
o
r
m
s
o
f
r
eg
u
latio
n
a
r
e
m
o
r
e
ce
n
tr
al
th
an
o
th
er
s
in
s
u
s
tain
in
g
lear
n
in
g
an
d
ad
o
p
tio
n
.
R
ec
en
t
s
tu
d
ies
f
u
r
th
er
co
n
f
ir
m
t
h
at
m
o
tiv
atio
n
al
f
ac
to
r
s
s
ig
n
if
ican
tly
in
f
lu
e
n
ce
th
e
u
p
tak
e
o
f
Gen
AI
s
er
v
ices,
w
h
er
e
tr
u
s
t
a
n
d
ac
ce
p
tan
ce
at
titu
d
es
m
ed
iate
th
e
in
f
lu
en
ce
o
f
s
o
cial,
tech
n
ical,
an
d
p
er
s
o
n
al
m
o
tiv
ato
r
s
o
n
co
n
tin
u
o
u
s
u
s
e
in
ten
tio
n
[
1
3
]
.
I
n
v
is
u
al
d
esig
n
,
o
n
e
th
in
g
th
at
r
ea
lly
s
ee
m
s
to
d
r
iv
e
s
tu
d
en
t
m
o
tiv
atio
n
is
h
o
w
q
u
ick
ly
an
d
im
p
r
ess
iv
ely
th
ese
AI
to
o
ls
ca
n
g
en
er
ate
r
esu
lts
,
esp
ec
ially
wh
en
s
tu
d
en
ts
a
r
e
p
e
r
s
o
n
ally
in
v
ested
in
th
eir
p
r
o
jects.
So
m
e
r
ec
e
n
t
s
tu
d
ies
s
u
g
g
est
th
at
wh
en
s
tu
d
en
ts
g
e
n
u
in
ely
e
n
jo
y
wh
at
th
ey
ar
e
wo
r
k
in
g
o
n
,
th
eir
IM
in
cr
ea
s
e
s
.
On
th
e
o
t
h
er
s
id
e,
wh
en
th
ey
f
ee
l p
u
s
h
e
d
to
p
ic
k
u
p
n
ew
d
i
g
ital sk
ills
,
th
at’
s
m
o
r
e
co
n
n
ec
ted
to
e
x
ter
n
al
p
r
ess
u
r
e.
T
h
e
r
o
le
o
f
AI
in
cr
ea
tin
g
v
is
u
als
ca
n
f
u
lf
ill
b
o
th
d
im
en
s
io
n
s
:
it
p
r
o
v
id
es
f
r
ee
d
o
m
f
o
r
ar
tis
tic
ex
p
er
im
en
tatio
n
an
d
c
o
n
tr
ib
u
tes
to
th
e
d
em
an
d
s
o
f
to
d
ay
’
s
cr
ea
tiv
e
ec
o
n
o
m
y
.
Ho
wev
e
r
,
also
n
o
ted
wer
e
ch
allen
g
es
s
u
ch
as
tech
n
o
lo
g
i
ca
l
an
x
iety
o
r
co
n
ce
r
n
ab
o
u
t
b
ein
g
m
a
d
e
r
ed
u
n
d
an
t
b
y
alg
o
r
ith
m
s
,
wh
ich
co
u
ld
n
eg
ativ
ely
im
p
ac
t
p
er
ce
p
tio
n
s
o
f
th
e
b
e
n
ef
its
[
1
4
]
.
R
esear
ch
with
g
r
ap
h
ic
d
esig
n
an
d
v
is
u
al
co
m
m
u
n
icatio
n
s
tu
d
en
ts
f
o
u
n
d
t
h
at
s
tu
d
en
ts
with
h
ig
h
er
lev
els
o
f
IM
r
ep
o
r
te
d
m
o
r
e
b
en
ef
its
f
r
o
m
A
I
,
esp
e
cially
if
th
ey
co
u
ld
g
en
er
ate
a
co
n
cr
ete,
o
r
ig
in
al
v
is
u
al
p
r
o
d
u
ct.
T
h
e
y
ten
d
e
d
t
o
s
ee
AI
as
u
s
ef
u
l
to
o
ls
to
in
s
p
ir
e
an
d
g
e
n
er
ate
cr
ea
tiv
ity
,
in
f
o
r
m
th
eir
s
ty
le
,
an
d
ad
d
r
ess
co
m
p
lex
v
is
u
al
p
r
o
b
lem
s
,
wh
ich
im
p
r
o
v
e
d
th
eir
em
er
g
in
g
p
r
o
f
ess
io
n
al
id
e
n
tity
.
Similar
l
y
,
Kad
y
ir
o
v
et
a
l.
[
7
]
n
o
ted
t
h
at
in
ar
t
a
n
d
d
esig
n
e
d
u
ca
tio
n
,
IM
s
ig
n
if
ican
tly
b
o
o
s
ts
cr
ea
tiv
e
p
er
f
o
r
m
an
ce
,
r
ein
f
o
r
cin
g
o
u
r
f
in
d
i
n
g
ab
o
u
t
m
o
tiv
atio
n
’
s
ce
n
tr
al
r
o
le.
I
n
c
o
n
clu
s
io
n
,
Gen
AI
is
ch
an
g
in
g
th
e
ch
a
r
ac
ter
o
f
d
esig
n
to
o
ls
an
d
th
e
s
u
b
jectiv
e
d
is
p
o
s
itio
n
s
o
f
th
e
u
s
er
s
o
f
t
h
ese
to
o
ls
.
T
h
e
r
o
le
o
f
m
o
tiv
atio
n
a
n
d
b
en
e
f
its
f
o
r
u
n
iv
er
s
ity
s
tu
d
e
n
ts
in
d
icate
s
th
at
th
e
r
e
is
a
r
ec
o
n
f
ig
u
r
ati
o
n
o
f
c
r
ea
tiv
e
a
n
d
ed
u
ca
tio
n
al
p
r
o
ce
s
s
es in
wh
ich
th
e
v
is
u
al
an
d
tech
n
o
lo
g
ical
wer
e
in
d
ialo
g
u
e
f
o
r
th
e
f
ir
s
t ti
m
e
in
th
is
way
.
T
h
is
s
tu
d
y
e
x
p
lo
r
es
h
o
w
E
M,
I
M,
a
n
d
th
e
u
s
e
o
f
Gen
AI
(
AI
u
s
ag
e)
in
f
lu
e
n
ce
s
tu
d
e
n
ts
’
p
er
ce
iv
e
d
b
en
ef
its
(
B
E
N)
in
a
d
v
er
tis
in
g
an
d
m
u
ltime
d
ia
p
r
o
g
r
a
m
s
.
Gr
o
u
n
d
e
d
in
s
elf
-
d
eter
m
in
atio
n
t
h
eo
r
y
,
th
e
r
esear
ch
ex
am
in
es
b
o
t
h
d
i
r
ec
t
an
d
in
d
ir
ec
t
r
elatio
n
s
h
ip
s
am
o
n
g
th
es
e
v
ar
iab
les
with
in
a
cr
ea
tiv
e,
tech
n
o
lo
g
y
-
f
o
cu
s
ed
ed
u
ca
tio
n
al
co
n
tex
t.
I
t
o
f
f
er
s
a
n
o
v
el
co
n
tr
ib
u
tio
n
b
y
an
a
ly
zin
g
th
e
d
y
n
am
ics
o
f
m
o
ti
v
atio
n
an
d
Gen
AI
ad
o
p
tio
n
s
p
ec
if
ically
with
in
v
is
u
al
d
is
cip
lin
es
s
u
ch
as
g
r
ap
h
ic
d
esig
n
,
illu
s
tr
atio
n
,
an
d
m
u
ltime
d
ia
p
r
o
d
u
ctio
n
.
T
h
u
s
,
th
e
d
ir
ec
t
h
y
p
o
th
eses
ar
e
:
−
H1
:
EM
h
as a
d
ir
ec
t im
p
ac
t
o
n
th
e
B
E
N
p
er
ce
iv
ed
b
y
s
tu
d
e
n
ts
.
−
H2
:
EM
h
as a
p
o
s
itiv
e
an
d
s
ig
n
if
ican
t in
f
lu
e
n
ce
o
n
IM
.
−
H3
:
EM
h
as a
d
ir
ec
t,
p
o
s
itiv
e
an
d
s
ig
n
if
ican
t r
elatio
n
s
h
ip
wi
th
th
e
u
s
e
o
f
Gen
AI
.
−
H4
:
IM
h
as a
d
ir
ec
t a
n
d
s
ig
n
if
i
ca
n
t r
elatio
n
s
h
ip
with
p
e
r
ce
iv
ed
B
E
N
.
−
H5
:
IM
h
as a
d
ir
ec
t a
n
d
s
ig
n
if
i
ca
n
t r
elatio
n
s
h
ip
with
th
e
u
s
e
o
f
Gen
AI
.
−
H6
: T
h
e
u
s
e
o
f
Gen
AI
h
as a
d
ir
ec
t a
n
d
s
ig
n
if
ican
t
r
elatio
n
s
h
i
p
with
th
e
p
er
ce
i
v
ed
B
E
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
.
15
,
No
.
1
,
Feb
r
u
a
r
y
20
2
6
:
544
-
5
54
546
I
n
ad
d
itio
n
,
th
e
in
d
ir
ec
t
h
y
p
o
t
h
eses
ar
e
:
−
H7
:
EM
h
as a
p
o
s
itiv
e
an
d
s
ig
n
if
ican
t in
f
lu
e
n
ce
o
n
p
er
ce
iv
e
d
B
E
N
,
m
ed
iated
b
y
th
e
u
s
e
o
f
Gen
AI
.
−
H8
:
IM
h
as a
p
o
s
itiv
e
an
d
s
ig
n
if
ican
t in
f
lu
en
ce
o
n
p
er
ce
iv
ed
B
E
N
,
m
ed
iated
b
y
th
e
u
s
e
o
f
Gen
AI
.
2.
M
E
T
H
O
D
2
.
1
.
Resea
rc
h
des
ig
n
T
h
is
r
esear
ch
was
q
u
an
titativ
e
an
d
co
r
r
elatio
n
al
an
d
u
s
ed
a
cr
o
s
s
-
s
ec
tio
n
al
d
esig
n
.
T
h
e
aim
was
to
ex
p
lo
r
e
EM
,
IM
,
an
d
AI
b
ase
d
tech
n
o
lo
g
y
u
s
e,
wh
ich
af
f
ec
ts
p
er
ce
iv
ed
B
E
N
to
s
tu
d
en
ts
.
T
h
e
r
esear
ch
is
in
th
e
v
is
u
al
ar
ts
an
d
g
r
ap
h
ic
d
e
s
ig
n
d
o
m
ain
an
d
f
o
c
u
s
es
o
n
in
v
esti
g
atin
g
h
o
w
th
ese
tech
n
o
lo
g
ical
to
o
ls
h
av
e
b
eg
u
n
t
o
af
f
ec
t t
h
e
cr
ea
tiv
e
p
r
ac
tices o
f
d
esig
n
,
illu
s
tr
atio
n
a
n
d
m
u
ltime
d
ia
s
tu
d
e
n
ts
.
2
.
2
.
P
a
rt
icipa
nts a
nd
s
t
ud
y
g
ro
up
T
h
e
r
esear
ch
in
clu
d
e
d
2
0
3
s
tu
d
en
ts
,
with
6
6
%
r
ep
o
r
tin
g
t
o
b
e
m
ale,
an
d
3
4
%
b
ein
g
f
e
m
ale.
T
h
e
m
o
d
al
ag
e
was
2
0
(
3
3
%
o
f
p
ar
ticip
an
ts
)
,
an
d
it
d
ec
lin
ed
f
r
o
m
th
at
p
o
in
t,
with
th
e
n
ex
t
co
m
m
o
n
ag
es
b
ein
g
2
1
(
1
7
.
7
%)
an
d
1
8
(
1
7
.
2
%),
s
u
g
g
esti
n
g
th
at
s
tu
d
en
ts
wer
e
q
u
ite
y
o
u
n
g
,
an
d
b
etwe
en
th
e
a
g
es
o
f
1
8
-
2
1
y
ea
r
s
.
W
ith
r
eg
ar
d
s
to
th
e
ad
v
an
ce
m
en
t
in
th
eir
ca
r
ee
r
,
th
e
m
o
s
t
co
m
m
o
n
p
r
o
g
r
ess
io
n
was
i
n
ter
m
s
o
f
s
em
ester
en
r
o
lled
,
m
o
s
t
s
tu
d
en
ts
wer
e
in
th
e
7
th
s
em
ester
(
4
1
.
9
%),
3
r
d
s
em
ester
2
1
.
7
%,
an
d
9
th
s
em
ester
1
6
.
7
%
u
n
d
er
th
at
ass
u
m
p
tio
n
.
Mo
s
t
p
ar
ticip
an
ts
h
ad
ad
eq
u
ate
u
n
iv
er
s
ity
ex
p
er
ien
ce
,
m
ea
n
in
g
th
at
t
h
ey
h
ad
s
ee
n
s
o
m
e
d
ig
ital u
s
e
an
d
wer
e
o
n
cr
ea
tiv
e
p
r
o
jects r
elate
d
to
t
h
e
s
tu
d
y
t
h
em
e.
2
.
3
.
Da
t
a
c
o
llect
io
n
a
nd
re
s
po
nd
ent
s
A
q
u
esti
o
n
n
air
e
was
d
ev
elo
p
ed
b
y
ad
a
p
tin
g
item
s
f
r
o
m
two
p
r
e
v
io
u
s
s
tu
d
ies:
[
1
5
]
,
[
1
6
]
.
T
h
e
f
in
al
in
s
tr
u
m
en
t
co
m
p
r
is
ed
5
0
item
s
d
is
tr
ib
u
ted
ac
r
o
s
s
s
ev
en
c
o
n
s
tr
u
cts:
EM
(
7
)
,
IM
(
7
)
,
u
s
e
o
f
Gen
AI
(
7
)
,
AI
s
k
ills
(
4
)
,
AI
lim
itatio
n
s
(
3
)
,
AI
-
r
elate
d
an
x
iety
(
1
0
)
,
an
d
p
e
r
ce
iv
ed
B
E
N
(
1
2
)
.
T
h
e
q
u
esti
o
n
n
air
e
was
s
p
ec
if
ically
ad
ap
ted
to
th
e
co
n
tex
t
o
f
s
tu
d
e
n
ts
in
v
is
u
al
d
is
cip
lin
es,
p
ar
ticu
lar
ly
g
r
ap
h
ic
d
esig
n
,
illu
s
tr
atio
n
,
an
d
m
u
ltime
d
ia
p
r
o
d
u
ctio
n
,
i
n
o
r
d
er
to
ca
p
tu
r
e
m
o
tiv
ati
o
n
an
d
p
e
r
ce
p
tio
n
s
r
eg
ar
d
in
g
th
e
u
s
e
o
f
Ge
n
AI
in
th
eir
cr
ea
tiv
e
p
r
o
ce
s
s
es.
R
es
p
o
n
s
es
wer
e
o
b
tain
ed
u
s
in
g
a
f
o
u
r
-
lev
el
L
ik
er
t
s
ca
le,
wh
er
e
1
in
d
icate
d
to
tal
d
is
ag
r
ee
m
en
t a
n
d
4
r
e
p
r
esen
te
d
f
u
ll a
g
r
ee
m
en
t.
Data
co
llectio
n
to
o
k
p
lace
o
v
er
two
wee
k
s
,
co
o
r
d
in
atin
g
d
ates
with
th
e
in
s
tr
u
cto
r
s
o
f
th
e
in
v
o
lv
ed
p
r
o
g
r
a
m
s
.
E
ac
h
q
u
esti
o
n
n
air
e
to
o
k
ap
p
r
o
x
im
ately
1
5
t
o
2
0
m
i
n
u
tes
p
er
p
a
r
ticip
an
t.
T
h
e
in
s
tr
u
m
e
n
t
was
ad
m
in
is
ter
ed
o
n
lin
e
t
h
r
o
u
g
h
Mic
r
o
s
o
f
t
Fo
r
m
s
,
an
d
th
e
lin
k
alo
n
g
with
a
QR
co
d
e
was
s
en
t
to
in
s
tr
u
ct
o
r
s
f
r
o
m
d
if
f
er
en
t
s
em
ester
s
,
wh
o
t
h
en
s
h
ar
ed
it
with
th
eir
s
tu
d
e
n
ts
v
ia
th
e
QR
co
d
e.
T
h
e
q
u
esti
o
n
n
air
e
in
clu
d
ed
clea
r
in
s
tr
u
ctio
n
s
an
d
th
e
s
tu
d
y
’
s
o
b
jectiv
es
to
r
ed
u
ce
th
e
lik
el
ih
o
o
d
o
f
r
an
d
o
m
o
r
r
u
s
h
ed
r
esp
o
n
s
es.
I
n
to
tal,
2
3
8
co
m
p
leted
q
u
esti
o
n
n
air
es
wer
e
r
ec
eiv
ed
.
Ho
wev
er
,
d
u
r
in
g
th
e
p
r
elim
in
ar
y
an
aly
s
is
,
3
3
r
esp
o
n
s
es
wer
e
ex
clu
d
ed
d
u
e
to
lack
o
f
v
ar
ian
ce
o
r
ex
ce
s
s
iv
e
v
ar
ian
ce
in
r
esp
o
n
s
es,
an
d
2
wer
e
r
em
o
v
ed
f
o
r
b
ein
g
in
co
m
p
lete.
As
a
r
esu
lt,
2
0
3
v
alid
r
esp
o
n
s
es
wer
e
r
etain
ed
f
o
r
a
n
aly
s
is
.
Su
b
s
eq
u
e
n
tly
,
th
e
r
esu
lts
wer
e
d
o
wn
lo
ad
e
d
f
r
o
m
Mic
r
o
s
o
f
t
Fo
r
m
s
in
to
a
Mic
r
o
s
o
f
t
E
x
c
el
tem
p
late.
Su
b
s
eq
u
en
tly
,
th
e
d
ata
m
atr
i
x
was
p
r
o
ce
s
s
ed
in
th
e
SP
SS
2
5
.
0
s
o
f
twar
e
an
d
t
h
en
,
th
e
.
s
av
f
il
e
was
tr
an
s
f
er
r
ed
to
th
e
an
al
y
s
is
en
v
ir
o
n
m
en
t
t
o
ap
p
ly
th
e
s
tr
u
ctu
r
al
eq
u
atio
n
m
o
d
el
u
s
in
g
p
ar
tial
least
s
q
u
ar
es
s
tr
u
ctu
r
al
eq
u
atio
n
m
o
d
elin
g
(
PLS
-
SEM
)
.
R
esp
o
n
d
en
ts
h
av
e
b
ee
n
in
f
o
r
m
ed
ab
o
u
t th
e
p
u
r
p
o
s
e
o
f
th
e
s
tu
d
y
in
wh
ich
th
ey
will p
ar
ticip
ate,
in
d
icatin
g
th
at
th
e
p
r
iv
ac
y
o
f
t
h
eir
d
ata
a
n
d
th
e
co
n
f
id
e
n
tiality
o
f
th
e
i
n
f
o
r
m
atio
n
co
llected
will b
e
r
esp
ec
t
ed
.
2
.
4
.
Descript
iv
e
o
v
e
rv
iew
o
f
t
he
s
a
m
ple
Stu
d
en
ts
d
em
o
n
s
tr
ated
a
ce
r
tai
n
lev
el
o
f
k
n
o
wled
g
e
an
d
u
s
ag
e
o
f
Gen
AI
to
o
ls
in
b
o
th
th
eir
ac
ad
em
ic
p
r
ac
tices,
as
well
a
s
f
o
r
th
eir
m
o
r
e
cr
ea
tiv
e
en
d
ea
v
o
r
s
w
ith
wr
itin
g
,
im
ag
e
cr
ea
tio
n
,
an
d
v
id
eo
cr
ea
tio
n
.
T
ab
le
1
illu
s
tr
ates
th
e
k
n
o
wl
ed
g
e
lev
els
an
d
u
s
ag
e
o
f
v
ar
i
o
u
s
Gen
AI
to
o
ls
am
o
n
g
th
e
s
tu
d
en
ts
.
T
h
er
e
is
a
h
ig
h
f
r
eq
u
e
n
cy
o
f
ac
tiv
e
u
s
ag
e
f
o
r
to
o
ls
s
u
ch
as
C
h
atGPT
an
d
C
an
v
a
-
8
9
%
o
r
m
o
r
e
s
tu
d
e
n
ts
in
d
icate
th
at
th
e
y
ar
e
b
o
th
f
am
iliar
with
an
d
ac
tiv
ely
u
s
in
g
th
e
to
o
ls
.
T
h
is
s
u
g
g
ests
a
s
tr
o
n
g
p
r
esen
t
u
p
ta
k
e
o
f
th
ese
to
o
ls
in
s
tu
d
en
t
ac
ad
em
ic
wo
r
k
.
B
etwe
en
s
tu
d
en
ts
C
h
atG
PT
is
c
o
m
m
o
n
l
y
u
s
ed
to
g
en
er
ate
tex
t,
d
o
in
g
cr
ea
tiv
e
wr
itin
g
,
g
en
er
ate
b
r
ain
s
to
r
m
id
ea
s
,
an
d
s
u
g
g
est
way
s
to
i
m
p
r
o
v
e
wr
itten
ass
ig
n
m
en
ts
.
C
o
n
v
er
s
ely
,
C
an
v
a
ap
p
ea
r
s
to
b
e
an
in
d
is
p
en
s
ab
le
to
o
l
f
o
r
g
en
e
r
atin
g
im
a
g
es
an
d
m
ed
ia
i
n
g
r
a
p
h
ic
d
esig
n
f
o
r
s
tu
d
en
ts
en
g
ag
e
d
in
v
is
u
al
an
d
m
u
ltime
d
ia
co
n
tex
ts
.
Mo
s
t
o
f
th
e
o
th
er
AI
to
o
ls
in
clu
d
ed
ar
e
m
o
r
e
s
p
ec
ialized
p
latf
o
r
m
s
f
o
r
v
is
u
al
an
d
a
u
d
io
v
is
u
al
cr
ea
tio
n
,
f
o
r
ex
a
m
p
le,
Stab
le
Dif
f
u
s
io
n
,
Mid
jo
u
r
n
e
y
,
Hey
Gen
AI
,
an
d
L
eo
n
ar
d
o
AI
.
W
h
ile
s
tu
d
en
ts
u
s
ed
th
ese
p
latf
o
r
m
s
less
o
n
th
e
w
h
o
le
(
8
.
4
%
to
1
4
.
8
%
o
f
s
tu
d
e
n
ts
u
s
in
g
th
ese)
,
a
m
o
d
er
ate
n
u
m
b
er
o
f
s
tu
d
en
ts
k
n
o
w
o
f
th
ese
to
o
ls
(
1
5
%
to
2
8
.
6
%
o
f
s
tu
d
en
ts
)
.
T
h
is
h
in
t
’
s
th
at
u
s
ag
e
o
f
th
ese
to
o
ls
will
lik
ely
in
cr
ea
s
e
in
ter
m
s
o
f
cr
ea
tin
g
v
is
u
als
an
d
au
d
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e
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th
e
o
b
ject
b
u
t
ar
e
s
till
ex
p
lo
r
in
g
h
o
w
to
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s
e
it
e
f
f
ec
tiv
ely
.
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n
co
u
r
ag
in
g
th
e
d
is
tr
ib
u
tio
n
an
d
tr
ain
in
g
o
f
t
h
ese
tech
n
o
lo
g
ies
c
o
u
ld
cr
ea
te
a
s
ig
n
if
ican
t
b
o
o
s
t
in
c
r
ea
tiv
ity
,
in
n
o
v
atio
n
,
an
d
q
u
a
lity
o
f
ac
ad
em
ic
wo
r
k
an
d
m
u
ltime
d
ia
p
r
o
jects.
Fin
ally
,
k
n
o
wled
g
e
an
d
u
s
e
o
f
Gen
AI
wh
en
s
tu
d
en
ts
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e
ate
n
o
t
o
n
ly
im
p
r
o
v
es
ef
f
icie
n
cy
an
d
q
u
ality
f
o
r
s
tu
d
en
ts
to
p
u
r
s
u
e
cr
ea
tiv
e
w
r
itin
g
p
r
o
ce
s
s
es,
b
u
t
also
ch
a
n
g
es
th
e
way
a
n
d
wh
at
ca
n
b
e
p
r
o
d
u
ce
d
wh
en
s
tu
d
en
ts
g
en
er
ate
v
is
u
al
an
d
au
d
io
v
is
u
al
r
ep
r
esen
tatio
n
in
ac
ad
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co
n
tex
ts
,
r
ei
n
f
o
r
cin
g
im
p
o
r
tan
t
in
ter
d
is
cip
lin
ar
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k
ills
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ee
d
ed
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n
tem
p
o
r
ar
y
h
ig
h
er
ed
u
ca
tio
n
.
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ab
le
1
.
Kn
o
wled
g
e
an
d
USE
to
o
ls
f
o
r
ac
ad
e
m
ic
wo
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k
A
I
t
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I
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k
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t
I
h
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se
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k
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d
I
h
a
v
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se
d
n
P
e
r
c
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t
a
g
e
(
%)
n
P
e
r
c
e
n
t
a
g
e
(
%)
n
P
e
r
c
e
n
t
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(
%)
C
h
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t
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P
T
1
0
.
5
17
8
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4
1
8
5
9
1
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o
p
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t
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3
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G
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n
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5
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P
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1
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2
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9
40
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9
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t
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.
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3
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I
1
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15
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M
i
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o
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r
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1
3
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0
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1
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30
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.
8
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o
u
.
c
o
m
1
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3
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3
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o
n
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r
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o
A
I
1
4
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1
.
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31
1
5
.
3
27
1
3
.
3
3.
F
I
E
L
DWO
RK
AND
DA
T
A
ANALY
SI
S
T
h
e
r
esear
ch
er
s
co
n
d
u
cted
a
n
an
aly
s
is
u
s
in
g
th
e
PLS
-
SEM
ap
p
r
o
ac
h
u
s
in
g
Sm
ar
tPLS
s
o
f
twar
e.
B
ef
o
r
e
ev
alu
atin
g
th
e
s
tr
u
ct
u
r
al
r
elatio
n
s
h
ip
s
,
th
e
r
esear
ch
e
r
n
ee
d
ed
to
ev
alu
ate
th
e
m
ea
s
u
r
em
en
t
m
o
d
el
f
o
r
q
u
ality
an
d
d
e
p
en
d
a
b
ilit
y
o
f
th
e
co
n
s
tr
u
cts.
T
h
ese
ev
a
lu
atio
n
s
co
n
f
ir
m
th
at
th
e
it
em
s
u
s
ed
in
th
e
q
u
esti
o
n
n
air
e
wer
e
r
eliab
le
a
n
d
m
e
asu
r
ed
wh
at
th
e
y
we
r
e
in
ten
d
ed
to
m
ea
s
u
r
e
th
eo
r
etic
ally
[
1
7
]
.
T
o
attain
in
ter
n
al
co
n
s
is
ten
cy
o
r
d
ep
en
d
ab
ilit
y
f
o
r
a
c
o
n
s
tr
u
ct,
b
o
th
th
e
C
r
o
n
b
ac
h
’
s
alp
h
a
an
d
c
o
m
p
o
s
ite
r
eliab
ilit
y
v
alu
es
m
u
s
t
b
e
g
r
ea
ter
th
a
n
0
.
7
0
[
1
8
]
.
I
n
t
h
e
o
r
ig
in
al
an
al
y
s
is
o
f
th
e
d
ata,
th
er
e
wer
e
5
0
in
d
icato
r
s
f
o
r
7
laten
t
v
ar
iab
les.
Af
ter
r
u
n
n
in
g
a
co
n
f
ir
m
ato
r
y
f
ac
to
r
an
al
y
s
is
,
1
9
in
d
icato
r
s
wer
e
r
em
o
v
ed
f
o
r
n
o
t
r
ea
ch
i
n
g
th
e
m
in
im
u
m
r
e
q
u
ir
ed
v
alu
e.
As
a
r
esu
lt,
v
ar
iab
les
“
AI
s
k
il
ls
”
,
“
AI
l
im
itat
io
n
s
”
,
an
d
“
AI
a
n
x
iety
”
,
wer
e
r
em
o
v
e
d
f
r
o
m
th
e
f
in
al
m
o
d
el
f
o
r
m
eth
o
d
o
l
o
g
ical
r
e
aso
n
s
an
d
v
er
if
ied
with
s
tatis
tical
an
aly
s
is
in
d
icatin
g
th
ese
co
n
s
tr
u
cts
d
o
n
o
t
m
ee
t
th
e
n
ec
ess
ar
y
f
ac
to
r
lo
a
d
in
g
cr
iter
ia,
th
is
s
tu
d
y
was
a
b
le
to
p
r
esen
t
a
m
o
r
e
p
ar
s
im
o
n
io
u
s
m
o
d
el
wh
ile
s
tr
en
g
th
en
in
g
r
eliab
ilit
y
,
a
n
d
ad
d
ed
co
n
f
id
en
ce
th
at
th
e
o
th
er
co
n
s
tr
u
cts
wer
e
clo
s
ely
r
elate
d
.
Fin
ally
,
all
o
th
er
co
n
s
tr
u
cts
s
h
o
wed
a
C
r
o
n
b
ac
h
’
s
alp
h
a
an
d
co
m
p
o
s
ite
r
eliab
ilit
y
g
r
ea
ter
th
an
0
.
7
0
,
s
u
g
g
esti
n
g
a
n
ac
ce
p
tab
le
lev
el
o
f
in
ter
n
al
co
n
s
is
ten
cy
o
f
th
e
to
o
ls
u
s
ed
,
as sh
o
wn
in
T
ab
le
2
.
T
h
e
liter
atu
r
e
d
escr
ib
es th
at
an
av
er
ag
e
v
a
r
ian
ce
ex
tr
ac
ted
(
AVE
)
v
alu
e
o
v
er
0
.
5
0
in
d
ic
ates
m
o
r
e
th
an
5
0
%
o
f
v
ar
ia
n
ce
o
f
th
e
item
s
is
ac
co
u
n
ted
f
o
r
b
y
th
e
s
ep
ar
at
e
laten
t
co
n
s
tr
u
ct,
in
d
icatin
g
g
o
o
d
co
n
v
er
g
e
n
t
v
alid
ity
[
1
9
]
.
I
n
o
u
r
ca
s
e,
all
co
n
s
tr
u
cts
h
ad
an
AVE
v
alu
e
ab
o
v
e
0
.
6
1
0
.
T
h
e
i
n
d
icato
r
r
el
iab
ilit
y
r
ef
er
s
to
ea
ch
item
’
s
a
b
ilit
y
to
ac
co
u
n
t f
o
r
th
e
v
ar
ian
ce
o
f
th
e
c
o
n
s
tr
u
cts
to
wh
ich
t
h
ey
b
elo
n
g
.
Facto
r
lo
ad
in
g
s
ar
e
r
o
u
tin
ely
u
s
ed
as
an
in
d
icato
r
o
f
th
is
r
eliab
ilit
y
.
Hair
et
a
l.
[
2
0
]
s
h
o
ws f
ac
to
r
lo
ad
in
g
s
o
f
a
v
al
u
e
o
f
0
.
7
0
in
d
icate
s
an
item
is
r
eli
ab
le.
Dis
cr
im
in
an
t
v
alid
ity
was
ev
alu
ated
b
ased
o
n
g
u
id
elin
es
f
r
o
m
th
e
liter
atu
r
e,
wh
ich
s
tate
th
at
f
o
r
ea
ch
co
n
s
tr
u
ct
to
ac
h
iev
e
d
is
cr
im
in
an
t
v
alid
ity
.
T
h
e
p
u
r
p
o
s
e
o
f
th
is
ev
alu
atio
n
is
to
co
n
f
i
r
m
th
at
a
r
ef
lectiv
e
co
n
s
tr
u
ct
m
ain
tain
s
s
tr
o
n
g
er
lin
k
s
to
its
o
wn
in
d
icato
r
s
th
a
n
to
th
e
in
d
icato
r
s
o
f
an
y
o
th
er
co
n
s
tr
u
ct
with
in
th
e
PLS
r
o
u
te
m
o
d
el
[
2
0
]
.
T
h
e
h
eter
o
tr
ait
-
m
o
n
o
tr
ait
r
atio
(
HT
MT
)
v
alu
e
m
u
s
t
b
e
b
elo
w
th
e
th
r
esh
o
ld
o
f
0
.
9
[
2
1
]
.
I
n
o
u
r
s
tu
d
y
,
as
s
h
o
wn
i
n
T
ab
le
3
,
all
HT
MT
v
alu
es
a
r
e
b
elo
w
0
.
7
1
,
in
d
icatin
g
a
d
eq
u
ate
d
is
cr
im
in
atio
n
b
etwe
en
th
e
d
if
f
er
en
t la
ten
t c
o
n
s
tr
u
cts.
T
h
e
Fo
r
n
ell
-
L
a
r
ck
er
cr
iter
io
n
in
d
icate
s
th
at,
f
o
r
th
er
e
to
b
e
d
is
cr
im
in
an
t
v
alid
ity
,
th
e
s
q
u
a
r
e
r
o
o
t
o
f
th
e
AVE
o
f
ea
ch
co
n
s
tr
u
ct
m
u
s
t
o
v
er
co
m
e
th
e
co
r
r
elatio
n
s
th
at
th
is
co
n
s
tr
u
ct
m
ain
tain
s
with
th
e
o
th
er
s
,
th
u
s
s
h
o
win
g
th
at
it
is
ad
eq
u
ately
d
if
f
er
e
n
tiated
f
r
o
m
th
em
[
2
2
]
.
T
h
e
s
q
u
ar
e
r
o
o
t
o
f
th
e
AVE
s
,
wh
ich
ar
e
th
e
d
iag
o
n
al
elem
e
n
ts
o
f
th
e
tab
le
(
th
e
b
o
ld
v
alu
es),
in
d
icate
th
at
ea
ch
co
n
s
tr
u
ct
is
lar
g
er
th
an
t
h
e
co
r
r
elatio
n
with
th
e
o
th
er
co
n
s
tr
u
cts;
th
u
s
,
we
ca
n
co
n
clu
d
e
th
at
all
co
n
s
tr
u
cts
(
B
E
N
,
E
M,
I
M,
an
d
USE
)
ac
h
iev
ed
d
is
cr
im
in
an
t
v
alid
ity
.
T
h
is
m
e
an
s
th
at
all
co
n
s
tr
u
cts
ea
ch
m
e
asu
r
e
th
eir
o
wn
co
n
ce
p
t,
an
d
d
o
n
o
t o
v
er
lap
with
th
e
o
th
er
c
o
n
s
tr
u
cts
in
th
e
m
o
d
el.
An
o
th
er
cr
iter
io
n
is
to
r
e
v
iew
m
u
ltico
llin
ea
r
ity
,
wh
ic
h
o
cc
u
r
s
wh
en
two
o
r
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
15
,
No
.
1
,
Feb
r
u
a
r
y
20
2
6
:
544
-
5
54
548
m
o
r
e
i
n
d
ep
e
n
d
en
t
v
ar
ia
b
les
with
in
a
m
u
ltip
le
r
eg
r
ess
io
n
m
o
d
el
s
h
o
w
h
ig
h
co
r
r
elatio
n
s
wi
th
ea
ch
o
th
e
r
[
2
3
]
.
So
m
eth
in
g
th
at
in
d
icate
s
th
e
m
u
ltico
llin
ea
r
ity
o
f
th
e
v
ar
iab
les
is
th
e
v
ar
ian
ce
in
f
latio
n
f
ac
to
r
(
VI
F).
B
y
th
e
way
,
a
VI
F
th
at
is
g
r
ea
ter
th
a
n
1
0
in
d
icate
s
a
h
ig
h
lev
el
o
f
m
u
ltico
llin
ea
r
ity
,
wh
ile
a
VI
F
th
at
is
clo
s
er
to
1
in
d
icate
s
th
at
th
er
e
is
n
o
m
u
ltico
llin
ea
r
ity
.
I
n
th
is
s
tu
d
y
,
n
o
item
h
ad
a
VI
F th
at
was h
ig
h
er
th
an
2
.
7
ac
co
r
d
in
g
to
T
ab
le
2
; th
e
r
ef
o
r
e
,
we
ca
n
s
ay
th
at
th
e
m
u
ltico
llin
ea
r
ity
w
as n
o
t a
co
n
ce
r
n
in
t
h
e
m
o
d
el.
T
ab
le
2
.
E
x
ter
n
al
lo
a
d
s
an
d
in
d
icato
r
r
eliab
ilit
y
C
o
n
st
r
u
c
t
I
t
e
ms
F
a
c
t
o
r
l
o
a
d
i
n
g
V
I
F
AVE
C
r
o
n
b
a
c
h
a
l
p
h
a
B
EN
B
EN
1
0
.
7
6
9
1
.
8
7
1
0
.
6
1
0
0
.
8
9
2
B
EN
2
0
.
7
2
3
1
.
7
4
1
B
EN
3
0
.
8
2
7
2
.
4
4
2
B
EN
6
0
.
8
5
0
2
.
7
7
8
B
EN
7
0
.
8
2
9
2
.
4
7
8
B
EN
8
0
.
7
3
3
1
.
9
0
3
B
EN
9
0
.
7
2
4
1
.
6
8
2
EM
EM
3
1
0
.
8
2
6
2
.
3
0
9
0
.
6
6
6
0
.
9
0
2
EM
3
2
0
.
7
8
5
2
.
1
9
8
EM
3
3
0
.
8
6
6
2
.
8
3
2
EM
3
4
0
.
8
1
4
2
.
6
4
0
EM
3
5
0
.
8
1
5
2
.
6
2
2
EM
3
6
0
.
7
8
7
1
.
6
2
1
IM
I
M
2
4
0
.
7
2
5
1
.
6
3
5
0
.
6
1
2
0
.
8
4
1
I
M
2
5
0
.
7
3
2
1
.
6
7
6
I
M
2
7
0
.
8
1
1
1
.
8
5
3
I
M
2
8
0
.
8
2
7
2
.
0
4
5
U
S
E
U
S
E1
0
.
8
1
4
2
.
0
2
3
0
.
6
5
4
0
.
7
3
9
U
S
E2
0
.
8
4
9
1
.
4
3
0
U
S
E4
0
.
7
6
2
1
.
5
1
6
T
ab
le
3
.
HT
MT
m
atr
i
x
an
d
Fo
r
n
ell
-
L
ar
ck
er
cr
iter
io
n
C
o
n
st
r
u
c
t
B
EN
EM
IM
U
S
E
H
TM
T
mat
r
i
x
B
EN
EM
0
.
3
8
8
IM
0
.
5
8
6
0
.
4
2
1
U
S
E
0
.
7
1
7
0
.
4
3
0
0
.
4
5
4
F
o
r
n
e
l
l
-
L
a
r
c
k
e
r
c
r
i
t
e
r
i
o
n
B
EN
0
.
7
8
1
EM
0
.
3
8
2
0
.
8
1
6
IM
0
.
5
1
0
0
.
4
0
3
0
.
7
8
2
U
S
E
0
.
5
9
9
0
.
3
7
6
0
.
3
7
2
0
.
8
0
9
3
.
1
.
M
o
del
f
it
e
v
a
lua
t
io
n
T
h
e
s
tan
d
ar
d
ized
r
o
o
t
m
ea
n
s
q
u
ar
e
r
esid
u
al
(
SR
MR)
is
u
s
ed
to
co
m
p
ar
e
th
e
a
d
ju
s
ted
m
o
d
el
with
a
s
atu
r
ated
m
o
d
el,
s
h
o
win
g
h
o
w
d
if
f
er
e
n
t
th
ey
a
r
e.
Gen
er
a
lly
,
th
e
lo
wer
th
e
SR
MR
v
alu
e
th
e
b
etter
th
e
f
it.
Valu
es
b
elo
w
0
.
0
8
ar
e
r
eg
ar
d
ed
as
g
en
er
ally
ac
ce
p
tab
le
[
2
4
]
.
Fo
r
o
u
r
s
tu
d
y
,
th
e
SR
MR
v
alu
e
f
o
r
th
e
esti
m
ated
m
o
d
el
(
0
.
0
7
)
is
ac
tu
ally
v
er
y
clo
s
e
to
th
at
o
f
t
h
e
s
atu
r
ated
m
o
d
el.
T
h
e
p
r
o
p
o
s
ed
m
o
d
el
as
s
h
o
wn
in
Fig
u
r
e
1
was
b
u
ilt
to
e
x
am
i
n
e
th
e
r
elatio
n
s
h
ip
s
am
o
n
g
IM
,
EM
,
Gen
AI
u
s
e,
an
d
p
e
r
ce
iv
ed
B
E
N
am
o
n
g
s
tu
d
en
ts
en
r
o
lled
in
th
e
p
u
b
licity
an
d
m
u
ltime
d
ia
p
r
o
g
r
am
at
a
h
i
g
h
er
ed
u
ca
tio
n
in
s
titu
tio
n
.
T
h
e
p
r
o
p
o
s
ed
m
o
d
el
en
tails
f
o
u
r
laten
t
co
n
s
tr
u
cts,
ea
ch
o
f
wh
ich
is
ex
p
r
ess
ed
th
r
o
u
g
h
d
if
f
e
r
en
t
item
s
o
r
in
d
icato
r
s
r
ep
r
esen
tin
g
d
i
f
f
er
en
t
d
im
en
s
io
n
s
o
f
th
e
v
a
r
iab
les
u
n
d
er
s
t
u
d
y
:
I
M,
E
M,
Ge
n
AI
u
s
e
(
U
SE)
,
an
d
p
er
ce
i
v
ed
B
E
N
o
f
AI
u
s
e.
Gen
AI
u
s
e
is
co
n
s
id
er
ed
to
b
e
th
e
m
an
y
to
o
ls
s
u
ch
as
C
h
atG
PT,
Sta
b
le
Dif
f
u
s
io
n
,
an
d
Hey
Gen
AI
th
at
s
tu
d
en
ts
u
s
e
t
o
g
en
er
ate
c
r
ea
tiv
e
wr
itin
g
,
im
ag
es,
v
id
eo
s
,
an
d
m
u
ltime
d
ia
co
n
ten
t.
T
h
e
an
aly
s
is
was
co
m
p
leted
u
s
in
g
b
o
o
ts
tr
ap
p
in
g
(
5
,
0
0
0
s
am
p
les)
to
en
s
u
r
e
r
esu
lts
wo
u
ld
h
o
ld
u
p
to
th
e
s
tatis
tical
r
ig
o
r
o
f
b
o
o
ts
tr
ap
p
in
g
.
T
o
ass
ess
th
e
p
r
ed
icti
v
e
ca
p
ab
ilit
ies
o
f
th
e
r
esear
ch
m
o
d
el
we
u
s
e
th
e
co
ef
f
icien
t
o
f
d
eter
m
in
atio
n
(
R
²)
.
W
ith
r
eg
a
r
d
to
R
²
an
d
ad
ju
s
ted
R
²,
th
e
r
esear
ch
m
o
d
el
d
em
o
n
s
tr
ates
p
r
ed
ictiv
e
r
elev
a
n
ce
,
as d
is
cu
s
s
ed
:
−
I
M:
th
is
co
n
s
tr
u
ct
is
ch
ar
ac
ter
ized
as
s
tu
d
en
ts
’
IM
to
u
s
e
AI
in
an
ac
ad
em
ic
co
n
tex
t
wh
ic
h
tr
an
s
lates
in
to
s
tu
d
en
ts
’
in
ter
est,
s
atis
f
ac
tio
n
an
d
ac
co
m
p
lis
h
m
en
t w
ith
th
e
t
ec
h
n
o
lo
g
y
.
−
E
M:
th
is
co
n
s
tr
u
ct
r
ef
er
s
to
s
t
u
d
en
ts
’
m
o
tiv
atio
n
s
to
u
s
e
AI
wh
ich
em
an
ate
f
r
o
m
e
x
tr
in
s
ic
s
o
u
r
ce
s
s
u
ch
as
ac
ad
em
ic
r
ewa
r
d
s
,
s
o
cial
r
ec
o
g
n
itio
n
,
a
n
d
en
v
ir
o
n
m
en
tal
p
r
ess
u
r
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
Mo
tiva
tio
n
a
n
d
g
en
era
tive
a
r
t
ificia
l in
tellig
en
ce
:
p
erceive
d
b
en
efits
a
mo
n
g
…
(
Yg
n
a
cio
To
ma
ylla
-
Qu
is
p
e
)
549
−
USE:
th
is
co
n
s
tr
u
ct
m
ea
s
u
r
e
d
s
tu
d
en
ts
co
n
tin
u
ed
h
a
b
itu
a
l
an
d
ef
f
ec
tiv
e
USE
f
o
r
ac
a
d
em
ic
p
r
ac
tice.
As
n
o
ted
,
u
s
e
p
r
im
ar
ily
r
ef
e
r
s
to
u
s
in
g
Gen
AI
to
o
ls
(
e.
g
.
,
C
h
atGPT
,
Stab
le
Dif
f
u
s
io
n
,
Mid
jo
u
r
n
ey
,
Hey
Gen
AI
)
u
s
ed
f
o
r
p
er
f
o
r
m
in
g
task
s
in
clu
d
in
g
c
r
ea
tiv
e
wr
itin
g
,
v
is
u
al
d
esig
n
,
im
ag
e
g
en
er
atio
n
,
a
n
d
v
id
eo
p
r
o
d
u
ctio
n
in
ac
a
d
em
ic
an
d
m
u
ltime
d
ia
c
o
n
tex
ts
.
−
B
E
N:
t
h
is
co
n
s
tr
u
ct
r
e
f
er
s
to
t
h
e
p
o
s
itiv
e
r
esu
lts
o
n
e
co
u
ld
e
x
p
ec
t
f
r
o
m
th
e
USE
wh
en
v
ie
wed
th
r
o
u
g
h
th
e
len
s
o
f
s
tu
d
en
ts
’
ac
ad
em
ic
p
er
f
o
r
m
an
ce
,
ef
f
icien
c
y
o
f
task
c
o
m
p
letio
n
a
n
d
en
h
an
ce
d
lear
n
in
g
.
Fig
u
r
e
1
.
Pro
p
o
s
ed
m
o
d
el
T
h
e
m
o
d
el
p
r
o
p
o
s
es
th
at
E
M
h
as
a
p
o
s
itiv
e
ef
f
ec
t
o
n
I
M;
t
h
is
s
u
g
g
ests
th
at
ex
ter
n
al
s
tim
u
lu
s
m
ay
p
r
o
m
o
te
p
er
s
o
n
al
ag
en
c
y
r
e
g
ar
d
in
g
AI
u
s
e.
B
o
th
I
M
a
n
d
E
M
a
r
e
p
r
ed
icto
r
s
o
f
U
SE,
wh
ich
co
n
n
ec
ts
m
o
tiv
atio
n
s
an
d
s
tu
d
en
ts
’
wil
lin
g
n
ess
to
u
tili
ze
AI
f
o
r
th
ei
r
wo
r
k
.
USE
also
p
r
ed
icts
B
E
N,
wh
ich
s
u
g
g
ests
th
at
in
cr
ea
s
ed
AI
u
s
e
lead
s
to
B
E
N
.
I
M
also
h
as
a
d
ir
ec
t
e
f
f
ec
t
o
n
B
E
N.
Fro
m
th
is
m
o
d
el
it
is
also
s
u
g
g
ested
th
at
s
tu
d
en
ts
with
s
tr
o
n
g
er
p
e
r
s
o
n
al
m
o
tiv
atio
n
co
n
s
id
er
th
e
B
E
N
th
at
co
m
e
f
r
o
m
AI
h
a
v
in
g
m
o
r
e
p
o
s
itiv
e
ex
p
er
ien
ce
s
.
USE
also
m
ed
iates
th
e
ef
f
ec
ts
in
th
is
m
o
d
el
p
r
o
v
id
in
g
f
u
r
th
e
r
u
n
d
er
s
tan
d
i
n
g
o
f
h
o
w
m
o
tiv
atio
n
s
ca
n
lead
to
p
o
s
itiv
e
ex
p
er
ien
ce
s
w
ith
AI
.
T
h
e
u
s
e
o
f
Ge
n
AI
tech
n
o
lo
g
y
to
o
ls
as
ce
n
tr
al
to
o
u
r
m
o
d
el
’
s
co
n
ce
p
t
o
f
USE,
n
o
t
ju
s
t
tech
n
o
lo
g
y
to
o
l
s
,
em
p
h
asizes
th
eir
d
is
tin
ctiv
e
r
o
le
as
f
ac
ilit
ato
r
s
o
f
c
r
ea
tiv
ity
an
d
ex
p
r
ess
io
n
in
s
tu
d
y
an
d
as
ex
p
r
ess
io
n
s
o
f
cr
ea
tiv
ity
in
ac
a
d
em
ic
an
d
a
r
tis
tic
p
r
o
d
u
ctio
n
.
I
t
is
c
h
o
s
en
to
e
x
p
lo
r
e
th
ese
r
elatio
n
s
h
ip
s
an
d
to
u
n
d
er
s
tan
d
th
em
m
o
r
e
d
ee
p
l
y
with
s
tr
u
ctu
r
al
eq
u
atio
n
m
o
d
ellin
g
(
SE
M)
with
Sm
ar
tPLS
p
r
o
v
id
e
d
th
e
m
o
s
t
r
ele
v
an
t
way
to
g
et
in
s
ig
h
ts
in
to
h
o
w
to
b
u
ild
p
e
d
ag
o
g
ically
s
o
u
n
d
s
tr
ateg
ies
in
ed
u
ca
tio
n
al
d
esig
n
to
f
ac
ilit
ate
ef
f
ec
tiv
e
USE
.
3
.
2
.
Dire
ct
e
f
f
ec
t
s
T
h
e
an
aly
s
is
was
ca
r
r
ied
o
u
t
with
b
o
o
ts
tr
ap
p
in
g
,
5
,
0
0
0
s
am
p
les,
to
en
s
u
r
e
th
e
v
alid
ity
o
f
r
esu
lts
,
as
s
ee
n
in
Fig
u
r
e
2
.
T
h
e
c
o
ef
f
ici
en
t
o
f
d
ete
r
m
in
atio
n
(
R
²)
was
u
s
ed
to
ass
ess
th
e
s
tr
u
ctu
r
al
m
o
d
el
’
s
p
r
e
d
ictiv
e
p
o
wer
.
T
h
e
m
o
d
el
ex
h
i
b
its
p
r
ed
ictiv
e
v
alid
ity
,
a
n
d
th
e
in
ter
p
r
etatio
n
o
f
th
e
R
²
v
alu
es,
as
well
as
th
e
ad
ju
s
ted
R
²
v
alu
es,
is
s
h
o
wn
.
T
h
e
v
al
u
e
o
f
R
²
s
h
o
ws
h
o
w
m
u
ch
o
f
th
e
v
ar
iatio
n
in
th
e
d
ep
en
d
en
t
v
ar
iab
les
(
USE,
B
E
N,
an
d
I
M)
is
ex
p
lain
e
d
b
y
th
e
m
o
d
el
as a
wh
o
le:
−
USE:
th
e
m
o
d
el
ca
p
tu
r
ed
1
9
.
9
%
o
f
th
e
v
ar
ian
ce
i
n
th
e
b
e
h
av
io
r
al
o
u
tco
m
e
-
p
ar
ticu
lar
ly
th
at
o
f
Gen
AI
to
o
ls
f
o
r
ac
ad
e
m
ic
wr
itin
g
,
d
e
s
ig
n
,
an
d
m
u
ltime
d
ia
co
n
te
n
t
cr
ea
tio
n
.
−
B
E
N:
th
e
m
o
d
el
p
ick
ed
u
p
o
n
4
6
%
o
f
th
e
v
ar
ian
ce
in
p
e
r
ce
iv
ed
B
E
N
to
ad
o
p
tio
n
f
o
r
Gen
AI
tech
n
o
lo
g
ies,
s
u
ch
as in
cr
ea
s
e
p
r
o
d
u
ctiv
ity
a
n
d
cr
ea
tiv
ity
to
n
am
e
a
f
ew.
−
I
M:
th
e
m
o
d
el
ca
p
tu
r
ed
1
6
.
2
%
o
f
th
e
v
ar
ian
ce
in
IM
.
Fo
llo
win
g
with
th
e
ad
ju
s
ted
R
²
v
alu
es
,
b
ec
au
s
e
th
ese
n
u
m
b
er
s
ar
e
ad
ju
s
ted
f
o
r
th
e
n
u
m
b
er
o
f
p
r
ed
icto
r
s
in
th
e
m
o
d
el
,
th
e
y
p
r
o
v
id
e
a
m
o
r
e
r
eliab
le
m
ea
s
u
r
e
th
an
R
²:
U
SE
(
19.
1
%
)
;
B
EN
(
45.2
%
)
;
I
M
(
15.
8%
)
.
EX
T
R
I
NS
I
C
M
OT
I
VA
T
I
ON
IN
T
R
I
NS
I
C
M
OT
I
VA
T
I
ON
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
15
,
No
.
1
,
Feb
r
u
a
r
y
20
2
6
:
544
-
5
54
550
Fig
u
r
e
2
.
Path
c
o
ef
f
icien
ts
T
h
e
r
esu
lts
f
r
o
m
p
ath
a
n
aly
s
is
,
as
s
h
o
wn
in
T
ab
le
4
,
d
eter
m
in
e
s
tu
d
en
ts
u
s
in
g
AI
m
o
r
e
o
f
ten
r
ep
o
r
t
g
r
ea
ter
B
E
N
.
E
n
g
ag
em
e
n
t
f
r
e
q
u
en
cy
(
USE)
s
h
o
ws
s
tr
o
n
g
p
o
s
itiv
e
in
f
lu
en
ce
o
n
p
e
r
ce
iv
ed
b
en
ef
it
(
β=0
.
4
5
1
,
t
=
6
.
8
4
1
,
p
<
0
.
0
0
1
)
.
Stu
d
e
n
ts
d
r
iv
en
b
y
p
e
r
s
o
n
al
in
ter
est
(
I
M)
also
p
er
ce
iv
e
m
o
r
e
B
E
N
.
IM
d
ir
ec
tly
in
cr
ea
s
es
p
er
ce
iv
ed
b
e
n
ef
it
(
β
=
0
.
3
0
6
,
t
=
3
.
9
0
6
,
p
<
0
.
0
0
1
)
.
E
M
d
o
es
n
o
t
af
f
ec
t
p
er
ce
iv
e
d
b
en
e
f
it.
T
h
e
r
elatio
n
s
h
ip
b
etwe
en
E
M
an
d
b
en
ef
it is
n
o
t sig
n
if
ican
t (
β
=
0
.
0
9
0
,
t
=
1
.
5
8
3
,
p
=
0
.
1
1
3
)
.
T
ab
le
4
.
Hy
p
o
th
esis
test
in
g
r
esu
lts
(
PLS
-
SEM
)
H
P
a
t
h
s
C
o
e
f
f
i
c
i
e
n
t
s
(
β
)
S
t
a
n
d
a
r
d
d
e
v
i
a
t
i
o
n
(
S
TD
EV
)
T
v
a
l
u
e
s
P
v
a
l
u
e
s
R
e
s
u
l
t
D
i
r
e
c
t
H1
EM
-
>
B
EN
0
.
0
9
0
0
.
0
5
7
1
.
5
8
3
0
.
1
1
3
N
o
t
s
u
p
p
o
r
t
e
d
H2
EM
-
>
I
M
0
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4
0
3
0
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0
7
3
5
.
4
9
5
0
.
0
0
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u
p
p
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r
t
e
d
H3
EM
-
>
U
S
E
0
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2
7
0
0
.
0
6
1
4
.
4
2
6
0
.
0
0
0
S
u
p
p
o
r
t
e
d
H4
IM
-
>
B
EN
0
.
3
0
6
0
.
0
7
8
3
.
9
0
6
0
.
0
0
0
S
u
p
p
o
r
t
e
d
H5
IM
-
>
U
S
E
0
.
2
6
3
0
.
0
7
7
3
.
4
0
6
0
.
0
0
1
S
u
p
p
o
r
t
e
d
H6
U
S
E
-
>
B
EN
0
.
4
5
1
0
.
0
6
9
6
.
5
6
9
0
.
0
0
0
S
u
p
p
o
r
t
e
d
I
n
d
i
r
e
c
t
H7
EM
-
>
U
S
E
-
>
B
EN
0
.
1
2
2
0
.
0
3
5
3
.
5
2
8
0
.
0
0
0
S
u
p
p
o
r
t
e
d
H8
IM
-
>
U
S
E
-
>
B
EN
0
.
1
1
9
0
.
0
3
7
3
.
2
3
5
0
.
0
0
1
S
u
p
p
o
r
t
e
d
3
.
3
.
I
nd
irec
t
ef
f
ec
t
s
T
h
e
f
in
d
in
g
s
p
r
o
v
id
e
ev
id
e
n
c
e
o
f
s
ig
n
if
ican
t
in
d
ir
ec
t
e
f
f
ec
t
s
th
at
f
u
r
th
er
illu
m
in
ate
th
e
li
n
k
b
etwe
en
m
o
tiv
atio
n
s
an
d
p
er
ce
iv
e
d
B
E
N
o
f
u
s
in
g
AI
in
th
e
d
o
m
ain
o
f
v
is
u
al
an
d
m
u
ltime
d
i
a
d
esig
n
.
E
M
h
as
a
p
o
s
itiv
e
an
d
s
ig
n
if
ican
t
in
d
i
r
ec
t
ef
f
ec
t
o
n
p
e
r
ce
iv
ed
B
E
N
(β
=
0
.
1
2
2
)
th
r
o
u
g
h
th
e
u
s
e
o
f
Gen
AI
to
o
ls
(
USE
)
as
an
o
u
tc
o
m
e
o
f
E
M.
T
h
is
m
ea
n
s
h
ig
h
er
E
M,
n
o
t o
n
ly
en
h
an
ce
s
th
e
lev
el
o
f
en
g
a
g
em
en
t
an
d
USE
b
u
t
it
also
r
ef
lects
in
in
cr
ea
s
ed
p
er
ce
i
v
ed
b
e
n
ef
it
in
th
is
ar
ea
,
wh
i
ch
is
d
em
o
n
s
tr
ated
b
y
s
tu
d
en
ts
u
s
in
g
Gen
AI
tech
n
o
lo
g
ies
i
n
th
ei
r
ac
a
d
em
i
c
wr
itin
g
,
v
is
u
al
p
r
esen
tatio
n
cr
ea
tio
n
,
an
d
m
u
ltime
d
ia
p
r
o
d
u
ctio
n
.
Fin
d
in
g
s
s
u
ch
as
th
ese
s
u
p
p
o
r
t
th
e
v
iew
o
f
E
M
in
th
e
e
f
f
ec
tiv
e
a
d
o
p
tio
n
o
f
Gen
AI
allo
win
g
s
tu
d
en
ts
to
en
h
an
ce
t
h
eir
p
er
s
o
n
al
lear
n
in
g
an
d
p
e
r
ce
p
tio
n
o
f
u
s
ef
u
ln
ess
o
f
Gen
AI
with
in
th
e
cr
ea
tiv
e
an
d
ac
ad
em
ic
co
n
tex
t.
I
n
ad
d
itio
n
,
I
M
h
as
a
p
o
s
itiv
e
an
d
s
ig
n
if
ican
t
in
d
ir
ec
t
ef
f
e
ct
o
n
B
E
N
(
β
=
0
.
1
1
9
)
th
r
o
u
g
h
USE
AI
.
Stu
d
e
n
ts
with
h
ig
h
I
M,
ar
e
lik
ely
to
u
s
e
Gen
AI
as
in
ten
d
ed
,
m
o
r
e
f
r
eq
u
e
n
tly
an
d
with
m
o
r
e
m
ea
n
in
g
,
p
r
o
d
u
cin
g
g
r
ea
ter
p
er
ce
i
v
ed
B
E
N
in
ter
m
s
o
f
ac
ad
em
ic
an
d
cr
ea
tiv
e
u
s
ag
e.
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
Mo
tiva
tio
n
a
n
d
g
en
era
tive
a
r
t
ificia
l in
tellig
en
ce
:
p
erceive
d
b
en
efits
a
mo
n
g
…
(
Yg
n
a
cio
To
ma
ylla
-
Qu
is
p
e
)
551
T
h
is
s
u
p
p
o
r
ts
th
e
p
er
s
p
ec
tiv
e
o
f
I
M
an
d
E
M
as
b
o
th
in
d
is
p
en
s
ab
le
f
o
r
o
b
tain
in
g
m
o
r
e
ed
u
ca
tio
n
a
l
an
d
cr
ea
tiv
e
B
E
N
f
r
o
m
Gen
AI
to
o
ls
u
s
ed
in
ed
u
ca
tio
n
al
an
d
p
r
o
f
ess
io
n
al
co
n
te
x
ts
.
T
h
is
in
ter
p
r
etatio
n
r
ein
f
o
r
ce
s
th
at
I
M
an
d
E
M
a
r
e
b
o
th
cr
itically
im
p
o
r
tan
t
i
n
d
ir
ec
t
an
tece
d
en
ts
o
f
B
E
N,
an
d
b
o
th
f
o
r
m
s
o
f
m
o
tiv
atio
n
ar
e
im
p
o
r
ta
n
t
to
e
n
s
u
r
e
th
e
m
a
x
im
u
m
e
d
u
ca
tio
n
al
an
d
p
r
o
f
ess
io
n
al
b
e
n
ef
it
i
s
o
b
tain
ed
f
r
o
m
th
e
u
s
e
o
f
Gen
AI
.
Fin
ally
,
th
e
f
-
s
q
u
ar
ed
ef
f
ec
t
s
izes
[
2
5
]
wer
e
r
ep
o
r
ted
,
as
:
USE→BEN:
f
²
=
0
.
3
0
2
(
m
o
d
er
ate
ef
f
ec
t)
,
E
M→U
SE:
f
²
=
0
.
0
7
6
(
s
m
all
ef
f
ec
t)
,
E
M→BEN:
f
²
=
0
.
0
1
2
(
v
er
y
s
m
all/n
o
t
s
ig
n
if
ican
t)
,
E
M→I
M:
f²
=
0
.
1
9
4
(
m
o
d
er
ate
ef
f
ec
t)
,
I
M→U
SE:
f
²
=
0
.
0
7
2
(
s
m
all/n
o
t
s
ig
n
if
ican
t)
,
a
n
d
I
M→BEN:
f
²
=
0
.
1
3
5
(
s
m
all/n
o
t
s
ig
n
if
ican
t)
.
4.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
Af
ter
th
e
SEM
an
aly
s
is
,
we
a
p
p
r
ec
iate
th
at
th
e
r
e
ar
e
s
o
m
e
th
eo
r
etica
l
an
d
p
r
ac
tical
im
p
li
ca
tio
n
s
o
n
m
o
tiv
atio
n
,
th
e
USE
an
d
th
e
p
er
ce
iv
ed
b
e
n
ef
its
am
o
n
g
s
tu
d
e
n
ts
in
ad
v
er
tis
in
g
an
d
m
u
ltime
d
ia
p
r
o
g
r
am
s
.
4
.
1
.
T
heo
re
t
ica
l
i
m
pli
ca
t
io
ns
T
h
e
r
esu
lts
h
ig
h
lig
h
t
th
e
ce
n
tr
al
r
o
le
o
f
I
M
in
ex
p
lain
in
g
b
o
th
th
e
ad
o
p
tio
n
o
f
Gen
AI
to
o
l
s
an
d
th
e
p
er
ce
p
tio
n
o
f
b
e
n
ef
its
.
Stu
d
e
n
ts
with
g
en
u
in
e
in
ter
est
r
ep
o
r
ted
g
r
ea
te
r
en
g
a
g
em
en
t
an
d
h
ig
h
er
p
er
ce
iv
e
d
ed
u
ca
tio
n
al
v
alu
e,
wh
ich
is
co
n
s
is
ten
t
with
Z
h
o
u
an
d
L
i
[
1
]
,
wh
o
f
o
u
n
d
t
h
at
m
o
tiv
atio
n
r
o
o
ted
i
n
s
elf
-
d
eter
m
in
atio
n
s
ig
n
if
ican
t
ly
d
r
iv
es
lear
n
in
g
o
u
tco
m
es
wh
en
m
e
d
iated
b
y
AI
.
Simil
ar
ly
,
o
u
r
f
in
d
i
n
g
s
r
ein
f
o
r
ce
o
b
s
er
v
atio
n
s
b
y
Kad
y
ir
o
v
et
a
l
.
[
7
]
,
wh
er
e
s
tu
d
en
t
s
p
er
ce
iv
ed
AI
as
u
s
ef
u
l
wh
e
n
th
ey
co
u
ld
lin
k
it
to
m
ea
n
in
g
f
u
l
an
d
co
m
p
lex
ta
s
k
s
.
I
n
c
o
n
tr
ast,
E
M
s
h
o
wed
n
o
s
ig
n
if
ica
n
t
d
ir
ec
t
ef
f
ec
t
o
n
p
er
ce
iv
e
d
b
e
n
ef
its
,
alth
o
u
g
h
it
p
o
s
itiv
ely
in
f
l
u
en
c
ed
AI
u
s
ag
e
an
d
s
u
p
p
o
r
ted
I
M
.
T
h
is
ap
p
ar
en
t
co
n
t
r
ad
ictio
n
i
s
r
ec
o
n
ciled
b
y
th
e
m
ed
iatio
n
a
n
aly
s
is
,
wh
ich
r
ev
ea
led
th
at
E
M
in
d
ir
ec
tly
c
o
n
tr
ib
u
ted
to
p
e
r
ce
iv
ed
b
en
ef
its
th
r
o
u
g
h
its
in
f
l
u
en
ce
o
n
AI
u
s
ag
e
a
n
d
,
to
a
less
er
e
x
ten
t,
AI
-
r
elate
d
a
n
x
iety
.
I
n
o
t
h
er
wo
r
d
s
,
e
x
ter
n
al
m
o
tiv
es
d
i
d
n
o
t
tr
an
s
late
in
to
b
en
ef
its
o
n
th
eir
o
wn
b
u
t
b
ec
am
e
ef
f
ec
tiv
e
o
n
ce
tr
an
s
f
o
r
m
ed
in
t
o
ac
tiv
e
en
g
a
g
em
en
t
with
AI
to
o
ls
o
r
m
o
d
er
ated
b
y
p
s
y
c
h
o
lo
g
ical
f
ac
to
r
s
.
T
h
is
p
ar
tially
d
if
f
er
s
f
r
o
m
So
v
a
et
a
l
.
[
2
]
wh
o
f
o
u
n
d
th
at
f
ac
to
r
s
lik
e
p
er
ce
iv
ed
u
s
ef
u
ln
ess
,
p
o
s
itiv
e
attitu
d
e,
an
d
tr
ain
in
g
s
ig
n
if
ican
tly
in
f
lu
en
ce
AI
ad
o
p
tio
n
am
o
n
g
e
co
n
o
m
ics
s
tu
d
en
ts
in
h
ig
h
er
ed
u
ca
tio
n
.
Ou
r
r
esu
lts
s
u
g
g
est
th
at
e
x
ter
n
al
p
r
ess
u
r
es
alo
n
e
ar
e
in
s
u
f
f
icien
t
u
n
less
tr
an
s
f
o
r
m
ed
i
n
to
in
tr
in
s
ic
in
t
er
est,
wh
ich
alig
n
s
with
th
e
b
alan
ce
d
v
iew
p
r
esen
ted
b
y
B
ai
an
d
W
an
g
[
5
]
,
wh
o
s
e
s
h
o
wed
th
at
b
o
th
in
ter
ac
tio
n
q
u
ality
an
d
o
u
tp
u
t
q
u
a
lity
o
f
Gen
AI
t
o
o
ls
s
ig
n
if
ica
n
tly
b
o
o
s
t
lear
n
i
n
g
m
o
tiv
atio
n
an
d
cr
ea
tiv
e
s
elf
-
e
f
f
icac
y
,
wh
ich
in
tu
r
n
m
ed
iate
l
ea
r
n
in
g
o
u
tco
m
es.
Stu
d
en
ts
r
ep
o
r
te
d
th
at
s
u
p
p
o
r
tiv
e
en
v
ir
o
n
m
e
n
ts
in
cr
ea
s
ed
th
eir
willin
g
n
ess
to
ad
o
p
t
AI
,
ec
h
o
in
g
th
e
f
in
d
in
g
s
o
f
Kan
g
et
a
l
.
[
1
3
]
,
wh
ich
em
p
h
asized
th
e
m
e
d
i
atin
g
r
o
le
o
f
tr
u
s
t
in
m
ain
tai
n
in
g
th
e
co
n
tin
u
o
u
s
USE
.
Fu
r
th
er
m
o
r
e,
o
u
r
o
b
s
er
v
atio
n
th
at
IM
r
ed
u
ce
s
tech
n
o
l
o
g
y
-
r
elate
d
an
x
iety
is
co
n
s
is
ten
t
with
W
an
g
[
2
6
]
,
wh
o
d
em
o
n
s
tr
ated
th
at
m
o
tiv
atio
n
ca
n
r
e
d
u
ce
em
o
tio
n
al
b
ar
r
ier
s
in
d
ig
ital
lear
n
i
n
g
.
Ov
er
all,
th
ese
r
esu
lts
s
u
p
p
o
r
t
t
h
e
s
elf
-
d
eter
m
in
atio
n
th
eo
r
y
f
r
a
m
ewo
r
k
[
1
0
]
,
r
ein
f
o
r
cin
g
th
at
th
e
m
o
s
t
s
u
s
tain
ab
le
lear
n
in
g
b
en
e
f
its
ar
is
e
f
r
o
m
a
d
y
n
am
ic
b
etwe
en
ex
tr
in
s
ic
tr
ig
g
er
s
an
d
in
tr
in
s
ic
en
g
ag
em
e
n
t
[
2
7
]
.
4
.
2
.
P
r
a
ct
ica
l
i
m
pli
ca
t
io
ns
T
h
e
p
r
ac
tical
im
p
licatio
n
s
o
f
th
ese
f
in
d
in
g
s
p
o
i
n
t
to
th
e
n
e
ed
f
o
r
ac
a
d
em
ic
p
r
o
g
r
am
s
to
f
o
s
ter
I
M
wh
ile
s
tr
ateg
ically
u
s
in
g
ex
t
r
in
s
ic
in
ce
n
tiv
es.
Fo
r
e
x
am
p
l
e,
wh
ile
ex
ter
n
al
r
ec
o
g
n
itio
n
(
e.
g
.
,
ce
r
tific
ates,
p
er
f
o
r
m
an
ce
awa
r
d
s
)
ca
n
g
e
n
er
ate
en
g
a
g
em
en
t,
th
e
lo
n
g
-
ter
m
b
e
n
ef
its
d
ep
en
d
o
n
th
e
d
ev
elo
p
m
en
t
o
f
s
tu
d
en
ts
’
g
en
u
in
e
in
ter
est
in
cr
ea
tiv
e
ex
p
er
im
en
tatio
n
with
AI
,
in
lin
e
with
W
ei
et
a
l
.
[
8
]
in
th
e
co
n
tex
t
o
f
d
esig
n
ed
u
ca
tio
n
.
T
h
e
r
ef
o
r
e
,
u
n
iv
er
s
ities
s
h
o
u
ld
n
o
t
o
n
ly
p
r
o
v
id
e
ac
ce
s
s
to
to
o
ls
,
b
u
t
als
o
cr
ea
te
s
u
p
p
o
r
tiv
e
p
ed
ag
o
g
ical
ec
o
s
y
s
tem
s
,
as
s
u
g
g
ested
b
y
Gu
o
a
n
d
W
an
g
[
1
4
]
,
wh
e
r
e
th
e
ad
o
p
tio
n
o
f
AI
is
f
r
am
ed
b
y
tr
u
s
t,
eth
ics,
an
d
p
r
o
f
ess
io
n
al
d
e
v
elo
p
m
en
t.
T
ea
ch
er
tr
ai
n
in
g
is
e
q
u
ally
ess
en
tial,
as
ed
u
ca
to
r
s
p
lay
a
ce
n
tr
al
r
o
le
in
g
u
id
in
g
th
e
u
s
e
o
f
AI
to
war
d
s
r
esp
o
n
s
ib
le
an
d
cr
ea
tiv
e
p
r
ac
tices,
as
co
n
f
ir
m
ed
b
y
Fan
g
a
n
d
J
ian
g
[
9
]
o
n
th
e
ch
allen
g
es o
f
AI
i
n
ar
ts
ed
u
ca
t
io
n
.
Am
o
n
g
th
e
lim
itatio
n
s
f
o
u
n
d
,
th
e
s
am
p
le
(
2
0
3
s
tu
d
en
ts
)
l
ac
k
s
d
iv
er
s
ity
,
lim
itin
g
g
en
er
aliza
tio
n
s
.
Fu
tu
r
e
r
esear
ch
s
h
o
u
ld
em
p
lo
y
m
u
lti
-
co
n
te
x
tu
al
s
am
p
les
an
d
lo
n
g
itu
d
in
al
d
esig
n
s
.
Ou
r
s
elf
-
r
ep
o
r
ted
d
ata
co
u
ld
co
n
tain
b
iases
(
s
o
cial
d
esira
b
ilit
y
)
.
I
n
ad
d
itio
n
,
th
e
s
tu
d
y
d
id
n
o
t
an
aly
ze
th
e
m
o
d
er
atin
g
v
ar
iab
les,
wh
ich
co
u
ld
h
av
e
e
n
r
ich
ed
its
ef
f
ec
ts
in
n
ew
s
tu
d
y
c
o
n
tex
ts
.
5.
C
O
NCLU
SI
O
N
Am
o
n
g
h
i
g
h
er
e
d
u
ca
tio
n
s
tu
d
en
ts
,
th
e
s
tu
d
y
f
in
d
in
g
s
s
h
o
w
th
at
b
o
th
EM
an
d
p
er
s
o
n
al
m
o
tiv
atio
n
g
r
ea
tly
in
f
lu
e
n
ce
th
e
s
ee
n
ad
v
an
tag
es
o
f
u
s
in
g
Ge
n
AI
.
E
x
ter
n
al
in
s
p
ir
atio
n
,
s
u
ch
as
ac
c
o
lad
es,
ce
r
tific
ates,
o
r
ac
ad
e
m
ic
r
ewa
r
d
s
,
r
aises
s
tu
d
en
ts
’
v
al
u
atio
n
o
f
t
h
e
ad
v
a
n
tag
es
o
f
AI
,
t
h
er
ef
o
r
e
im
p
ly
i
n
g
th
at
co
n
te
x
tu
al
in
f
lu
en
ce
s
ca
n
in
cr
ea
s
e
in
ter
e
s
t
an
d
o
p
en
n
ess
to
th
ese
n
ew
tech
n
o
lo
g
ies.
Dr
iv
en
b
y
in
ter
n
al
in
ter
ests
an
d
p
r
o
f
ess
io
n
al
d
ev
elo
p
m
e
n
t o
b
je
ctiv
es,
p
er
s
o
n
al
m
o
tiv
atio
n
also
g
r
ea
tly
e
n
h
an
ce
s
o
n
e
’
s
v
iew
o
f
b
e
n
ef
its
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
15
,
No
.
1
,
Feb
r
u
a
r
y
20
2
6
:
544
-
5
54
552
E
x
ter
n
al
m
o
tiv
ato
r
s
ca
n
s
h
ap
e
s
tu
d
en
ts
’
p
er
ce
p
tio
n
s
o
f
th
e
v
alu
e
o
f
AI
,
b
u
t
th
e
y
d
o
no
t
n
ec
ess
ar
ily
s
h
ap
e
h
o
w
s
tu
d
en
ts
ca
n
u
s
e
th
em
.
W
h
ile
a
r
ewa
r
d
o
r
r
ec
o
g
n
i
tio
n
m
ay
m
o
tiv
ate
s
tu
d
en
ts
to
ex
p
er
im
en
t w
ith
o
r
tr
y
th
ese
to
o
ls
,
th
at
alo
n
e
co
u
ld
n
o
t tr
an
s
f
o
r
m
h
o
w
th
ey
p
er
c
eiv
e
th
e
tr
u
e
v
alu
e
o
f
wh
at
Gen
AI
h
as in
ter
m
s
o
f
its
co
n
tr
ib
u
tio
n
to
th
eir
lear
n
i
n
g
an
d
g
r
o
wth
in
cr
ea
tiv
e
s
k
ills
.
I
n
f
ield
s
th
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c
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g
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o
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u
ltime
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tech
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o
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y
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AI
is
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alu
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s
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o
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n
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ity
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itu
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t
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s
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l
d
also
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elp
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s
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esp
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ity
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tific
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itio
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a
d
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itio
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ca
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titu
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s
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s
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o
r
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r
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p
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th
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d
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g
s
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y
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p
ar
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n
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cr
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am
s
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n
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u
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al
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n
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ic
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o
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l
s
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e.
g
.
,
C
h
atGPT
,
Mid
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u
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y
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r
R
u
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way
ML
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in
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lu
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an
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s
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UNDING
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M
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Un
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Nac
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eq
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[
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553
RE
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NC
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S
[
1
]
L.
Z
h
o
u
a
n
d
J.
L
i
,
“
T
h
e
i
mp
a
c
t
o
f
C
h
a
t
G
P
T
o
n
l
e
a
r
n
i
n
g
m
o
t
i
v
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t
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o
n
:
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st
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d
y
b
a
se
d
o
n
s
e
l
f
-
d
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t
e
r
mi
n
a
t
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t
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y
,
”
Ed
u
c
a
t
i
o
n
S
c
i
e
n
c
e
a
n
d
Ma
n
a
g
e
m
e
n
t
,
v
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.
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,
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o
.
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p
p
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o
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:
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0
.
5
6
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7
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/
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sm0
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.
[
2
]
R
.
S
o
v
a
,
C
.
T
u
d
o
r
,
C
.
V
.
T
a
r
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a
v
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l
e
a
,
a
n
d
R
.
I
.
D
i
e
a
c
o
n
e
s
c
u
,
“
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r
t
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f
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c
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a
l
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l
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g
e
n
c
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a
d
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n
h
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g
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d
u
c
a
t
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:
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p
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t
s,
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l
e
c
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c
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.
1
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o
.
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o
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c
s1
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3
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2
.
[
3
]
B
.
G
a
o
,
R
.
Li
u
,
a
n
d
J
.
C
h
u
,
“
Ex
p
l
o
r
i
n
g
t
r
e
n
d
s
o
f
a
c
c
e
p
t
a
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a
r
t
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f
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c
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a
l
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n
t
e
l
l
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g
e
n
c
e
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d
u
c
a
t
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o
n
:
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sy
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t
e
m
a
t
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c
l
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t
e
r
a
t
u
r
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v
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e
w
,
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n
I
n
t
e
r
n
a
t
i
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l
C
o
n
f
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u
m
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[
4
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K
.
L
i
,
“
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AI
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b
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se
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sy
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t
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ms
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n
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h
n
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[
5
]
Y
.
B
a
i
a
n
d
S
.
W
a
n
g
,
“
I
mp
a
c
t
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v
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A
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d
e
n
t
s’
l
e
a
r
n
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n
g
o
u
t
c
o
mes
:
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t
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n
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y
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m
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d
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t
e
d
a
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v
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a
p
p
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c
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,
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c
i
e
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t
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f
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c
Re
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t
s
,
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.
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