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1
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I
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J
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15
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20
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4
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5
1416
T
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[
2
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4
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Ou
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p
r
o
v
i
n
g
e
d
u
ca
tio
n
al
ex
p
e
r
ien
ce
s
.
Mo
r
eo
v
er
,
we
em
p
h
asize
th
e
im
p
o
r
ta
n
ce
o
f
d
is
tin
g
u
is
h
in
g
b
etwe
en
AI
-
ass
is
ted
an
d
Gen
AI
-
co
m
p
lem
e
n
t
ac
tio
n
s
th
r
o
u
g
h
th
e
u
s
e
o
f
lea
r
n
in
g
a
n
aly
tics
.
AI
-
ass
is
ted
ac
tio
n
s
in
v
o
lv
e
m
ac
h
in
es
p
er
f
o
r
m
in
g
ac
tio
n
s
wh
ile
h
u
m
an
s
m
a
k
e
t
h
e
d
ec
is
io
n
s
,
wh
er
ea
s
AI
-
co
m
p
lem
en
t
ac
tio
n
s
in
v
o
lv
e
co
llab
o
r
ativ
e
d
ec
is
io
n
-
m
ak
in
g
b
etwe
en
h
u
m
an
s
an
d
m
ac
h
in
es.
T
h
is
d
if
f
er
en
tiatio
n
allo
ws
u
s
to
a
d
d
r
ess
eth
ical
co
n
s
id
er
atio
n
s
,
s
u
ch
as
en
s
u
r
in
g
eq
u
itab
le
ac
ce
s
s
to
ad
v
an
ce
d
AI
to
o
ls
f
o
r
all
s
tu
d
en
ts
[
5
]
–
[
7
]
.
B
y
co
n
d
u
ctin
g
th
is
s
t
u
d
y
,
we
in
ten
d
to
co
n
tr
ib
u
te
t
o
th
e
r
esp
o
n
s
ib
le
im
p
lem
en
tatio
n
o
f
Gen
AI
in
lear
n
in
g
a
n
aly
tics
with
in
h
ig
h
er
ed
u
ca
tio
n
.
Ou
r
f
in
d
in
g
s
will sh
ed
lig
h
t
o
n
th
e
p
o
ten
tial b
en
ef
its
o
f
Gen
AI
to
o
ls
as lea
r
n
in
g
ass
is
tan
ts
wh
ile
ad
d
r
ess
in
g
eth
ical
co
n
s
id
er
atio
n
s
.
Ultim
ately
,
th
i
s
r
esear
ch
s
ee
k
s
a
s
o
lu
tio
n
to
en
s
u
r
e
th
at
th
e
in
teg
r
atio
n
o
f
Gen
AI
in
ed
u
ca
tio
n
is
co
n
d
u
cted
in
a
m
an
n
er
th
at
i
s
eq
u
itab
le,
tr
an
s
p
ar
e
n
t,
an
d
b
en
ef
icial
f
o
r
all
s
tu
d
e
n
ts
.
T
h
e
in
teg
r
atio
n
o
f
AI
in
e
d
u
ca
tio
n
h
as
b
ee
n
co
n
d
u
cted
i
n
a
way
th
at
is
n
o
t
eq
u
itab
le
an
d
t
r
an
s
p
ar
en
t,
b
u
t
r
ath
er
b
en
ef
icial
f
o
r
a
p
a
r
ticu
lar
g
r
o
u
p
.
Oth
er
s
wer
e
ig
n
o
r
ed
a
n
d
d
i
d
n
o
t
h
av
e
th
e
s
am
e
o
p
p
o
r
tu
n
ities
to
lear
n
.
Giv
en
th
e
im
p
o
r
tan
ce
o
f
eth
ics,
Gen
AI
is
a
s
u
p
er
h
elp
f
u
l
to
o
l
t
h
at
ca
n
m
ak
e
le
ar
n
in
g
m
u
ch
m
o
r
e
en
g
ag
in
g
,
p
e
r
s
o
n
alize
less
o
n
s
f
o
r
ea
ch
s
tu
d
en
t,
an
d
b
o
o
s
t
cr
ea
tiv
ity
.
Ho
wev
er
,
to
ac
h
ie
v
e
th
ese
g
r
ea
t
r
esu
lts
,
we
m
u
s
t
en
s
u
r
e
th
at
s
tu
d
en
ts
d
o
n
o
t
m
is
u
s
e
it
f
o
r
ch
ea
tin
g
o
r
ac
ad
em
ic
d
is
h
o
n
esty
.
B
y
p
r
o
v
id
in
g
th
e
r
ig
h
t
g
u
id
an
ce
an
d
teac
h
in
g
s
tu
d
e
n
ts
h
o
w
to
u
s
e
Gen
AI
r
e
s
p
o
n
s
ib
ly
,
it
b
ec
o
m
es
a
to
o
l
th
at
r
ein
f
o
r
ce
s
eth
ical
s
tan
d
ar
d
s
(
E
S)
a
n
d
p
r
o
m
o
tes
o
r
ig
in
al
th
in
k
i
n
g
.
Ultim
ately
,
wh
en
we
p
r
io
r
itize
eth
ics
,
th
e
p
o
ten
tial
f
o
r
lo
n
g
-
ter
m
im
p
ac
t
is
h
u
g
e.
I
t
a
llo
ws
s
tu
d
en
ts
to
d
ev
elo
p
ess
en
tial
life
lo
n
g
s
k
ills
(
L
L
S)
th
at
th
ey
will
n
ee
d
f
ar
b
ey
o
n
d
th
e
class
r
o
o
m
.
T
h
is
s
tu
d
y
s
u
b
s
eq
u
e
n
tly
d
is
cu
s
s
es
lit
er
atu
r
e
r
ev
iew
to
ex
p
lain
th
e
ex
is
tin
g
k
n
o
wled
g
e
r
elate
d
to
th
e
cu
r
r
en
t
f
ield
o
f
s
tu
d
y
.
T
h
e
th
ir
d
s
ec
tio
n
o
f
th
is
s
tu
d
y
is
th
e
r
esear
ch
m
eth
o
d
.
T
h
e
f
o
u
r
t
h
s
ec
tio
n
d
em
o
n
s
tr
ates
r
esu
lts
an
d
d
is
cu
s
s
io
n
to
s
u
p
p
o
r
t
th
e
an
aly
s
is
o
f
th
e
r
esu
lt
s
.
Fin
ally
,
t
h
is
s
tu
d
y
ex
p
lain
s
co
n
clu
s
io
n
,
lim
itatio
n
,
an
d
f
u
t
u
r
e
s
tu
d
ies.
2.
L
I
T
E
R
AT
U
RE
R
E
VI
E
W
2
.
1
.
T
ec
hn
o
lo
g
y
a
cc
ept
a
nce
m
o
del
T
AM
is
p
r
im
ar
ily
u
s
ed
d
u
e
t
o
a
s
ig
n
if
ican
t
lev
el
o
f
p
er
ce
iv
ed
u
s
ef
u
ln
ess
an
d
f
o
r
th
e
p
er
c
eiv
ed
ea
s
e
o
f
u
s
e
[
8
]
.
T
h
e
in
ten
tio
n
to
e
m
p
lo
y
Gen
AI
is
s
ig
n
if
ican
tly
p
o
s
itiv
ely
im
p
ac
ted
b
y
attitu
d
e.
T
h
e
in
ten
tio
n
to
ad
o
p
t A
I
is
co
n
s
id
er
a
b
ly
im
p
a
cted
n
eg
ativ
ely
b
y
in
d
iv
id
u
al
co
n
ce
r
n
s
[
9
]
.
T
h
e
p
er
ce
iv
e
d
u
s
ef
u
ln
ess
an
d
ea
s
e
o
f
u
s
e
o
f
Gen
AI
tec
h
n
o
lo
g
y
is
a
cr
u
cial
d
eter
m
i
n
an
t
o
f
its
ac
ce
p
tan
ce
in
h
ig
h
er
ed
u
ca
tio
n
.
T
h
is
is
in
lin
e
with
th
e
T
AM
th
at
s
h
if
ts
to
war
d
b
len
d
ed
l
ea
r
n
in
g
co
n
tex
ts
an
d
g
r
o
win
g
em
p
h
asis
o
n
s
tu
d
en
t
m
o
tiv
atio
n
an
d
p
er
ce
iv
e
d
u
s
e
f
u
ln
ess
[
1
0
]
.
Per
ce
iv
e
d
u
s
ef
u
l
n
ess
in
th
e
co
n
tex
t
o
f
AI
in
e
d
u
ca
tio
n
m
ay
b
e
lin
k
ed
to
th
e
tec
h
n
o
lo
g
y
’
s
ca
p
ac
ity
to
im
p
r
o
v
e
in
s
tr
u
ctio
n
an
d
lear
n
in
g
,
wh
er
ea
s
ea
s
e
o
f
u
s
e
m
ay
b
e
co
n
n
ec
ted
to
th
e
s
y
s
tem
’
s
u
s
er
-
f
r
ien
d
lin
ess
[
1
1
]
.
T
AM
as
th
e
m
o
s
t
in
f
lu
en
tial
an
d
lead
in
g
s
cien
tific
p
ar
ad
ig
m
in
i
n
v
esti
g
atin
g
th
e
ac
ce
p
tan
ce
o
f
ed
u
ca
t
io
n
al
tech
n
o
lo
g
y
b
y
s
tu
d
e
n
ts
,
teac
h
er
s
,
an
d
o
th
e
r
s
tak
eh
o
ld
er
s
.
2
.
2
.
G
enAI in hig
her
ed
uca
t
io
n
W
ith
its
r
ev
o
lu
tio
n
ar
y
ap
p
r
o
ac
h
to
teac
h
in
g
an
d
lear
n
in
g
,
Gen
AI
h
as
b
ee
n
i
n
co
r
p
o
r
ate
d
in
to
th
e
ed
u
ca
tio
n
al
s
ec
to
r
m
o
r
e
a
n
d
m
o
r
e
[
1
1
]
.
T
h
er
e
a
r
e
f
o
u
r
p
r
i
m
ar
y
ca
teg
o
r
ies
o
f
Gen
AI
:
tex
t
g
en
er
atio
n
,
p
ictu
r
e
cr
ea
tio
n
,
s
o
u
n
d
g
en
er
atio
n
,
an
d
v
id
eo
p
r
o
d
u
ctio
n
.
AI
h
a
s
b
ee
n
ap
p
lied
to
im
p
r
o
v
e
ed
u
ca
tio
n
al
r
esu
lts
,
in
cr
ea
s
e
s
tu
d
en
t
en
g
a
g
em
en
t,
an
d
g
e
n
er
ate
p
er
s
o
n
alize
d
l
ea
r
n
in
g
e
x
p
er
ien
ce
s
[
1
2
]
.
G
en
AI
s
y
s
tem
s
lik
e
C
h
atb
o
ts
an
d
v
ir
tu
al
tu
to
r
s
th
at
h
av
e
en
ab
le
d
p
er
s
o
n
alize
d
lear
n
in
g
p
at
h
way
s
,
in
s
tan
tan
e
o
u
s
f
ee
d
b
ac
k
,
an
d
in
ter
ac
tiv
e
lear
n
in
g
s
ettin
g
s
[
1
2
]
.
As
a
r
esu
lt,
AI
ca
n
b
e
u
s
ed
to
im
p
r
o
v
e
lear
n
in
g
o
u
tco
m
es
(
L
O)
by
f
ac
ilit
atin
g
th
e
p
r
o
d
u
ctio
n
o
f
co
n
ten
t
an
d
d
ata
an
d
b
y
lev
e
r
ag
in
g
th
e
co
g
n
itiv
e
d
ev
el
o
p
m
en
t
b
eh
a
v
io
r
s
th
at
co
m
e
with
it
[
1
]
,
[
1
3
]
.
Alza
h
r
an
i
[
1
4
]
e
m
p
lo
y
e
d
a
q
u
an
titativ
e
m
eth
o
d
o
l
o
g
y
,
g
at
h
er
in
g
d
ata
f
r
o
m
3
5
0
h
ig
h
er
ed
u
ca
tio
n
s
tu
d
en
ts
u
s
in
g
a
s
tr
u
ct
u
r
ed
q
u
esti
o
n
n
air
e.
T
h
e
s
tu
d
y
d
e
v
e
lo
p
ed
a
co
n
ce
p
tu
al
m
o
d
el
b
a
s
ed
o
n
t
h
e
u
n
if
ied
th
eo
r
y
o
f
ac
ce
p
ta
n
ce
(
UT
A)
an
d
T
AM
to
an
aly
ze
h
o
w
s
tu
d
en
ts
p
er
ce
iv
e
an
d
b
eh
av
e
to
w
ar
d
s
AI
tech
n
o
lo
g
y
.
On
e
k
ey
f
in
d
i
n
g
is
th
at
p
er
c
eiv
ed
r
is
k
n
eg
ativ
ely
in
f
lu
e
n
ce
s
s
tu
d
en
ts
’
attitu
d
es
to
war
d
s
AI
in
e
d
u
ca
tio
n
,
wh
er
ea
s
p
er
ce
iv
ed
p
e
r
f
o
r
m
an
ce
g
ain
s
an
d
r
eso
u
r
ce
a
v
ailab
ilit
y
p
lay
a
m
o
r
e
s
ig
n
if
ican
t
r
o
le
th
an
p
er
ce
iv
e
d
Evaluation Warning : The document was created with Spire.PDF for Python.
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2252
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2
I
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teg
r
a
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g
en
era
tive
A
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in
h
i
g
h
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d
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lifelo
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1417
ea
s
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h
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less
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l
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p
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r
e
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u
g
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esti
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a
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f
o
r
f
u
r
t
h
er
ex
p
lo
r
atio
n
an
d
v
alid
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n
.
Kelly
et
a
l
.
[
1
]
c
o
n
d
u
cted
a
s
y
s
tem
atic
r
ev
iew
o
f
s
tu
d
ies
p
u
b
lis
h
ed
b
etwe
en
2
0
1
9
an
d
2
0
2
2
,
f
o
cu
s
in
g
o
n
ele
m
en
ts
r
elate
d
to
AI
tech
n
o
lo
g
y
ac
ce
p
tan
ce
.
Mo
s
t
s
tu
d
ies
r
ev
iewe
d
u
tili
ze
d
o
n
lin
e
q
u
esti
o
n
n
air
es
an
d
s
u
r
v
ey
s
,
with
b
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av
io
r
al
in
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tio
n
b
ein
g
t
h
e
m
o
s
t
co
m
m
o
n
m
ea
s
u
r
e
o
f
ac
ce
p
tan
ce
.
T
h
e
ex
p
a
n
d
ed
T
AM
was
f
r
eq
u
e
n
tly
u
s
ed
,
h
ig
h
lig
h
tin
g
attitu
d
es,
tr
u
s
t,
an
d
p
er
ce
iv
ed
u
s
ef
u
ln
ess
as
k
ey
f
ac
to
r
s
.
T
h
is
r
ev
iew
u
n
d
er
s
c
o
r
es
th
e
n
ee
d
f
o
r
f
u
r
th
er
r
es
ea
r
ch
in
to
tr
u
s
t
an
d
p
er
ce
iv
ed
u
s
ef
u
ln
ess
to
en
h
a
n
ce
AI
ad
o
p
tio
n
.
E
d
u
ca
tio
n
a
l
s
tr
ateg
ies
s
h
o
u
ld
f
o
cu
s
o
n
b
u
ild
in
g
tr
u
s
t
an
d
d
em
o
n
s
tr
atin
g
t
h
e
p
r
ac
tical
b
e
n
ef
its
o
f
AI
tech
n
o
lo
g
ies.
Kan
o
n
t
et
a
l
.
[
1
2
]
u
s
ed
th
e
T
AM
to
in
v
esti
g
ate
f
ac
to
r
s
in
f
lu
en
cin
g
th
e
ad
o
p
tio
n
o
f
Gen
AI
tech
n
o
lo
g
ies
am
o
n
g
T
h
ai
u
n
i
v
er
s
ity
s
tu
d
en
ts
.
Usi
n
g
a
s
am
p
le
o
f
9
1
1
s
tu
d
e
n
ts
,
th
e
s
tu
d
y
e
m
p
lo
y
ed
s
tr
u
ctu
r
al
eq
u
atio
n
m
o
d
elin
g
(
SEM
)
to
a
n
aly
ze
d
ata.
T
h
e
f
in
d
i
n
g
s
r
ev
e
aled
th
at
ex
p
ec
ted
b
en
ef
its
,
p
e
r
ce
iv
ed
u
s
ef
u
l
n
ess
,
attitu
d
e
to
war
d
s
tech
n
o
lo
g
y
,
an
d
b
eh
av
i
o
r
al
in
ten
tio
n
s
ig
n
if
ican
tly
in
f
lu
en
ce
AI
ad
o
p
tio
n
.
T
h
e
s
tu
d
y
’
s
co
n
tex
t,
b
ein
g
s
p
ec
if
ic
to
T
h
ai
s
tu
d
en
ts
,
m
ig
h
t
af
f
ec
t
its
g
en
er
aliza
b
ilit
y
to
o
th
er
c
u
ltu
r
al
an
d
ed
u
ca
tio
n
al
s
ettin
g
s
.
W
en
g
et
a
l
.
[
1
5
]
co
n
clu
d
e
d
th
at
m
o
r
e
em
p
h
asi
s
s
h
o
u
ld
b
e
p
lace
d
o
n
two
LO
:
ca
r
ee
r
-
d
r
iv
en
co
m
p
eten
cies
an
d
LLS
,
as
th
ey
ar
e
b
ec
o
m
in
g
in
cr
e
asin
g
ly
cr
u
cial
in
Gen
AI
-
f
ac
ilit
ated
lear
n
in
g
en
v
ir
o
n
m
en
ts
.
Kh
o
d
a
k
ar
am
i
e
t
a
l
.
[
1
6
]
f
o
u
n
d
th
at
tech
n
o
lo
g
y
s
tr
ateg
y
p
lay
s
a
m
ed
iatin
g
r
o
le
in
th
e
in
war
d
ex
p
o
r
t
p
er
f
o
r
m
a
n
ce
o
f
h
ig
h
e
r
ed
u
ca
tio
n
.
T
h
is
s
u
g
g
ests
th
at
Ma
lay
s
ian
h
ig
h
er
ed
u
ca
tio
n
in
s
titu
tio
n
s
(
HE
I
s
)
s
h
o
u
ld
b
e
eq
u
ip
p
e
d
with
t
h
e
l
atest
ed
u
ca
tio
n
-
r
elate
d
tech
n
o
lo
g
ies
to
im
p
r
o
v
e
th
eir
p
er
f
o
r
m
an
ce
.
As
a
r
esu
lt,
th
e
u
s
e
o
f
tech
n
o
lo
g
y
in
e
d
u
ca
tio
n
is
cr
u
cial
f
o
r
in
cr
ea
s
in
g
p
er
f
o
r
m
a
n
ce
.
T
h
e
th
r
e
e
s
tu
d
ies
u
tili
ze
d
iv
er
s
e
m
eth
o
d
o
lo
g
ies
—
q
u
an
tita
tiv
e
s
u
r
v
ey
s
,
s
y
s
tem
atic
r
ev
i
ews,
an
d
SEM
—
p
r
o
v
id
in
g
a
well
-
r
o
u
n
d
ed
u
n
d
er
s
tan
d
in
g
o
f
AI
ac
ce
p
tan
ce
.
T
h
is
d
i
v
er
s
ity
is
a
s
tr
en
g
th
,
o
f
f
er
i
n
g
b
o
th
b
r
ea
d
th
an
d
d
ep
t
h
o
f
in
s
ig
h
ts
.
T
h
e
co
n
s
is
ten
t u
s
e
o
f
estab
lis
h
ed
f
r
am
ewo
r
k
s
lik
e
UT
A
an
d
T
AM
en
h
an
ce
s
th
e
cr
ed
ib
ilit
y
o
f
th
e
s
tu
d
ies
a
n
d
a
llo
ws
f
o
r
co
m
p
ar
is
o
n
o
f
f
in
d
i
n
g
s
.
T
h
ese
m
o
d
els
ar
e
c
r
u
cial
f
o
r
id
e
n
tify
in
g
k
e
y
f
ac
to
r
s
in
f
lu
e
n
cin
g
AI
ac
ce
p
ta
n
ce
.
Fu
tu
r
e
r
esear
ch
s
h
o
u
ld
in
co
r
p
o
r
ate
m
ix
ed
-
m
eth
o
d
s
ap
p
r
o
ac
h
es
to
ca
p
tu
r
e
a
m
o
r
e
h
o
lis
tic
u
n
d
er
s
tan
d
in
g
o
f
s
tu
d
en
ts
’
attitu
d
es
a
n
d
b
e
h
av
io
r
s
to
war
d
s
AI
.
C
o
m
p
ar
a
tiv
e
s
tu
d
ies
ac
r
o
s
s
d
if
f
er
en
t
r
eg
i
o
n
s
an
d
ed
u
ca
ti
o
n
al
s
ettin
g
s
co
u
ld
p
r
o
v
id
e
v
alu
ab
le
in
s
ig
h
ts
in
to
h
o
w
cu
ltu
r
al
an
d
co
n
tex
t
u
al
f
ac
to
r
s
in
f
lu
en
ce
AI
ac
ce
p
ta
n
ce
.
B
y
ad
d
r
ess
in
g
th
ese
ar
ea
s
,
ed
u
ca
tio
n
al
in
s
titu
tio
n
s
ca
n
b
etter
lev
er
ag
e
AI
tech
n
o
lo
g
y
to
en
h
an
ce
LO
an
d
s
tu
d
en
t
en
g
ag
em
e
n
t.
B
ased
o
n
th
e
co
n
ce
p
tu
al
f
r
am
ew
o
r
k
,
as
in
Fig
u
r
e
1
,
th
e
s
tu
d
y
’
s
h
y
p
o
th
eses
ar
e:
i)
Gen
AI
h
as
a
p
o
s
itiv
e
co
r
r
elati
o
n
with
LO
in
h
ig
h
er
ed
u
ca
ti
o
n
(
H1
)
;
ii)
ES
h
as
a
p
o
s
itiv
e
c
o
r
r
elatio
n
with
LO
in
h
ig
h
er
ed
u
ca
tio
n
(
H2
)
;
iii)
LO
h
as
a
p
o
s
itiv
e
c
o
r
r
elatio
n
with
LLS
in
h
ig
h
e
r
ed
u
ca
tio
n
(
H
3
)
.
R
ec
en
t
s
tu
d
ies
h
av
e
ex
p
lo
r
ed
th
e
in
teg
r
atio
n
o
f
AI
tech
n
o
l
o
g
ies,
s
u
ch
as
C
h
atG
PT,
in
e
d
u
ca
tio
n
al
s
ettin
g
s
,
f
o
cu
s
in
g
o
n
th
eir
ac
ce
p
tan
ce
,
u
tili
ty
,
an
d
im
p
ac
t
o
n
LO
.
T
h
is
r
ev
iew
cr
itically
ex
am
in
es
th
e
f
in
d
in
g
s
[
1
7
]
–
[
1
9
]
,
h
ig
h
lig
h
tin
g
th
e
s
tr
en
g
th
s
an
d
lim
itatio
n
s
o
f
th
eir
r
esear
ch
.
Kizilce
c
[
1
7
]
c
o
n
d
u
c
ted
r
esear
ch
o
n
th
e
u
s
e
o
f
th
e
ac
ad
em
ic
r
esis
tan
ce
m
o
d
el
(
AR
M)
an
d
T
AM
in
th
e
co
n
tex
t o
f
ed
u
ca
tio
n
.
T
h
e
s
t
u
d
y
h
ig
h
lig
h
ted
th
e
im
p
o
r
tan
ce
o
f
p
er
ce
iv
e
d
u
tili
ty
an
d
p
er
ce
iv
e
d
ea
s
e
o
f
u
s
e
o
f
tech
n
o
lo
g
y
in
u
s
er
ac
ce
p
tab
i
lity
.
I
t
em
p
h
asized
th
e
in
f
lu
en
c
e
o
f
s
o
cial,
p
s
y
c
h
o
lo
g
ical,
an
d
cu
ltu
r
al
elem
en
ts
o
n
tech
n
o
lo
g
y
ad
o
p
tio
n
.
T
h
e
s
tu
d
y
p
r
im
ar
ily
d
is
cu
s
s
es
th
eo
r
etica
l
asp
ec
ts
with
o
u
t
p
r
o
v
id
in
g
s
u
b
s
tan
ti
al
em
p
ir
ical
d
ata
to
s
u
p
p
o
r
t
its
claim
s
.
Fu
tu
r
e
r
esear
ch
s
h
o
u
ld
i
n
clu
d
e
q
u
an
ti
tativ
e
an
d
q
u
alitativ
e
d
ata
to
v
alid
ate
th
e
p
r
o
p
o
s
ed
m
o
d
els.
B
o
u
b
k
er
[
1
8
]
i
n
v
esti
g
ated
h
o
w
C
h
atGPT
,
an
AI
-
b
ased
to
o
l,
m
ay
im
p
r
o
v
e
LO
f
o
r
s
tu
d
en
ts
.
T
h
e
s
tu
d
y
f
o
u
n
d
th
at
p
e
r
ce
iv
ed
u
ti
lity
,
C
h
atGPT
u
s
ag
e,
an
d
s
tu
d
en
t
h
ap
p
in
ess
wer
e
in
f
lu
en
ce
d
b
y
o
u
tp
u
t
q
u
ality
.
So
cial
in
f
lu
en
ce
also
p
lay
ed
a
s
ig
n
if
ican
t
r
o
le
in
h
o
w
b
en
ef
icial
p
eo
p
le
p
er
ce
iv
e
d
C
h
atGPT
to
b
e
an
d
h
o
w
th
ey
u
tili
ze
d
it.
Per
ce
iv
ed
ea
s
e
o
f
u
s
e
h
ad
a
s
u
b
s
tan
tial im
p
ac
t o
n
s
tu
d
en
ts
’
p
leasu
r
e
a
n
d
p
er
ce
iv
ed
u
s
ef
u
ln
ess
.
T
h
e
u
s
e
o
f
co
n
v
en
ien
ce
s
am
p
lin
g
m
ay
in
tr
o
d
u
ce
b
ias,
li
m
itin
g
th
e
g
en
er
aliza
b
ilit
y
o
f
th
e
f
in
d
in
g
s
.
Fu
tu
r
e
s
tu
d
ies s
h
o
u
ld
co
n
s
id
er
m
o
r
e
d
iv
er
s
e
an
d
r
ep
r
esen
tativ
e
s
a
m
p
les.
Ng
u
y
en
et
a
l
.
[
1
9
]
s
tu
d
ied
th
e
in
teg
r
atio
n
o
f
C
h
atGPT
at
Ho
C
h
i
Min
h
C
ity
Un
i
v
er
s
ity
o
f
T
ec
h
n
o
lo
g
y
an
d
E
d
u
ca
tio
n
(
H
C
MU
T
E
)
an
d
its
im
p
ac
t
o
n
s
t
u
d
en
ts
’
lear
n
in
g
p
r
ac
tices.
T
h
e
s
tu
d
y
f
o
u
n
d
th
at
s
tu
d
en
ts
ex
ten
s
iv
ely
u
s
ed
C
h
atGPT
f
o
r
lear
n
in
g
an
d
in
f
o
r
m
atio
n
s
ea
r
ch
es.
Ho
wev
e
r
,
th
er
e
wer
e
also
co
n
ce
r
n
s
ab
o
u
t
d
im
in
is
h
ed
cr
ea
tiv
ity
,
ac
ad
em
ic
d
is
h
o
n
esty
,
an
d
eth
ical
is
s
u
es
s
u
ch
as
in
f
o
r
m
atio
n
s
ec
u
r
ity
an
d
p
lag
iar
is
m
.
T
h
e
s
tu
d
y
’
s
s
am
p
le
s
ize
(
7
3
s
tu
d
e
n
ts
an
d
1
5
f
ac
u
lty
m
e
m
b
er
s
)
m
a
y
n
o
t
b
e
s
u
f
f
icien
t
to
d
r
aw
b
r
o
ad
c
o
n
clu
s
io
n
s
.
L
a
r
g
er
-
s
ca
le
s
tu
d
ies
ar
e
n
ee
d
ed
to
co
n
f
i
r
m
th
e
f
in
d
i
n
g
s
.
Hash
m
i
an
d
B
al
[
2
0
]
m
en
tio
n
ed
v
alu
ab
le
in
s
ig
h
ts
in
to
t
h
e
ad
o
p
tio
n
an
d
p
er
ce
p
tio
n
o
f
Gen
AI
in
h
ig
h
er
ed
u
ca
tio
n
.
T
h
eir
s
tu
d
y
ex
p
lo
r
es
th
e
co
n
n
ec
tio
n
b
etwe
en
tr
an
s
p
ar
e
n
cy
a
n
d
r
esp
o
n
s
ib
ilit
y
in
u
s
i
n
g
Gen
AI
.
T
h
e
f
in
d
in
g
s
s
u
g
g
est
th
at
HE
I
s
ca
n
lev
er
ag
e
Gen
AI
to
b
etter
p
r
ep
ar
e
s
tu
d
en
ts
f
o
r
u
s
in
g
tec
h
n
o
lo
g
y
b
ey
o
n
d
th
e
class
r
o
o
m
.
T
h
e
s
tu
d
y
also
h
ig
h
lig
h
ts
th
e
im
p
o
r
tan
ce
o
f
r
esp
o
n
s
ib
le
im
p
lem
en
tatio
n
an
d
ad
d
r
ess
es
co
n
ce
r
n
s
s
u
ch
as
ac
ad
em
ic
in
teg
r
ity
.
Miller
[
2
1
]
f
o
cu
s
ed
o
n
h
o
w
Gen
AI
is
u
s
ed
in
u
n
iv
er
s
ity
class
r
o
o
m
s
em
p
lo
y
in
g
r
esear
ch
m
eth
o
d
o
lo
g
y
o
f
f
o
cu
s
g
r
o
u
p
s
,
ex
p
e
r
t
o
b
s
er
v
ati
o
n
s
,
an
d
in
f
o
r
m
al
co
n
v
er
s
atio
n
s
.
T
h
e
s
tu
d
y
in
d
icate
s
th
at
t
h
e
u
s
ag
e
o
f
Gen
AI
to
o
ls
in
class
r
o
o
m
s
i
s
ac
ce
p
t
ab
le,
b
u
t
ed
u
ca
to
r
s
m
ay
h
av
e
r
ea
s
o
n
s
b
o
th
to
u
s
e
an
d
n
o
t
to
u
s
e
th
em
.
T
h
e
f
in
d
in
g
s
em
p
h
asize
th
e
n
ee
d
f
o
r
a
b
alan
ce
d
ap
p
r
o
ac
h
to
in
te
g
r
atin
g
Gen
AI
tec
h
n
o
l
o
g
ies in
h
ig
h
er
e
d
u
ca
tio
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
.
2
,
Ap
r
il
20
2
6
:
1
4
1
5
-
1
4
2
5
1418
Gu
illén
-
Yp
ar
r
ea
an
d
Her
n
á
n
d
ez
-
R
o
d
r
íg
u
ez
[
2
2
]
in
v
esti
g
a
ted
u
n
d
er
g
r
ad
u
ate
en
g
in
ee
r
in
g
s
tu
d
en
ts
’
u
n
d
er
s
tan
d
i
n
g
o
f
Gen
AI
,
its
ap
p
licatio
n
s
,
a
n
d
m
o
r
al
im
p
licatio
n
s
.
T
h
e
r
esear
ch
a
d
o
p
ts
a
m
ix
ed
-
m
eth
o
d
ap
p
r
o
ac
h
.
T
h
e
f
in
d
in
g
s
r
ev
ea
l
th
at
C
h
atGPT
is
th
e
m
o
s
t
wi
d
ely
u
s
ed
Gen
AI
ap
p
licatio
n
am
o
n
g
s
tu
d
en
ts
,
b
u
t
in
s
tr
u
cto
r
s
h
av
e
n
eg
ativ
e
o
p
in
io
n
s
ab
o
u
t
t
h
is
tech
n
o
lo
g
y
.
T
h
e
s
tu
d
y
h
i
g
h
lig
h
ts
th
e
im
p
o
r
ta
n
ce
o
f
co
n
s
id
er
in
g
s
tu
d
en
t
p
er
s
p
ec
tiv
es
an
d
ad
d
r
ess
in
g
in
s
tr
u
cto
r
s
’
co
n
ce
r
n
s
in
th
e
im
p
lem
e
n
tatio
n
o
f
Gen
AI
.
T
h
e
p
u
r
p
o
s
e
o
f
a
q
u
alitativ
e
s
tu
d
y
co
n
d
u
cted
b
y
Su
m
m
e
r
s
et
a
l
.
[
2
3
]
was
t
o
in
v
esti
g
ate
n
u
r
s
in
g
s
tu
d
e
n
ts
’
v
iewp
o
in
ts
o
n
th
e
u
s
e
an
d
in
co
r
p
o
r
atio
n
o
f
Ge
n
AI
tech
n
o
lo
g
ies
in
th
eir
co
u
r
s
ewo
r
k
.
T
h
is
s
tu
d
y
co
n
d
u
c
ted
s
em
i
-
s
tr
u
ctu
r
ed
in
ter
v
iews
with
n
u
r
s
in
g
s
tu
d
en
ts
u
s
in
g
a
q
u
alitativ
e
d
escr
ip
tiv
e
m
eth
o
d
o
lo
g
y
.
T
h
is
r
esear
ch
was
ca
r
r
ied
o
u
t
in
a
r
u
r
al
Au
s
tr
alian
u
n
iv
e
r
s
ity
in
th
e
f
ield
o
f
n
u
r
s
in
g
.
Fo
r
th
is
s
tu
d
y
,
in
ter
v
iews
with
13
f
ir
s
t
-
an
d
s
ec
o
n
d
-
y
ea
r
n
u
r
s
in
g
s
tu
d
en
ts
wer
e
co
n
d
u
cted
.
T
h
e
d
ata
a
n
aly
s
is
p
r
o
d
u
ce
d
s
ix
s
ep
ar
ate
to
p
ics,
in
clu
d
in
g
th
e
in
f
lu
e
n
ce
o
f
AI
to
o
ls
o
n
ed
u
ca
tio
n
,
th
e
cr
ea
tio
n
o
f
an
e
q
u
itab
le
lear
n
i
n
g
en
v
ir
o
n
m
e
n
t,
th
e
m
o
r
al
im
p
licatio
n
s
o
f
u
s
in
g
AI
,
th
e
in
teg
r
atio
n
o
f
tech
n
o
l
o
g
y
,
s
af
e
an
d
u
s
ef
u
l a
p
p
licatio
n
s
,
an
d
g
en
e
r
atio
n
al
d
is
p
ar
ities
.
−
Gen
AI
co
m
p
lem
e
n
t a
ctio
n
h
as
a
p
o
s
itiv
e
co
r
r
elatio
n
with
L
L
S
in
h
ig
h
er
e
d
u
ca
tio
n
(
H4
).
−
ES
h
as a
p
o
s
itiv
e
r
elatio
n
with
LLS
in
h
ig
h
e
r
ed
u
ca
tio
n
(
H5
).
T
h
e
co
n
ce
p
tu
al
r
esear
c
h
f
r
a
m
ewo
r
k
u
s
ed
in
th
is
s
tu
d
y
is
p
r
esen
ted
in
Fig
u
r
e
1
.
B
ased
o
n
th
e
T
AM
,
th
e
f
r
am
ewo
r
k
ass
er
ts
th
at
th
e
u
s
e
o
f
Gen
AI
an
d
et
h
ical
p
r
in
cip
les
ca
n
im
p
ac
t
th
e
r
es
u
lts
o
f
th
e
lear
n
in
g
p
r
o
ce
s
s
,
wh
ich
s
u
b
s
eq
u
en
tly
af
f
ec
ts
th
e
ac
q
u
is
itio
n
o
f
life
lo
n
g
lear
n
in
g
s
k
ills
.
Als
o
,
th
e
m
o
d
el
co
n
s
id
er
s
d
ir
ec
t
im
p
licatio
n
s
o
f
th
e
Ge
n
AI
an
d
ES
o
n
LLS
,
w
h
ich
g
iv
es
a
d
etailed
f
r
am
ewo
r
k
to
u
s
e
to
test
th
e
f
iv
e
r
esear
ch
h
y
p
o
th
eses
.
Fig
u
r
e
1
.
R
esear
ch
f
r
am
ewo
r
k
o
f
th
e
s
tu
d
y
3.
RE
S
E
ARCH
M
E
T
H
O
D
T
h
e
s
tu
d
y
e
m
p
lo
y
e
d
a
q
u
an
titativ
e
ap
p
r
o
ac
h
to
in
v
esti
g
ate
s
tu
d
en
ts
’
AI
u
s
e
to
war
d
s
lear
n
in
g
an
aly
tics
wh
ile
m
ain
tain
in
g
ES
in
h
ig
h
er
e
d
u
ca
tio
n
.
T
h
e
p
ar
ticip
an
ts
wer
e
u
n
d
er
g
r
a
d
u
ate
an
d
g
r
a
d
u
ate
s
tu
d
en
ts
en
r
o
lled
at
th
e
I
n
ter
n
atio
n
al
Un
iv
er
s
ity
o
f
B
u
s
in
ess
Ag
r
icu
ltu
r
e
an
d
T
ec
h
n
o
lo
g
y
(
I
UB
AT
)
B
u
s
in
es
s
Sch
o
o
l,
Dh
ak
a,
B
an
g
lad
esh
.
Data
f
r
o
m
a
s
am
p
le
o
f
1
8
0
s
tu
d
en
ts
was
g
ath
er
ed
s
y
s
tem
atica
lly
u
s
in
g
a
q
u
esti
o
n
n
air
e,
wh
ich
m
ad
e
it
p
o
s
s
ib
le
to
lear
n
a
b
o
u
t
th
e
v
a
r
io
u
s
asp
ec
ts
im
p
ac
tin
g
s
tu
d
e
n
ts
’
u
s
ag
e
o
f
AI
i
n
th
eir
ed
u
ca
tio
n
.
T
h
e
s
tu
d
y
u
tili
ze
d
co
n
v
en
ien
ce
s
am
p
lin
g
,
a
f
o
r
m
o
f
n
o
n
-
p
r
o
b
ab
il
ity
s
am
p
lin
g
.
T
h
e
p
ar
ticip
an
ts
in
clu
d
ed
u
n
d
e
r
g
r
ad
u
ate
a
n
d
g
r
ad
u
ate
s
tu
d
e
n
ts
en
r
o
lled
at
th
e
I
UB
AT
B
u
s
in
ess
Sch
o
o
l,
Dh
a
k
a,
B
an
g
lad
esh
.
T
h
e
s
am
p
le
cr
ite
r
ia
wer
e
clea
r
ly
d
ef
in
e
d
as
s
t
u
d
en
ts
in
h
ig
h
er
ed
u
ca
tio
n
at
th
e
af
o
r
em
en
tio
n
ed
in
s
titu
tio
n
.
Par
ticip
an
ts
m
u
s
t
b
e
en
r
o
lled
as
u
n
d
er
g
r
ad
u
at
e
o
r
g
r
ad
u
ate
s
tu
d
en
ts
at
th
e
I
UB
AT
B
u
s
in
ess
Sch
o
o
l,
an
d
th
e
d
esire
d
s
am
p
le
s
ize
was 1
8
0
s
tu
d
en
ts
.
T
h
e
s
u
r
v
e
y
q
u
esti
o
n
n
air
e,
wh
i
ch
s
er
v
ed
as
th
e
r
esear
c
h
to
o
l,
in
clu
d
ed
f
iv
e
s
ec
tio
n
s
an
d
was
cr
ea
ted
to
co
llect
d
ata
f
o
r
th
e
s
tu
d
y
.
T
h
e
p
r
im
a
r
y
o
b
jectiv
e
o
f
P
ar
t
1
was
g
ath
er
in
g
d
em
o
g
r
a
p
h
ic
d
ata
f
r
o
m
th
e
s
am
p
le,
s
u
ch
as
y
ea
r
o
f
s
t
u
d
y
,
d
ep
ar
tm
en
t,
g
en
d
e
r
,
ag
e,
an
d
lev
el
o
f
ed
u
ca
tio
n
.
Un
d
er
s
tan
d
in
g
t
h
e
ch
ar
ac
ter
is
tics
an
d
co
m
p
o
s
itio
n
o
f
th
e
r
esp
o
n
d
er
s
r
eq
u
ir
es
k
n
o
wled
g
e
o
f
th
is
in
f
o
r
m
atio
n
.
T
h
e
p
u
r
p
o
s
e
o
f
th
e
s
ec
o
n
d
p
ar
t
o
f
th
e
q
u
esti
o
n
n
ai
r
e
was
to
lear
n
m
o
r
e
ab
o
u
t
u
s
ag
e
p
atter
n
s
o
f
Gen
AI
.
T
h
e
tr
u
s
t,
attitu
d
es,
s
o
cial
n
o
r
m
s
,
a
n
d
c
u
ltu
r
e
ar
o
u
n
d
th
e
u
s
e
o
f
Gen
AI
in
e
d
u
ca
tio
n
al
a
ctiv
ities
wer
e
ex
am
in
ed
i
n
th
is
p
ar
t.
I
t
is
p
o
s
s
ib
le
to
g
ain
in
f
o
r
m
atio
n
in
to
s
tu
d
e
n
ts
’
ex
p
o
s
u
r
e
to
an
d
f
am
iliar
i
ty
with
Gen
AI
b
y
an
aly
zi
n
g
t
h
eir
cu
r
r
en
t
u
s
ag
e
h
ab
its
.
T
h
e
th
ir
d
s
ec
tio
n
o
f
t
h
e
s
u
r
v
ey
ex
am
in
e
d
Gen
AI
i
n
l
ea
r
n
in
g
a
n
aly
tics
.
L
ea
r
n
i
n
g
a
n
d
teac
h
in
g
m
ay
b
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
I
n
teg
r
a
tin
g
g
en
era
tive
A
I
in
h
i
g
h
er e
d
u
ca
tio
n
fo
r
lifelo
n
g
le
a
r
n
in
g
(
Mo
z
a
ffa
r
A
la
m
C
h
o
w
d
h
u
r
y
)
1419
en
h
an
ce
d
b
y
p
e
r
ce
iv
ed
u
s
e
in
th
e
co
n
tex
t
o
f
Gen
AI
in
ed
u
ca
tio
n
.
I
n
o
r
d
er
t
o
s
h
ed
lig
h
t
o
n
h
o
w
Gen
AI
will
im
p
ac
t
s
o
ciety
o
v
er
tim
e,
th
e
f
o
u
r
th
p
o
r
tio
n
o
f
th
e
s
tu
d
y
lo
o
k
ed
in
t
o
th
e
lo
n
g
-
ter
m
ef
f
ec
ts
o
f
Gen
AI
.
T
h
e
s
u
r
v
ey
’
s
f
if
th
s
eg
m
e
n
t
lo
o
k
ed
at
th
e
u
s
e
o
f
Gen
AI
ES
.
T
h
is
will
o
f
f
er
g
u
id
an
ce
o
n
a
v
o
id
in
g
p
lag
iar
is
m
,
m
ain
tain
in
g
in
f
o
r
m
atio
n
s
ec
u
r
ity
,
an
d
elim
in
atin
g
ac
ad
em
ic
d
is
h
o
n
esty
.
E
ac
h
item
was
r
a
ted
b
y
p
a
r
ticip
an
ts
o
n
a
5
-
L
ik
er
t scale
,
with
ea
ch
p
o
in
t r
ep
r
esen
tin
g
th
eir
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el
o
f
ag
r
ee
m
e
n
t.
T
h
e
r
elatio
n
b
etwe
en
th
e
s
tu
d
y
’
s
in
d
ep
en
d
en
t
a
n
d
d
ep
e
n
d
en
t
v
ar
iab
les
was
ex
am
in
ed
b
y
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e
r
esear
ch
er
s
u
s
in
g
th
e
SEM
.
T
AM
was
u
s
ed
in
th
e
s
tu
d
y
in
o
r
d
e
r
to
g
e
n
er
ate
th
e
o
r
ie
s
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d
v
alid
ate
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e
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n
ce
p
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al
m
o
d
el.
I
n
ad
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itio
n
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aly
ze
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s
e
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tu
d
ies
o
f
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ch
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o
ls
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d
in
s
titu
tio
n
s
th
at
h
av
e
i
m
p
lem
en
ted
Gen
AI
to
o
ls
to
u
n
d
e
r
s
tan
d
th
eir
im
p
a
ct
an
d
eth
ical
co
n
s
id
er
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s
.
I
n
th
is
s
tu
d
y
,
d
ata
an
aly
s
is
was
d
o
n
e
u
s
in
g
Sm
ar
tP
L
S
4
.
T
o
v
er
i
f
y
c
o
n
v
e
r
g
e
n
t
v
alid
ity
,
th
e
in
v
esti
g
atio
n
in
clu
d
e
d
a
n
e
x
am
in
atio
n
at
f
ac
to
r
lo
a
d
in
g
s
,
co
m
p
o
s
ite
r
eliab
ilit
y
(
C
R
)
,
an
d
av
er
ag
e
v
ar
ian
ce
ex
tr
ac
ted
.
Prio
r
to
s
tar
tin
g
th
e
SEM
s
tu
d
y
,
test
s
wer
e
r
u
n
to
co
n
f
ir
m
th
e
m
u
ltico
llin
ea
r
ity
an
d
n
o
r
m
ality
ass
u
m
p
tio
n
s
.
Usi
n
g
Sm
ar
tPLS
s
o
f
twar
e
(
v
er
s
io
n
4
.
0
)
,
th
e
SEM
an
aly
s
is
in
ten
d
ed
to
in
v
esti
g
ate
co
n
n
ec
tio
n
s
b
etwe
en
laten
t
v
ar
iab
les
an
d
d
iv
e
d
ee
p
er
in
to
th
e
p
r
o
p
o
s
ed
m
o
d
el.
C
o
n
f
id
e
n
ce
in
ter
v
als we
r
e
g
en
er
ated
u
s
in
g
b
o
o
ts
tr
ap
p
in
g
to
ass
ess
th
e
im
p
o
r
tan
ce
o
f
th
e
c
o
r
r
elatio
n
s
in
th
e
m
o
d
el
[
2
4
]
,
[
2
5
]
.
4.
RE
SU
L
T
S
4
.
1
.
De
m
o
g
r
a
ph
ic
ba
ck
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ro
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ab
le
1
s
h
o
ws th
at
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lev
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as:
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s
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y
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9
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ajo
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1
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o
f
th
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esp
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n
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n
ts
wer
e
en
r
o
lle
d
in
th
e
B
ac
h
elo
r
o
f
B
u
s
in
ess
Ad
m
in
is
tr
atio
n
(
BBA
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p
r
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,
wh
ile
th
e
r
em
ain
in
g
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9
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e
Ma
s
ter
o
f
B
u
s
in
ess
Ad
m
in
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tr
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MBA
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p
r
o
g
r
am
.
T
ab
le
1
.
Dem
o
g
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ap
h
ic
r
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lts
V
a
r
i
a
b
l
e
La
b
e
l
N
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mb
e
r
P
e
r
c
e
n
t
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g
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(
%)
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M
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mal
e
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1
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4
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6
A
g
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Le
ss
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h
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n
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a
r
s
18
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y
e
a
r
s
23
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2
7
y
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a
r
s
M
o
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h
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n
2
7
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a
r
s
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1
9
53
6
1
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7
6
5
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7
2
9
.
3
3
.
3
C
u
r
r
e
n
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st
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d
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a
r
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a
r
1
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r
2
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r
3
Y
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r
4
27
33
47
74
1
4
.
9
1
8
.
2
2
6
.
0
4
0
.
9
Ed
u
c
a
t
i
o
n
U
n
d
e
r
g
r
a
d
s
t
u
d
e
n
t
s
M
a
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s
t
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e
n
t
s
1
5
4
27
8
5
.
1
1
4
.
9
4
.
2
.
Descript
iv
e
a
na
ly
s
is
T
ab
le
2
s
h
o
ws
th
e
m
ea
n
an
d
s
tan
d
ar
d
d
ev
iatio
n
f
o
r
th
e
v
a
r
iab
les
in
v
esti
g
ated
in
th
is
s
tu
d
y
.
Ge
n
AI
h
ad
th
e
h
ig
h
est
m
ea
n
s
co
r
e
o
f
1
.
0
0
0
o
u
t
o
f
5
.
0
,
with
a
s
tan
d
ar
d
d
ev
iatio
n
o
f
0
.
0
.
T
h
is
s
u
g
g
ests
th
at
r
esp
o
n
d
en
ts
a
g
r
ee
d
th
at
t
h
e
u
s
e
o
f
Gen
AI
e
n
h
an
ce
d
LO
wh
e
n
th
er
e
was
a
h
ig
h
lev
el
o
f
tr
u
s
t
th
at
u
s
in
g
it
h
ad
a
s
ig
n
if
ican
t
im
p
ac
t.
T
h
e
m
ea
n
s
co
r
e
f
o
r
LO
was
0
.
8
4
5
o
u
t
o
f
5
.
0
,
with
a
s
tan
d
ar
d
d
ev
ia
tio
n
o
f
0
.
0
2
8
.
T
h
is
in
d
icate
s
th
at
u
s
in
g
th
e
lear
n
er
’
s
in
ter
ac
tio
n
s
,
s
u
ch
as
click
s
,
n
av
ig
atio
n
p
atter
n
s
,
an
d
tim
e
s
p
en
t
o
n
Gen
AI
,
ca
n
im
p
r
o
v
e
LO
a
n
d
h
av
e
a
lo
n
g
-
ter
m
ef
f
ec
t
o
n
d
if
f
er
en
t
ty
p
es
o
f
ass
ess
m
en
t,
s
u
ch
as
q
u
izze
s
an
d
ass
ig
n
m
en
ts
.
Similar
ly
,
th
e
ES
h
ad
a
m
ea
n
s
co
r
e
o
f
0
.
2
9
1
o
u
t
o
f
5
.
0
,
with
a
s
tan
d
ar
d
d
e
v
iatio
n
o
f
0
.
0
7
8
.
T
h
is
s
u
g
g
ests
th
at
th
e
u
s
e
o
f
Gen
AI
m
ay
d
im
in
is
h
s
tu
d
e
n
ts
’
cr
ea
tiv
ity
.
4
.
3
.
M
ea
s
urem
ent
mo
del
T
h
e
p
u
r
p
o
s
e
o
f
th
is
s
tag
e
wa
s
to
d
eter
m
in
e
th
e
r
eliab
ilit
y
an
d
v
alid
ity
o
f
th
e
m
ea
s
u
r
e
m
en
t
m
o
d
el.
C
o
n
s
tr
u
ct
r
eliab
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y
,
d
is
cr
im
i
n
an
t
v
alid
ity
,
an
d
co
n
v
er
g
en
t
v
alid
ity
wer
e
u
s
ed
to
ass
ess
th
e
m
ea
s
u
r
e
m
en
t
m
o
d
el.
E
ac
h
v
ar
iab
le
in
th
e
s
tu
d
y
was
ev
alu
ated
f
o
r
co
n
s
tr
u
ct
r
eliab
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y
u
s
in
g
its
u
n
iq
u
e
C
r
o
n
b
ac
h
’
s
alp
h
a
co
ef
f
icien
t.
All
v
alu
es
ex
ce
e
d
ed
th
e
r
ec
o
m
m
e
n
d
ed
ac
ce
p
ta
n
ce
cr
iter
ia
o
f
0
.
7
[
2
6
]
.
CR
o
f
th
e
s
tr
u
ctu
r
e
was
also
ex
am
in
ed
,
a
n
d
all
v
alu
es
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ab
o
v
e
0
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7
,
in
d
icatin
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s
atis
f
ac
to
r
y
r
eliab
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y
[
2
6
]
.
T
o
ev
alu
ate
th
e
r
eliab
ilit
y
o
f
th
e
in
d
icato
r
s
,
f
a
cto
r
lo
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in
g
s
wer
e
an
aly
z
ed
.
Acc
o
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d
in
g
to
Su
m
m
er
s
et
a
l
.
[
2
3
]
,
lo
a
d
in
g
s
o
f
0
.
5
o
r
h
ig
h
er
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co
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id
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ac
ce
p
tab
le.
T
h
e
r
esu
lts
in
T
ab
le
2
s
h
o
w
th
at
all
item
s
m
et
th
is
cr
iter
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,
ex
ce
p
t
f
o
r
Gen
AI
2
,
Gen
AI
3
,
Gen
AI
4
,
E
S1
,
E
S2
,
E
S3
,
L
O1
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L
L
S4
,
a
n
d
L
L
S5
.
T
h
ese
item
s
wer
e
r
em
o
v
ed
d
u
e
to
th
eir
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
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t
J
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v
al
&
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d
u
c
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Vo
l
.
15
,
No
.
2
,
Ap
r
il
20
2
6
:
1
4
1
5
-
1
4
2
5
1420
lo
w
lo
ad
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g
s
.
Ad
d
itio
n
ally
,
t
h
e
av
er
a
g
e
v
ar
ia
n
ce
ex
tr
ac
te
d
(
AVE
)
was
ca
lcu
lated
to
d
et
er
m
in
e
co
n
v
er
g
e
n
t
v
alid
ity
,
as
ad
v
is
ed
b
y
Su
m
m
er
s
et
a
l
.
[
2
3
]
.
T
h
e
AVE
v
alu
es
r
an
g
ed
f
r
o
m
0
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6
4
8
to
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o
f
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ich
wer
e
ab
o
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e
0
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5
0
,
in
d
icatin
g
h
ig
h
co
n
v
er
g
e
n
t v
alid
ity
.
T
ab
le
2
.
L
o
ad
in
g
,
m
ea
n
,
s
tan
d
ar
d
d
ev
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n
,
C
r
o
n
b
ac
h
’
s
alp
h
a
,
C
R
an
d
AVE
C
o
n
st
r
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c
t
s
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n
d
i
c
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s
F
a
c
t
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o
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d
i
n
g
(
>
0
.
5
)
M
e
a
n
S
t
a
n
d
a
r
d
d
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a
t
i
o
n
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r
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n
b
a
c
h
’
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l
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a
(
>
0
.
7
)
CR
(
>
0
.
7
)
AVE
(
>
0
.
5
)
Q
2
ES
ES1
1
.
0
0
0
0
.
2
9
1
0
.
0
7
8
1
.
0
0
0
1
.
0
0
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1
.
0
0
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G
e
n
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I
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n
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1
1
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0
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0
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0
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0
0
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1
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0
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0
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LO
LO
2
LO
3
LO
4
0
.
7
8
4
0
.
7
8
6
0
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8
4
5
0
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7
8
0
0
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7
8
0
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8
4
6
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5
2
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0
6
0
0
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0
2
8
0
.
7
2
9
0
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7
3
8
0
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6
4
8
LLS
LLS1
LLS2
LLS3
0
.
7
9
6
0
.
8
5
9
0
.
8
1
9
0
.
7
9
4
0
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8
5
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0
.
8
1
7
0
.
0
5
0
0
.
0
2
6
0
.
0
4
1
0
.
7
6
5
0
.
7
6
5
0
.
6
8
1
4
.
4
.
Dis
cr
im
ina
t
e
v
a
lid
it
y
T
h
r
ee
tech
n
i
q
u
es
wer
e
u
s
ed
t
o
ev
alu
ate
d
is
cr
im
in
a
n
t
v
alid
i
ty
:
cr
o
s
s
-
lo
ad
in
g
s
,
Fo
r
n
ell
-
L
a
r
ck
er
,
an
d
th
e
h
eter
o
t
r
ait
-
m
o
n
o
tr
ait
r
atio
(
HT
MT
)
.
I
n
o
r
d
er
to
em
p
lo
y
th
e
cr
o
s
s
-
lo
ad
in
g
s
s
tr
ateg
y
,
t
h
e
lo
ad
i
n
g
o
f
ea
c
h
in
d
icato
r
m
u
s
t
b
e
g
r
ea
ter
t
h
a
n
th
e
s
u
m
o
f
its
cr
o
s
s
-
lo
ad
in
g
s
.
T
h
e
f
in
d
in
g
s
d
em
o
n
s
tr
ate
d
th
at
th
e
lo
a
d
in
g
o
f
ea
ch
in
d
icato
r
i
n
T
ab
le
3
ex
ce
ed
s
th
e
s
u
m
o
f
its
cr
o
s
s
-
lo
ad
in
g
s
.
T
ab
le
3
.
Dis
cr
im
in
an
t v
ali
d
ity
(
cr
o
s
s
-
lo
ad
in
g
)
V
a
r
i
a
b
l
e
ES
G
e
n
A
I
LO
LLS
ES4
1
.
0
0
0
0
.
1
8
4
0
.
3
4
2
0
.
2
6
1
G
e
n
A
I
1
0
.
1
8
4
1
.
0
0
0
0
.
3
3
3
0
.
4
4
0
LO
2
LO
3
LO
4
0
.
2
7
8
0
.
3
2
6
0
.
2
3
3
0
.
3
2
7
0
.
3
1
4
0
.
2
6
3
0
.
7
8
4
0
.
7
8
6
0
.
8
4
5
0
.
4
5
5
0
.
4
6
3
0
.
6
2
8
LLS1
LLS2
LLS3
0
.
2
5
6
0
.
2
5
8
0
.
1
3
3
0
.
3
6
2
0
.
3
4
0
0
.
3
8
5
0
.
5
4
5
0
.
5
2
5
0
.
5
3
1
0
.
7
9
6
0
.
8
5
9
0
.
8
1
9
A
s
tatis
tical
m
eth
o
d
u
s
ed
to
e
v
alu
ate
th
e
ex
ten
t
t
o
wh
ich
a
m
ea
s
u
r
em
en
t
to
o
l
ac
cu
r
ately
r
ef
lects
th
e
u
n
d
er
ly
i
n
g
c
o
n
ce
p
ts
it
is
in
ten
d
ed
to
m
ea
s
u
r
e
is
k
n
o
wn
as
c
o
n
s
tr
u
ct
v
alid
ity
.
I
t
is
a
cr
u
cial
asp
ec
t
o
f
ass
ess
in
g
th
e
r
eliab
ilit
y
an
d
v
alid
ity
o
f
t
h
e
h
y
p
o
th
esis
test
in
g
in
th
is
s
tu
d
y
.
T
h
e
p
ar
tial
least
s
q
u
ar
es
SEM
(
PLS
-
SEM
)
m
eth
o
d
b
u
ild
s
o
n
estab
lis
h
ed
m
eth
o
d
o
l
o
g
ies
an
d
th
e
Fo
r
n
ell
-
L
ar
ck
er
cr
iter
io
n
f
ac
ilit
ates
m
ea
s
u
r
em
en
t
m
o
d
el
ev
alu
atio
n
[
2
7
]
.
T
h
is
h
el
p
s
d
et
er
m
in
e
if
t
h
er
e
is
a
s
ig
n
if
ica
n
t d
if
f
er
en
ce
b
etwe
en
th
e
v
ar
ia
b
les,
th
u
s
v
alid
atin
g
th
e
o
u
ter
m
o
d
el
’
s
d
is
cr
im
in
an
t
v
alid
ity
.
I
n
o
th
er
wo
r
d
s
,
if
t
h
e
d
iag
o
n
al
c
o
m
p
o
n
en
ts
ar
e
l
ar
g
er
t
h
an
t
h
e
o
t
h
er
elem
en
ts
in
th
e
s
am
e
r
o
w
an
d
co
lu
m
n
,
it
d
em
o
n
s
tr
ates
a
s
u
f
f
icien
t
lev
el
o
f
d
is
tin
ctio
n
b
et
wee
n
th
e
v
ar
iab
les.
Dis
cr
im
in
an
t
v
alid
ity
is
ess
en
tial
f
o
r
th
is
s
tu
d
y
,
as
it
s
u
p
p
o
r
ts
th
e
v
alid
ity
o
f
th
e
h
y
p
o
th
e
s
is
test
in
g
.
T
ab
le
4
in
d
icate
s
ex
ce
llen
t
d
is
cr
im
in
an
t
v
alid
ity
,
as
th
e
s
q
u
ar
e
r
o
o
t
o
f
th
e
av
er
a
g
e
v
a
r
ian
ce
r
etr
i
ev
ed
f
o
r
ea
ch
s
tu
d
y
v
ar
iab
le
is
h
ig
h
er
th
an
th
e
co
r
r
elatio
n
b
etwe
en
th
e
o
th
er
v
ar
i
ab
les
[
2
7
]
.
Fu
r
th
er
m
o
r
e
,
HT
MT
was
u
s
ed
to
ass
ess
d
is
cr
im
in
an
t
v
alid
ity
.
HT
MT
is
a
m
ea
s
u
r
e
o
f
th
e
m
ea
n
co
r
r
elatio
n
s
b
etwe
en
d
if
f
e
r
en
t
co
n
s
tr
u
cts
(
i.e
.
,
h
eter
o
t
r
ait
-
h
e
ter
o
m
eth
o
d
co
r
r
elatio
n
s
)
,
r
at
h
er
th
an
t
h
e
av
e
r
ag
e
co
r
r
elatio
n
s
o
f
in
d
icato
r
s
with
in
th
e
s
am
e
c
o
n
s
tr
u
ct.
Acc
o
r
d
in
g
to
Hair
et
a
l
.
[
2
8
]
,
HT
MT
v
alu
es
ab
o
v
e
0
.
9
0
ca
n
b
e
p
r
o
b
lem
atic.
T
ab
le
5
p
r
esen
ts
th
e
r
esu
lts
o
f
th
e
HT
MT
an
aly
s
is
,
wh
ich
d
em
o
n
s
tr
ated
s
atis
f
ac
to
r
y
d
is
cr
im
in
an
t
v
alid
ity
as
all
v
alu
es
wer
e
b
elo
w
th
e
th
r
esh
o
ld
o
f
0
.
9
0
.
Ov
er
all,
th
e
m
ea
s
u
r
e
m
en
t
m
o
d
el
u
s
ed
in
th
is
s
tu
d
y
ex
h
ib
ited
e
x
ce
llen
t
d
is
cr
im
in
an
t
v
alid
ity
,
as
co
n
f
ir
m
ed
b
y
th
e
c
o
n
v
e
r
g
en
t
v
alid
ity
an
d
HT
MT
an
aly
s
is
.
T
ab
le
4
.
Fo
r
n
ell
–
L
ar
ck
e
r
cr
ite
r
io
n
f
o
r
d
is
cr
im
in
an
t
v
alid
ity
V
a
r
i
a
b
l
e
ES
G
e
n
A
I
LO
LLS
ES
1
.
0
0
0
G
e
n
A
I
0
.
1
8
4
1
.
0
0
0
LO
0
.
3
4
2
0
.
3
3
3
0
.
8
0
5
LLS
0
.
2
6
1
0
.
4
4
0
0
.
6
4
7
0
.
8
2
5
T
ab
le
5
.
HT
MT
d
is
cr
im
in
an
t
v
alid
ity
V
a
r
i
a
b
l
e
ES
G
e
n
A
I
LO
LLS
ES
G
e
n
A
I
0
.
1
8
4
LO
0
.
4
0
6
0
.
3
9
0
LLS
0
.
2
9
9
0
.
5
0
2
0
.
8
5
7
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I
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J
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Fig
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s
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h
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ip
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Gen
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ES
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at
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p
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r
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ized
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ip
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r
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ath
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f
f
icien
ts
an
d
t
h
e
lev
el
o
f
s
ig
n
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ican
ce
(
T
ab
le
5
)
.
W
ith
f
iv
e
m
ain
h
y
p
o
th
eses
in
p
lace
,
th
e
s
tr
u
ctu
r
al
m
o
d
el
ass
es
s
m
en
t
s
h
o
ws
th
e
co
r
r
esp
o
n
d
in
g
h
y
p
o
th
esis
test
s
,
as
s
h
o
wn
in
T
a
b
le
6
an
d
Fig
u
r
e
2
.
LO
is
s
ig
n
if
ican
tl
y
p
r
e
d
icted
b
y
Gen
AI
,
p
r
o
v
id
in
g
s
u
p
p
o
r
t
f
o
r
H1
with
a
s
ig
n
if
ican
ce
lev
el
o
f
p
<
0
.
0
1
.
Similar
ly
,
H2
is
also
ac
c
ep
ted
with
a
s
ig
n
if
ican
ce
lev
el
o
f
p
<0
.
0
1
,
as
it
is
ev
id
en
t
th
at
LO
is
s
ig
n
if
ican
tly
p
r
ed
icted
b
y
ES
.
Ad
d
itio
n
ally
,
it
ca
n
b
e
co
n
clu
d
ed
th
at
LO
h
av
e
a
m
ajo
r
im
p
ac
t
o
n
LLS
,
th
u
s
s
u
p
p
o
r
ti
n
g
H3
with
a
s
ig
n
if
ican
ce
le
v
el
o
f
p
<0
.
0
1
.
Fu
r
th
er
m
o
r
e,
th
e
p
o
s
itiv
e
in
f
l
u
en
ce
o
f
Gen
AI
o
n
LLS
is
also
ev
id
en
t
with
a
s
ig
n
if
ican
ce
le
v
el
o
f
p
<0
.
0
1
,
s
u
p
p
o
r
tin
g
t
h
e
ac
ce
p
tan
ce
o
f
H4
.
Ho
wev
er
,
th
e
ES
is
n
o
t
f
o
u
n
d
to
h
av
e
a
s
ig
n
if
ican
t
im
p
ac
t
o
n
LLS
,
as
in
d
icate
d
b
y
a
s
ig
n
if
ican
ce
lev
el
o
f
p
>0
.
0
5
,
th
u
s
n
o
t su
p
p
o
r
tin
g
H
5
.
T
h
e
d
ir
ec
t
im
p
ac
t
o
f
Gen
AI
o
n
LLS
is
s
ig
n
if
ican
tly
s
tr
o
n
g
er
.
T
h
is
is
s
h
o
wn
b
y
th
e
s
tan
d
ar
d
ized
p
at
h
co
ef
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icien
t,
wh
ich
m
ea
s
u
r
es
th
e
s
tr
en
g
th
o
f
t
h
e
r
elatio
n
s
h
i
p
b
etwe
en
ex
o
g
en
o
u
s
(
ex
ter
n
al)
an
d
en
d
o
g
en
o
u
s
(
in
ter
n
al)
d
im
en
s
io
n
s
.
A
p
p
r
o
x
im
ately
4
7
.
6
%
o
f
th
e
v
ar
ia
tio
n
in
t
h
e
LLS
c
an
b
e
attr
ib
u
ted
to
Gen
AI
.
I
n
co
n
tr
ast,
Gen
AI
ac
co
u
n
ts
f
o
r
o
n
l
y
1
9
.
2
%
o
f
th
e
v
ar
iatio
n
in
th
e
LO
.
Mo
r
eo
v
er
,
th
e
d
i
r
ec
t
ef
f
ec
t
o
f
ES
is
also
s
ig
n
if
ican
t,
ac
co
u
n
tin
g
f
o
r
ap
p
r
o
x
im
ately
1
9
.
2
% o
f
th
e
v
ar
iatio
n
in
th
e
LO
.
I
n
th
is
s
tu
d
y
,
t
h
e
e
f
f
ec
t
s
ize
(
f
2
)
is
an
im
p
o
r
tan
t
m
etr
ic.
Acc
o
r
d
in
g
to
Hair
et
a
l
.
[
2
9
]
,
f
2
s
h
o
ws
th
e
p
r
o
p
o
r
tio
n
ate
im
p
ac
t
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f
a
p
r
e
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ictiv
e
co
n
s
tr
u
ct
o
n
an
e
n
d
o
g
en
o
u
s
co
n
s
tr
u
ct.
C
u
i
et
a
l
.
[
3
0
]
d
ef
in
e
d
f
2
v
al
u
es
o
f
0
.
0
2
,
0
.
1
5
,
o
r
0
.
3
5
as
in
d
ic
atin
g
lo
w,
m
e
d
iu
m
,
o
r
lar
g
e
i
m
p
ac
ts
,
r
esp
ec
tiv
ely
.
T
h
er
ef
o
r
e,
th
e
f
2
r
esu
lts
o
f
th
e
s
tu
d
y
ar
e
cr
u
cial.
B
ased
o
n
th
e
f
2
r
esu
lts
,
th
er
e
a
r
e
lo
w
t
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lar
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e
im
p
ac
ts
o
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s
er
v
e
d
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etw
ee
n
Gen
AI
an
d
L
O
(
f
2
=0
.
0
9
3
)
,
E
S
an
d
L
O
(
f
2
=
0
.
1
0
1
)
,
an
d
L
O
an
d
L
L
S
(
f
2
=0
.
4
7
6
)
.
Ho
wev
e
r
,
th
e
im
p
a
ct
s
ize
o
f
th
e
lin
k
b
etwe
en
Gen
AI
a
n
d
L
L
S
is
lo
wer
(
f
2
=0
.
1
0
6
)
.
Acc
o
r
d
in
g
to
C
u
i
et
a
l
.
[
3
0
]
,
m
u
ltic
o
llin
ea
r
ity
m
u
s
t
b
e
ex
am
in
ed
t
o
en
s
u
r
e
th
at
th
e
e
x
o
g
en
o
u
s
laten
t
co
n
s
tr
u
cts
ar
e
n
o
t
s
ig
n
if
ica
n
tly
in
ter
co
n
n
e
cted
.
T
ab
le
5
s
h
o
ws
th
at
all
v
alu
es
f
o
r
th
e
v
ar
ian
ce
in
f
latio
n
f
ac
to
r
wer
e
less
th
an
5
,
as
s
tated
b
y
Hair
et
a
l
.
[
2
9
]
.
T
h
is
in
d
icate
s
th
at
m
u
ltico
llin
ea
r
ity
is
n
o
t p
r
esen
t in
th
e
ex
ter
n
al
laten
t c
o
n
s
tr
u
cts.
I
n
T
ab
le
5
,
1
9
.
2
%
o
f
th
e
v
a
r
iatio
n
in
LO
ca
n
b
e
ex
p
lain
ed
b
y
Gen
AI
an
d
b
y
ES
.
Ho
wev
er
,
wh
e
n
co
n
s
id
er
in
g
LO
an
d
its
im
p
ac
t
o
n
LLS
,
th
is
p
er
ce
n
tag
e
in
cr
ea
s
es
to
4
7
.
6
%,
in
d
icatin
g
a
g
r
ea
ter
in
f
lu
en
ce
f
r
o
m
ES
a
n
d
th
e
Gen
AI
ef
f
e
ct
co
m
b
in
ed
.
Ad
d
itio
n
ally
,
G
en
AI
ac
co
u
n
ts
f
o
r
4
6
.
6
%
o
f
t
h
e
v
ar
iatio
n
in
th
e
lo
n
g
-
ter
m
ef
f
ec
t,
wh
ich
is
a
ls
o
a
h
ig
h
e
r
p
e
r
ce
n
tag
e.
T
h
er
ef
o
r
e,
it
ca
n
b
e
c
o
n
clu
d
e
d
th
at
Gen
AI
h
as
a
s
ig
n
if
ican
t im
p
ac
t o
n
LO
,
an
d
th
at
b
o
th
Gen
AI
an
d
ES
h
av
e
a
g
r
ea
ter
ef
f
ec
t o
n
LO
w
h
en
c
o
n
s
id
er
ed
to
g
eth
er
.
T
ab
le
6
.
Stru
ctu
r
al
p
ath
a
n
aly
s
is
r
esu
lts
H
y
p
o
t
h
e
s
e
s
S
t
d
.
β
S
a
mp
l
e
m
e
a
n
S
t
a
n
d
a
r
d
d
e
v
i
a
t
i
o
n
t
-
st
a
t
i
s
t
i
c
s
p
-
v
a
l
u
e
s
D
e
c
i
s
i
o
n
R
2
f
2
V
I
F
H
1
:
G
e
n
A
I
-
>
LO
0
.
3
1
2
0
.
2
7
8
0
.
0
8
6
3
.
2
5
3
0
.
0
0
0
A
c
c
e
p
t
e
d
0
.
1
5
7
0
.
1
1
5
1
.
0
3
5
H
2
:
ES
-
>
LO
0
.
2
1
7
0
.
2
9
1
0
.
0
7
8
3
.
7
1
3
0
.
0
0
4
A
c
c
e
p
t
e
d
0
.
1
5
7
0
.
0
5
5
1
.
0
3
5
H
3
:
LO
-
>
LLS
0
.
5
5
2
0
.
5
6
1
0
.
0
8
0
6
.
9
4
4
0
.
0
0
0
A
c
c
e
p
t
e
d
0
.
4
8
1
0
.
4
7
6
1
.
2
3
8
H
4
:
G
e
n
A
I
-
>
LLS
0
.
2
5
1
0
.
2
4
5
0
.
0
7
7
3
.
2
6
8
0
.
0
0
1
A
c
c
e
p
t
e
d
0
.
4
8
1
0
.
1
0
8
1
.
1
3
1
H
5
:
ES
-
>
LLS
0
.
0
5
8
0
.
0
2
2
0
.
0
8
2
0
.
3
0
5
0
.
3
1
4
R
e
j
e
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d
0
.
4
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1
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0
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.
1
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Fig
u
r
e
2
.
Stru
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m
o
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el
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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15
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1422
5.
DIS
CU
SS
I
O
N
T
h
e
f
in
d
in
g
s
o
f
th
is
s
tu
d
y
s
u
p
p
o
r
t
t
h
e
r
elatio
n
s
h
i
p
b
etwe
e
n
Gen
AI
a
n
d
LO
.
T
h
is
alig
n
s
with
th
e
r
esu
lts
o
f
s
ev
er
al
p
r
ev
io
u
s
s
tu
d
ies,
in
clu
d
in
g
th
o
s
e
b
y
L
im
e
t
a
l
.
[
1
1
]
.
Fo
r
i
n
s
tan
ce
,
L
im
et
a
l
.
[
1
1
]
f
o
u
n
d
th
at
Gen
AI
ca
n
h
elp
im
p
r
o
v
e
tea
ch
in
g
a
n
d
lear
n
in
g
.
Similar
ly
,
Du
ah
an
d
Mc
Giv
er
n
[
3
1
]
d
em
o
n
s
tr
ated
th
at
Gen
AI
ca
n
im
p
r
o
v
e
ed
u
ca
tio
n
al
o
u
tco
m
es
th
r
o
u
g
h
p
er
s
o
n
alize
d
s
u
p
p
o
r
t,
th
o
u
g
h
th
ey
c
au
tio
n
th
at
eth
ical
s
af
eg
u
ar
d
s
ar
e
ess
en
tial
to
m
itig
ate
r
is
k
s
o
f
o
v
er
r
elian
ce
an
d
ac
ad
em
ic
m
is
co
n
d
u
ct.
T
h
e
r
esu
lts
ar
e
also
co
n
s
is
ten
t
with
th
e
f
i
n
d
in
g
s
o
f
Kan
o
n
t
et
a
l
.
[
1
2
]
,
wh
o
d
is
co
v
er
ed
t
h
at
ex
p
ec
ted
b
en
ef
its
,
p
er
ce
i
v
ed
u
s
ef
u
ln
ess
,
attitu
d
e
to
war
d
s
te
ch
n
o
lo
g
y
,
a
n
d
b
e
h
av
io
r
al
i
n
ten
tio
n
s
ig
n
if
ican
tly
i
n
f
lu
en
ce
AI
ad
o
p
tio
n
.
F
u
r
t
h
e
r
m
o
r
e
,
B
o
u
b
k
e
r
[
1
8
]
f
o
u
n
d
a
n
A
I
-
b
a
s
e
d
t
o
o
l
i
m
p
r
o
v
e
s
LO
f
o
r
s
t
u
d
e
n
ts
.
K
h
o
d
a
k
a
r
a
m
i
e
t
a
l
.
[
1
6
]
f
o
u
n
d
th
at
tech
n
o
lo
g
y
s
tr
ateg
y
p
lay
s
a
m
e
d
iatin
g
r
o
le
in
th
e
p
er
f
o
r
m
a
n
ce
o
f
h
ig
h
er
e
d
u
ca
tio
n
an
d
HE
I
s
s
h
o
u
ld
b
e
e
q
u
ip
p
e
d
with
th
e
latest
ed
u
ca
tio
n
-
r
elate
d
tech
n
o
lo
g
ies
to
im
p
r
o
v
e
th
eir
p
er
f
o
r
m
a
n
ce
.
T
h
is
s
u
g
g
ests
th
at
s
tu
d
en
ts
at
I
UB
AT
B
u
s
in
es
s
Sch
o
o
l
m
ay
en
h
an
ce
th
eir
lear
n
in
g
ex
p
e
r
ien
ce
th
r
o
u
g
h
th
e
u
s
e
o
f
Gen
AI
.
T
h
er
ef
o
r
e,
t
h
e
f
in
d
in
g
s
o
f
th
is
s
tu
d
y
s
u
p
p
o
r
t
H
1.
T
h
e
r
esu
lts
o
f
t
h
is
s
tu
d
y
co
n
f
ir
m
a
co
r
r
elatio
n
b
etwe
en
ES
an
d
LO
wh
e
n
u
tili
zin
g
Gen
AI
f
o
r
lear
n
in
g
.
I
t
was
f
o
u
n
d
t
h
at
s
t
u
d
en
ts
ar
e
h
ig
h
ly
m
o
tiv
ated
t
o
ex
p
lo
it
p
la
g
iar
is
m
wh
en
u
s
in
g
th
is
to
o
l.
T
h
is
alig
n
s
with
th
e
r
esu
lts
o
f
Ng
u
y
en
et
a
l
.
[
1
9
]
.
Fo
r
in
s
tan
ce
,
Ng
u
y
en
et
a
l
.
[
1
9
]
f
o
u
n
d
th
at
s
tu
d
en
ts
ex
ten
s
iv
ely
u
s
ed
C
h
atGPT
f
o
r
lear
n
in
g
.
Ho
wev
er
,
th
e
r
e
wer
e
also
co
n
ce
r
n
s
ab
o
u
t
d
im
in
is
h
ed
c
r
ea
tiv
ity
,
ac
ad
em
i
c
d
is
h
o
n
esty
,
a
n
d
eth
ical
is
s
u
es
s
u
ch
as
in
f
o
r
m
atio
n
s
ec
u
r
ity
an
d
p
lag
iar
is
m
.
T
h
is
s
u
g
g
ests
th
at
s
tu
d
en
ts
at
I
UB
AT
B
u
s
in
ess
Sch
o
o
l
m
ay
m
o
tiv
ate
s
tu
d
en
ts
to
en
h
an
ce
th
eir
lear
n
in
g
ex
p
er
ien
ce
th
r
o
u
g
h
th
e
u
s
e
o
f
Gen
AI
wh
ile
m
ain
tain
in
g
ES
.
T
h
er
ef
o
r
e,
th
e
f
i
n
d
in
g
s
o
f
th
is
s
tu
d
y
s
u
p
p
o
r
t
H
2.
T
h
e
f
in
d
in
g
s
o
f
th
is
s
tu
d
y
s
u
p
p
o
r
t th
e
r
elatio
n
s
h
i
p
b
etwe
en
LO
an
d
t
h
e
lo
n
g
-
ter
m
ef
f
ec
ts
.
T
h
is
alig
n
s
with
th
e
r
esu
lts
o
f
W
en
g
et
a
l
.
[
1
5
]
.
Fo
r
in
s
tan
ce
,
W
en
g
et
a
l
.
[
1
5
]
co
n
clu
d
e
d
th
at
life
lo
n
g
lear
n
in
g
s
k
ills
ar
e
b
ec
o
m
in
g
in
cr
ea
s
in
g
ly
cr
u
cia
l
in
Gen
AI
-
f
ac
ilit
ated
LO
.
T
h
is
s
u
g
g
ests
th
at
s
tu
d
en
ts
at
I
UB
AT
B
u
s
in
ess
Sch
o
o
l
m
ay
en
h
a
n
ce
th
eir
LO
th
r
o
u
g
h
th
e
u
s
e
o
f
Gen
AI
,
in
o
r
d
er
to
im
p
r
o
v
e
LLS
.
T
h
er
ef
o
r
e,
th
e
f
in
d
i
n
g
s
o
f
th
is
s
tu
d
y
s
u
p
p
o
r
t
H
3.
Similar
ly
,
th
e
f
i
n
d
in
g
s
o
f
th
is
s
tu
d
y
also
s
u
p
p
o
r
t
th
e
r
elatio
n
s
h
ip
b
etwe
en
Ge
n
AI
a
n
d
LLS
.
T
h
is
is
in
lin
e
with
th
e
r
esu
lts
o
f
W
en
g
et
a
l
.
[
1
5
]
,
wh
o
d
is
co
v
e
r
ed
th
at
th
e
u
s
e
o
f
Gen
AI
h
as
led
to
th
e
d
ev
el
o
p
m
en
t
o
f
a
d
iv
er
s
e
r
an
g
e
o
f
tar
g
ete
d
LO
,
in
clu
d
in
g
ess
en
tial
LLS
an
d
ca
r
ee
r
-
o
r
ie
n
ted
co
m
p
ete
n
cies.
T
h
is
in
d
icate
s
th
at
s
tu
d
en
ts
at
I
UB
AT
B
u
s
in
ess
Sch
o
o
l
co
u
ld
en
h
a
n
ce
th
eir
LO
th
r
o
u
g
h
th
e
u
s
e
o
f
Gen
AI
,
u
ltima
tely
im
p
r
o
v
in
g
th
eir
life
lo
n
g
lea
r
n
in
g
s
k
ills
.
T
h
er
ef
o
r
e
,
th
e
f
i
n
d
in
g
s
o
f
th
is
s
tu
d
y
s
u
p
p
o
r
t
H
4.
T
h
is
s
tu
d
y
aim
s
to
in
v
esti
g
ate
th
e
r
elatio
n
s
h
ip
b
etwe
en
LO
an
d
th
e
u
s
e
o
f
Gen
AI
in
h
ig
h
e
r
ed
u
ca
tio
n
.
Ad
d
itio
n
ally
,
it
aim
s
to
ex
p
lo
r
e
th
e
im
p
ac
t
o
f
Gen
AI
o
n
th
e
d
e
v
elo
p
m
e
n
t
o
f
LLS
.
T
h
ese
r
esear
ch
f
in
d
in
g
s
will
co
n
tr
ib
u
te
to
th
e
ex
is
tin
g
b
o
d
y
o
f
liter
atu
r
e
an
d
p
r
o
v
id
e
a
th
eo
r
etica
l
co
n
tr
i
b
u
tio
n
t
o
th
e
f
ield
.
T
h
e
p
r
ac
tical
im
p
licatio
n
s
o
f
t
h
is
s
tu
d
y
s
u
g
g
est
th
at
th
e
u
s
e
o
f
Gen
AI
,
wh
en
u
s
ed
eth
icall
y
,
ca
n
en
h
a
n
ce
LO
f
o
r
s
tu
d
e
n
ts
in
h
ig
h
er
ed
u
ca
t
io
n
.
Fu
r
t
h
er
m
o
r
e,
it
ca
n
ai
d
in
th
e
d
ev
elo
p
m
en
t
o
f
LLS
.
B
y
id
en
tify
in
g
th
e
in
f
lu
en
ce
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f
Gen
AI
o
n
LO
an
d
LLS
,
th
is
s
tu
d
y
will p
r
o
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id
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v
alu
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h
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ca
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s
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d
p
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licy
m
ak
e
r
s
.
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er
all,
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co
n
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ib
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e
u
n
d
er
s
tan
d
in
g
o
f
t
h
e
p
o
ten
tial
b
en
ef
its
o
f
in
co
r
p
o
r
atin
g
Gen
AI
in
to
h
ig
h
er
e
d
u
ca
tio
n
.
6.
CO
NCLU
SI
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N
T
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f
in
d
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o
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s
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n
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er
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tili
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g
Gen
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,
as
s
tu
d
en
ts
m
ay
b
e
tem
p
te
d
to
m
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u
s
e
th
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to
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ls
f
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r
ac
ad
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o
n
e
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ty
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wev
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r
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Ge
n
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n
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r
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n
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r
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tiv
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lear
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r
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r
e,
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g
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ter
m
e
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f
ec
ts
o
f
Gen
AI
u
s
ag
e
ar
e
p
r
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m
is
in
g
,
as it c
o
n
tr
ib
u
tes to
th
e
d
e
v
elo
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m
en
t o
f
ess
en
tial
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.
T
h
e
r
esear
ch
is
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ased
o
n
a
s
p
ec
if
ic
ed
u
ca
tio
n
al
in
s
titu
tio
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,
wh
ich
m
ay
lim
it
th
e
g
en
er
ali
za
b
ilit
y
o
f
th
e
f
in
d
in
g
s
to
o
th
er
c
o
n
te
x
ts
o
r
p
o
p
u
latio
n
s
.
T
h
e
eth
ical
im
p
licatio
n
s
o
f
Gen
AI
u
s
ag
e,
p
ar
ticu
lar
ly
co
n
ce
r
n
in
g
ac
ad
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m
ic
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r
it
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r
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ir
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o
n
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o
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g
ex
a
m
in
atio
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an
d
d
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s
s
io
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Fu
tu
r
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h
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aim
t
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p
lo
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e
th
e
l
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g
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ter
m
im
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ac
t
s
o
f
Gen
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ed
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ca
tio
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ettin
g
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b
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n
d
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UB
AT
B
u
s
in
ess
Sch
o
o
l.
Ad
d
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ally
,
it
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b
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wh
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Fu
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i
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v
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t
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u
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h
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d
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ca
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RE
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NC
E
S
[
1
]
S
.
K
e
l
l
y
,
S
.
-
A
.
K
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y
e
,
a
n
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O
.
O
v
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o
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Tr
e
s
p
a
l
a
c
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s,
“
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h
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sy
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t
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t
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s
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7
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2
5
.
[
2
]
G
.
K
u
r
t
z
e
t
a
l
.
,
“
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t
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o
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r
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s,
”
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d
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.
[
3
]
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-
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mr
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,
H
.
M
.
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sh
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[
4
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Z.
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me
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Re
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v
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.
[
5
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Y
.
Ji
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Y
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V
.
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M
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e
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v
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A
I
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h
i
g
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e
r
e
d
u
c
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t
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o
n
:
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g
l
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b
a
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e
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t
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v
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n
d
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d
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n
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C
o
m
p
u
t
e
rs
&
E
d
u
c
a
t
i
o
n
:
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t
i
f
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c
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j
.
c
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e
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i
.
2
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4
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0
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4
8
.
[
6
]
R
.
M
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c
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-
V
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d
u
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t
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g
:
c
a
n
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t
o
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s
t
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t
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m
e
s?
”
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x
p
e
rt
S
y
s
t
e
m
s
w
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t
h
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p
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6
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.
e
sw
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2
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3
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2
1
8
2
0
.
[
19
]
T.
N
.
T.
N
g
u
y
e
n
,
N
.
V.
L
a
i
,
a
n
d
Q
.
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g
u
y
e
n
,
“
A
r
t
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f
i
c
i
a
l
i
n
t
e
l
l
i
g
e
n
c
e
(
A
I
)
i
n
e
d
u
c
a
t
i
o
n
:
a
c
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se
s
t
u
d
y
o
n
C
h
a
t
G
P
T’
s
i
n
f
l
u
e
n
c
e
o
n
st
u
d
e
n
t
l
e
a
r
n
i
n
g
b
e
h
a
v
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o
r
s,”
E
d
u
c
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t
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o
n
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l
Pr
o
c
e
ss
I
n
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rn
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t
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l
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p
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j
.
2
0
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4
.
1
3
2
.
7
.
[
20
]
N
.
H
a
s
h
mi
a
n
d
A
.
S
.
B
a
l
,
“
G
e
n
e
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a
t
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v
e
A
I
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n
h
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g
h
e
r
e
d
u
c
a
t
i
o
n
a
n
d
b
e
y
o
n
d
,
”
B
u
si
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e
ss
H
o
r
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z
o
n
s
,
v
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l
.
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7
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o
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5
,
p
p
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0
7
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4
,
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4
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6
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j
.
b
u
s
h
o
r
.
2
0
2
4
.
0
5
.
0
0
5
.
[
21
]
R
.
E.
M
i
l
l
e
r
,
“
P
a
n
d
o
r
a
’
s
c
a
n
o
f
w
o
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m
s:
a
y
e
a
r
o
f
g
e
n
e
r
a
t
i
v
e
A
I
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
,
”
p
o
r
t
a
l
:
L
i
b
ra
ri
e
s
a
n
d
t
h
e
Ac
a
d
e
m
y
,
v
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l
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4
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o
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,
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p
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–
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4
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n
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4
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:
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0
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3
5
3
/
p
l
a
.
2
0
2
4
.
a
9
1
6
9
8
8
.
[
22
]
N
.
G
u
i
l
l
é
n
-
Y
p
a
r
r
e
a
a
n
d
F
.
H
e
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n
á
n
d
e
z
-
R
o
d
r
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g
u
e
z
,
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U
n
v
e
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l
i
n
g
g
e
n
e
r
a
t
i
v
e
A
I
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
:
i
n
si
g
h
t
s
f
r
o
m
e
n
g
i
n
e
e
r
i
n
g
st
u
d
e
n
t
s
a
n
d
p
r
o
f
e
sso
r
s,
”
i
n
2
0
2
4
I
EEE
G
l
o
b
a
l
En
g
i
n
e
e
ri
n
g
E
d
u
c
a
t
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o
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n
f
e
re
n
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e
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U
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O
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)
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y
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4
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p
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–
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C
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N
6
0
3
1
2
.
2
0
2
4
.
1
0
5
7
8
8
7
6
.
[
23
]
A
.
S
u
mm
e
r
s,
M
.
El
H
a
d
d
a
d
,
R
.
P
r
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c
h
a
r
d
,
K
.
-
A
.
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l
a
r
k
e
,
J.
Le
e
,
a
n
d
F
.
O
p
r
e
scu
,
“
N
a
v
i
g
a
t
i
n
g
c
h
a
l
l
e
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g
e
s
a
n
d
o
p
p
o
r
t
u
n
i
t
i
e
s
:
n
u
r
si
n
g
st
u
d
e
n
t
’
s
v
i
e
w
s
o
n
g
e
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e
r
a
t
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v
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A
I
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n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
,
”
N
u
rse
E
d
u
c
a
t
i
o
n
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n
Pr
a
c
t
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c
e
,
v
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l
.
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9
,
p
.
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0
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0
6
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g
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4
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d
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6
/
j
.
n
e
p
r
.
2
0
2
4
.
1
0
4
0
6
2
.
[
24
]
F
.
M
a
g
n
o
,
F
.
C
a
ssi
a
,
a
n
d
C
.
M
.
R
i
n
g
l
e
,
“
A
b
r
i
e
f
r
e
v
i
e
w
o
f
p
a
r
t
i
a
l
l
e
a
st
sq
u
a
r
e
s
st
r
u
c
t
u
r
a
l
e
q
u
a
t
i
o
n
m
o
d
e
l
i
n
g
(
P
LS
-
S
EM
)
u
se
i
n
q
u
a
l
i
t
y
m
a
n
a
g
e
me
n
t
st
u
d
i
e
s,”
T
h
e
T
Q
M
J
o
u
rn
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l
,
v
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l
.
3
6
,
n
o
.
5
,
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p
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2
4
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,
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y
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4
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o
i
:
1
0
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1
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8
/
TQ
M
-
06
-
2
0
2
2
-
0
1
9
7
.
[
25
]
N
.
N
.
V
a
l
l
e
e
t
a
l
.
,
“
M
o
d
e
l
i
n
g
l
e
a
r
n
e
r
s’
b
e
h
a
v
i
o
r
a
l
i
n
t
e
n
t
i
o
n
t
o
w
a
r
d
u
s
i
n
g
a
r
t
i
f
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c
i
a
l
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t
e
l
l
i
g
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n
c
e
i
n
e
d
u
c
a
t
i
o
n
,
”
S
o
c
i
a
l
S
c
i
e
n
c
e
s
&
H
u
m
a
n
i
t
i
e
s Op
e
n
,
v
o
l
.
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0
,
p
.
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0
1
1
6
7
,
2
0
2
4
,
d
o
i
:
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0
.
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0
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6
/
j
.
ssa
h
o
.
2
0
2
4
.
1
0
1
1
6
7
.
[
26
]
L.
G
.
F
o
o
,
H
.
R
a
h
ma
n
i
,
a
n
d
J
.
L
i
u
,
“
A
I
-
g
e
n
e
r
a
t
e
d
c
o
n
t
e
n
t
(
A
I
G
C
)
f
o
r
v
a
r
i
o
u
s
d
a
t
a
mo
d
a
l
i
t
i
e
s:
a
su
r
v
e
y
,
”
AC
M
C
o
m
p
u
t
i
n
g
S
u
r
v
e
y
s
,
v
o
l
.
5
7
,
n
o
.
9
,
p
p
.
1
–
6
6
,
S
e
p
.
2
0
2
5
,
d
o
i
:
1
0
.
1
1
4
5
/
3
7
2
8
6
3
3
.
[
27
]
J.
F
.
H
a
i
r
,
M
.
S
a
r
st
e
d
t
,
C
.
M
.
R
i
n
g
l
e
,
P
.
N
.
S
h
a
r
m
a
,
a
n
d
B
.
D
.
Li
e
n
g
a
a
r
d
,
“
G
o
i
n
g
b
e
y
o
n
d
t
h
e
u
n
t
o
l
d
f
a
c
t
s
i
n
P
LS
–
S
E
M
a
n
d
mo
v
i
n
g
f
o
r
w
a
r
d
,
”
E
u
ro
p
e
a
n
J
o
u
r
n
a
l
o
f
M
a
rke
t
i
n
g
,
v
o
l
.
5
8
,
n
o
.
1
3
,
p
p
.
8
1
–
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0
6
,
D
e
c
.
2
0
2
4
,
d
o
i
:
1
0
.
1
1
0
8
/
EJ
M
-
08
-
2
0
2
3
-
0
6
4
5
.
[
28
]
J.
F
.
H
a
i
r
,
M
.
C
.
H
o
w
a
r
d
,
a
n
d
C
.
N
i
t
z
l
,
“
A
ss
e
ssi
n
g
m
e
a
s
u
r
e
m
e
n
t
mo
d
e
l
q
u
a
l
i
t
y
i
n
P
LS
-
S
E
M
u
s
i
n
g
c
o
n
f
i
r
mat
o
r
y
c
o
m
p
o
s
i
t
e
a
n
a
l
y
si
s
,
”
J
o
u
r
n
a
l
o
f
B
u
si
n
e
ss
Re
s
e
a
r
c
h
,
v
o
l
.
1
0
9
,
p
p
.
1
0
1
–
1
1
0
,
M
a
r
.
2
0
2
0
,
d
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i
:
1
0
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1
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6
/
j
.
j
b
u
sr
e
s.
2
0
1
9
.
1
1
.
0
6
9
.
[
29
]
J.
F
.
H
a
i
r
,
R
.
E.
A
n
d
e
r
s
o
n
,
a
n
d
R
.
L.
Ta
t
h
a
m
,
Mu
l
t
i
v
a
ri
a
t
e
d
a
t
a
a
n
a
l
y
si
s
w
i
t
h
re
a
d
i
n
g
s
,
2
n
d
e
d
.
N
e
w
Y
o
r
k
:
M
a
c
mi
l
l
a
n
P
u
b
l
i
s
h
i
n
g
C
o
.
,
I
n
c
.
,
1
9
8
6
.
[
30
]
L.
C
u
i
,
H
.
J
i
a
n
g
,
H
.
D
e
n
g
,
a
n
d
T
.
Z
h
a
n
g
,
“
Th
e
i
n
f
l
u
e
n
c
e
o
f
t
h
e
d
i
f
f
u
si
o
n
o
f
f
o
o
d
s
a
f
e
t
y
i
n
f
o
r
ma
t
i
o
n
t
h
r
o
u
g
h
so
c
i
a
l
me
d
i
a
o
n
c
o
n
su
mers
’
p
u
r
c
h
a
se
i
n
t
e
n
t
i
o
n
s,
”
D
a
t
a
T
e
c
h
n
o
l
o
g
i
e
s a
n
d
A
p
p
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c
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t
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s
,
v
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l
.
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3
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o
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,
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p
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u
n
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9
,
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o
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1
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8
/
D
TA
-
05
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2
0
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8
-
0
0
4
6
.
[
31
]
J.
E.
D
u
a
h
a
n
d
P
.
M
c
G
i
v
e
r
n
,
“
H
o
w
g
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r
a
t
i
v
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a
r
t
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f
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c
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e
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t
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t
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v
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si
t
y
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sa
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o
l
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c
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e
s,
”
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n
t
e
r
n
a
t
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o
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l
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o
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-
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3
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.
B
I
O
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RAP
H
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AUTH
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Mo
z
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r
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ist
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ro
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sin
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tern
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(AM
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ies
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s
so
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(S
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witze
rlan
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He
c
a
n
b
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c
o
n
tac
ted
a
t
e
m
a
il
:
m
c
h
o
w
d
h
u
ry
@
iu
b
a
t.
e
d
u
.
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