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li
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ly
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h
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ll
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ts,
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ted
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ts
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fl
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g
b
e
h
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v
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ra
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m
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ti
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n
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rd
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io
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stro
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rs o
f
a
d
o
p
ti
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n
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ly
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u
n
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e
m
e
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ler,
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a
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ly
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o
t
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ss
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n
d
p
e
rc
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d
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se
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U)
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is
stu
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tri
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tes
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n
d
e
q
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ly
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g
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te
G
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n
AI
tec
h
n
o
l
o
g
ies
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n
to
a
c
a
d
e
m
ic ec
o
sy
ste
m
s.
K
ey
w
o
r
d
s
:
AHP
AI
in
ed
u
ca
tio
n
E
T
AM
E
th
ical
AI
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s
e
Fu
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DE
MA
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Gen
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AI
ad
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atic
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is
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rticle
u
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d
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e
CC B
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SA
li
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e
n
se
.
C
o
r
r
e
s
p
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ing
A
uth
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r
:
Ken
Go
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r
o
C
o
lleg
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f
T
ec
h
n
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lo
g
y
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C
eb
u
T
ec
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n
o
lo
g
ical
Un
iv
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s
ity
-
C
ar
m
en
C
am
p
u
s
R
.
M.
Du
r
an
o
Av
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u
e,
6
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C
ar
m
en
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C
eb
u
,
Ph
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p
in
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m
ail:
k
en
.
g
o
r
r
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@
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p
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1.
I
NT
RO
D
UCT
I
O
N
T
h
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in
teg
r
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f
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tific
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tellig
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AI
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i
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to
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tio
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al
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titu
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b
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f
AI
-
d
r
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n
tech
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l
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ies
[
1
]
.
Am
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ese
in
n
o
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s
,
C
h
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—
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s
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R
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ter
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o
f
f
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in
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s
er
v
ices
s
u
ch
Evaluation Warning : The document was created with Spire.PDF for Python.
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[
2
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,
[
3
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ea
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ar
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[
4
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,
an
d
lib
r
a
r
y
an
d
in
f
o
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m
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s
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v
ices
[
5
]
.
W
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in
ed
u
ca
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d
,
u
s
e,
an
d
c
r
itically
ass
ess
AI
s
y
s
tem
s
an
d
th
eir
b
r
o
a
d
er
s
o
cieta
l im
p
ac
t.
Dev
elo
p
in
g
AI
liter
ac
y
in
v
o
lv
es
m
aster
in
g
co
n
ce
p
ts
,
m
eth
o
d
o
lo
g
ies,
a
n
d
d
ec
is
io
n
-
m
ak
i
n
g
f
r
am
ewo
r
k
s
in
AI
,
as
well
as
cr
itically
ev
alu
atin
g
th
ese
s
y
s
tem
s
an
d
th
eir
im
p
licatio
n
s
[
6
]
,
[
7
]
.
I
t
also
en
co
m
p
ass
es
u
n
d
er
s
tan
d
i
n
g
t
h
e
leg
al,
eth
ical,
a
n
d
s
o
cieta
l
d
im
en
s
io
n
s
o
f
AI
tech
n
o
lo
g
ies
an
d
ef
f
ec
tiv
ely
en
g
ag
in
g
in
d
is
co
u
r
s
e
ar
o
u
n
d
th
ese
to
p
ics
[
8
]
.
As
a
n
ac
ce
s
s
ib
le
an
d
in
ter
ac
tiv
e
p
latf
o
r
m
,
C
h
atGPT
ca
n
em
p
o
wer
b
o
t
h
ed
u
ca
to
r
s
an
d
lear
n
er
s
to
b
etter
n
av
ig
ate
a
n
d
p
ar
ticip
ate
in
th
e
ev
o
lv
in
g
lan
d
s
ca
p
e
o
f
AI
.
I
n
p
r
e
v
io
u
s
r
e
p
o
r
ts
[
9
]
,
[
1
0
]
,
C
h
atGPT
h
as
b
ee
n
d
escr
ib
e
d
as
tr
an
s
f
o
r
m
ativ
e,
ac
h
ie
v
in
g
wid
esp
r
ea
d
u
s
e
with
in
6
m
o
n
t
h
s
o
f
its
lau
n
c
h
an
d
s
ettin
g
a
n
ew
r
ec
o
r
d
f
o
r
u
s
er
a
d
o
p
tio
n
.
I
ts
in
cr
ea
s
in
g
p
o
p
u
lar
ity
am
o
n
g
u
n
iv
er
s
ity
s
tu
d
e
n
ts
an
d
tech
-
f
o
r
war
d
in
d
u
s
tr
ies
h
as
s
p
ar
k
ed
d
e
b
ate:
s
h
o
u
ld
C
h
atGPT
b
e
r
estricte
d
as
a
p
o
s
s
ib
le
en
ab
ler
o
f
ac
a
d
em
ic
d
is
h
o
n
esty
,
o
r
em
b
r
ac
ed
f
o
r
its
p
o
ten
tial
to
e
n
h
an
ce
lear
n
in
g
ef
f
icien
cy
a
n
d
q
u
ality
?
E
d
u
ca
tio
n
h
as
lo
n
g
b
ee
n
in
f
o
r
m
ed
b
y
f
o
u
n
d
atio
n
al
th
eo
r
ies
s
u
ch
as
co
n
s
tr
u
cti
v
is
m
,
b
eh
av
io
r
is
m
,
s
itu
ated
co
g
n
itio
n
,
s
o
cio
-
cu
ltu
r
al
th
eo
r
y
,
co
g
n
itiv
e
lo
ad
th
e
o
r
y
,
u
n
i
v
er
s
al
d
esig
n
f
o
r
lear
n
in
g
(
UDL
)
,
cr
itical
r
ac
e
th
eo
r
y
,
s
o
cial
lear
n
in
g
t
h
eo
r
y
,
s
elf
-
ef
f
icac
y
th
eo
r
y
,
an
d
s
elf
-
d
eter
m
in
atio
n
th
e
o
r
y
.
T
h
ese
f
r
am
ewo
r
k
s
,
th
o
u
g
h
m
et
with
v
ar
ied
o
p
in
i
o
n
s
,
h
av
e
s
h
ap
ed
in
s
tr
u
ctio
n
a
l
d
esig
n
an
d
p
ed
ag
o
g
y
o
v
e
r
tim
e.
Similar
ly
,
th
e
em
er
g
en
ce
o
f
to
o
ls
lik
e
C
h
atGPT
is
n
o
w
s
u
b
tly
r
esh
ap
in
g
th
e
teac
h
in
g
an
d
lear
n
in
g
lan
d
s
ca
p
e.
W
h
ile
Gen
AI
is
s
ti
ll
m
atu
r
in
g
,
it
is
s
tead
il
y
in
f
lu
en
cin
g
ed
u
ca
tio
n
al
p
r
a
ctice
an
d
p
o
licy
.
T
h
is
p
r
o
g
r
e
s
s
io
n
r
aises
cr
it
ical
q
u
esti
o
n
s
ab
o
u
t
its
b
r
o
ad
er
i
m
p
licatio
n
s
.
Fo
r
in
s
tan
ce
,
wh
ile
C
h
atGPT
d
o
es
n
o
t
u
n
d
er
m
in
e
all
ex
is
tin
g
lear
n
in
g
th
eo
r
ies,
it
ap
p
ea
r
s
to
alig
n
with
s
o
m
e
—
p
ar
ticu
lar
ly
s
elf
-
ef
f
icac
y
an
d
s
elf
-
d
e
ter
m
in
atio
n
th
eo
r
y
.
T
h
ese
m
o
d
els
s
u
g
g
est
th
at
le
ar
n
er
s
with
s
u
f
f
icien
t
f
o
u
n
d
a
tio
n
al
k
n
o
wled
g
e
an
d
in
tr
in
s
ic
m
o
tiv
atio
n
m
ay
b
en
ef
it
m
o
r
e
f
r
o
m
C
h
atGPT
’
s
im
m
ed
iate
f
ee
d
b
ac
k
th
a
n
tr
ad
itio
n
al
in
s
tr
u
ctio
n
.
Fin
ally
,
th
is
ev
o
lu
tio
n
also
p
r
o
m
p
ts
im
p
o
r
tan
t
wo
r
k
f
o
r
ce
co
n
s
id
er
atio
n
s
:
s
h
o
u
ld
o
r
g
a
n
izatio
n
s
r
ed
u
ce
r
elian
ce
o
n
r
o
les
s
u
s
ce
p
tib
le
to
au
to
m
atio
n
,
o
r
in
s
tead
p
r
io
r
it
ize
h
ir
in
g
in
d
iv
id
u
als
wh
o
c
an
in
teg
r
ate
AI
to
o
ls
lik
e
C
h
atGPT
to
en
h
an
ce
p
r
o
d
u
ctiv
ity
[
1
1
]
?
T
h
is
s
tu
d
y
f
o
cu
s
es o
n
th
e
f
o
llo
win
g
r
esear
ch
q
u
esti
o
n
s
:
−
Ho
w
d
o
es
u
n
iv
er
s
ity
s
u
p
p
o
r
t
(
US)
in
f
lu
en
ce
s
tu
d
en
ts
’
a
n
d
teac
h
er
s
’
awa
r
e
n
ess
,
p
er
ce
iv
ed
ea
s
e
o
f
u
s
e
(
PEU)
,
an
d
in
te
n
tio
n
to
a
d
o
p
t
Gen
AI
to
o
ls
in
ed
u
ca
ti
o
n
al
s
ettin
g
s
?
−
W
h
at
s
p
ec
if
ic
U
S
m
ec
h
an
is
m
s
ca
n
b
e
im
p
lem
en
ted
to
b
r
id
g
e
th
e
g
ap
in
awa
r
e
n
ess
an
d
ef
f
ec
tiv
e
u
tili
za
tio
n
o
f
Gen
AI
t
o
o
ls
am
o
n
g
s
tu
d
en
ts
an
d
ed
u
ca
t
o
r
s
?
−
Ho
w
d
o
attitu
d
es
to
war
d
Gen
AI
an
d
p
er
ce
i
v
ed
u
s
ef
u
ln
ess
(
PU)
in
f
lu
en
ce
th
e
r
elatio
n
s
h
i
p
b
etwe
en
US
an
d
in
ten
tio
n
to
u
s
e
(
I
U)
Gen
AI
to
o
ls
in
ed
u
ca
tio
n
?
T
h
is
s
tu
d
y
u
tili
ze
s
a
co
m
b
in
at
io
n
o
f
a
n
aly
tical
h
ier
ar
ch
y
p
r
o
ce
s
s
(
AHP)
,
f
u
zz
y
d
ec
is
io
n
-
m
ak
in
g
tr
ial
an
d
ev
alu
atio
n
lab
o
r
ato
r
y
(
Fu
zz
y
DE
MA
T
E
L
)
,
th
e
ex
ten
d
ed
tech
n
o
lo
g
y
ac
ce
p
tan
ce
m
o
d
el
(
E
T
AM
)
,
an
d
th
em
atic
an
aly
s
is
to
co
m
p
r
eh
en
s
iv
ely
ex
a
m
in
e
th
e
ad
o
p
tio
n
o
f
Gen
AI
in
e
d
u
ca
ti
o
n
.
E
ac
h
o
f
th
ese
m
eth
o
d
o
l
o
g
ies
b
r
in
g
s
u
n
iq
u
e
s
tr
en
g
th
s
,
allo
win
g
f
o
r
a
r
o
b
u
s
t
ex
p
lo
r
atio
n
o
f
th
e
f
ac
t
o
r
s
in
f
lu
en
cin
g
a
d
o
p
tio
n
.
AHP
i
s
em
p
lo
y
ed
to
p
r
io
r
itiz
e
cr
itical
v
ar
iab
les
s
u
ch
as
att
itu
d
e
to
war
d
s
g
en
er
ativ
e
AI
,
I
U,
PU
,
an
d
o
th
er
s
.
T
h
r
o
u
g
h
p
air
wis
e
co
m
p
ar
is
o
n
s
an
d
th
e
ca
lcu
latio
n
o
f
p
r
i
o
r
ity
weig
h
ts
,
AHP
s
y
s
tem
atica
lly
id
en
tifie
s
th
e
m
o
s
t
in
f
lu
en
tial
f
ac
to
r
s
,
wit
h
attitu
d
e
to
wa
r
d
s
g
e
n
er
ati
v
e
(
AT
G
)
a
n
d
I
U
em
e
r
g
in
g
as
k
e
y
d
r
iv
er
s
.
Ad
d
itio
n
ally
,
th
e
c
o
n
s
is
ten
cy
r
atio
(
C
R
)
en
s
u
r
es
th
e
r
eliab
il
ity
o
f
th
e
p
air
wis
e
ju
d
g
m
e
n
ts
,
ad
d
in
g
r
ig
o
r
to
th
e
p
r
io
r
itizatio
n
p
r
o
ce
s
s
.
Fu
zz
y
DE
MA
T
E
L
c
o
m
p
le
m
en
ts
AHP
b
y
a
n
aly
zin
g
ca
u
s
al
r
elatio
n
s
h
ip
s
b
etwe
e
n
v
ar
ia
b
les,
d
is
tin
g
u
is
h
in
g
b
etwe
en
in
f
lu
e
n
tial
f
ac
to
r
s
(
e.
g
.
,
PU
an
d
AT
G)
an
d
t
h
o
s
e
th
at
ar
e
m
o
r
e
in
f
lu
en
ce
d
b
y
o
th
er
s
(
e.
g
.
,
awa
r
en
ess
an
d
US
)
.
I
t
s
p
r
o
m
in
e
n
ce
a
n
d
r
elatio
n
s
co
r
es
p
r
o
v
id
e
cr
itical
in
s
ig
h
t
s
in
to
th
e
d
y
n
am
ic
in
ter
d
ep
en
d
en
cies
am
o
n
g
v
a
r
iab
les,
g
u
id
in
g
s
tr
ateg
ic
ef
f
o
r
t
s
to
ad
d
r
ess
ad
o
p
tio
n
b
ar
r
ier
s
.
T
h
e
in
teg
r
atio
n
o
f
f
u
zz
y
lo
g
ic
i
n
th
is
m
eth
o
d
a
llo
ws
f
o
r
th
e
in
co
r
p
o
r
atio
n
o
f
s
u
b
jectiv
e
ex
p
er
t
ju
d
g
m
e
n
ts
,
ac
co
m
m
o
d
atin
g
u
n
ce
r
tain
ty
a
n
d
en
h
an
cin
g
th
e
p
r
ac
tical
ap
p
licab
ilit
y
o
f
th
e
f
in
d
in
g
s
.
T
h
e
E
T
AM
f
r
a
m
ewo
r
k
ex
ten
d
s
th
e
tr
ad
itio
n
al
tech
n
o
lo
g
y
ac
ce
p
t
an
ce
m
o
d
el
(
T
AM
)
b
y
in
co
r
p
o
r
atin
g
ad
d
itio
n
al
co
n
s
tr
u
cts
s
u
ch
as
awa
r
en
es
s
an
d
US
.
R
eg
r
ess
io
n
an
d
co
r
r
elatio
n
an
aly
s
es
with
in
E
T
AM
r
ev
ea
l
b
o
th
d
ir
ec
t
an
d
in
d
ir
ec
t
p
ath
way
s
in
f
lu
en
cin
g
u
s
er
ad
o
p
tio
n
.
AT
G
is
id
en
tifie
d
as
th
e
m
o
s
t
s
ig
n
if
ican
t
p
r
ed
icto
r
o
f
I
U,
wh
ile
in
d
ir
ec
t
p
ath
way
s
,
s
u
ch
as
PEU
in
f
l
u
en
cin
g
AT
G
an
d
I
U,
f
u
r
th
e
r
h
i
g
h
lig
h
t
t
h
e
in
tr
icate
r
elatio
n
s
h
ip
s
b
et
wee
n
v
ar
iab
les.
T
h
is
ap
p
r
o
ac
h
p
r
o
v
id
es a
ctio
n
a
b
le
in
s
ig
h
ts
in
to
h
o
w
tar
g
eted
in
ter
v
en
tio
n
s
ca
n
e
f
f
ec
tiv
ely
e
n
h
an
ce
ad
o
p
tio
n
r
ates.
T
h
em
atic
an
aly
s
is
is
in
co
r
p
o
r
ated
to
ca
p
tu
r
e
q
u
alitativ
e
d
i
m
en
s
io
n
s
o
f
u
s
er
ex
p
e
r
ien
ce
s
,
o
f
f
er
i
n
g
a
d
ee
p
er
u
n
d
er
s
tan
d
in
g
o
f
th
e
co
n
tex
tu
al
f
ac
to
r
s
s
h
ap
in
g
ad
o
p
tio
n
,
p
er
ce
p
tio
n
,
an
d
US
.
B
y
id
en
tify
in
g
r
ec
u
r
r
in
g
th
em
es
an
d
p
atter
n
s
in
q
u
alitativ
e
d
ata,
th
em
atic
an
aly
s
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co
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p
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en
ts
th
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q
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an
titativ
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m
eth
o
d
s
,
u
n
co
v
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r
in
g
s
u
b
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in
s
ig
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t
s
in
to
m
o
tiv
atio
n
s
,
b
ar
r
ier
s
,
an
d
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s
er
p
er
ce
p
tio
n
s
.
T
h
is
m
eth
o
d
en
r
ich
es
th
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
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5
2
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8
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I
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t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
14
,
No
.
6
,
Dec
em
b
er
20
25
:
4
7
7
0
-
4
7
8
4
4772
s
tu
d
y
b
y
h
ig
h
lig
h
tin
g
f
ac
to
r
s
th
at
m
ay
n
o
t
b
e
ev
id
en
t
in
n
u
m
er
ical
an
aly
s
es,
s
u
ch
as
cu
lt
u
r
al
o
r
in
s
titu
tio
n
al
in
f
lu
en
ce
s
o
n
a
d
o
p
tio
n
b
e
h
a
v
io
r
.
B
y
in
teg
r
atin
g
th
ese
m
eth
o
d
o
lo
g
ies,
th
e
s
tu
d
y
a
d
o
p
ts
a
m
u
lti
-
f
ac
eted
ap
p
r
o
ac
h
,
c
o
m
b
in
i
n
g
q
u
a
n
titativ
e
p
r
io
r
itizatio
n
(
AHP)
,
c
au
s
al
r
elatio
n
s
h
ip
m
ap
p
i
n
g
(
Fu
zz
y
DE
MA
T
E
L
)
,
b
eh
av
io
r
al
m
o
d
elin
g
(
E
T
A
M)
,
an
d
q
u
alitativ
e
ex
p
lo
r
atio
n
(
th
em
atic
an
al
y
s
is
)
.
T
h
is
co
m
p
r
eh
en
s
iv
e
f
r
am
ewo
r
k
en
a
b
les
a
s
y
s
tem
atic
u
n
d
e
r
s
tan
d
in
g
o
f
Gen
AI
a
d
o
p
tio
n
i
n
ed
u
ca
tio
n
,
f
ac
ilit
atin
g
th
e
d
ev
elo
p
m
en
t
o
f
tar
g
ete
d
s
tr
ateg
ies
to
a
d
d
r
ess
th
e
n
ee
d
s
o
f
b
o
t
h
s
tu
d
en
t
s
an
d
ed
u
ca
to
r
s
an
d
en
s
u
r
in
g
th
e
eq
u
itab
le
an
d
ef
f
ec
tiv
e
in
teg
r
atio
n
o
f
Gen
AI
to
o
ls
in
to
ed
u
ca
tio
n
al
p
r
ac
tice
s
.
2.
L
I
T
E
R
AT
U
RE
R
E
VI
E
W
2
.
1
.
Student
perc
ept
io
n
s
in
G
en
AI
Stu
d
en
ts
o
f
ten
v
iew
Gen
AI
as
a
v
alu
ab
le
to
o
l
f
o
r
ac
ad
em
ic
s
u
p
p
o
r
t,
r
ec
o
g
n
izin
g
its
ab
ilit
y
to
en
h
an
ce
lear
n
in
g
ex
p
e
r
ien
ce
s
an
d
p
r
o
v
id
e
a
co
m
p
etitiv
e
ac
a
d
em
ic
ad
v
an
tag
e
[
1
2
]
.
No
n
eth
eless
,
th
ey
r
em
ain
m
in
d
f
u
l
o
f
ch
allen
g
es,
i
n
clu
d
in
g
r
is
k
s
r
elate
d
to
p
lag
i
ar
is
m
,
p
r
iv
ac
y
is
s
u
es,
an
d
th
e
im
p
o
r
tan
ce
o
f
estab
lis
h
in
g
clea
r
in
s
titu
tio
n
al
g
u
id
elin
es
[
1
3
]
.
I
n
h
ig
h
e
r
ed
u
c
atio
n
,
s
tu
d
en
ts
em
p
h
a
s
ize
th
e
n
ee
d
f
o
r
p
ed
ag
o
g
ical
s
tr
ateg
ies
th
at
f
o
s
ter
cr
itical
th
in
k
in
g
,
eth
ical
a
war
en
ess
,
an
d
d
ig
ital
liter
ac
y
s
k
ills
in
co
n
ju
n
ctio
n
with
Gen
AI
u
s
e
[
1
4
]
.
Ad
d
itio
n
ally
,
s
u
r
v
ey
s
r
e
v
ea
l
th
at
m
an
y
s
tu
d
en
ts
a
d
v
o
ca
te
f
o
r
t
h
e
in
teg
r
atio
n
o
f
Gen
A
I
in
to
cu
r
r
icu
la,
d
esp
ite
lin
g
e
r
in
g
c
o
n
ce
r
n
s
ab
o
u
t
its
p
o
te
n
tial
co
n
s
eq
u
en
c
es.
I
n
ad
d
itio
n
,
th
e
o
p
i
n
io
n
s
o
f
in
d
iv
id
u
als
p
lay
a
s
ig
n
if
ican
t
r
o
le
in
h
o
w
s
u
cc
ess
f
u
lly
tech
n
ical
ad
v
an
ce
m
e
n
ts
ar
e
ad
o
p
t
ed
[
1
5
]
.
I
n
o
r
d
er
to
ascer
tain
if
s
tu
d
en
ts
ar
e
p
r
ep
ar
ed
to
in
co
r
p
o
r
ate
tech
n
o
l
o
g
i
ca
l
ad
v
an
ce
m
en
ts
lik
e
Gen
AI
in
to
th
eir
teac
h
in
g
m
eth
o
d
s
in
a
way
th
at
m
a
x
i
m
izes
th
eir
b
en
ef
its
,
it
is
cr
u
cial
to
co
n
s
id
er
th
eir
o
p
in
io
n
s
an
d
p
er
ce
p
tio
n
s
o
f
th
ese
tech
n
o
lo
g
ies
[
1
6
]
,
[
1
7
]
.
I
t
is
im
p
o
r
tan
t
to
n
o
te
th
at
d
e
v
elo
p
in
g
s
tr
ateg
ies
an
d
tactics
to
in
teg
r
ate
Gen
AI
tech
n
o
lo
g
y
in
t
o
c
u
r
r
icu
la
an
d
en
ac
tin
g
s
u
itab
le
p
o
licies
p
r
esen
t
s
ig
n
if
ican
t
o
b
s
tacle
s
f
o
r
h
ig
h
er
ed
u
ca
tio
n
in
s
titu
tio
n
s
[
1
8
]
.
As
a
r
esu
lt,
it
is
cr
itical
to
en
g
ag
e
s
tu
d
en
ts
b
y
lear
n
i
n
g
a
b
o
u
t
th
ei
r
p
er
s
p
ec
tiv
es
an
d
u
n
d
er
s
tan
d
i
n
g
th
eir
p
er
ce
p
tio
n
s
,
as
th
ey
ar
e
im
p
o
r
tan
t
s
tak
eh
o
ld
er
s
wh
o
ac
tiv
ely
c
o
n
tr
ib
u
te
to
th
e
s
u
cc
ess
o
f
in
teg
r
atio
n
a
n
d
d
e
v
elo
p
m
e
n
t
p
r
o
ce
s
s
es
[
1
9
]
.
T
ea
ch
er
s
a
n
d
ad
m
in
is
tr
ato
r
s
lo
o
k
in
g
to
ad
o
p
t
s
u
itab
le
an
d
ap
p
licab
le
p
o
licies
an
d
s
u
cc
ess
f
u
lly
in
teg
r
ate
an
d
im
p
r
o
v
e
p
r
o
ce
d
u
r
es
will
g
et
im
p
o
r
tan
t
in
s
ig
h
ts
f
r
o
m
r
ev
ea
lin
g
u
n
iv
er
s
ity
s
tu
d
en
ts
’
p
er
s
p
ec
tiv
es o
n
th
e
r
o
le
o
f
Ge
n
AI
in
ed
u
ca
tio
n
.
2
.
2
.
O
pp
o
rt
un
it
ies a
nd
a
p
pli
ca
t
io
ns
W
ith
n
u
m
er
o
u
s
o
p
p
o
r
tu
n
itie
s
to
en
h
an
ce
lear
n
in
g
,
Gen
AI
tech
n
o
lo
g
ies
ar
e
in
cr
ea
s
in
g
ly
b
ein
g
in
teg
r
ated
in
to
e
d
u
ca
tio
n
al
s
e
ttin
g
s
.
T
h
ese
tech
n
o
lo
g
ies
h
o
ld
th
e
p
o
ten
tial
to
b
o
o
s
t
p
r
o
d
u
ctiv
ity
an
d
f
o
s
ter
s
tu
d
en
t
en
g
ag
e
m
en
t
b
y
ass
is
ti
n
g
ed
u
ca
t
o
r
s
,
au
to
m
atin
g
task
s
,
an
d
p
er
s
o
n
alizin
g
in
s
tr
u
ctio
n
[
2
0
]
,
[
2
1
]
.
I
n
ar
ts
ed
u
ca
tio
n
,
Gen
AI
is
r
ec
o
g
n
ize
d
as
a
v
alu
ab
le
to
o
l
f
o
r
g
en
er
a
tin
g
cr
ea
tiv
e
co
n
ten
t;
h
o
wev
e
r
,
it
is
im
p
o
r
tan
t
to
n
o
te
th
at
tech
n
o
lo
g
y
ca
n
n
o
t
r
ep
lace
th
e
ir
r
e
p
lace
ab
le
h
u
m
a
n
elem
en
t
[
2
2
]
.
Similar
ly
,
in
m
ed
ical
ed
u
ca
tio
n
,
Gen
AI
s
u
p
p
o
r
ts
s
elf
-
d
ir
ec
ted
lear
n
in
g
an
d
s
im
u
lates
r
ea
l
-
wo
r
ld
s
ce
n
ar
io
s
,
y
et
it
also
p
r
esen
ts
ch
allen
g
es,
s
u
ch
as
en
s
u
r
in
g
d
ata
ac
cu
r
a
cy
an
d
m
ain
tain
i
n
g
ac
ad
e
m
ic
in
teg
r
ity
[
1
2
]
.
Mo
r
eo
v
er
,
Gen
AI
to
o
ls
,
s
u
ch
as
C
h
atGPT
,
h
av
e
b
ee
n
em
p
lo
y
e
d
in
elem
e
n
tar
y
e
d
u
ca
tio
n
to
t
ailo
r
co
u
r
s
e
m
ater
ials
to
s
tu
d
e
n
ts
’
v
ar
y
in
g
lev
els
o
f
u
n
d
er
s
tan
d
in
g
,
th
er
e
b
y
p
r
o
m
o
tin
g
m
o
tiv
ated
an
d
ef
f
ec
tiv
e
lear
n
in
g
[
2
3
]
.
2
.
3
.
T
he
im
pa
ct
o
f
G
enAI
o
n e
du
ca
t
io
n
T
h
r
o
u
g
h
th
e
p
r
o
v
is
io
n
o
f
cu
ttin
g
-
ed
g
e
to
o
ls
an
d
tech
n
iq
u
es
th
at
im
p
r
o
v
e
lear
n
in
g
e
x
p
er
ien
ce
s
,
Gen
AI
is
d
r
am
atica
lly
ch
an
g
i
n
g
th
e
e
d
u
ca
tio
n
al
la
n
d
s
ca
p
e.
I
n
tellig
en
t
tu
to
r
i
n
g
s
y
s
tem
s
,
ad
ap
tab
le
lear
n
i
n
g
en
v
ir
o
n
m
en
ts
,
an
d
in
d
iv
id
u
a
lized
lear
n
in
g
s
u
p
p
o
r
t
ar
e
all
b
ein
g
o
f
f
e
r
ed
b
y
Gen
AI
tech
n
o
lo
g
ies
lik
e
C
h
atGPT
,
wh
ich
ar
e
b
ein
g
i
n
co
r
p
o
r
ated
in
to
a
v
ar
iety
o
f
e
d
u
ca
tio
n
al
co
n
tex
ts
.
T
h
ese
te
ch
n
o
lo
g
ies
m
ak
e
it
p
o
s
s
ib
le
to
cr
ea
te
a
v
ar
iety
o
f
ed
u
ca
tio
n
al
r
eso
u
r
ce
s
,
s
u
ch
a
s
tex
ts
,
p
ictu
r
es,
an
d
v
id
eo
s
,
th
at
ar
e
cu
s
to
m
ized
to
th
e
u
n
iq
u
e
lear
n
in
g
s
ty
les
an
d
p
r
o
f
iles
o
f
ea
ch
s
tu
d
en
t
[
1
5
]
,
[
2
4
]
.
Gen
AI
is
ch
an
g
in
g
lear
n
in
g
o
b
jectiv
es
an
d
ass
ess
m
en
t
p
r
ac
tices
in
h
i
g
h
er
ed
u
ca
tio
n
,
e
n
co
u
r
ag
in
g
c
ar
ee
r
-
d
r
i
v
en
c
o
m
p
eten
cies
an
d
life
tim
e
lear
n
in
g
ab
ilit
ies
[
2
5
]
.
Ho
wev
er
,
th
e
in
co
r
p
o
r
atio
n
o
f
Gen
AI
also
b
r
in
g
s
u
p
eth
ical
is
s
u
es
in
clu
d
in
g
d
ata
p
r
iv
ac
y
,
ac
ad
em
ic
in
teg
r
ity
,
an
d
b
ias,
wh
ich
ca
lls
f
o
r
tr
an
s
p
a
r
en
t m
o
d
els an
d
r
esp
o
n
s
ib
le
u
s
e
[
2
6
]
.
Gen
AI
h
as
an
im
p
ac
t
o
n
s
p
e
cif
ic
ed
u
ca
tio
n
al
ar
ea
s
,
s
u
ch
as
m
ed
ical
an
d
en
g
in
ee
r
i
n
g
ed
u
ca
tio
n
,
wh
er
e
it
ac
ts
as
a
ca
taly
s
t
f
o
r
ch
an
g
e
b
y
im
p
r
o
v
in
g
teac
h
i
n
g
p
r
o
ce
d
u
r
es
an
d
id
en
tify
i
n
g
n
ew
o
p
p
o
r
tu
n
ities
[
2
7
]
.
No
twith
s
tan
d
in
g
its
ad
v
an
tag
es,
th
e
q
u
ick
u
p
tak
e
o
f
Gen
AI
in
ed
u
ca
tio
n
n
e
ce
s
s
itate
s
r
ig
o
r
o
u
s
ev
alu
atio
n
o
f
its
d
r
awb
ac
k
s
,
i
n
clu
d
in
g
m
ain
tain
in
g
d
ata
q
u
a
lity
an
d
r
eso
lv
in
g
eth
ical
co
n
s
tr
ain
ts
[
2
8
]
.
Gen
A
I
m
ay
g
r
ea
tly
im
p
r
o
v
e
s
tu
d
en
t
wo
r
k
an
d
lear
n
in
g
f
ee
d
b
ac
k
,
b
u
t
it
also
n
ee
d
s
th
e
r
ig
h
t
k
in
d
o
f
p
ed
ag
o
g
ical
ass
is
tan
ce
to
h
elp
s
tu
d
en
ts
d
e
v
elo
p
th
eir
d
ig
ital
liter
ac
y
,
c
r
itical
th
in
k
in
g
,
a
n
d
eth
ical
s
k
il
ls
[
1
4
]
.
I
n
o
r
d
er
to
ef
f
ec
tiv
ely
u
tili
ze
Gen
AI
p
r
o
m
is
e
wh
ile
r
ed
u
cin
g
r
elate
d
h
az
ar
d
s
,
ed
u
ca
to
r
s
,
r
esear
ch
er
s
,
an
d
p
o
licy
m
ak
er
s
m
u
s
t w
o
r
k
to
g
et
h
er
an
d
m
o
d
if
y
ed
u
ca
tio
n
al
p
r
o
ce
d
u
r
es a
s
it
d
ev
elo
p
s
[
1
5
]
.
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
P
ercep
tio
n
s
a
n
d
in
s
titu
tio
n
a
l rea
d
in
ess
fo
r
g
en
era
tive
A
I
a
d
o
p
tio
n
in
e
d
u
ca
tio
n
u
s
in
g
…
(
K
en
Go
r
r
o
)
4773
2
.
4
.
E
v
o
lutio
n o
f
t
he
e
x
t
ended
t
e
chno
lo
g
y
a
cc
ept
a
nce
m
o
del
T
h
e
E
T
AM
h
as
p
r
o
v
en
cr
u
ci
al
to
u
n
d
e
r
s
tan
d
in
g
h
o
w
u
s
er
s
ac
ce
p
t
an
d
em
p
lo
y
tech
n
o
l
o
g
y
ac
r
o
s
s
m
u
ltip
le
ar
ea
s
.
T
h
e
two
k
e
y
c
o
n
s
tr
u
cts
wer
e
th
e
p
r
im
ar
y
e
m
p
h
asis
o
f
Dav
is
’
s
o
r
i
g
in
al
E
T
AM
:
PU
an
d
PEU.
Ho
wev
er
,
r
esear
ch
er
s
s
tar
ted
ex
p
an
d
i
n
g
th
e
m
o
d
el
to
in
c
o
r
p
o
r
ate
m
o
r
e
elem
en
ts
th
at
ca
n
af
f
ec
t
co
n
s
u
m
er
ac
ce
p
t
-
ab
ilit
y
as
tec
h
n
o
lo
g
y
ad
o
p
tio
n
s
ce
n
ar
i
o
s
g
r
ew
i
n
cr
ea
s
in
g
ly
in
tr
icate
.
Fo
r
e
x
a
m
p
le,
ac
co
r
d
in
g
to
a
m
eta
-
an
aly
tic
an
aly
s
is
,
th
e
E
T
AM
p
lu
s
ad
d
s
m
o
r
e
f
ac
to
r
s
to
en
h
an
ce
m
o
d
el
f
it
an
d
co
n
s
is
ten
cy
wh
en
f
o
r
ec
asti
n
g
tech
n
o
lo
g
y
ad
o
p
ti
o
n
[
2
9
]
.
T
o
im
p
r
o
v
e
th
e
m
o
d
el’
s
ex
p
lan
ato
r
y
ca
p
ac
ity
an
d
ad
ap
t
it
to
v
ar
i
o
u
s
cir
cu
m
s
tan
ce
s
,
th
is
ex
p
a
n
s
io
n
h
as
b
ee
n
ess
en
tial.
E
T
AM
h
as
b
ee
n
ex
te
n
d
ed
in
s
ev
e
r
al
d
o
m
ain
s
,
in
cl
u
d
in
g
h
ea
lth
in
f
o
r
m
atics
an
d
b
lo
c
k
c
h
ain
tech
n
o
lo
g
y
.
I
n
h
ea
lth
in
f
o
r
m
atics,
th
e
m
o
d
el
h
as
b
ee
n
m
o
d
if
ied
to
in
clu
d
e
f
ac
to
r
s
lik
e
s
u
b
jectiv
e
n
o
r
m
an
d
s
elf
-
ef
f
icac
y
,
w
h
ich
r
ep
r
esen
t
th
e
d
y
n
am
ic
ch
ar
a
cter
o
f
h
ea
lth
ca
r
e
en
v
ir
o
n
m
en
ts
[
3
0
]
.
Similar
l
y
,
to
b
etter
u
n
d
er
s
tan
d
a
d
o
p
tio
n
b
eh
av
io
r
s
f
o
r
b
lo
ck
ch
ain
tech
n
o
lo
g
y
,
ch
ar
ac
ter
is
tics
s
u
ch
as
s
tr
ateg
ic
m
an
ag
em
en
t
a
n
d
s
o
cial
im
p
ac
t
at
th
e
co
r
p
o
r
ate
lev
el,
as
well
as
in
d
iv
id
u
al
in
n
o
v
atio
n
an
d
s
elf
-
ef
f
icac
y
,
h
av
e
b
ee
n
ad
d
e
d
to
th
e
E
T
A
M
[
3
1
]
.
T
h
ese
ad
ju
s
tm
en
ts
h
i
g
h
lig
h
t
th
e
m
o
d
el’
s
ad
ap
tab
ilit
y
an
d
th
e
im
p
o
r
tan
ce
o
f
ad
ju
s
tin
g
it
to
u
n
iq
u
e
te
ch
n
ical
an
d
o
r
g
an
izatio
n
al
s
itu
atio
n
s
to
im
p
r
o
v
e
f
o
r
ec
ast
ac
cu
r
ac
y
.
T
h
e
E
T
A
M
is
wid
ely
u
s
ed
an
d
r
ev
iewe
d
in
d
if
f
er
e
n
t
s
ec
to
r
s
,
in
clu
d
i
n
g
e
-
co
m
m
er
ce
[
3
2
]
,
I
C
T
in
ed
u
ca
tio
n
[
3
3
]
,
an
d
im
p
ac
t
r
ec
o
g
n
itio
n
tech
n
o
lo
g
y
[
3
4
]
.
T
h
ese
s
tu
d
ies
h
av
e
s
h
o
w
n
th
at
th
e
E
T
AM
is
u
s
ef
u
l
f
o
r
u
n
d
er
s
tan
d
i
n
g
u
s
e
r
ac
ce
p
tab
ilit
y
o
f
v
a
r
io
u
s
tech
n
o
lo
g
ical
ad
v
an
ce
m
e
n
ts
.
B
y
in
clu
d
in
g
o
th
e
r
r
elev
an
t
asp
ec
ts
,
th
e
E
T
AM
g
iv
es
a
m
o
r
e
t
h
o
r
o
u
g
h
an
d
co
n
tex
t
-
s
p
ec
if
ic
k
n
o
wled
g
e
o
f
th
e
f
ac
to
r
s
im
p
ac
tin
g
tech
n
o
lo
g
y
u
p
tak
e
an
d
u
s
ag
e
[
3
5
]
.
Ad
d
itio
n
ally
,
E
T
AM
h
as
r
ec
e
iv
ed
atten
tio
n
in
t
h
e
liter
atu
r
e
an
d
p
r
ac
tice
ac
r
o
s
s
m
o
s
t
o
f
t
h
e
wo
r
ld
.
Hen
ce
,
its
ap
p
licab
ilit
y
in
ex
p
lain
in
g
th
e
b
eh
a
v
io
r
o
f
u
s
er
s
in
th
e
ad
o
p
tio
n
o
f
tech
n
o
l
o
g
ies
is
n
o
t
d
o
u
b
tf
u
l.
Stu
d
ies
p
o
in
t
to
s
ev
e
r
al
f
ac
to
r
s
th
at
co
u
ld
e
x
p
lain
t
h
e
ac
ce
p
tan
ce
o
f
t
h
e
n
ew
tec
h
n
o
lo
g
y
,
with
th
e
ex
ten
d
ed
v
er
s
io
n
o
f
T
AM
b
ein
g
wid
el
y
u
s
ed
to
test
th
e
g
o
o
d
n
ess
o
f
f
it
o
f
th
e
m
o
d
e
[
2
9
]
.
T
h
e
UT
AUT
2
m
o
d
el,
an
ev
o
l
v
ed
v
er
s
io
n
o
f
T
AM
,
h
as
also
b
ee
n
d
is
cu
s
s
ed
an
d
s
u
g
g
ested
f
o
r
u
s
e
in
s
ev
er
al
ar
ea
s
,
th
u
s
r
ef
lectin
g
its
d
ev
elo
p
m
e
n
t
[
3
6
]
.
W
ith
in
th
e
co
n
tex
t
o
f
b
lo
ck
c
h
ain
te
ch
n
o
lo
g
y
ad
o
p
tio
n
,
a
n
E
T
A
M
in
teg
r
ates
b
o
th
m
an
ag
em
en
t
p
r
ac
tices
an
d
s
o
cial
in
f
lu
en
ce
as
f
ac
to
r
s
wo
r
t
h
ex
am
i
n
in
g
[
3
1
]
.
Fo
r
in
s
tan
c
e,
in
t
h
e
ed
u
ca
tio
n
f
ield
,
T
AM
h
as
b
ee
n
m
o
d
if
i
ed
s
o
th
at
it
ca
n
b
e
ap
p
lied
to
ass
ess
th
e
o
v
er
all
ef
f
ec
t
iv
en
ess
o
f
v
ir
t
u
al
class
r
o
o
m
s
b
y
ad
d
in
g
n
ew
c
o
n
s
tr
u
cts
s
u
ch
as
t
h
e
d
eg
r
ee
o
f
co
g
n
itiv
e
e
n
g
ag
em
e
n
t
a
n
d
u
s
er
s
’
well
-
b
ein
g
an
d
co
m
f
o
r
t
[
28
]
.
I
n
th
e
s
am
e
m
a
n
n
er
,
in
th
e
s
h
ar
i
n
g
ec
o
n
o
m
y
,
an
ex
ten
d
ed
T
AM
h
as
also
b
ee
n
u
s
ed
in
th
e
ca
s
e
o
f
Air
b
n
b
with
a
n
em
p
h
asis
o
n
n
etwo
r
k
ef
f
ec
ts
an
d
tr
u
s
t
[
3
7
]
.
T
h
is
m
o
d
el
h
as
also
b
ee
n
u
s
ed
in
p
r
ed
ictin
g
s
tu
d
en
ts
’
IU
tab
let
co
m
p
u
ter
s
b
ased
o
n
s
elf
-
ef
f
icac
y
an
d
tech
n
o
lo
g
y
an
x
iety
[3
8
]
.
I
n
th
e
f
i
eld
o
f
en
g
in
ee
r
i
n
g
,
in
f
o
r
m
atio
n
an
d
co
m
m
u
n
icati
o
n
tech
n
o
lo
g
y
(
I
C
T
)
teac
h
in
g
m
eth
o
d
s
h
av
e
s
o
m
eh
o
w
b
ee
n
r
ev
iewe
d
to
ex
ten
d
th
e
T
AM
to
e
v
alu
ate
th
e
lev
el
o
f
e
n
g
ag
em
e
n
t
an
d
lear
n
i
n
g
o
f
s
tu
d
en
ts
[
39
]
.
Fo
r
p
u
r
p
o
s
es
o
f
au
g
m
en
ted
r
ea
lity
(
AR
)
an
d
v
ir
tu
al
r
ea
lit
y
(
VR
)
in
ed
u
ca
tio
n
,
a
m
o
d
if
i
ed
T
AM
lo
o
k
s
at
teac
h
er
s
,
th
e
l
ea
r
n
in
g
T
AM
o
f
W
eCh
at
h
as
b
ee
n
e
x
p
an
d
ed
to
in
co
r
p
o
r
ate
b
e
h
av
io
r
al
co
n
s
tr
u
cts
s
u
ch
as
c
o
n
f
o
r
m
in
g
b
e
h
av
io
r
a
n
d
lan
g
u
a
g
e
s
elf
-
esteem
,
wh
ich
ar
e
h
elp
f
u
l
f
o
r
lan
g
u
ag
e
lear
n
er
s
[
4
0
]
.
Pre
p
ar
ed
n
ess
b
y
a
d
d
in
g
tec
h
n
o
lo
g
ical
c
o
n
ten
t
k
n
o
wled
g
e
[
4
1
]
.
Fin
ally
,
th
e
a
d
o
p
tio
n
o
f
m
o
b
ile
f
o
o
d
o
r
d
e
r
in
g
ap
p
licatio
n
s
h
as
also
b
ee
n
ex
am
in
ed
u
s
in
g
th
e
ex
ten
d
ed
[
4
2
]
b
u
t
r
ath
er
co
n
c
en
tr
atin
g
o
n
p
e
r
s
o
n
al
s
elf
-
ef
f
i
ca
cy
an
d
tr
u
s
two
r
th
in
ess
.
I
t
ca
n
b
e
s
ee
n
f
r
o
m
th
e
p
r
ev
io
u
s
s
tu
d
ies
th
at
th
e
E
T
AM
is
ex
ten
s
ib
le
in
co
n
tex
t
an
d
p
s
y
ch
o
lo
g
ical
p
ar
a
m
eter
s
f
o
r
a
b
etter
u
n
d
er
s
tan
d
i
n
g
o
f
th
e
ac
ce
p
ta
n
ce
o
f
v
a
r
io
u
s
tech
n
o
lo
g
ies b
y
th
e
u
s
er
s
.
3.
M
E
T
H
O
D
3
.
1
.
Da
t
a
c
o
llect
io
n
An
o
n
lin
e
s
u
r
v
e
y
was
ad
m
i
n
is
ter
ed
v
ia
a
Go
o
g
le
Fo
r
m
lin
k
an
d
d
is
tr
ib
u
ted
th
r
o
u
g
h
v
ar
i
o
u
s
s
o
cial
m
ed
ia
p
latf
o
r
m
s
f
r
o
m
Octo
b
e
r
2
3
to
Dec
em
b
er
9
,
2
0
2
4
.
T
o
en
h
a
n
ce
r
e
p
r
esen
tativ
en
ess
,
r
an
d
o
m
s
am
p
lin
g
was
em
p
lo
y
ed
b
y
in
v
itin
g
p
a
r
ticip
an
ts
ac
r
o
s
s
d
if
f
er
e
n
t
ca
m
p
u
s
es
an
d
d
ep
ar
tm
e
n
ts
o
f
C
eb
u
T
ec
h
n
o
lo
g
ical
Un
iv
er
s
ity
,
en
s
u
r
in
g
a
d
i
v
er
s
e
d
em
o
g
r
ap
h
ic
o
f
b
o
th
f
ac
u
lt
y
an
d
s
tu
d
en
ts
.
T
h
is
m
eth
o
d
was
ch
o
s
en
f
o
r
its
ef
f
icien
cy
,
co
n
v
en
ien
ce
,
an
d
co
s
t
-
ef
f
ec
tiv
en
ess
.
A
to
tal
o
f
1
,
4
1
8
r
esp
o
n
s
es
wer
e
co
llec
ted
;
h
o
wev
e
r
,
1
2
2
wer
e
id
en
tifie
d
as
d
u
p
licates.
Af
ter
d
ata
clea
n
in
g
,
1
,
2
9
6
v
alid
r
esp
o
n
s
es
r
em
ain
ed
an
d
w
er
e
in
clu
d
ed
in
t
h
e
f
in
al
an
aly
s
is
.
T
h
er
e
wer
e
m
o
r
e
f
em
ale
(
6
6
%)
th
a
n
m
ale
(
3
4
%)
p
ar
ticip
an
ts
.
T
h
eir
ag
es
r
a
n
g
ed
f
r
o
m
1
7
to
6
1
y
ea
r
s
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ld
,
with
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clu
s
ter
ed
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o
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n
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th
e
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g
e
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g
e
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o
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r
s
.
Ad
d
itio
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ally
,
9
2
%
o
f
th
e
p
ar
ticip
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ts
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d
en
ts
,
wh
ile
th
e
r
em
ai
n
in
g
8
% we
r
e
f
ac
u
lty
m
em
b
er
s
.
3
.
2
.
M
ea
s
urem
ent
T
h
e
m
ain
in
s
tr
u
m
en
t
u
s
ed
in
th
e
s
tu
d
y
was
a
s
u
r
v
ey
q
u
e
s
tio
n
n
air
e
wh
ich
in
clu
d
e
d
m
e
asu
r
em
en
t
item
s
th
at
wer
e
ad
ap
ted
f
r
o
m
v
alid
ated
s
ca
les.
T
h
e
co
n
s
tr
u
cts
ex
am
in
ed
wer
e:
US
with
8
item
s
,
awa
r
en
ess
with
4
item
s
,
PU
wi
th
5
ite
m
s
,
PEU
w
ith
4
item
s
,
AT
G
AI
with
4
i
tem
s
,
an
d
IU
with
4
item
s
.
All
m
ea
s
u
r
em
en
t
item
s
wer
e
r
at
ed
o
n
a
7
-
p
o
in
t
L
ik
e
r
t
s
ca
le,
r
an
g
in
g
f
r
o
m
“
s
tr
o
n
g
ly
a
g
r
ee
”
to
“stro
n
g
l
y
d
is
ag
r
ee
”.
Me
an
wh
ile,
ac
tu
al
u
s
ag
e
(
AU)
was
m
ea
s
u
r
ed
u
s
in
g
a
s
ca
le
o
f
1
to
7
with
1
a
s
“
n
ev
er
”
an
d
7
as
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
14
,
No
.
6
,
Dec
em
b
er
20
25
:
4
7
7
0
-
4
7
8
4
4774
“e
v
er
y
tim
e
”.
Fo
r
t
h
e
q
u
alitativ
e
co
m
p
o
n
en
t,
r
esp
o
n
d
en
ts
a
n
s
wer
ed
3
o
p
en
-
en
d
e
d
q
u
esti
o
n
s
r
eg
ar
d
in
g
th
eir
u
n
iv
er
s
ity
’
s
p
o
licies
o
n
Gen
AI
,
as
well
as
th
e
b
e
n
ef
its
an
d
ch
allen
g
es
th
ey
ex
p
er
ie
n
c
ed
in
u
s
in
g
it.
T
h
e
s
u
r
v
ey
was a
d
m
in
is
ter
ed
v
ia
Go
o
g
le
Fo
r
m
s
f
o
r
co
n
v
en
ien
t
ac
ce
s
s
.
3
.
3
.
Co
ns
t
ruct
a
nd
d
ef
ini
t
io
n
T
h
e
in
s
tr
u
m
e
n
t
u
s
ed
i
n
th
is
s
tu
d
y
was
b
ased
o
n
th
e
c
o
n
s
tr
u
cts
d
is
cu
s
s
ed
in
s
u
b
-
s
ec
tio
n
s
.
T
h
e
r
esp
o
n
d
en
ts
o
f
th
e
s
tu
d
y
ar
e
s
t
u
d
en
ts
an
d
f
ac
u
lty
f
r
o
m
C
eb
u
T
ec
h
n
o
lo
g
ical
Un
iv
er
s
ity
.
T
h
e
item
in
d
icato
r
s
in
th
e
f
o
llo
win
g
s
ec
tio
n
s
wer
e
ad
ap
ted
an
d
r
ewo
r
d
e
d
f
r
o
m
p
r
ev
io
u
s
ly
v
alid
ated
in
s
tr
u
m
e
n
ts
to
alig
n
with
th
e
s
p
ec
if
ic
co
n
tex
t
o
f
th
is
s
tu
d
y
o
n
Gen
AI
in
h
ig
h
er
ed
u
ca
tio
n
.
Or
ig
in
al
s
o
u
r
ce
s
h
av
e
b
ee
n
ap
p
r
o
p
r
iately
cited
with
in
ea
ch
co
r
r
esp
o
n
d
i
n
g
s
ec
tio
n
.
3
.
4
.
Act
ua
l
u
s
a
g
e
AU
r
ef
er
s
to
r
ea
l
b
eh
a
v
io
r
i
n
ad
o
p
tin
g
a
s
y
s
tem
.
I
t
is
m
ea
s
u
r
ed
b
y
t
h
e
am
o
u
n
t
o
f
tim
e
s
p
en
t
in
ter
ac
tin
g
with
th
e
tech
n
o
lo
g
y
o
r
th
e
f
r
eq
u
en
cy
o
f
u
s
e.
I
tem
i
n
d
icato
r
s
:
h
o
w
f
r
eq
u
e
n
tly
d
o
y
o
u
u
s
e
Gen
AI
in
y
o
u
r
teac
h
in
g
,
r
esear
c
h
,
o
r
a
d
m
in
is
tr
ativ
e
r
esp
o
n
s
ib
ilit
ies?
i)
I
h
av
e
n
ev
e
r
u
s
ed
it
;
ii)
I
u
s
e
it
less
th
an
1
0
%
o
f
th
e
tim
e
;
iii)
I
u
s
e
it
ar
o
u
n
d
3
0
%
o
f
th
e
tim
e
;
i
v
)
I
u
s
e
it
ap
p
r
o
x
im
ately
h
alf
o
f
th
e
tim
e
;
v
)
I
u
s
e
it
in
ab
o
u
t
7
0
% o
f
m
y
task
s
; v
i)
I
u
s
e
it i
n
n
ea
r
ly
all
task
s
(
ar
o
u
n
d
9
0
%
)
; a
n
d
v
ii)
I
r
ely
o
n
it e
v
er
y
ti
m
e
.
3
.
5
.
I
nte
ntio
n t
o
u
se
I
U
r
ef
er
s
to
t
h
e
u
s
er
’
s
in
ten
t
io
n
o
r
willin
g
n
ess
to
u
s
e
tech
n
o
lo
g
y
[
4
3
].
I
tem
i
n
d
icato
r
s
:
i)
I
am
o
p
en
t
o
u
s
in
g
Gen
AI
to
o
ls
lik
e
C
h
atGPT
m
o
v
in
g
f
o
r
war
d
;
i
i)
I
f
ac
c
ess
to
Gen
AI
is
a
v
ailab
le,
I
w
o
u
ld
p
lan
to
u
s
e
it
[
4
4
]
;
iii)
I
e
x
p
ec
t
t
o
k
ee
p
u
s
in
g
Ge
n
AI
to
o
ls
in
m
y
w
o
r
k
;
an
d
i
v
)
I
wo
u
ld
s
u
g
g
est
t
h
at
o
th
er
s
tr
y
u
s
in
g
Gen
AI
[4
5
].
3
.
6
.
At
t
it
ud
e
t
o
wa
rd
G
enAI
T
h
e
d
eg
r
ee
o
f
s
tu
d
e
n
ts
’
f
av
o
r
ab
le
o
r
u
n
f
av
o
r
ab
le
ev
al
u
atio
n
r
eg
ar
d
in
g
ad
o
p
tin
g
Ge
n
AI
te
ch
n
o
lo
g
ies
in
th
eir
lear
n
i
n
g
p
r
o
ce
s
s
[
4
6
].
I
tem
i
n
d
icato
r
s
:
i)
I
b
eliev
e
th
e
u
s
e
o
f
Gen
AI
is
b
en
e
f
icial
;
ii)
I
am
at
ea
s
e
in
co
r
p
o
r
atin
g
Gen
AI
i
n
to
m
y
ac
tiv
ities
;
iii)
I
am
p
leased
wi
th
m
y
ex
p
e
r
ien
ce
u
s
in
g
Ge
n
AI
[4
7
]
;
a
n
d
iv
)
I
a
m
s
u
p
p
o
r
tiv
e
o
f
in
itiativ
es to
u
s
e
Gen
AI
.
3
.
7
.
P
er
ce
iv
ed
u
s
ef
uln
e
s
s
T
h
e
ex
te
n
t
to
wh
ich
a
p
er
s
o
n
th
in
k
s
a
s
p
ec
if
ic
s
y
s
tem
w
o
u
ld
im
p
r
o
v
e
p
e
r
f
o
r
m
an
ce
at
wo
r
k
[
38
].
I
tem
i
n
d
icato
r
s
:
i)
Gen
AI
ca
n
h
elp
im
p
r
o
v
e
th
e
q
u
ality
o
f
m
y
o
u
tp
u
ts
[
48
]
;
ii)
Usi
n
g
AI
to
o
ls
m
ak
es
m
e
m
o
r
e
p
r
o
d
u
ctiv
e
;
iii)
My
ef
f
icien
cy
in
task
s
in
cr
ea
s
es
wh
en
I
u
s
e
Gen
AI
;
iv
)
Gen
AI
ca
n
r
e
d
u
ce
th
e
tim
e
I
s
p
en
d
o
n
r
o
u
tin
e
wo
r
k
; a
n
d
v
)
I
b
eliev
e
Gen
AI
co
n
tr
ib
u
tes p
o
s
itiv
ely
t
o
teac
h
in
g
a
n
d
lear
n
in
g
p
r
o
ce
s
s
es [
49
].
3
.
8
.
P
er
ce
iv
ed
ea
s
e
o
f
us
e
T
h
e
ex
ten
t
to
wh
ich
a
p
er
s
o
n
th
in
k
s
th
at
u
tili
zin
g
a
s
p
ec
if
ic
m
eth
o
d
wo
u
ld
b
e
ea
s
y
.
I
tem
i
n
d
icato
r
s
:
i)
I
th
in
k
I
ca
n
q
u
ick
ly
g
r
asp
h
o
w
to
u
s
e
Gen
AI
to
o
ls
;
ii)
I
t
d
o
es
n
o
t
tak
e
m
u
ch
ef
f
o
r
t
to
wo
r
k
with
Gen
AI
;
iii)
I
co
n
s
id
er
Gen
AI
u
s
er
-
f
r
ie
n
d
ly
; a
n
d
iv
)
I
f
in
d
it e
asy
to
l
ea
r
n
h
o
w
t
o
u
s
e
Gen
AI
to
o
ls
ef
f
ec
tiv
ely
.
3
.
9
.
Univ
er
s
it
y
s
up
po
rt
It
r
ef
er
s
to
th
e
r
elev
an
t
s
u
p
p
o
r
tin
g
p
o
licies
f
o
r
t
h
e
u
s
e
o
f
G
en
AI
.
I
tem
i
n
d
icato
r
s
:
i)
T
h
e
u
n
iv
er
s
ity
o
f
f
er
s
s
u
p
p
o
r
t
o
r
in
itiativ
es
f
o
r
Gen
AI
u
s
e
;
ii)
I
v
alu
e
in
s
titu
tio
n
al
r
eso
u
r
ce
s
r
elate
d
t
o
Gen
AI
;
iii)
My
u
n
iv
er
s
ity
p
r
o
m
o
tes
in
n
o
v
ati
o
n
th
r
o
u
g
h
th
e
u
s
e
o
f
em
e
r
g
in
g
tec
h
n
o
lo
g
ies
lik
e
Gen
AI
;
iv
)
T
h
er
e
ar
e
o
p
p
o
r
tu
n
ities
f
o
r
tr
ain
i
n
g
an
d
d
ev
elo
p
m
e
n
t
in
u
s
in
g
Ge
n
AI
;
v
)
T
h
e
in
s
titu
tio
n
h
as
clea
r
p
o
licies
o
n
wh
en
AI
u
s
e
is
ap
p
r
o
p
r
iate
;
v
i)
Gu
id
elin
es
ar
e
av
ailab
le
to
en
s
u
r
e
ac
ad
em
ic
h
o
n
esty
wh
en
u
s
in
g
Gen
AI
;
v
ii)
R
esp
o
n
s
ib
le
u
s
e
o
f
Gen
AI
is
ad
d
r
ess
ed
b
y
th
e
in
s
titu
tio
n
’
s
s
tr
ateg
y
;
an
d
v
iii
)
T
h
e
u
n
i
v
er
s
ity
h
as
way
s
to
m
o
n
ito
r
a
n
d
m
a
n
ag
e
in
a
p
p
r
o
p
r
iate
AI
u
s
ag
e.
3
.
1
0
.
Awa
re
nes
s
It
e
n
c
o
m
p
ass
es
u
n
d
er
s
ta
n
d
in
g
o
f
t
h
e
c
a
p
a
b
ili
ties
,
a
p
p
li
c
ati
o
n
s
,
a
n
d
li
m
it
ati
o
n
s
o
f
Gen
AI
[
50
].
I
te
m
i
n
d
ica
to
r
s
:
i
)
I
am
f
a
m
i
liar
with
wh
at
Gen
AI
is
;
ii)
I
talk
ab
o
u
t
Gen
AI
with
c
o
lleag
u
es
o
r
p
ee
r
s
;
iii)
I
u
n
d
er
s
tan
d
h
o
w
to
u
s
e
G
en
AI
ap
p
r
o
p
r
iately
;
an
d
i
v
)
I
r
ec
o
g
n
ize
h
o
w
Ge
n
AI
m
a
y
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d
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s
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Un
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n
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3
.
1
2
.
Descript
iv
e
a
na
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s
is
T
ab
le
1
s
u
m
m
ar
izes
t
h
e
a
v
er
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r
atin
g
s
f
o
r
s
tu
d
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ts
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t
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ch
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s
ac
r
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s
s
k
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y
v
ar
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h
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tab
le
h
ig
h
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d
escr
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s
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av
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ag
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r
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s
f
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s
tu
d
en
ts
an
d
teac
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s
.
Stu
d
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ts
an
d
teac
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s
p
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ce
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a
n
d
u
s
e
Gen
AI
d
if
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en
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.
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r
ex
am
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r
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PU
an
d
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U
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an
s
tu
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ts
,
s
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g
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esti
n
g
a
s
tr
o
n
g
er
in
clin
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n
to
war
d
in
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r
atin
g
Gen
AI
in
to
th
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a
ctiv
ities
.
Var
iab
les
lik
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awa
r
e
n
ess
an
d
US
s
h
o
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lo
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s
am
o
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g
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tu
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ts
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s
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f
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tiv
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u
s
e
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f
Gen
AI
to
o
ls
.
T
ab
le
1
.
Descr
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s
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V
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T
-
test
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co
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s
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ac
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Gen
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h
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in
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ap
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u
p
p
o
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tin
g
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tu
d
en
ts
in
th
e
e
f
f
e
ctiv
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ad
o
p
tio
n
an
d
in
teg
r
atio
n
o
f
Gen
AI
to
o
ls
.
T
ab
le
2
.
T
-
T
est r
esu
lts
co
m
p
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s
tu
d
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Ana
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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.
I
n
co
n
tr
ast,
v
ar
iab
les
s
u
ch
as
awa
r
e
n
ess
an
d
US
wer
e
ass
ig
n
ed
lo
wer
weig
h
ts
,
s
u
g
g
esti
n
g
th
ey
p
lay
a
s
ec
o
n
d
ar
y
r
o
le
co
m
p
ar
e
d
to
attitu
d
e
an
d
in
ten
tio
n
.
T
h
ese
r
esu
lts
h
ig
h
lig
h
t
th
e
im
p
o
r
ta
n
ce
o
f
f
o
s
ter
in
g
a
p
o
s
itiv
e
attitu
d
e
to
war
d
Gen
AI
t
o
en
c
o
u
r
a
g
e
b
r
o
ad
er
a
d
o
p
tio
n
.
T
h
e
p
r
io
r
ity
weig
h
ts
f
o
r
th
e
s
e
v
en
c
r
iter
ia
r
ec
o
g
n
ized
as
a
f
f
e
ctin
g
th
e
ad
o
p
tio
n
an
d
u
tili
za
tio
n
o
f
Ge
n
AI
wer
e
o
b
tain
ed
th
r
o
u
g
h
th
e
AHP.
T
h
ese
weig
h
ts
r
e
f
lect
th
e
r
el
ativ
e
s
ig
n
if
ican
ce
o
f
ea
ch
f
a
cto
r
as
s
ee
n
b
y
th
e
r
esp
o
n
d
en
ts
.
T
h
e
f
in
d
i
n
g
s
in
d
icate
th
at
th
e
AT
G
AI
ca
r
r
ies
th
e
g
r
ea
test
weig
h
t
(
0
.
2
5
)
,
im
p
ly
in
g
th
at
u
s
er
s
’
o
v
er
all
f
av
o
r
ab
le
o
r
u
n
f
av
o
r
a
b
le
ass
es
s
m
en
t
o
f
Gen
AI
is
t
h
e
k
ey
f
ac
to
r
i
n
f
lu
en
ci
n
g
its
ad
o
p
tio
n
.
Nex
t
is
I
U
with
a
weig
h
t
o
f
0
.
2
0
,
al
o
n
g
with
PU
at
0
.
1
8
,
s
h
o
win
g
th
a
t
th
e
d
r
iv
e
t
o
k
ee
p
u
s
in
g
th
e
t
ec
h
n
o
lo
g
y
a
n
d
th
e
b
elief
in
its
ad
v
an
tag
es
ar
e
s
ig
n
if
ican
t
in
f
lu
en
ce
s
as
well.
At
th
e
s
am
e
tim
e,
AU
ca
r
r
ies
a
m
o
d
er
ate
weig
h
t
o
f
0
.
1
5
,
in
d
icatin
g
th
at
p
r
esen
t
b
eh
av
i
o
r
h
o
ld
s
s
ig
n
if
ican
ce
b
u
t
is
less
im
p
ac
tf
u
l
th
a
n
th
e
attitu
d
in
al
an
d
in
ten
tio
n
-
d
r
iv
en
f
ac
to
r
s
.
PEU
(
0
.
1
0
)
,
US
(
0
.
0
7
)
,
an
d
awa
r
e
n
ess
(
0
.
0
5
)
ar
e
r
ated
lo
wer
,
in
d
icatin
g
th
at
wh
ile
th
ese
elem
en
ts
in
f
lu
en
ce
th
e
o
v
er
all
ch
o
ice,
th
ey
ar
e
n
o
t th
e
m
ain
f
ac
to
r
s
f
r
o
m
th
e
u
s
er
s
’
v
iewp
o
in
t.
T
ab
le
3
.
AHP
p
r
io
r
ity
weig
h
ts
C
r
i
t
e
r
i
a
P
r
i
o
r
i
t
y
w
e
i
g
h
t
s
AU
0
.
1
5
IU
0
.
2
0
A
TG
0
.
2
5
PU
0
.
1
8
P
EU
0
.
1
0
US
0
.
0
7
A
w
a
r
e
n
e
ss
0
.
0
5
3
.
1
5
.
F
uzzy
DE
M
A
T
E
L
Ana
ly
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is
3.
15
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.
M
a
t
hem
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t
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ul
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f
F
uzzy
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M
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h
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Fu
zz
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MA
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L
m
eth
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v
o
lv
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th
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o
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win
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tep
s
:
co
n
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tr
u
ct
th
e
d
ir
ec
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-
r
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m
atr
ix
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,
wh
er
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ij
r
ep
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th
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d
i
r
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t in
f
lu
en
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o
f
f
ac
to
r
i
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n
f
ac
to
r
j
.
−
No
r
m
alize
th
e
d
ir
ec
t
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r
elatio
n
m
atr
ix
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∑
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1
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(
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P
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A
I
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ir
ec
t
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r
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atr
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−
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wh
er
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is
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e
to
tal
in
f
lu
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m
atr
ix
,
I
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n
tity
m
atr
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d
N
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alize
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atr
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alcu
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p
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o
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in
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(
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1
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−
I
n
ter
p
r
et
th
e
r
esu
lts
:
i)
f
ac
to
r
s
with
h
ig
h
D+
R
ar
e
p
r
o
m
in
en
t
an
d
p
lay
an
im
p
o
r
ta
n
t
r
o
le
i
n
th
e
s
y
s
tem
;
ii)
f
ac
to
r
s
with
p
o
s
itiv
e
D−
R
ar
e
n
et
in
f
lu
e
n
ce
r
s
(
ca
u
s
in
g
m
o
r
e
ef
f
ec
t
t
h
an
th
e
y
r
ec
eiv
e
)
;
an
d
iii)
f
ac
to
r
s
with
n
eg
ativ
e
D−
R
ar
e
n
et
r
ec
eiv
er
s
(
r
ec
eiv
in
g
m
o
r
e
e
f
f
ec
t t
h
an
th
ey
ca
u
s
e)
.
3.
15
.
2
.
Resul
t
s
T
h
e
Fu
zz
y
DE
MA
T
E
L
r
esu
lts
,
in
clu
d
in
g
p
r
o
m
in
e
n
ce
(
D+
R
)
an
d
r
elatio
n
(
D
-
R
)
f
o
r
all
v
ar
i
ab
les,
ar
e
p
r
esen
ted
in
T
a
b
le
4
.
T
h
e
tab
le
p
r
esen
ts
th
e
r
esu
lts
o
f
th
e
Fu
zz
y
DE
MA
T
E
L
an
aly
s
is
,
h
ig
h
lig
h
tin
g
PU
an
d
AT
G
AI
as
th
e
p
r
im
ar
y
d
r
iv
in
g
f
ac
to
r
s
with
in
th
e
s
y
s
tem
,
b
o
th
ex
h
ib
itin
g
h
i
g
h
p
r
o
m
in
en
ce
s
co
r
es.
I
n
co
n
tr
ast,
awa
r
en
ess
an
d
US
ar
e
m
o
r
e
r
ea
ctiv
e
v
ar
iab
les,
m
ea
n
in
g
th
ey
ar
e
m
o
r
e
in
f
lu
e
n
ce
d
b
y
o
th
er
f
ac
to
r
s
th
an
th
ey
in
f
lu
e
n
ce
o
th
er
s
th
em
s
elv
es.
T
h
ese
in
s
ig
h
ts
s
u
g
g
est
th
at
in
s
titu
tio
n
s
aim
in
g
to
in
cr
ea
s
e
Gen
AI
ad
o
p
tio
n
s
h
o
u
ld
f
o
cu
s
o
n
en
h
an
cin
g
th
e
PU
o
f
th
ese
to
o
ls
—
s
u
ch
as
b
y
d
em
o
n
s
tr
atin
g
p
r
ac
tical,
r
ea
l
-
wo
r
ld
ap
p
licatio
n
s
—
wh
ich
ca
n
,
in
t
u
r
n
,
p
o
s
itiv
ely
s
h
ap
e
u
s
er
attitu
d
es
an
d
d
r
i
v
e
f
u
r
th
er
ad
o
p
tio
n
.
Fu
r
th
e
r
m
o
r
e
,
th
e
PU
s
u
r
f
ac
ed
as
th
e
m
o
s
t
s
ig
n
if
ican
t
f
ac
to
r
,
h
o
ld
in
g
th
e
h
ig
h
est
p
r
o
m
in
en
ce
s
co
r
e
(
D+
R
=2
4
)
.
T
h
is
s
u
g
g
ests
th
at
PU
is
clo
s
ely
lin
k
ed
with
o
th
er
v
a
r
iab
les
in
th
e
s
y
s
tem
; n
o
n
eth
eless
,
its
n
eg
ativ
e
r
elati
o
n
v
alu
e
(
D−
R
=
-
2
)
in
d
icate
s
it
is
m
ain
ly
af
f
ec
te
d
b
y
o
th
er
f
ac
to
r
s
in
s
tead
o
f
b
ein
g
a
k
e
y
d
r
iv
er
its
elf
.
I
n
th
e
s
am
e
way
,
I
U
d
em
o
n
s
tr
ates
a
s
ig
n
if
ican
t
in
ter
ac
tio
n
lev
el
(
D+
R
=2
2
)
y
et
h
as
a
s
lig
h
tly
n
eg
ativ
e
r
elatio
n
v
alu
e
(
D−
R
=
-
1
)
,
s
u
g
g
esti
n
g
it a
ls
o
s
er
v
es a
s
m
o
r
e
o
f
an
o
u
tco
m
e
v
ar
iab
le
with
in
th
e
s
y
s
tem
.
C
o
n
v
er
s
ely
,
AU
s
h
o
ws
s
u
b
s
tan
tial
in
ter
ac
tio
n
(
D+
R
=2
1
)
an
d
a
b
e
n
ef
icial
ca
u
s
al
lin
k
(
D−
R
=+
4
)
,
m
ar
k
in
g
it
as
a
k
ey
f
ac
to
r
th
a
t
d
ir
ec
tly
in
f
lu
en
ce
s
b
eh
av
io
r
s
in
th
e
m
o
d
el.
AT
G
AI
h
as
a
s
ig
n
if
ican
t
ca
u
s
al
im
p
ac
t
(
D−
R
=+
3
)
,
in
d
icatin
g
th
at
a
f
av
o
r
a
b
le
attitu
d
e
f
ac
ili
tates
an
d
en
h
an
ce
s
th
e
ac
ce
p
tan
ce
an
d
e
f
f
ec
t
o
f
o
th
er
elem
en
ts
.
Sig
n
if
ican
tly
,
PEU
em
er
g
es
as
th
e
m
o
s
t
in
f
lu
en
tial
ca
u
s
al
elem
en
t,
b
o
asti
n
g
th
e
h
ig
h
est
p
o
s
itiv
e
co
r
r
elatio
n
s
co
r
e
(
D−
R
=+
5
)
,
s
ig
n
if
y
in
g
it
is
th
e
m
ain
ca
taly
s
t
th
at
af
f
ec
ts
o
th
er
v
ar
iab
les
th
r
o
u
g
h
o
u
t
th
e
s
y
s
tem
.
At
th
e
s
am
e
ti
m
e,
US
ex
h
ib
its
d
im
in
is
h
ed
o
v
er
all
s
ig
n
if
ican
ce
(
D+
R
=1
8
)
an
d
a
n
e
g
ativ
e
r
elatio
n
s
h
ip
v
alu
e
(
D−
R
=
-
3
)
,
s
u
g
g
esti
n
g
it
o
p
er
ates
m
o
r
e
as
a
r
esp
o
n
s
iv
e
ele
m
en
t
in
f
l
u
en
ce
d
b
y
e
x
ter
n
al
f
ac
to
r
s
r
ath
e
r
th
a
n
in
s
tig
atin
g
ch
an
g
e.
Fin
ally
,
awa
r
en
ess
h
as
th
e
least
s
ig
n
if
ican
ce
(
D+
R
=1
7
)
an
d
a
n
eu
t
r
al
r
elatio
n
s
h
ip
v
alu
e
(
D−
R
=0
)
,
i
n
d
icatin
g
th
at
it m
ain
tain
s
a
b
alan
ce
d
p
o
s
itio
n
—
n
eith
er
s
tr
o
n
g
ly
in
f
lu
e
n
cin
g
n
o
r
b
ein
g
g
r
ea
tly
in
f
lu
e
n
ce
d
—
th
u
s
s
er
v
in
g
as a
p
o
ten
tial stab
ilizer
in
th
e
m
o
d
el
.
T
ab
le
4
.
Fu
zz
y
DE
MA
T
E
L
r
e
s
u
lts
in
clu
d
in
g
all
v
ar
iab
les
C
r
i
t
e
r
i
a
P
r
o
mi
n
e
n
c
e
(
D
+
R
)
R
e
l
a
t
i
o
n
(
D
-
R)
AU
21
4
IU
22
-
1
A
TG
20
3
PU
24
-
2
P
EU
19
5
US
18
-
3
A
w
a
r
e
n
e
ss
17
0
3
.
1
6
.
E
x
t
ended t
ec
hn
o
lo
g
y
a
cc
ept
a
nce
m
o
del
T
h
e
E
T
AM
f
r
am
ewo
r
k
in
clu
d
es
th
e
co
n
s
tr
u
cts
s
h
o
w
n
in
T
a
b
le
5
,
with
th
eir
co
r
r
elatio
n
s
.
T
h
e
tab
le
s
h
o
ws
co
r
r
elatio
n
m
atr
ix
o
f
k
ey
co
n
s
tr
u
cts
f
r
o
m
th
e
E
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h
ig
h
lig
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tin
g
s
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o
n
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r
elatio
n
s
h
ip
s
th
at
in
f
lu
en
ce
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
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2
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8
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14
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er
20
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Gen
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o
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tio
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a
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ly
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ile
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ig
n
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ican
tly
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G,
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d
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US
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d
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ess
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t
m
ea
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icatin
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eir
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ir
ec
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h
ese
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i
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d
in
g
s
r
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f
o
r
ce
t
h
e
im
p
o
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o
f
e
n
h
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g
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u
s
ef
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ess
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d
ea
s
e
o
f
u
s
e,
s
u
p
p
o
r
ted
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y
i
n
s
titu
tio
n
al
s
tr
ateg
ies.
T
ab
le
5
.
C
o
r
r
elatio
n
m
atr
ix
f
o
r
E
T
AM
c
o
n
s
tr
u
cts
C
o
n
st
r
u
c
t
US
A
w
a
r
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e
ss
PU
P
EU
A
TG
IU
US
1
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0
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4
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1
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5
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5
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0
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0
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4
9
0
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0
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3.
16
.
1
.
Reg
re
s
s
io
n a
na
ly
s
is
re
s
ults
T
ab
le
6
p
r
esen
ts
th
e
r
eg
r
ess
io
n
r
esu
lts
f
o
r
th
e
E
T
AM
,
s
h
o
win
g
th
at
AT
G
AI
is
th
e
s
tr
o
n
g
est
p
r
ed
icto
r
o
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U
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f
o
l
lo
wed
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y
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.
2
2
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ad
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s
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ec
t
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8
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,
w
h
ile
awa
r
en
ess
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d
US
s
h
o
wed
m
in
im
al
d
i
r
ec
t
in
f
lu
en
ce
.
T
h
ese
r
esu
lts
h
ig
h
lig
h
t
th
e
im
p
o
r
tan
c
e
o
f
f
o
s
ter
in
g
p
o
s
itiv
e
attitu
d
es a
n
d
PU to
d
r
iv
e
ad
o
p
tio
n
,
s
u
p
p
o
r
ted
b
y
tar
g
ete
d
aw
ar
en
ess
an
d
in
s
titu
tio
n
al
s
tr
ateg
ies.
3.
16
.
2
.
I
nd
irec
t
ef
f
ec
t
s
AT
G
AI
h
as
th
e
s
tr
o
n
g
est
d
i
r
ec
t
im
p
ac
t
o
n
I
U
(
r
e
g
r
ess
io
n
co
ef
f
icien
t=
0
.
5
1
0
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.
I
n
d
ir
ec
t
p
ath
way
s
(
PEU→a
ttit
u
d
e→I
U
)
also
co
n
tr
ib
u
te
to
u
s
er
ac
ce
p
tan
ce
.
US
h
as
a
wea
k
er
d
ir
ec
t
ef
f
e
ct,
b
u
t
it
in
d
ir
ec
tly
in
f
lu
en
ce
s
ad
o
p
tio
n
v
ia
o
th
e
r
f
ac
to
r
s
lik
e
PU.
E
f
f
o
r
ts
to
im
p
r
o
v
e
th
e
ea
s
e
o
f
u
s
e
an
d
AT
G
AI
will
h
av
e
th
e
m
o
s
t
s
ig
n
if
ican
t
im
p
ac
t
o
n
a
d
o
p
tio
n
r
ates.
Un
iv
e
r
s
ities
s
h
o
u
ld
p
r
o
v
id
e
tar
g
eted
s
u
p
p
o
r
t
p
r
o
g
r
am
s
t
o
e
n
h
an
ce
ea
s
e
o
f
u
s
e
an
d
f
o
s
ter
p
o
s
itiv
e
attitu
d
es.
T
ab
le
7
p
r
esen
ts
th
e
co
m
p
u
te
d
p
ath
e
f
f
ec
ts
am
o
n
g
th
e
v
ar
iab
les,
s
h
o
win
g
h
o
w
PU,
PEU,
an
d
U
S in
f
lu
en
ce
AI
a
d
o
p
tio
n
in
ten
t
io
n
(
I
U)
t
h
r
o
u
g
h
attitu
d
e
to
wa
r
d
Gen
AI
.
3.
16
.
3
.
T
hem
a
t
ic
a
na
ly
s
is
T
ab
le
8
s
h
o
ws
em
er
g
en
t
th
em
es
o
r
n
ar
r
ativ
es
wh
en
we
ask
th
e
r
esp
o
n
d
en
ts
o
n
th
e
q
u
esti
o
n
:
“wh
at
p
o
licies
d
o
es
y
o
u
r
s
ch
o
o
l
h
av
e
r
eg
ar
d
i
n
g
th
e
u
s
e
o
f
Ge
n
AI
in
ed
u
ca
tio
n
?”
T
ab
le
8
p
r
esen
ts
em
er
g
en
t
th
em
es
f
r
o
m
th
e
t
h
em
atic
an
aly
s
is
o
f
s
ch
o
o
l
p
o
licies
r
elate
d
to
t
h
e
u
s
e
o
f
Gen
AI
in
ed
u
ca
tio
n
,
o
f
f
er
in
g
im
p
o
r
tan
t
q
u
alitativ
e
in
s
ig
h
ts
th
at
co
m
p
lem
en
t th
e
q
u
an
titativ
e
d
ata.
T
h
e
th
em
atic
an
aly
s
is
p
r
o
v
id
es
v
alu
ab
le
q
u
alitativ
e
in
s
ig
h
ts
in
to
th
e
ad
o
p
tio
n
o
f
Gen
AI
in
ed
u
ca
tio
n
,
c
o
m
p
lem
en
tin
g
b
r
o
ad
e
r
q
u
a
n
titativ
e
f
in
d
in
g
s
o
f
ten
o
b
s
er
v
ed
in
r
elate
d
r
esear
ch
.
T
h
e
id
en
tifie
d
th
em
es
r
ev
ea
l
g
ap
s
in
in
s
titu
tio
n
al
s
u
p
p
o
r
t
an
d
h
ig
h
lig
h
t
th
e
d
iv
er
s
e
attitu
d
es
an
d
p
r
ac
tice
s
s
u
r
r
o
u
n
d
in
g
Ge
n
AI
in
teg
r
at
io
n
in
s
ch
o
o
ls
.
T
h
e
ab
s
en
ce
o
f
a
u
n
if
ied
s
ch
o
o
l
-
wid
e
p
o
licy
,
as
n
o
te
d
in
th
e
th
em
atic
an
aly
s
is
,
r
ef
lects
a
lack
o
f
s
tr
u
ctu
r
ed
awa
r
e
n
ess
in
itiativ
es
an
d
in
s
titu
tio
n
al
g
u
id
an
ce
.
T
h
is
g
ap
lik
ely
co
n
tr
ib
u
tes
to
li
m
ited
u
n
d
e
r
s
tan
d
in
g
a
n
d
in
c
o
n
s
is
ten
t
p
r
ac
tices,
p
ar
ticu
lar
ly
am
o
n
g
s
tu
d
e
n
ts
,
wh
o
o
f
ten
r
ely
o
n
f
r
a
g
m
en
ted
o
r
in
s
tr
u
cto
r
-
s
p
ec
if
ic
r
u
les.
W
ith
o
u
t
clea
r
p
o
licies
o
r
d
is
s
em
in
atio
n
m
ec
h
a
n
is
m
s
,
th
e
p
o
ten
tial
b
e
n
ef
its
o
f
Gen
AI
to
o
ls
m
ay
r
em
ain
u
n
d
er
u
ti
lized
,
u
n
d
e
r
s
co
r
in
g
th
e
n
ee
d
f
o
r
c
o
m
p
r
e
h
en
s
iv
e
in
s
titu
tio
n
al
s
tr
ateg
ies.
T
h
e
v
ar
iab
ilit
y
in
in
s
tr
u
cto
r
r
esp
o
n
s
es,
h
ig
h
lig
h
ted
in
th
e
a
n
aly
s
is
,
u
n
d
er
s
co
r
es
th
e
r
o
le
o
f
teac
h
er
s
in
s
h
ap
in
g
th
e
a
d
o
p
tio
n
o
f
G
en
AI
.
I
n
s
tr
u
cto
r
s
’
d
if
f
er
i
n
g
le
v
els
o
f
f
am
iliar
ity
,
attitu
d
es,
an
d
willin
g
n
ess
to
in
teg
r
ate
th
ese
t
o
o
ls
r
esu
lt
i
n
in
co
n
s
is
ten
t
s
tu
d
en
t
ex
p
er
i
en
ce
s
.
T
h
is
d
is
p
ar
ity
s
u
g
g
ests
th
at
wh
ile
s
o
m
e
ed
u
ca
to
r
s
v
iew
Gen
AI
as
a
v
alu
ab
le
to
o
l,
o
th
er
s
r
e
m
ain
h
esit
an
t,
em
p
h
asizin
g
th
e
n
e
ed
f
o
r
s
tan
d
ar
d
ized
tr
ain
in
g
an
d
in
s
titu
tio
n
al
s
u
p
p
o
r
t to
b
r
id
g
e
th
ese
g
a
p
s
.
E
th
ical
co
n
s
id
er
atio
n
s
also
e
m
er
g
e
as
a
k
e
y
th
em
e
,
with
s
ch
o
o
ls
em
p
h
asizin
g
th
e
i
m
p
o
r
tan
ce
o
f
ac
ad
em
ic
in
teg
r
it
y
an
d
r
esp
o
n
s
ib
le
u
s
e
o
f
AI
.
T
h
is
f
o
c
u
s
alig
n
s
with
th
e
b
r
o
a
d
er
r
ec
o
g
n
itio
n
th
at
f
o
s
ter
in
g
p
o
s
itiv
e
attitu
d
es
to
war
d
tech
n
o
lo
g
y
d
e
p
en
d
s
o
n
ad
d
r
ess
in
g
eth
ical
co
n
ce
r
n
s
.
C
lear
g
u
id
e
lin
es
o
n
th
e
eth
ical
u
s
e
o
f
AI
,
p
air
ed
with
tr
an
s
p
ar
en
cy
a
n
d
p
r
o
p
er
citatio
n
p
r
ac
tices,
ar
e
cr
itical
f
o
r
en
s
u
r
in
g
r
esp
o
n
s
ib
le
ad
o
p
tio
n
.
Ad
d
itio
n
ally
,
th
e
t
h
em
es
o
f
tr
ain
in
g
,
g
u
id
a
n
ce
,
an
d
b
alan
cin
g
b
en
ef
its
with
r
is
k
s
h
ig
h
lig
h
t
th
e
im
p
o
r
tan
ce
o
f
in
s
titu
tio
n
al
e
f
f
o
r
ts
in
p
r
o
m
o
tin
g
e
f
f
ec
tiv
e
ad
o
p
tio
n
.
Pro
v
id
i
n
g
r
eso
u
r
ce
s
,
tr
ain
in
g
,
a
n
d
r
ea
l
-
wo
r
ld
a
p
p
licatio
n
s
ca
n
e
n
h
an
ce
t
h
e
PU
o
f
AI
to
o
ls
wh
ile
m
itig
atin
g
r
is
k
s
s
u
ch
as
o
v
er
-
r
elian
ce
o
r
m
is
u
s
e.
B
y
f
o
s
ter
in
g
a
p
o
s
itiv
e
attitu
d
e
th
r
o
u
g
h
tar
g
eted
i
n
ter
v
en
tio
n
s
an
d
s
u
cc
ess
s
to
r
ies,
in
s
titu
tio
n
s
ca
n
h
elp
b
o
th
s
tu
d
en
ts
an
d
e
d
u
ca
t
o
r
s
v
iew
Gen
AI
as a
to
o
l th
at
en
h
an
ce
s
,
r
ath
e
r
th
an
r
ep
lace
s
,
tr
ad
itio
n
al
lear
n
in
g
p
r
o
ce
s
s
es.
Ov
er
all,
th
e
th
em
at
ic
an
aly
s
is
o
f
f
er
s
ac
tio
n
ab
le
in
s
ig
h
ts
f
o
r
i
n
s
titu
tio
n
s
s
ee
k
in
g
to
in
teg
r
ate
Gen
AI
ef
f
ec
tiv
ely
.
Ad
d
r
ess
in
g
th
e
g
ap
s
in
awa
r
en
ess
,
in
s
titu
tio
n
al
s
u
p
p
o
r
t,
a
n
d
tr
ai
n
in
g
wh
ile
em
p
h
asizin
g
eth
ica
l
u
s
e
ca
n
cr
ea
te
an
e
n
v
ir
o
n
m
en
t
wh
er
e
Gen
AI
to
o
ls
ar
e
ad
o
p
ted
eq
u
itab
ly
an
d
e
f
f
ec
tiv
ely
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Evaluation Warning : The document was created with Spire.PDF for Python.
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t
o
o
l
r
a
t
h
e
r
t
h
a
n
a
s
h
o
r
t
c
u
t
f
o
r
a
c
a
d
e
mi
c
t
a
sk
s
.
4.
CO
NCLU
SI
O
N
T
h
is
s
tu
d
y
h
ig
h
lig
h
ts
th
e
p
iv
o
tal
r
o
le
o
f
US
in
f
ac
ilit
atin
g
th
e
ad
o
p
tio
n
o
f
Gen
AI
to
o
ls
am
o
n
g
s
tu
d
en
ts
an
d
ed
u
ca
to
r
s
.
C
lear
d
if
f
er
en
ce
s
in
p
e
r
ce
p
tio
n
s
an
d
u
s
ag
e
em
er
g
ed
:
teac
h
e
r
s
r
ep
o
r
ted
h
ig
h
er
lev
els
o
f
IU
(
6
.
0
6
)
a
n
d
PU
(
5
.
8
4
)
co
m
p
ar
ed
to
s
tu
d
en
ts
(
I
U=
4
.
9
3
,
PU=5
.
1
5
)
.
Mo
r
eo
v
e
r
,
s
tu
d
en
ts
d
em
o
n
s
tr
ated
lo
wer
awa
r
en
ess
(
3
.
7
0
)
a
n
d
p
er
ce
iv
ed
US
(
US=4
.
3
0
)
,
id
e
n
tify
in
g
c
r
itical
ar
ea
s
f
o
r
i
n
s
titu
tio
n
al
im
p
r
o
v
em
e
n
t.
Qu
an
titativ
e
r
esu
lts
co
n
f
ir
m
ed
th
at
AT
G
AI
was
th
e
m
o
s
t in
f
lu
en
tial p
r
ed
icto
r
o
f
IU
(
co
ef
f
i
cien
t=0
.
5
1
0
)
,
with
PU
an
d
PEU
p
lay
in
g
s
ig
n
i
f
ican
t r
o
les in
s
h
ap
in
g
b
o
t
h
attitu
d
es a
n
d
ad
o
p
tio
n
b
e
h
av
io
r
.
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