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in
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se
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g
h
ig
h
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d
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c
a
ti
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n
stu
d
e
n
ts.
K
ey
w
o
r
d
s
:
AI
f
atig
u
e
L
aten
t p
r
o
f
ile
a
n
aly
s
is
Stre
s
s
m
an
ag
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en
t
Stu
d
en
t p
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f
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Stu
d
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t w
ell
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T
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p
tio
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T
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se
.
C
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r
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s
p
o
nd
ing
A
uth
o
r
:
J
o
h
n
Pau
l P.
Mir
an
d
a
C
o
lleg
e
o
f
C
o
m
p
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tin
g
Stu
d
ies,
Pam
p
an
g
a
State
Un
iv
er
s
ity
San
J
u
an
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Me
x
ico
,
Pam
p
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a,
Ph
ilip
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m
ail: jp
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1.
I
NT
RO
D
UCT
I
O
N
Ar
tific
ial
in
tellig
en
ce
(
AI
)
to
o
ls
n
o
w
s
u
p
p
o
r
t
wr
itin
g
,
p
r
o
b
lem
s
o
lv
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f
ee
d
b
ac
k
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er
atio
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an
d
p
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o
d
u
ctiv
ity
task
s
in
h
ig
h
e
r
ed
u
ca
tio
n
s
ettin
g
s
[
1
]
,
[
2
]
.
Un
iv
er
s
ities
in
cr
ea
s
in
g
ly
ex
p
ec
t
s
tu
d
en
ts
t
o
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o
n
s
tr
ate
AI
liter
ac
y
,
p
r
o
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p
t
f
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r
m
u
latio
n
s
k
ills
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d
cr
iti
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ju
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m
e
n
t
wh
e
n
in
te
r
ac
tin
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with
th
ese
s
y
s
tem
s
[
2
]
.
E
d
u
ca
t
o
r
s
r
e
p
o
r
t
g
ain
s
in
ef
f
icien
c
y
a
n
d
in
s
tr
u
ctio
n
al
s
u
p
p
o
r
t.
Desp
ite
th
ese,
th
ey
also
e
n
co
u
n
ter
ch
allen
g
es
r
elate
d
to
tr
ain
in
g
,
cu
r
r
icu
lu
m
r
e
d
esig
n
,
an
d
c
h
an
g
es
in
s
tu
d
en
t
-
teac
h
er
in
ter
ac
tio
n
[
3
]
.
B
ey
o
n
d
Evaluation Warning : The document was created with Spire.PDF for Python.
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1964
th
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tatio
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co
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s
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s
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AI
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er
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x
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m
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s
d
escr
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it
as
AI
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f
atig
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[
4
]
.
T
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co
n
d
itio
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r
ef
e
r
s
to
s
u
s
tain
ed
c
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itiv
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s
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ain
an
d
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al
ex
h
au
s
tio
n
th
at
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g
e
f
r
o
m
r
ep
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ted
ev
alu
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n
,
v
er
if
icatio
n
,
a
n
d
ad
a
p
tatio
n
to
AI
-
g
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er
ate
d
o
u
t
p
u
ts
.
E
m
p
ir
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ca
l
r
ev
iews
o
f
AI
u
s
e
in
h
ig
h
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ed
u
ca
tio
n
r
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t
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ly
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s
o
f
d
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atig
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d
well
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ce
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s
am
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s
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d
en
ts
,
wh
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ig
h
lig
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t
th
e
p
r
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ce
o
f
AI
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s
p
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s
tr
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o
r
s
th
at
r
eq
u
ir
e
f
o
cu
s
ed
i
n
v
esti
g
atio
n
[
5
]
.
Stu
d
ies
o
n
g
en
er
ativ
e
AI
a
d
o
p
tio
n
in
e
d
u
ca
tio
n
al
c
o
n
tex
ts
f
u
r
th
er
id
en
tif
y
p
s
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ch
o
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ical
s
tr
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s
lin
k
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to
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tin
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s
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ter
ac
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d
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f
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asize
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ce
o
f
AI
-
in
d
u
ce
d
f
atig
u
e
as
a
d
is
tin
ct
co
n
s
tr
u
ct
[
6
]
–
[
8
]
.
Alth
o
u
g
h
r
elate
d
r
esear
ch
co
n
n
ec
ts
th
ese
o
u
tco
m
es
to
tech
n
o
s
tr
ess
an
d
co
g
n
itiv
e
s
tr
ain
in
d
ig
ital
en
v
ir
o
n
m
en
ts
,
ex
is
tin
g
s
tu
d
ies
r
ar
ely
is
o
late
AI
-
s
p
ec
if
ic
m
ec
h
an
is
m
s
with
in
ac
ad
em
ic
co
n
tex
ts
[
8
]
–
[
1
1
]
.
S
tu
d
ies
o
n
s
tu
d
en
t
well
-
b
ein
g
p
r
esen
t
m
ix
ed
ev
id
e
n
ce
o
n
th
e
co
n
s
eq
u
en
ce
s
o
f
AI
u
s
e.
R
esear
ch
s
h
o
ws
th
at
AI
s
y
s
tem
s
ca
n
en
h
a
n
ce
lear
n
in
g
th
r
o
u
g
h
p
er
s
o
n
aliza
tio
n
,
r
ap
id
f
ee
d
b
ac
k
,
an
d
co
llab
o
r
ativ
e
af
f
o
r
d
an
ce
s
th
at
s
u
p
p
o
r
t
ac
ad
e
m
ic
en
g
ag
em
en
t
[
2
]
,
[
1
2
]
.
Stu
d
en
ts
o
f
ten
r
ep
o
r
t
h
i
g
h
er
p
r
o
d
u
ctiv
ity
an
d
im
p
r
o
v
e
d
la
n
g
u
ag
e
s
u
p
p
o
r
t
wh
en
th
ey
r
el
y
o
n
AI
to
o
ls
f
o
r
c
o
u
r
s
ewo
r
k
[
1
3
]
.
At
th
e
s
am
e
tim
e,
s
ch
o
lar
s
ass
o
ciate
ex
ce
s
s
iv
e
d
ep
en
d
en
ce
o
n
AI
with
b
u
r
n
o
u
t
s
y
m
p
to
m
s
,
r
e
d
u
ce
d
s
elf
-
r
eg
u
latio
n
,
an
d
d
ec
lin
es
in
p
s
y
ch
o
lo
g
ical
well
-
b
ein
g
[
1
4
]
,
[
1
5
]
.
T
h
ese
s
tu
d
ies
s
u
g
g
est
th
at
b
en
ef
its
an
d
r
is
k
s
co
ex
is
t
r
ath
er
th
an
f
o
llo
w
a
s
in
g
le
tr
ajec
to
r
y
.
C
u
r
r
en
t
liter
atu
r
e,
h
o
wev
er
,
ten
d
s
to
tr
ea
t
s
tu
d
en
ts
as
a
h
o
m
o
g
en
e
o
u
s
g
r
o
u
p
,
wh
ich
lim
its
u
n
d
er
s
tan
d
in
g
o
f
h
o
w
d
if
f
e
r
en
t p
atter
n
s
o
f
AI
u
s
e
r
elate
to
f
atig
u
e
o
u
tco
m
es.
R
esear
ch
in
th
e
Ph
ilip
p
in
e
h
ig
h
er
ed
u
ca
tio
n
c
o
n
tex
t
s
h
o
ws
r
ap
id
s
tu
d
en
t
ad
o
p
tio
n
o
f
AI
to
o
ls
,
p
ar
ticu
lar
ly
f
o
r
wr
itin
g
a
n
d
ac
ad
em
ic
s
u
p
p
o
r
t
task
s
[
1
6
]
.
E
m
p
ir
ical
ev
id
en
ce
p
o
in
ts
t
o
u
n
ev
e
n
lev
els
o
f
awa
r
en
ess
,
co
n
f
id
e
n
ce
,
an
d
u
s
e
ac
r
o
s
s
ag
e
g
r
o
u
p
s
,
ac
ad
em
ic
y
ea
r
s
,
an
d
d
is
cip
lin
es
[
1
7
]
.
Su
ch
v
ar
iatio
n
im
p
lies
th
at
s
tu
d
en
ts
en
co
u
n
te
r
AI
-
r
elate
d
d
em
a
n
d
s
in
d
if
f
e
r
en
t
way
s
,
y
et
lo
ca
l
s
tu
d
ies
r
ar
ely
ex
am
in
e
th
ese
d
if
f
er
en
ce
s
s
y
s
tem
atica
lly
.
Mo
s
t
ex
is
tin
g
wo
r
k
r
elies
o
n
d
escr
ip
tiv
e
co
m
p
a
r
is
o
n
s
o
r
g
en
er
al
attitu
d
e
m
ea
s
u
r
es
r
ath
er
th
a
n
p
e
r
s
o
n
-
ce
n
te
r
ed
a
p
p
r
o
ac
h
es.
As
a
r
esu
lt,
t
h
e
lit
er
atu
r
e
p
r
o
v
i
d
es
lim
ited
g
u
id
an
ce
f
o
r
id
e
n
tify
in
g
wh
ich
s
tu
d
en
ts
f
ac
e
h
i
g
h
er
r
is
k
s
o
f
AI
-
r
elate
d
s
tr
ain
.
T
h
is
g
ap
co
n
s
tr
ain
s
th
e
d
esig
n
o
f
ta
r
g
eted
i
n
s
titu
tio
n
al
r
esp
o
n
s
es in
d
ev
elo
p
in
g
h
ig
h
e
r
ed
u
ca
tio
n
s
y
s
tem
s
.
T
h
is
s
tu
d
y
a
d
d
r
ess
es
th
is
g
ap
t
h
r
o
u
g
h
laten
t
p
r
o
f
ile
a
n
aly
s
is
(
L
PA)
th
at
ex
a
m
in
es
AI
-
in
d
u
c
ed
f
atig
u
e
am
o
n
g
h
ig
h
er
ed
u
ca
tio
n
s
tu
d
e
n
ts
in
th
e
Ph
ilip
p
in
e
co
n
tex
t.
E
x
is
tin
g
r
esear
ch
em
p
h
asizes th
e
in
s
tr
u
ctio
n
al
an
d
p
r
o
d
u
ctiv
ity
b
e
n
ef
its
o
f
AI
.
D
esp
ite
th
ese,
th
er
e
a
r
e
lim
ited
ev
id
en
ce
o
n
h
o
w
s
tu
d
en
ts
ex
p
er
ien
ce
AI
u
s
e
i
n
v
ar
ied
an
d
u
n
ev
en
way
s
.
T
h
i
s
s
tu
d
y
id
en
tifie
s
d
is
t
in
ct
s
tu
d
en
t
p
r
o
f
iles
b
ased
o
n
AI
liter
ac
y
,
s
elf
-
ef
f
icac
y
,
tech
n
o
s
tr
ess
,
co
g
n
itiv
e
lo
ad
,
a
n
d
f
atig
u
e
lev
els.
T
h
e
p
er
s
o
n
-
ce
n
ter
ed
ap
p
r
o
ac
h
m
o
v
es
th
e
an
aly
s
is
awa
y
f
r
o
m
av
er
ag
e
ef
f
ec
ts
an
d
to
war
d
s
t
r
u
ctu
r
ed
p
atter
n
s
th
at
r
ep
r
ese
n
t
m
ea
n
in
g
f
u
l
s
u
b
g
r
o
u
p
s
o
f
AI
u
s
er
s
.
T
h
e
s
tu
d
y
co
n
n
ec
ts
th
ese
p
r
o
f
iles
with
d
if
f
er
en
ce
s
in
AI
u
s
ag
e
in
ten
s
ity
an
d
ac
a
d
em
ic
d
em
an
d
s
to
e
x
p
lain
h
o
w
f
atig
u
e
m
an
if
ests
ac
r
o
s
s
co
n
d
itio
n
s
wh
ich
m
ay
p
r
o
v
id
e
em
p
ir
ical
g
r
o
u
n
d
in
g
f
o
r
p
o
ten
tial
tar
g
e
ted
in
ter
v
en
tio
n
s
to
p
r
o
p
er
l
y
s
u
p
p
o
r
t su
s
tain
ab
le
a
n
d
b
alan
ce
d
AI
u
s
e
in
h
ig
h
e
r
e
d
u
ca
tio
n
.
2.
M
E
T
H
O
D
T
h
is
s
tu
d
y
em
p
lo
y
ed
a
q
u
a
n
titativ
e,
cr
o
s
s
-
s
ec
tio
n
al
d
esig
n
to
id
en
tify
laten
t
p
r
o
f
iles
o
f
co
lleg
e
s
tu
d
en
ts
b
ased
o
n
th
eir
ex
p
er
ien
ce
s
with
AI
-
in
d
u
ce
d
f
atig
u
e
an
d
to
ex
am
in
e
th
e
f
ac
to
r
s
in
f
lu
en
cin
g
th
ese
p
r
o
f
iles
.
R
esp
o
n
d
en
ts
wer
e
r
eq
u
ir
ed
to
m
ee
t th
e
f
o
llo
win
g
in
clu
s
io
n
cr
iter
ia:
th
ey
m
u
s
t b
e
ac
tiv
ely
en
r
o
lled
in
a
co
lleg
e
o
r
u
n
iv
e
r
s
ity
in
th
e
Ph
ilip
p
in
es
an
d
h
av
e
ex
p
e
r
ien
ce
u
s
in
g
AI
to
o
ls
f
o
r
ac
ad
em
i
c
p
u
r
p
o
s
es.
Stu
d
en
ts
wh
o
d
id
n
o
t
u
s
e
AI
to
o
ls
in
th
eir
ac
ad
em
ic
wo
r
k
wer
e
e
x
clu
d
ed
f
r
o
m
th
e
s
tu
d
y
.
T
h
e
s
u
r
v
ey
in
s
tr
u
m
en
t
co
n
s
is
ted
o
f
3
6
item
s
,
with
3
1
item
s
ad
ap
ted
f
r
o
m
ex
is
tin
g
v
alid
ated
s
tu
d
ies
(
T
ab
le
1
)
.
T
h
e
in
s
tr
u
m
en
t
m
ea
s
u
r
ed
c
o
n
s
tr
u
cts
r
elate
d
to
AI
u
s
ag
e
in
te
n
s
ity
,
AI
liter
ac
y
,
s
elf
-
ef
f
icac
y
,
p
er
ce
iv
ed
u
s
ef
u
ln
ess
,
co
g
n
itiv
e
lo
ad
,
s
leep
q
u
ality
,
g
en
er
al
f
atig
u
e
lev
els,
tech
n
o
s
tr
ess
,
an
d
attitu
d
e
to
war
d
AI
.
T
o
en
s
u
r
e
clar
ity
an
d
r
eliab
ilit
y
,
th
e
i
n
s
tr
u
m
en
t
was
p
ilo
t
-
test
ed
with
3
0
s
tu
d
en
ts
b
ef
o
r
e
f
u
ll
im
p
lem
en
tatio
n
.
T
h
e
f
in
al
s
u
r
v
ey
was
d
is
tr
ib
u
ted
v
ia
Go
o
g
le
Fo
r
m
s
,
u
s
in
g
s
tu
d
en
t
g
r
o
u
p
c
h
ats
o
n
Me
s
s
en
g
er
f
o
r
d
is
s
em
in
atio
n
.
Data
co
llectio
n
o
cc
u
r
r
e
d
f
r
o
m
No
v
em
b
er
to
Dec
em
b
er
2
0
2
4
.
T
h
e
s
tu
d
y
u
s
ed
r
e
f
er
r
al
a
p
p
r
o
ac
h
to
id
en
tify
p
o
ten
tial
r
esp
o
n
d
en
ts
f
o
r
th
e
s
tu
d
y
.
I
n
it
ially
,
s
tu
d
en
ts
in
a
u
n
iv
er
s
ity
wer
e
ask
ed
to
an
s
wer
th
e
s
u
r
v
ey
an
d
f
o
r
war
d
th
e
Go
o
g
le
Fo
r
m
lin
k
to
th
eir
cla
s
s
m
ates
o
r
f
r
ien
d
s
f
r
o
m
with
in
an
d
o
u
ts
id
e
th
eir
u
n
iv
er
s
ity
wh
o
ar
e
u
s
in
g
AI
to
o
ls
.
E
th
ical
co
n
s
id
er
atio
n
s
ad
h
er
ed
to
t
h
e
p
r
in
cip
les
o
u
tl
in
ed
in
th
e
Ph
ilip
p
in
e
Data
Priv
ac
y
Act
an
d
th
e
g
u
id
elin
es f
o
r
th
e
co
n
d
u
ct
a
n
d
r
ep
o
r
tin
g
o
f
s
u
r
v
ey
r
esear
ch
.
T
h
e
d
ata
co
llected
f
r
o
m
th
e
f
in
al
s
u
r
v
ey
wer
e
an
aly
ze
d
u
s
in
g
Py
th
o
n
a
n
d
its
ass
o
ciate
d
lib
r
ar
ies.
Pan
d
as
was
u
s
ed
f
o
r
d
ata
cle
an
in
g
,
p
r
ep
r
o
ce
s
s
in
g
,
an
d
a
g
g
r
eg
atio
n
o
f
m
u
lti
-
item
co
n
s
tr
u
cts
in
to
co
m
p
o
s
ite
s
co
r
es.
I
t
was
al
s
o
u
s
ed
f
o
r
th
e
d
escr
ip
tiv
e
s
tatis
tic
s
(
e.
g
.
,
m
ea
n
s
an
d
s
tan
d
ar
d
d
ev
iati
o
n
s
)
wer
e
u
s
ed
to
s
u
m
m
ar
ize
d
em
o
g
r
ap
h
ic
in
f
o
r
m
atio
n
an
d
k
ey
v
ar
iab
les.
Sci
k
it
-
lear
n
was
u
tili
ze
d
to
p
e
r
f
o
r
m
s
tan
d
ar
d
izatio
n
o
f
d
ata
an
d
co
n
d
u
ct
L
PA
u
s
in
g
g
a
u
s
s
ian
m
ix
tu
r
e
m
o
d
els
.
L
PA
is
a
p
er
s
o
n
-
ce
n
ter
ed
ap
p
r
o
ac
h
u
s
ed
to
i
d
en
tify
s
u
b
g
r
o
u
p
s
with
in
p
o
p
u
latio
n
s
b
ased
o
n
s
h
ar
ed
ch
ar
ac
ter
is
tics
.
I
n
ed
u
ca
tio
n
al
s
ettin
g
s
,
L
P
A
h
as
b
ee
n
ap
p
lied
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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t J Ar
tif
I
n
tell
I
SS
N:
2252
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8
9
3
8
AI
-
in
d
u
ce
d
fa
tig
u
e
a
mo
n
g
s
tu
d
en
ts
in
h
ig
h
er e
d
u
ca
tio
n
:
a
l
a
ten
t p
r
o
file a
n
a
lysi
s
(
Dyn
a
h
D.
S
o
r
ia
n
o
)
1965
to
s
tu
d
y
b
u
r
n
o
u
t,
en
g
ag
em
en
t,
an
d
q
u
ality
o
f
life
am
o
n
g
s
tu
d
en
ts
[
1
8
]
–
[
2
0
]
.
L
PA
h
as
also
b
ee
n
u
s
ed
to
ex
am
in
e
th
e
r
elatio
n
s
h
ip
b
et
wee
n
tim
e
p
er
s
p
ec
tiv
e,
b
u
r
n
o
u
t,
an
d
d
ep
r
ess
io
n
in
ad
o
lesc
en
ts
[
2
1
]
,
as
well
a
s
h
ea
lth
-
r
elate
d
q
u
ality
o
f
life
,
s
leep
q
u
ality
,
an
d
in
ter
n
et
ad
d
ictio
n
am
o
n
g
m
ed
ical
s
tu
d
en
ts
[
2
2
]
.
Mo
d
el
s
elec
tio
n
co
n
s
id
er
ed
f
it
s
tatis
tics
(
Ak
aik
e
in
f
o
r
m
atio
n
cr
it
er
io
n
(
AI
C
)
an
d
B
ay
esian
in
f
o
r
m
atio
n
cr
iter
io
n
(
B
I
C
)
)
,
class
if
icat
io
n
q
u
ality
(
en
tr
o
p
y
)
,
p
r
o
f
ile
s
ize
ad
eq
u
a
cy
,
an
d
ex
p
er
t
r
ev
iew
o
f
co
m
p
etin
g
s
tr
u
ctu
r
e
o
f
in
f
o
r
m
atio
n
cr
iter
ia
ac
r
o
s
s
d
if
f
er
en
t
m
o
d
el
s
p
ec
if
icatio
n
s
was
p
er
f
o
r
m
ed
u
s
in
g
Py
th
o
n
in
J
u
p
y
ter
No
teb
o
o
k
en
v
ir
o
n
m
en
t.
T
h
e
r
esu
lts
o
f
t
h
e
L
PA
wer
e
in
ter
p
r
eted
t
o
i
d
en
tify
d
is
tin
ct
s
tu
d
en
t
p
r
o
f
il
es
ch
ar
ac
ter
ized
b
y
v
ar
y
in
g
lev
els
o
f
AI
liter
ac
y
,
s
elf
-
ef
f
icac
y
,
tech
n
o
s
tr
ess
,
c
o
g
n
itiv
e
lo
a
d
,
f
atig
u
e,
a
n
d
attitu
d
es
to
war
d
AI
.
Af
ter
s
elec
tin
g
th
e
f
in
al
L
PA
s
tr
u
ctu
r
e,
in
f
er
e
n
tial
co
m
p
ar
i
s
o
n
s
wer
e
co
n
d
u
cted
ac
r
o
s
s
p
r
o
f
iles
.
C
h
i
-
s
q
u
ar
e
test
s
o
f
in
d
ep
en
d
e
n
ce
wer
e
a
p
p
lied
to
ex
a
m
in
e
wh
eth
e
r
ca
te
g
o
r
ical
v
ar
ia
b
les
(
e.
g
.
,
s
ex
)
d
i
f
f
er
ed
s
ig
n
if
ica
n
tly
ac
r
o
s
s
laten
t
p
r
o
f
iles
.
On
e
-
w
ay
an
aly
s
is
o
f
v
ar
ian
ce
(
ANOV
A)
was
u
s
ed
to
co
m
p
ar
e
m
ea
n
d
if
f
er
e
n
ce
s
in
co
n
tin
u
o
u
s
co
n
s
tr
u
ct
s
co
r
es a
c
r
o
s
s
p
r
o
f
iles
.
T
ab
le
1
.
Op
e
r
atio
n
al
d
ef
i
n
itio
n
s
,
m
ea
s
u
r
em
en
t scale
s
,
an
d
s
o
u
r
ce
s
o
f
c
o
n
s
tr
u
cts in
th
e
i
n
s
tr
u
m
en
t
C
o
n
st
r
u
c
t
D
e
f
i
n
i
t
i
o
n
I
t
e
ms
M
e
a
su
r
e
me
n
t
S
o
u
r
c
e
A
I
u
sag
e
i
n
t
e
n
s
i
t
y
Th
e
f
r
e
q
u
e
n
c
y
a
n
d
d
u
r
a
t
i
o
n
o
f
A
I
t
o
o
l
u
s
a
g
e
f
o
r
a
c
a
d
e
m
i
c
p
u
r
p
o
s
e
s.
2
Li
k
e
r
t
s
c
a
l
e
a
n
d
r
a
t
i
o
C
u
s
t
o
m
-
d
e
v
e
l
o
p
e
d
A
I
l
i
t
e
r
a
c
y
Th
e
d
e
g
r
e
e
o
f
u
n
d
e
r
st
a
n
d
i
n
g
,
e
f
f
e
c
t
i
v
e
u
se,
a
n
d
a
w
a
r
e
n
e
ss
o
f
t
h
e
l
i
m
i
t
a
t
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o
n
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o
f
A
I
t
o
o
l
s.
3
Li
k
e
r
t
s
c
a
l
e
[
2
3
]
,
[
2
4
]
Te
c
h
n
o
s
t
r
e
ss
Th
e
s
t
r
e
ss
a
n
d
o
v
e
r
w
h
e
l
m
c
a
u
se
d
b
y
u
si
n
g
A
I
t
o
o
l
s
,
i
n
c
l
u
d
i
n
g
d
i
f
f
i
c
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l
t
y
a
d
a
p
t
i
n
g
t
o
o
r
man
a
g
i
n
g
t
h
e
i
r
c
o
m
p
l
e
x
i
t
i
e
s
.
3
Li
k
e
r
t
s
c
a
l
e
[
8
]
,
[
2
5
]
S
e
l
f
-
e
f
f
i
c
a
c
y
i
n
A
I
u
se
Th
e
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o
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f
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s
a
b
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f
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t
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se
A
I
t
o
o
l
s
f
o
r
a
c
a
d
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mi
c
t
a
s
k
s.
2
Li
k
e
r
t
s
c
a
l
e
[
2
6
]
,
[
2
7
]
P
e
r
c
e
i
v
e
d
u
s
e
f
u
l
n
e
ss
o
f
A
I
Th
e
e
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t
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t
t
o
w
h
i
c
h
A
I
t
o
o
l
s
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mp
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p
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r
f
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ma
n
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n
d
e
f
f
i
c
i
e
n
c
y
.
3
Li
k
e
r
t
s
c
a
l
e
[
2
8
]
,
[
2
9
]
C
o
g
n
i
t
i
v
e
l
o
a
d
Th
e
m
e
n
t
a
l
e
f
f
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t
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e
q
u
i
r
e
d
t
o
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se
A
I
t
o
o
l
s
e
f
f
e
c
t
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v
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y
f
o
r
l
e
a
r
n
i
n
g
.
3
Li
k
e
r
t
s
c
a
l
e
[
3
0
]
,
[
3
1
]
S
l
e
e
p
q
u
a
l
i
t
y
Th
e
i
mp
a
c
t
o
f
A
I
-
r
e
l
a
t
e
d
a
c
a
d
e
mi
c
t
a
sk
s
o
n
st
u
d
e
n
t
s’
a
b
i
l
i
t
y
t
o
s
l
e
e
p
w
e
l
l
a
n
d
f
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e
l
r
e
st
e
d
.
2
Li
k
e
r
t
s
c
a
l
e
[
3
2
]
–
[
3
4
]
G
e
n
e
r
a
l
f
a
t
i
g
u
e
l
e
v
e
l
s
Th
e
o
v
e
r
a
l
l
p
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y
s
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c
a
l
a
n
d
me
n
t
a
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x
h
a
u
s
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o
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e
x
p
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d
f
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m
p
r
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l
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n
g
e
d
o
r
f
r
e
q
u
e
n
t
A
I
u
s
e
.
3
Li
k
e
r
t
s
c
a
l
e
[
3
5
]
,
[
3
6
]
A
t
t
i
t
u
d
e
t
o
w
a
r
d
A
I
Th
e
d
e
g
r
e
e
o
f
p
o
si
t
i
v
i
t
y
o
r
n
e
g
a
t
i
v
i
t
y
i
n
s
t
u
d
e
n
t
s’
p
e
r
c
e
p
t
i
o
n
s
o
f
A
I
t
o
o
l
s
a
n
d
t
h
e
i
r
p
o
t
e
n
t
i
a
l
.
3
Li
k
e
r
t
s
c
a
l
e
[
3
7
]
,
[
3
8
]
2
.
1
.
De
m
o
g
r
a
ph
ic
pro
f
ile
o
f
t
he
re
s
po
nd
ent
s
T
h
er
e
3
8
8
r
esp
o
n
d
en
ts
in
th
is
s
tu
d
y
.
All a
r
e
s
tu
d
en
ts
f
r
o
m
u
n
iv
er
s
ities
in
C
en
tr
al
L
u
zo
n
,
Ph
ilip
p
in
es.
T
h
ey
6
0
.
6
%
ar
e
f
em
ale
a
n
d
3
9
.
4
%
ar
e
m
ale.
T
h
e
a
g
e
r
an
g
e
d
o
f
th
e
r
esp
o
n
d
e
n
ts
wer
e
1
7
t
o
3
5
y
ea
r
s
o
ld
.
T
h
e
r
esp
o
n
d
en
ts
m
ajo
r
ed
in
e
d
u
ca
tio
n
an
d
teac
h
e
r
tr
ain
in
g
(
2
8
.
4
%),
to
u
r
is
m
an
d
h
o
s
p
it
ality
m
an
ag
em
en
t
(
2
3
.
2
%),
c
o
m
p
u
te
r
s
cien
ce
an
d
in
f
o
r
m
atio
n
tech
n
o
lo
g
y
(
2
0
.
6
%),
en
g
in
ee
r
in
g
an
d
tech
n
o
lo
g
y
(
1
8
%),
h
u
m
an
ities
an
d
s
o
cial
s
cien
ce
s
(
7
.
5
%),
b
u
s
in
ess
an
d
m
an
ag
em
en
t
(
1
.
8
%),
an
d
m
at
h
e
m
atics
an
d
n
atu
r
al
s
cien
ce
s
(
0
.
5
%).
Mo
r
e
th
an
h
alf
o
r
th
e
r
esp
o
n
d
en
ts
a
r
e
th
ir
d
y
ea
r
(
5
5
.
4
%).
T
h
is
was
f
o
ll
o
wed
b
y
f
ir
s
t
y
ea
r
(
3
6
.
1
%),
f
o
u
r
th
y
ea
r
(
6
.
4
%),
an
d
s
ec
o
n
d
y
ea
r
(
2
.
1
%).
T
h
e
3
3
.
8
%
o
f
th
e
r
esp
o
n
d
en
ts
s
tated
th
at
th
ey
alwa
y
s
h
av
e
ac
ce
s
s
to
a
lap
to
p
o
r
co
m
p
u
ter
f
o
r
th
eir
ac
ad
em
ic
u
s
e.
I
n
ter
m
s
o
f
th
eir
u
s
e
o
f
AI
to
o
ls
f
o
r
ac
ad
em
ic
p
u
r
p
o
s
es,
5
0
.
5
%
o
f
th
e
r
es
p
o
n
d
e
n
ts
in
d
icate
d
th
at
th
e
y
s
o
m
etim
es
u
s
e
th
em
.
On
ly
5
.
9
%
an
d
1
7
.
5
%
m
en
tio
n
ed
th
ey
u
s
e
th
em
o
f
t
en
an
d
alwa
y
s
r
esp
ec
tiv
ely
.
T
h
ese
r
esp
o
n
d
en
ts
ar
e
u
s
in
g
AI
to
o
ls
f
o
r
th
eir
s
tu
d
ies
f
r
o
m
o
n
e
u
p
t
o
6
0
h
o
u
r
s
tim
es
a
wee
k
.
On
av
er
a
g
e
t
h
ey
ar
e
u
s
in
g
A
I
to
o
ls
th
r
ee
h
o
u
r
s
p
er
wee
k
.
T
h
e
4
9
%
o
f
th
em
s
tated
th
at
th
e
y
a
r
e
u
s
in
g
AI
to
o
ls
at
least
f
o
r
a
n
h
o
u
r
a
wee
k
.
T
h
e
2
5
.
3
%
o
f
t
h
em
ar
e
d
ed
icatin
g
o
n
e
h
o
u
r
o
f
t
h
eir
wee
k
f
o
r
ac
ad
em
ic
task
s
o
u
ts
id
e
class
h
o
u
r
s
.
T
h
e
av
er
ag
e
h
o
u
r
s
d
ed
icate
d
b
y
th
e
r
esp
o
n
d
en
ts
t
o
ac
a
d
em
ic
task
s
o
u
ts
id
e
class
h
o
u
r
s
is
s
ev
e
n
h
o
u
r
s
.
T
h
e
1
0
.
1
%
o
f
th
e
r
e
s
p
o
n
d
en
ts
r
e
p
o
r
te
d
d
ed
icatin
g
2
0
o
r
m
o
r
e
h
o
u
r
s
o
u
ts
id
e
class
h
o
u
r
s
.
On
e
r
esp
o
n
d
en
t
r
ep
o
r
ted
allo
ca
tin
g
1
0
0
h
o
u
r
s
f
o
r
ac
ad
e
m
ic
task
s
o
u
ts
id
e
class
e
s
alo
n
e.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
3
.
1
.
Descript
iv
e
s
t
a
t
is
t
ics
T
ab
le
2
s
h
o
ws
th
at
s
tu
d
en
ts
u
s
e
AI
to
o
ls
m
o
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atter
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icate
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r
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le
3
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T
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p
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ile
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also
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e
p
r
o
f
ile
ad
eq
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ac
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cr
it
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s
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i
n
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r
s
o
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ter
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d
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is
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ter
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d
s
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itized
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it.
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ter
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s
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r
d
if
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r
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s
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m
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ete
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ce
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tr
ain
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d
im
en
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io
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s
.
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e
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h
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s
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s
with
r
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ig
h
AI
liter
ac
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an
d
s
elf
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f
icac
y
,
l
o
w
tech
n
o
s
tr
ess
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d
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g
n
itiv
e
l
o
ad
,
b
u
t
p
o
o
r
s
leep
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u
ality
an
d
m
o
d
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ate
f
atig
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e.
Pr
o
f
ile
2
r
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r
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ted
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v
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wh
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s
er
s
with
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er
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w
AI
liter
ac
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elf
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f
icac
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,
an
d
p
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r
ce
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u
s
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ln
ess
,
c
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m
b
in
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with
h
ig
h
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g
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itiv
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lo
ad
,
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ig
h
tech
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o
s
tr
ess
,
p
o
o
r
s
leep
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u
ality
,
an
d
h
i
g
h
f
atig
u
e.
Pro
f
ile
3
r
e
f
lecte
d
m
o
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ate
an
d
s
tab
le
u
s
er
s
with
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ete
n
ce
an
d
m
a
n
ag
ea
b
le
tech
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o
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ess
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f
atig
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e.
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f
ile
4
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s
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ile
5
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d
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u
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ln
ess
,
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ar
tif
I
n
tell
I
SS
N:
2252
-
8
9
3
8
AI
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in
d
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fa
tig
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a
lysi
s
(
Dyn
a
h
D.
S
o
r
ia
n
o
)
1967
b
u
t
also
h
ig
h
tech
n
o
s
tr
ess
,
h
i
g
h
co
g
n
itiv
e
lo
ad
,
p
o
o
r
s
leep
q
u
ality
,
an
d
h
ig
h
f
atig
u
e.
Pr
o
f
ile
6
co
n
s
is
ted
o
f
lo
w
-
s
tr
ess
m
o
d
er
ate
u
s
er
s
wit
h
lo
wer
co
m
p
ete
n
ce
lev
els
b
u
t
lo
w
tech
n
o
s
tr
ess
an
d
c
o
g
n
iti
v
e
lo
ad
an
d
s
tab
le
s
leep
q
u
ality
an
d
f
atig
u
e
lev
el
s
.
T
ab
le
4
.
Dis
tin
ct
p
r
o
f
iles
P
r
o
f
i
l
e
n
La
b
e
l
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y
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h
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r
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t
e
r
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c
s
1
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o
m
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t
b
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sers
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g
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c
e
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o
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l
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n
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m
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h
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e
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d
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t
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sers
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t
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o
mp
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t
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e
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ma
n
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g
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t
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t
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t
r
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si
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t
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t
f
a
t
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g
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e
,
a
n
d
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l
e
e
p
i
ss
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e
s
5
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4
5
H
i
g
h
-
i
n
t
e
n
s
i
t
y
s
t
r
a
i
n
e
d
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s
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r
s
H
i
g
h
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sa
g
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,
h
i
g
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o
m
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t
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c
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g
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st
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o
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l
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p
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d
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f
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t
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e
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w
-
st
r
a
i
n
se
l
e
c
t
i
v
e
u
sers
Lo
w
-
to
-
mo
d
e
r
a
t
e
c
o
m
p
e
t
e
n
c
e
,
l
o
w
st
r
a
i
n
,
a
n
d
s
t
a
b
l
e
s
l
e
e
p
a
n
d
f
a
t
i
g
u
e
3
.
3
.
Dif
f
er
ence
s
in L
P
A
pro
f
iles
a
nd
t
heir
de
s
cr
iptiv
e
s
t
a
t
is
t
ics
T
h
e
ch
i
-
s
q
u
a
r
e
test
s
h
o
wed
n
o
s
tatis
tically
s
ig
n
if
ican
t
ass
o
ciatio
n
b
etwe
en
s
ex
a
n
d
lat
en
t
p
r
o
f
ile
m
em
b
er
s
h
ip
,
χ²(
5
)
=
1
0
.
4
8
,
p
=0
6
3
,
with
a
s
m
all
ef
f
ec
t
s
ize
(
C
r
am
ér
’
s
V
=1
6
)
w
h
ich
in
d
icate
s
a
lim
ited
d
if
f
er
en
ce
s
in
th
e
d
is
tr
ib
u
tio
n
o
f
m
ale
an
d
f
em
ale
r
esp
o
n
d
en
ts
ac
r
o
s
s
p
r
o
f
iles
.
T
h
is
r
esu
lt
s
u
g
g
ests
th
at
p
r
o
f
ile
m
em
b
er
s
h
ip
d
i
d
n
o
t
s
u
b
s
tan
ti
ally
v
ar
y
b
y
s
ex
in
th
e
p
r
esen
t
s
am
p
le.
On
th
e
o
th
er
h
an
d
,
ANOV
A
s
h
o
wed
s
tatis
t
ically
s
ig
n
if
ican
t
d
if
f
er
en
ce
s
ac
r
o
s
s
p
r
o
f
iles
f
o
r
s
le
ep
q
u
ality
,
tech
n
o
s
tr
ess
,
AI
liter
ac
y
,
p
e
r
ce
iv
ed
u
s
ef
u
ln
ess
,
AI
u
s
ag
e
in
ten
s
ity
,
g
en
er
al
f
atig
u
e,
c
o
g
n
itiv
e
l
o
ad
,
an
d
s
elf
-
ef
f
icac
y
(
all
p
<
.
0
0
1
)
.
Sleep
q
u
ality
s
h
o
wed
th
e
s
tr
o
n
g
est
p
r
o
f
ile
s
ep
ar
atio
n
,
F(5
,
3
8
2
)
=
4
4
.
6
9
,
p
<
.
0
0
1
,
with
p
o
o
r
e
r
s
leep
o
b
s
er
v
e
d
in
th
e
h
ig
h
-
s
tr
ain
p
r
o
f
iles
(
p
a
r
ticu
lar
ly
p
r
o
f
iles
2
an
d
5
)
an
d
m
o
r
e
s
tab
le
s
leep
o
u
tco
m
es
in
p
r
o
f
i
le
6
.
T
ec
h
n
o
s
tr
ess
also
d
if
f
er
ed
s
ig
n
if
ica
n
tly
ac
r
o
s
s
p
r
o
f
iles
,
F(5
,
3
8
2
)
=
2
7
.
0
5
,
p
<
.
0
0
1
,
with
th
e
h
ig
h
est
le
v
els
co
n
ce
n
tr
ated
i
n
p
r
o
f
iles
2
a
n
d
5
an
d
co
m
p
ar
ativ
ely
lo
wer
lev
els
in
p
r
o
f
iles
1
an
d
6
.
C
o
m
p
eten
ce
-
r
ela
ted
co
n
s
tr
u
cts
also
v
ar
ied
s
ig
n
if
ica
n
tly
,
i
n
clu
d
in
g
AI
liter
ac
y
,
F(
5
,
3
8
2
)
=1
2
.
9
1
,
p
<.
0
0
1
,
an
d
s
elf
-
e
f
f
icac
y
,
F(5
,
3
8
2
)
=4
.
2
4
,
p
<0
0
1
,
wh
er
e
p
r
o
f
ile
2
r
e
f
lecte
d
th
e
lo
west
co
m
p
ete
n
ce
a
n
d
p
r
o
f
iles
1
a
n
d
5
r
ef
lecte
d
h
ig
h
er
co
m
p
eten
ce
p
atter
n
s
.
I
n
co
n
tr
ast,
attitu
d
e
to
war
d
AI
d
id
n
o
t
s
ig
n
if
ican
t
ly
d
if
f
er
ac
r
o
s
s
p
r
o
f
iles
,
F(5
,
3
8
2
)
=2
,
p
=.
0
7
8
wh
ich
s
h
o
ws a
r
elativ
ely
s
im
ilar
attitu
d
es to
war
d
AI
d
esp
ite
d
if
f
er
en
ce
s
in
f
atig
u
e
-
r
elate
d
o
u
tco
m
es.
4.
CO
NCLU
SI
O
N
T
h
i
s
s
tu
d
y
d
e
m
o
n
s
tr
at
e
s
th
a
t
s
tu
d
en
t
s
’
e
x
p
er
ien
ce
s
w
ith
AI
to
o
l
s
v
ar
y
s
ig
n
if
ica
n
t
ly
.
T
h
ey
co
v
er
d
i
s
t
in
c
t
p
r
o
f
i
le
s
th
a
t
r
an
g
e
f
r
o
m
lo
w
-
s
tr
e
s
s
,
b
al
an
c
ed
u
s
er
s
to
h
ig
h
-
in
t
en
s
i
ty
,
f
a
tig
u
ed
in
d
iv
id
u
al
s
.
T
h
e
s
e
r
es
u
l
t
s
s
h
o
w
th
e
im
p
o
r
t
an
c
e
o
f
ta
il
o
r
ed
in
ter
v
en
t
io
n
s
to
ad
d
r
es
s
s
p
ec
if
i
c
c
h
al
le
n
g
e
s
s
u
ch
as
lo
w
A
I
l
it
er
a
cy
,
tech
n
o
s
tr
es
s
,
a
n
d
s
leep
d
is
r
u
p
tio
n
s
.
Fo
r
in
s
t
an
c
e,
s
tu
d
en
t
s
u
n
d
er
p
r
o
f
i
le
1
r
eq
u
ir
e
s
u
p
p
o
r
t
in
im
p
r
o
v
i
n
g
tim
e
m
an
ag
em
en
t
an
d
m
i
n
im
iz
in
g
AI
-
r
e
la
ted
s
l
ee
p
d
i
s
r
u
p
t
i
o
n
s
,
w
h
i
le
p
r
o
f
il
e
2
s
tu
d
e
n
t
s
b
en
ef
it
f
r
o
m
f
o
u
n
d
at
io
n
al
AI
liter
ac
y
tr
ain
i
n
g
to
b
u
ild
c
o
n
f
id
e
n
ce
a
n
d
r
e
d
u
ce
tech
n
o
s
tr
ess
.
Simp
lifie
d
to
o
ls
an
d
en
h
a
n
ce
d
u
s
er
s
u
p
p
o
r
t
ca
n
f
u
r
th
e
r
ea
s
e
th
eir
co
g
n
itiv
e
lo
a
d
.
Fo
r
p
r
o
f
il
e
3
,
p
er
io
d
ic
s
u
p
p
o
r
t
an
d
r
eso
u
r
ce
s
ar
e
s
u
f
f
icien
t
to
m
ain
tain
th
eir
b
alan
ce
d
u
s
a
g
e
an
d
p
r
ev
en
t
b
u
r
n
o
u
t,
as
m
i
n
im
al
in
ter
v
en
tio
n
is
o
th
e
r
wis
e
n
ee
d
ed
.
L
ik
ewise,
s
tu
d
en
ts
in
p
r
o
f
ile
4
m
a
y
g
ai
n
f
r
o
m
s
tr
ess
m
an
ag
e
m
en
t
te
ch
n
iq
u
es
a
n
d
s
tr
ateg
ies
to
im
p
r
o
v
e
s
leep
q
u
ality
,
alo
n
g
s
id
e
o
p
tim
ize
d
AI
to
o
ls
to
lo
wer
co
g
n
itiv
e
lo
ad
.
Similar
ly
,
in
ter
v
e
n
tio
n
s
f
o
r
p
r
o
f
ile
5
s
h
o
u
ld
f
o
cu
s
o
n
r
ed
u
cin
g
tec
h
n
o
s
tr
ess
an
d
co
g
n
itiv
e
lo
ad
th
r
o
u
g
h
u
s
er
-
f
r
ien
d
ly
to
o
l
d
esig
n
,
wh
ile
en
co
u
r
ag
in
g
b
r
ea
k
s
an
d
b
etter
s
leep
h
ab
its
to
allev
iate
f
atig
u
e.
Fo
r
p
r
o
f
ile
6
,
o
p
p
o
r
tu
n
ities
to
en
h
an
ce
AI
liter
ac
y
a
n
d
s
elf
-
ef
f
icac
y
c
a
n
h
elp
th
em
m
ax
im
ize
th
e
b
en
ef
its
o
f
AI
to
o
ls
,
alth
o
u
g
h
th
eir
lo
w
s
tr
ess
lev
el
s
in
d
icate
th
at
m
in
im
al
ad
d
itio
n
a
l
s
u
p
p
o
r
t
is
n
ec
ess
ar
y
.
T
h
r
o
u
g
h
L
PA,
th
e
s
tu
d
y
was
ab
l
e
to
h
ig
h
lig
h
t
th
e
p
o
ten
tial
f
o
r
p
r
o
f
ile
-
s
p
ec
if
ic
in
ter
v
en
tio
n
s
t
o
ad
d
r
ess
s
tu
d
en
ts
’
u
n
iq
u
e
n
ee
d
s
r
elate
d
t
o
AI
-
in
d
u
ce
d
f
atig
u
e.
I
n
s
titu
tio
n
s
ca
n
n
o
t
o
n
ly
im
p
r
o
v
e
ac
ad
e
m
ic
o
u
tco
m
es
b
ased
o
n
th
ese
r
esu
lts
b
u
t
als
o
f
o
s
ter
p
o
s
itiv
e
an
d
em
p
o
wer
ex
p
er
ien
ce
s
with
em
er
g
in
g
tec
h
n
o
lo
g
ies.
ACK
NO
WL
E
DG
M
E
N
T
S
T
h
is
s
tu
d
y
wo
u
ld
lik
e
to
ex
ten
d
its
s
in
ce
r
e
g
r
atitu
d
e
to
all
th
e
s
tu
d
en
ts
wh
o
p
ar
ticip
ated
.
W
ith
o
u
t
th
eir
co
n
s
en
t a
n
d
co
o
p
er
atio
n
,
th
is
r
esear
ch
wo
u
ld
n
o
t h
a
v
e
b
ee
n
p
o
s
s
ib
le.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
T
h
is
s
tu
d
y
is
s
u
p
p
o
r
ted
b
y
t
h
e
au
th
o
r
s
in
d
i
v
id
u
al
af
f
iliatio
n
.
No
f
u
n
d
in
g
in
v
o
lv
e
d
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
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8
9
3
8
I
n
t J Ar
tif
I
n
tell
,
Vo
l.
1
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ty
M
a
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m
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th
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d
in
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m
istry
a
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d
f
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o
d
sc
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c
e
,
h
e
is
p
a
ss
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n
a
te
a
b
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m
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t
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ti
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ic
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c
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ti
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d
p
ro
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ss
io
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a
l
p
ra
c
ti
c
e
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
a
b
m
a
rti
n
e
z
@p
a
m
p
a
n
g
a
sta
teu
.
e
d
u
.
p
h
.
Ra
y
m
o
n
d
A.
Ca
b
r
e
r
a
is
a
n
a
ss
o
c
iate
p
ro
fe
ss
o
r
a
n
d
t
h
e
c
o
m
m
u
n
it
y
e
x
ten
si
o
n
se
rv
ice
s
re
p
re
se
n
tativ
e
o
f
t
h
e
S
c
h
o
o
l
o
f
Co
m
p
u
ti
n
g
a
t
Ho
l
y
A
n
g
e
l
Un
iv
e
rsity
,
P
h
il
ip
p
in
e
s.
He
is
a
m
e
m
b
e
r
o
f
th
e
P
h
il
i
p
p
in
e
S
o
c
iety
o
f
I
n
fo
rm
a
ti
o
n
Tec
h
n
o
l
o
g
y
Ed
u
c
a
to
rs
In
c
.
,
a
n
d
th
e
M
e
c
h
a
tro
n
ics
Ro
b
o
ti
c
s
S
o
c
iet
y
o
f
th
e
P
h
il
i
p
p
i
n
e
s.
His
re
se
a
rc
h
in
te
re
sts
a
re
re
late
d
to
a
rti
ficia
l
in
telli
g
e
n
c
e
,
in
tern
e
t
o
f
t
h
in
g
s,
a
n
d
i
n
fo
rm
a
ti
o
n
tec
h
n
o
lo
g
y
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
ra
c
a
b
re
ra
@h
a
u
.
e
d
u
.
p
h
.
J
a
y
m
a
r
k
A.
Ya
m
b
a
o
is
th
e
p
ro
g
ra
m
c
o
o
r
d
in
a
t
o
r
f
o
r
Ba
c
h
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lo
r
o
f
S
c
ien
c
e
i
n
In
fo
rm
a
ti
o
n
Tec
h
n
o
l
o
g
y
a
t
P
a
m
p
a
n
g
a
S
tate
Un
i
v
e
rsity
-
M
e
x
ico
Ca
m
p
u
s.
He
h
a
s
a
m
a
ste
r’s
d
e
g
re
e
in
IT
a
t
S
y
ste
m
P
lu
s
C
o
ll
e
g
e
F
o
u
n
d
a
ti
o
n
i
n
An
g
e
les
Cit
y
,
P
h
il
i
p
p
i
n
e
s.
He
is
n
o
w
p
u
rsu
i
n
g
h
is
d
o
c
to
r
o
f
IT
i
n
t
h
e
sa
m
e
in
stit
u
ti
o
n
wi
th
a
fo
c
u
s
o
n
S
o
ftwa
re
E
n
g
i
n
e
e
rin
g
a
n
d
Da
ta
S
c
ien
c
e
.
He
is
a
m
e
m
b
e
r
o
f
th
e
P
h
il
i
p
p
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n
e
S
o
c
iet
y
o
f
In
f
o
rm
a
ti
o
n
Tec
h
n
o
lo
g
y
E
d
u
c
a
to
rs
(P
S
ITE
)
–
Re
g
io
n
3
a
n
d
th
e
I
n
tern
a
ti
o
n
a
l
Co
n
g
re
ss
o
f
I
n
n
o
v
a
ti
o
n
-
Ba
se
d
Ed
u
c
a
to
rs
a
n
d
Re
se
a
rc
h
e
rs,
In
c
.
He
a
lso
v
a
lu
e
s
h
is
p
e
rso
n
a
l
li
fe
.
His
re
se
a
rc
h
in
tere
st
in
c
lu
d
e
s
we
b
d
e
v
e
lo
p
m
e
n
t,
d
a
ta
sc
ien
c
e
,
a
n
d
in
fo
rm
a
ti
o
n
tec
h
n
o
lo
g
y
e
d
u
c
a
ti
o
n
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
jay
a
m
b
a
o
@p
a
m
p
a
n
g
a
sta
teu
.
e
d
u
.
p
h
.
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