In
te
r
n
ation
al Jou
r
n
al o
f Evalu
ation
an
d
Re
sear
c
h
in
Ed
u
c
ation
(IJER
E)
Vol.
15
, No.
4
,
August
20
26
, pp.
330
1
~
3309
I
S
S
N: 2252
-
8822
,
DO
I
:
10.11591/
ij
e
re
.
v
15
i
4
.
38954
3301
Jou
rn
al h
o
mepage
:
htt
p://i
jere
.iaesc
ore
.c
om
A
cademi
c procrast
ination a
nd achieve
men
t am
ong unive
rsi
ty
st
udents under
A
I overrel
ia
n
ce and contextual fact
ors
Tan
g M
y S
an
g
1
, Le Qu
oc
Th
an
g
2
1
H
o C
hi
Mi
nh U
ni
ve
r
si
ty
of
B
a
nki
ng, Ho Chi
Mi
nh C
it
y, V
ie
tn
a
m
2
H
o C
hi
Mi
nh C
i
ty
U
ni
ve
r
si
ty
of
Ec
onomi
c
s a
nd F
in
a
n
c
e
(
U
E
F
)
, H
o C
hi
Mi
nh C
i
ty
, V
ie
tn
a
m
Ar
tic
le In
fo
ABS
TRAC
T
Ar
ti
c
le hi
st
ory
:
Rec
e
ived
F
e
b
3
,
2026
Revised
Jun
26
,
2026
Ac
c
e
pt
e
d
Ju
l
9
,
2026
Academic
procrastination
re
mains
a
persistent
challenge
in
higher
education,
particularly
as
artificial
intelligence
(AI
)
tools
b
ecome
increasingly
integrated
into
students’
l
earning
activities.
While
AI
can
assist
with
academic
tasks,
excessive
reliance
on
such
technol
ogies
may
influence
students’
learning
behavior
s
and
time
management.
This
study
employed
a
quantitative
,
cross
-
se
ction
al
design
to
examine
the
fa
ctors
associated
with
academic
procrasti
nation
an
d
its
relations
hip
with
acad
emic
achievement
in
higher
education
contexts
where
AI
tools
are
wid
ely
used.
Data
were
collected
from
301
universi
ty
student
s
and
analyzed
using
partial
least
squares
structural
equation
modeling
(PLS
-
SEM).
Th
e
results
indicate
that
the
model
explains
a
su
bstantial
proportion
of
v
ariance
in
academic
procrastination
(R²=0
.
72)
and
a
mode
rate
prop
ortion
in
academic
achievement
(R²=0
.
30).
Academic
procrasti
nation
shows
a
signifi
cant
relationshi
p
with
a
cademic
achievement
(β=
0
.
551,
p
<
0
.
001).
Among
the
predictors,
self
-
regulat
ed
learning
(
β=
-
0.
800)
an
d
school
attachment
(β=
-
0.
803)
exhibit
the
stro
ngest
negative
associations
with
procrastination,
while
AI
overreliance
(
β=
0.
430)
increases
academic
pr
ocrastination.
Digital
competence
(β
=
-
0.
441)
als
o
contributes
to
reducing
p
rocrastination.
These
findings
suggest
that
acade
mic
procrastinati
on
function
s
as
a
key
mechanism
linking
individual,
contex
tual,
and
technologi
cal
f
actors
to
academic
outcomes
in
technology
-
su
pported
higher
education
.
The
results
highlight
the
importance
of
strengthening
students’
self
-
regulated
learning
and
promoting
cautious
and
resp
onsible
AI
use
in
higher
edu
cation.
Key
wor
d
s
:
Ac
a
de
mi
c
p
roc
r
a
st
ination
Ac
a
de
mi
c
a
c
hiev
e
ment
A
I
ove
r
re
li
a
nc
e
Highe
r e
duc
a
ti
on
S
e
lf
-
re
gulate
d l
e
a
rning
This
is
an
open
access
articl
e
under
the
CC
BY
-
SA
licen
se.
Cor
respondi
n
g A
u
th
o
r:
Le
Quoc
Th
a
ng
Ho Chi
Mi
nh Ci
ty Unive
rsity of Ec
onomi
c
s a
nd F
inanc
e
(U
EF
)
Ho Chi
Mi
nh Ci
ty, Vietn
a
m
Email:
thanglq@ue
f.e
du.
vn
1.
INTRODUC
TI
ON
Ac
a
de
mi
c
a
c
hiev
e
ment
is
a
ke
y
indi
c
a
tor
of
high
e
r
e
duc
a
ti
on
e
ff
e
c
ti
ve
ne
s
s
[1]
,
incr
e
a
si
ngly
li
nke
d
to
mea
sura
ble
outcome
s
a
li
gne
d
with
sust
a
inable
de
ve
lopm
e
nt
goa
l
4
a
nd
human
c
a
pit
a
l
de
v
e
lopm
e
nt
[2]
.
At
the
sam
e
ti
me,
digi
t
a
l
tra
nsfo
rma
ti
on
ha
s
e
xpa
nde
d
the
use
of
a
rti
fic
ial
int
e
ll
igenc
e
(A
I)
t
ools
li
ke
ChatGP
T
in
a
c
a
de
mi
c
ta
sks
[3]
.
W
hil
e
g
e
ne
r
a
ti
ve
A
I
e
nha
nc
e
s
lea
rning
e
ff
icie
n
c
y,
it
a
ls
o
r
a
is
e
s
c
onc
e
rns
a
bout
ove
rr
e
li
a
nc
e
a
nd
it
s
im
pa
c
t
on
st
ude
nt
s’
self
-
r
e
gulation,
e
nga
ge
ment,
a
nd
lea
rning
be
ha
viors.
Unde
rsta
nding
these
e
ff
e
c
ts
is
e
ssential
for
uni
ve
rsiti
e
s
a
im
ing
to
ba
lanc
e
tec
hnologi
c
a
l
innovation
with
sust
a
inable
lea
rning outc
omes.
Ac
a
de
mi
c
pro
c
ra
st
inatio
n
is
c
onsi
st
e
ntl
y
li
nke
d
t
o
lowe
r
a
c
a
d
e
mi
c
pe
rf
o
r
manc
e
[4]
.
K
e
y
pre
dictor
s
include
self
-
r
e
gulate
d
lea
rning,
digi
tal
c
ompete
nc
e
,
a
nd
digi
tal
li
ter
a
c
y
[5]
,
[6]
,
while
c
ontextua
l
fac
tors
suc
h
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8822
I
nt
J Eva
l &
Res Edu
c
,
V
ol.
15
, No.
4
,
August
20
26
:
3
30
1
-
3309
3302
a
s school
a
tt
a
c
hment
a
nd
fa
mi
ly sup
port
a
ls
o he
lp
re
duc
e
pro
c
ra
st
ination
[7
]
. S
e
lf
-
r
e
gulate
d
lea
rning suppor
ts
planning
a
nd
moni
toring,
digi
tal
c
ompete
nc
e
fa
c
i
li
tate
s
e
ff
icie
nt
te
c
hnology
use
,
a
nd
digi
tal
li
ter
a
c
y
e
na
ble
s
c
riti
c
a
l
e
ng
a
ge
ment,
whi
le
c
ontextua
l
support
st
a
bil
ize
s
mot
ivation
a
nd
e
nga
ge
ment.
How
e
ve
r,
these
f
a
c
tors
a
re
oft
e
n st
udied se
pa
r
a
te
ly, wit
h li
mi
ted integr
a
te
d models.
Rec
e
nt
st
udies
sugge
st
that
A
I
ov
e
rr
e
li
a
nc
e
may
we
a
k
e
n
meta
c
ogni
ti
ve
c
ontrol
a
nd
in
c
rea
se
a
voidanc
e
[8]
,
[9]
,
y
e
t
it
is
ra
re
ly
in
c
luded
in
pro
c
ra
st
ination
fr
a
m
e
wor
ks.
Exist
ing
re
sea
r
c
h
tends
t
o
e
xa
mi
ne
tec
hnology
use
or
self
-
r
e
gulation
in
is
olation,
li
mi
ti
ng
unde
rsta
nding
of
how
AI
-
re
late
d
b
e
ha
vio
rs
int
e
ra
c
t
with
psyc
hologi
c
a
l
a
nd
c
ontextua
l
fa
c
tors.
As
A
I
be
c
omes
mor
e
p
re
va
lent
in
higher
e
duc
a
ti
on,
thi
s
ga
p
c
onst
ra
ins
insi
ght i
nto i
ts
risks and
unint
e
nde
d e
f
f
e
c
ts
on st
ude
nt per
fo
rma
nc
e
.
This
st
udy
de
ve
lops
a
nd
tests
a
n
int
e
gra
ted
model
in
whic
h
self
-
reg
ulate
d
lea
rning,
digi
ta
l
c
ompete
nc
e
,
digi
tal
li
ter
a
c
y,
fa
mi
ly
support,
schoo
l
a
tt
a
c
hment,
a
nd
A
I
ove
rr
e
li
a
nc
e
pr
e
dict
a
c
a
de
mi
c
proc
ra
st
ination,
whi
c
h
in
turn
a
f
fects
a
c
a
de
mi
c
a
c
hieve
ment.
Using
pa
rtia
l
lea
st
squa
r
e
s
st
ruc
tur
a
l
e
qua
ti
on
modeling
(PLS
-
S
EM)
,
i
t
e
xa
mi
ne
s
the
re
lations
hips
a
mong
tec
hnologi
c
a
l,
indi
vidual,
a
nd
c
ontextu
a
l
fa
c
tors
withi
n
a
si
ngle
fr
a
mew
o
rk.
The
st
udy
c
ontribut
e
s
by
incor
por
a
ti
ng
A
I
o
ve
rr
e
li
a
n
c
e
int
o
the
proc
ra
st
ination
fr
a
mew
o
rk
a
nd
posi
ti
oni
ng
proc
ra
st
ination
a
s
the
ke
y
mec
ha
nis
m
li
nking
mul
ti
ple
pre
dictor
s
to
a
c
hieve
ment.
Com
pa
re
d
to
prio
r
r
e
sea
rc
h
that
e
xa
mi
ne
s
these
fa
c
tors
s
e
pa
r
a
tely,
thi
s
m
ode
l
off
e
rs
a
more
c
omp
re
he
nsi
v
e
view
of
st
ude
nt
be
ha
vior
in
A
I
-
int
e
gr
a
ted
c
ont
e
xts
.
The
findings
p
rovide
pr
a
c
ti
c
a
l
im
pli
c
a
ti
ons
fo
r
p
romoti
ng
re
sponsi
ble A
I
use
a
nd st
re
ngthening st
ude
nts
’ se
l
f
-
re
gulation and
e
nga
g
e
ment.
2.
LI
TE
RA
TURE RE
VIE
W
2.1.
Fou
n
d
ation
t
h
e
or
y
This
st
udy
is
groun
de
d
i
n
self
-
re
gulation
f
a
il
ure
theor
y
,
whic
h
view
s
a
c
a
de
mi
c
proc
r
a
st
ination
a
s
a
bre
a
kdown
in
planning
a
nd
be
h
a
viora
l
c
ontrol
ra
the
r
than
a
la
c
k
of
a
b
il
it
y
[6]
.
I
n
A
I
-
int
e
gr
a
te
d
lea
rning
c
ontexts,
ove
rr
e
li
a
n
c
e
o
n
AI
c
a
n
be
view
e
d
a
s
a
for
m
of
self
-
re
gula
tory
fa
il
ure
that
re
duc
e
s
a
c
ti
ve
e
nga
ge
ment
a
nd
incr
e
a
s
e
s
a
c
a
de
mi
c
p
roc
r
a
st
ination.
S
oc
ial
c
ognit
ive
the
ory
a
nd
r
a
ti
ona
l
e
mot
ive
be
ha
vior
theor
y
fur
th
e
r
e
xplain
h
ow
c
ontextua
l
suppo
rt
a
nd
be
li
e
fs
a
bout
e
f
for
t
s
ha
pe
pro
c
ra
st
ination
b
e
h
a
vior
[10]
.
The
se
pe
rspe
c
ti
ve
s
guide
the
propo
sed
model
by
posi
ti
oning
self
-
re
gulate
d
lea
rning,
c
ontextua
l
f
a
c
tors
suc
h
a
s
schoo
l
a
tt
a
c
hment
a
nd
fa
mi
ly
support,
a
nd
A
I
ove
rr
e
li
a
nc
e
a
s
pr
e
dictor
s
of
a
c
a
d
e
mi
c
proc
r
a
st
ination,
whic
h in t
urn inf
luenc
e
s
a
c
a
d
e
mi
c
a
c
hiev
e
ment.
2.2.
Hyp
othesis
d
e
ve
lop
m
e
n
t
Ac
a
de
m
ic
pr
oc
ra
st
i
na
t
i
on
i
s
t
he
i
nt
e
n
t
io
na
l
de
lay
of
a
c
a
de
m
ic
ta
sk
s
de
sp
i
te
k
no
wi
ng
i
t
ma
y
ha
rm
p
e
rf
orm
a
nc
e
[
11]
.
I
t
fr
a
gm
e
n
t
s
lea
rn
in
g,
d
e
la
y
s
e
ff
or
t
un
t
i
l
de
a
d
l
in
e
s
,
a
nd
c
om
pre
sse
s
s
t
ud
y
t
im
e
,
in
c
re
a
si
ng
c
og
ni
t
ive
l
oa
d
a
nd
l
i
mi
t
in
g
de
e
pe
r
pr
oc
e
s
s
in
g.
S
in
c
e
a
c
a
de
m
ic
a
c
hi
e
ve
men
t
de
pe
n
ds
o
n
su
s
tai
ne
d
e
f
for
t
[1
2]
,
p
roc
ra
s
t
ina
t
io
n
oft
e
n
lea
d
s
t
o
low
e
r
-
q
ua
l
it
y
w
or
k
a
nd
h
ig
he
r
s
tre
ss
,
un
de
rm
i
n
in
g
o
u
tco
me
s.
A
lt
hou
g
h
s
o
me
s
t
ude
n
ts
may
be
ne
fi
t
fr
om
pre
s
sure
in
spe
c
if
ic
c
a
se
s
[1
3]
,
suc
h
e
ff
e
c
t
s
a
re
te
mp
ora
r
y.
Re
pe
a
ted
p
roc
ra
s
ti
na
ti
on
re
i
nfor
c
e
s
a
vo
i
da
nc
e
a
n
d
st
re
s
s,
we
a
ke
n
in
g
p
e
rf
or
ma
nc
e
o
ve
r
t
im
e
[1
4]
.
F
r
om
a
ra
ti
on
a
l
e
m
ot
i
ve
be
ha
v
ior
t
he
or
y
p
e
rs
pe
c
t
ive
,
i
t
re
fl
e
c
ts
a
v
o
ida
nc
e
-
dri
ve
n
be
l
ief
s
(e
.g
.,
fe
a
r
of
fa
i
lure
)
.
I
n
AI
-
su
pp
or
ted
e
n
vir
on
me
nt
s,
h
e
a
v
y
re
l
ia
nc
e
o
n
AI
may
f
ur
the
r
e
nc
oura
ge
ta
s
k
d
e
la
y
b
y
re
d
uc
i
ng
the
pe
rc
e
i
ve
d
c
os
t
of
p
o
st
po
nin
g
e
ff
or
t.
H1
:
a
c
a
de
mi
c
proc
ra
s
t
inat
i
on
n
e
ga
t
ive
ly
a
ff
e
c
t
s
a
c
a
de
m
ic
a
c
hie
ve
men
t
.
S
e
lf
-
re
gulate
d
le
a
rning
r
e
fe
rs
to
how
st
ude
nts
plan,
mana
ge
,
a
nd
a
djust
their
lea
rning
[15]
a
nd
is
st
rongly
a
ssocia
ted
with
lowe
r
a
c
a
de
mi
c
proc
ra
st
ination.
P
roc
ra
st
ination
re
fle
c
ts
a
fa
il
ur
e
of
self
-
r
e
gulator
y
c
ontrol
ra
the
r
than
si
mpl
e
poor
ti
me
mana
ge
ment
[10]
,
e
v
e
n
whe
n
st
ude
nts
re
c
ogniz
e
it
s
ne
ga
ti
v
e
c
onse
que
nc
e
s.
S
tra
tegie
s
suc
h
a
s
m
e
tac
ognit
ive
moni
toring,
ti
me
mana
ge
ment,
a
nd
e
ff
o
rt
re
gula
ti
on
he
lp
re
duc
e
proc
ra
st
ination.
S
tudents
who
plan,
tra
c
k
progr
e
ss,
a
nd
pe
rsist
a
re
l
e
ss
li
ke
ly
to
de
lay
tasks
[16]
,
whe
reas
we
a
k
sel
f
-
r
e
gulation
lea
ds
to
prior
it
izi
ng
short
-
ter
m
c
omfor
t.
Evide
nc
e
c
onsi
st
e
ntl
y
shows
that
st
ronge
r
self
-
r
e
gulation
re
duc
e
s
proc
ra
st
ination
a
nd
im
prove
s
outcome
s
[15]
.
Base
d
on
thi
s
re
a
soni
ng,
thi
s
st
udy
propo
sed
the
following
hypothesis
(
H2
)
:
s
e
lf
-
r
e
gulate
d
le
a
rning
is
ne
ga
ti
ve
ly
re
l
a
ted
to
a
c
a
d
e
mi
c
proc
ra
st
ination.
I
n
digi
tal
a
nd
AI
-
supp
orte
d
lea
rning
e
nviron
ments,
digi
tal
c
ompete
nc
e
influe
nc
e
s
a
c
a
de
mi
c
proc
ra
st
ination
prima
rily
through
st
ude
nts
’
a
bil
it
y
to
ini
ti
a
te
a
nd
mana
ge
a
c
a
de
mi
c
tasks
e
ff
i
c
iently.
S
tudents
with
st
ronge
r
digi
tal
c
o
mpete
nc
e
e
xpe
ri
e
nc
e
fewe
r
te
c
hnica
l
b
a
rr
ie
rs
a
n
d
lowe
r
te
c
hnology
-
re
l
a
ted
a
nxiety
,
whic
h
re
du
c
e
s
a
voidanc
e
a
nd
task
de
lay
[6]
.
W
he
n
digi
tal
c
ompete
n
c
e
i
s
li
mi
ted,
a
c
a
de
mi
c
task
s
may
feel
more
de
manding
than
they
a
c
tually
a
r
e
,
incr
e
a
si
ng
unc
e
rta
int
y
a
nd
the
li
ke
li
hood
of
post
pone
ment
[17]
.
This
mec
ha
nis
m
be
c
omes
more
salien
t
in
lea
rning
c
ontexts
whe
re
a
c
a
d
e
mi
c
a
c
ti
vit
ies
a
re
c
los
e
ly
ti
e
d
to
digi
tal
platfo
rms.
Ac
c
ordingly,
digi
tal
c
ompete
nc
e
is
e
xpe
c
ted
to
re
du
c
e
a
c
a
de
mi
c
proc
ra
st
ination.
H3
:
d
igi
tal
c
ompete
nc
e
is
n
e
ga
ti
ve
ly
re
late
d to a
c
a
de
mi
c
p
roc
ra
st
ination.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J Eva
l &
Res Edu
c
I
S
S
N:
2252
-
8822
Ac
ade
mic
pro
c
rast
inat
ion and achie
v
e
me
nt amon
g unive
rsi
ty students unde
r AI … (
T
ang M
y
Sang
)
3303
Digit
a
l
li
ter
a
c
y
a
f
fects
a
c
a
de
mi
c
p
roc
r
a
st
ination
through
st
ude
nts
’
c
a
p
a
c
i
ty
to
c
riti
c
a
ll
y
e
va
luate
infor
mation
a
nd
r
e
gulate
a
tt
e
nti
on
in
digi
tal
e
nvironmen
ts
.
Unlike
ope
r
a
ti
ona
l
digi
tal
ski
ll
s,
digi
ta
l
li
ter
a
c
y
he
lps
st
ude
nts
re
si
st
digi
tal
dis
tra
c
ti
ons
a
nd
a
void
pa
ssi
ve
r
e
li
a
nc
e
on
a
uto
mate
d
support,
whi
c
h
m
a
y
re
du
c
e
a
c
a
d
e
mi
c
proc
r
a
st
ination
[18]
.
S
tudents
with
l
im
i
ted
digi
tal
li
ter
a
c
y
a
re
more
li
ke
ly
to
e
nga
ge
with
digi
tal
c
ontent
unc
riti
c
a
ll
y,
re
inf
orc
ing
a
voidan
c
e
-
o
rie
nte
d
lea
rning
b
e
ha
viors
[19]
.
I
n
tec
hnology
-
media
ted
lea
rning
c
ontexts,
thi
s
re
gulator
y
func
ti
on
be
c
omes
incr
e
a
si
ngly
im
porta
nt
a
s
st
ude
nts
fa
c
e
c
onst
a
nt
e
x
posure
to
AI
-
ge
n
e
ra
ted
output
s.
T
he
re
fo
re
,
higher
digi
tal
li
ter
a
c
y
is
e
xpe
c
t
e
d
to
re
duc
e
a
c
a
d
e
mi
c
proc
ras
ti
na
ti
on.
H4
:
d
igi
tal li
ter
a
c
y is n
e
ga
ti
ve
ly re
late
d to a
c
a
de
m
ic pr
oc
r
a
st
ination.
F
or
univer
si
ty
st
ude
nts
,
fa
mi
ly
support
func
ti
ons
mainly
a
s
a
ba
c
kg
ro
und
re
sourc
e
that
sha
pe
s
mot
ivation
a
nd
c
oping
tende
nc
ies
ra
ther
than
di
re
c
tl
y
re
gul
a
ti
ng
da
il
y
a
c
a
de
mi
c
b
e
ha
vior.
Emot
ional
a
nd
ins
trume
ntal
support
fr
om
fa
mi
ly
c
a
n
st
a
bil
ize
st
ude
nts
’
lea
rning
c
o
ndit
ions
a
nd
re
duc
e
st
r
e
ss,
whic
h
indi
re
c
tl
y
lowe
rs
a
voidan
c
e
a
nd
proc
r
a
st
ination
[20]
.
How
e
ve
r,
in
highl
y
a
utonom
ous
lea
rning
e
nvi
ronme
nts
,
the
influe
nc
e
of
fa
mi
ly
support
is
li
ke
ly
to
b
e
we
a
k
e
r
than
that
of
ins
ti
tut
ional
or
indi
v
idu
a
l
fa
c
tors
.
As
a
re
sul
t,
fa
mi
ly
suppo
rt
is
e
xpe
c
ted
to
be
ne
ga
ti
ve
ly
a
ssocia
ted
with
a
c
a
de
mi
c
proc
ra
st
ination,
a
lbeit
with
a
modest ef
f
e
c
t.
H5
: f
a
mi
ly sup
port is nega
ti
ve
ly re
late
d to ac
a
de
mi
c
pro
c
r
a
st
ination.
S
c
hool
a
tt
a
c
hment
re
fers
to
st
ude
nts
’
sense
of
c
onne
c
ti
on
to
their
schoo
l
a
nd
lea
rning
e
nvironmen
t
[21]
,
whic
h
influe
nc
e
s
h
ow
they
h
a
ndle
a
c
a
d
e
mi
c
de
mands.
S
trong
a
tt
a
c
hment
promotes
e
ng
a
ge
ment
a
nd
pe
rsist
e
nc
e
,
while
low
a
tt
a
c
hment
is
a
ssoci
a
ted
with
is
olation,
re
duc
e
d
mot
ivation,
a
n
d
gre
a
te
r
proc
ra
st
ination.
A
st
rong
sense
of
be
longi
ng
supp
orts
e
mot
ional
st
a
bil
it
y
a
nd
foc
us
on
long
-
ter
m
g
oa
ls
[22]
.
This
fa
c
tor
is
e
spe
c
i
a
ll
y
im
porta
nt
in
tec
hnology
-
r
ich
a
nd
A
I
-
support
e
d
e
nv
ironments
[23]
.
S
tudents
who
fe
e
l
c
onne
c
ted
a
r
e
more
li
ke
l
y
to
use
digi
tal
tool
s
purpo
sef
ull
y
ra
the
r
than
fo
r
a
voidanc
e
.
Evide
n
c
e
s
hows
that
st
ronge
r
schoo
l
a
tt
a
c
hme
nt
is
li
nke
d
to
gre
a
t
e
r
a
c
a
de
mi
c
r
e
sponsi
bil
it
y,
lo
we
r
pro
c
r
a
st
ination
[7]
,
a
nd
be
tt
e
r
psyc
hologi
c
a
l
a
djust
ment
a
nd
lea
rning
pe
rsist
e
n
c
e
[24]
.
H6
:
s
c
hool
a
tt
a
c
hment
is
ne
ga
ti
ve
ly
r
e
late
d
to
a
c
a
d
e
mi
c
proc
r
a
st
ination.
A
I
ove
rr
e
li
a
n
c
e
re
f
e
rs
to
e
xc
e
ssi
ve
de
p
e
nde
n
c
e
o
n
A
I
tool
s
for
c
ompl
e
ti
ng
a
c
a
de
mi
c
t
a
sks,
whic
h
may
we
a
k
e
n
self
-
re
gulat
ion
a
nd
proa
c
ti
ve
e
nga
g
e
ment.
W
he
n
st
ude
nts
rel
y
on
A
I
for
im
media
te
sol
uti
ons,
they
a
r
e
mor
e
li
ke
ly
to
p
ost
pone
mea
ningful
t
a
sk
e
nga
ge
ment,
a
ssum
ing
th
a
t
A
I
support
c
a
n
c
ompe
nsa
te
fo
r
de
laye
d
e
f
for
t
[25]
.
Thi
s
re
li
a
nc
e
r
e
duc
e
s
met
a
c
ognit
ive
moni
toring
a
nd
e
nc
oura
g
e
s
a
voidanc
e
-
orie
nted
lea
rning
st
ra
tegie
s
[26]
.
I
n
A
I
-
supporte
d
lea
rning
e
nvironmen
ts
,
suc
h
de
pe
nde
nc
e
may
legiti
mi
z
e
t
a
sk
de
lay
ra
ther
than
re
duc
e
it
.
The
re
fo
re
,
higher
leve
ls
of
A
I
ov
e
rr
e
li
a
nc
e
a
r
e
e
xp
e
c
ted
to
incr
e
a
se
a
c
a
de
mi
c
proc
ra
st
ination.
H7
:
A
I
ove
rr
e
li
a
n
c
e
is
posi
ti
ve
ly
re
late
d
to
a
c
a
de
mi
c
proc
ra
st
ination.
Bui
ldi
ng
on
thi
s
pe
rspe
c
ti
ve
,
the
p
ropose
d
model
int
e
gra
t
e
s
indi
v
idual,
c
ontextua
l,
a
nd
te
c
hnologi
c
a
l
f
a
c
tors,
with
a
c
a
de
mi
c
proc
ra
st
ination as the
c
e
n
tra
l m
e
c
ha
nis
m l
inki
ng them to ac
a
de
mi
c
a
c
hiev
e
ment
,
a
s shown in F
igure
1.
F
igure
1. P
ropose
d
re
se
a
r
c
h model
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
-
8822
I
nt
J Eva
l &
Res Edu
c
,
V
ol.
15
, No.
4
,
August
20
26
:
3
30
1
-
3309
3304
3.
M
ET
HO
D
T
h
is
s
tu
dy
e
m
pl
oye
d
a
qu
a
n
t
it
a
t
ive
,
c
r
os
s
-
sec
ti
ona
l
sur
ve
y
of
s
tu
de
n
t
s
fr
om
p
ri
va
te
u
n
iver
s
it
ie
s
w
ho
re
gu
lar
l
y
u
se
d
i
gi
ta
l
tec
hn
o
lo
gi
e
s
a
nd
AI
to
ol
s
in
t
he
ir
a
c
a
de
m
ic
w
ork
.
T
h
is
gr
ou
p
wa
s
sele
c
te
d
due
to
t
he
i
r
h
i
ghe
r
lea
r
ni
ng
a
u
t
on
omy
,
gre
a
ter
e
xp
os
ure
t
o
di
gi
t
a
l
p
la
tfo
rm
s,
a
nd
m
ore
fl
e
x
i
ble
in
st
ruc
t
io
na
l
e
nv
iro
n
men
t
s,
m
a
k
i
ng
t
he
m
s
u
it
a
b
le
fo
r
e
xa
m
i
ni
ng
se
lf
-
re
g
u
lat
i
on
,
tec
hn
ol
og
y
use
,
a
nd
p
roc
ra
s
ti
na
t
io
n
in
AI
-
s
u
pp
or
ted
l
e
a
r
ni
ng
.
Al
l
pa
r
t
ic
ipa
nt
s
pr
ov
ide
d
i
nfor
me
d
c
on
se
nt
a
f
ter
be
in
g
in
for
me
d
of
t
he
s
tu
dy’
s
pu
rp
ose
,
v
o
lu
nt
a
ry
n
a
t
ure
,
a
n
d
t
he
ir
r
ig
ht
to
wi
t
hdra
w
a
t
a
ny
t
im
e
.
Da
t
a
we
re
c
ol
lec
te
d
vi
a
a
n
on
l
ine
que
st
i
on
na
ire
.
Af
ter
re
m
ov
in
g
inc
o
mp
le
te
or
i
n
va
li
d
re
s
po
nse
s,
3
01
va
l
id
c
a
se
s
we
re
re
t
a
i
ne
d
.
Th
i
s
sam
p
le
si
z
e
is
a
de
q
ua
te
for
P
L
S
-
S
EM
,
e
na
b
l
in
g
a
na
ly
s
is
o
f mu
l
ti
p
le la
ten
t var
i
a
b
le
s
a
nd
m
e
d
ia
ti
on
e
ff
e
c
ts
. P
a
rt
ic
ipa
n
ts
c
a
me
f
rom
va
r
io
us
a
c
a
de
mi
c
di
sc
ip
l
ine
s,
c
a
pt
ur
i
ng
d
ive
rs
i
ty
i
n
lea
rn
ing
de
ma
nd
s
a
n
d
tec
hn
ol
ogy
use
.
All
c
onst
ruc
ts
we
re
m
e
a
s
ure
d
usi
ng
e
st
a
bli
she
d
sc
a
les
a
d
a
pted
f
rom
prior
s
tudi
e
s
a
nd
a
djust
e
d
to
the
re
sea
rc
h
c
ontext.
S
e
lf
-
r
e
gulate
d
lea
rning
wa
s
mea
sure
d
usi
ng
it
e
ms
re
fle
c
ti
ng
how
st
ude
nts
ma
na
ge
their
lea
rning
a
c
ti
vit
ies,
suc
h
a
s
“
setti
ng
c
lea
r
a
c
a
de
m
ic
lea
rning
goa
ls
”
[15]
.
Digit
a
l
c
ompete
nc
e
w
a
s
a
ssesse
d
through
st
ude
nts
’
a
bil
it
y
to
use
dig
it
a
l
too
ls
e
ff
e
c
ti
ve
ly
for
a
c
a
de
mi
c
tas
ks,
for
e
xa
mpl
e
,
“
usi
ng
a
dva
nc
e
d
sea
rc
h
func
ti
ons
to
loca
te
a
c
a
d
e
mi
c
infor
mation”
[
27]
.
Digit
a
l
li
ter
a
c
y
fo
c
u
sed
on
c
riti
c
a
l
a
nd
re
spo
nsi
ble
use
of
digi
tal
tec
hnologi
e
s,
including
“
a
wa
re
ne
ss
o
f
e
thi
c
a
l
be
h
a
vior
in
onli
ne
a
c
a
de
mi
c
e
nvironme
nts
”
[18]
.
F
a
mi
ly
support
wa
s
mea
sure
d
through
p
e
rceived
e
nc
oura
g
e
ment
a
nd
a
ssi
s
tanc
e
f
rom
f
a
mi
ly
membe
rs,
suc
h
a
s
“
e
nc
our
a
ge
ment
to
be
gin
a
nd
sust
a
in
a
c
a
d
e
mi
c
wor
k”
[28]
.
S
c
ho
ol
a
tt
a
c
hment
c
a
pture
d
st
ude
nts
’
e
mot
ional c
onne
c
ti
on to t
he
inst
it
uti
on, fo
r instanc
e
,
“
feeli
ng pr
oud to be a
st
ude
nt at the unive
rsity”
[21]
.
A
I
ove
rr
e
li
a
nc
e
w
a
s
a
s
sesse
d
usi
ng
indi
c
a
tors
of
e
xc
e
ssi
ve
de
p
e
nde
n
c
e
on
A
I
tool
s,
suc
h
a
s
“
re
duc
e
d
indep
e
nde
nt
m
a
na
ge
ment
o
f
a
c
a
de
mi
c
tasks
due
to
A
I
us
e
”
[2
5]
.
Although
the
A
I
ov
e
rr
e
li
a
nc
e
c
onst
ruc
t
wa
s
a
da
pt
e
d
f
rom
a
ge
n
e
ra
l
tec
hnolo
gy
de
pe
nde
n
c
e
s
c
a
le,
the
it
e
ms
we
r
e
r
e
vis
e
d
to
re
fle
c
t
e
xc
e
ssi
ve
re
li
a
n
c
e
on
A
I
tool
s
for
a
c
a
de
mi
c
tasks
ra
ther
than
soc
ial
media
use
.
Ac
a
de
mi
c
proc
ra
st
in
a
ti
on
wa
s
mea
sure
d
through
be
ha
viors
re
late
d
to
a
c
a
de
mi
c
proc
ra
st
ination,
suc
h
a
s
“
post
poning
the
st
a
rt
of
major
a
ssi
gnments
unti
l
jus
t
b
e
for
e
th
e
de
a
dli
ne
”
[11]
.
Ac
a
de
mi
c
a
c
hiev
e
ment
wa
s
a
ssesse
d
usi
ng
s
e
lf
-
re
porte
d
indi
c
a
tors
of
lea
rning
outcome
s,
including
“
pe
rc
e
ived
im
prove
ment
in
a
c
a
de
mi
c
ski
ll
s
through
c
ou
rse
wor
k
”
[29]
. All i
tems we
re
ra
te
d on a
se
ve
n
-
point
Liker
t
sc
a
le r
a
nging fr
om st
ron
gly di
sagr
e
e
to st
rongly a
gre
e
.
Da
ta
w
e
re
a
na
lyz
e
d
usi
ng
P
LS
-
S
EM,
whic
h
is
sui
table
for
e
xplaining
a
nd
pre
di
c
ti
ng
a
c
a
de
mi
c
proc
ra
st
ination
in
c
omp
lex
models
with
mul
ti
ple
a
nte
c
e
de
nts
a
nd
m
e
diation,
without
re
quir
ing
st
ric
t
norma
li
ty
a
ssum
pti
ons.
The
a
na
lys
is
invol
ve
d
t
wo
st
e
ps:
e
va
luating
the
mea
sure
ment
model
(r
e
li
a
bil
it
y
a
nd
va
li
dit
y)
a
nd
testi
ng
the
st
ruc
tura
l
model
(hypo
thesiz
e
d
r
e
lations
hips
a
nd
media
ti
on).
Boot
st
rap
ping
wa
s
a
ppli
e
d
to
a
ssess
pa
th
si
gnific
a
nc
e
.
As
da
ta
w
e
re
self
-
re
po
rte
d
a
nd
c
oll
e
c
t
e
d
a
t
a
si
ngle
ti
me
point
,
c
omm
on
method bias w
a
s a
ls
o e
xa
mi
ne
d.
4.
RES
ULT
S
AN
D D
IS
C
USS
IO
N
The
st
udy
sample
c
omprised
301
univer
si
ty
st
ude
nts
.
F
e
male
pa
rticipa
nts
c
onst
it
uted
a
sl
ight
l
y
lar
ge
r
propo
rtion
of
the
sample
(58%
),
whe
r
e
a
s
male
pa
rticipa
nts
a
c
c
oun
ted
for
42%.
I
n
te
rms
of
a
c
a
de
mi
c
st
a
nding,
the
major
it
y
of
re
sponde
nts
w
e
r
e
in
their
sec
ond
a
nd
thi
rd
ye
a
rs
of
st
udy,
re
p
re
sentin
g
a
pprox
im
a
tely
two
-
thi
rd
s
of
the
tot
a
l
sample.
F
irst
-
ye
a
r
st
ude
nts
c
o
mprised
a
bout
one
-
fif
t
h
of
the
pa
rticipa
nts
,
with
the
rem
a
inder
be
ing
fina
l
-
y
e
a
r
st
ude
nts
.
P
a
rticipa
nts
we
re
dr
a
wn
f
rom
diver
se
a
c
a
d
e
mi
c
dis
c
ipl
ines.
S
tudents
maj
oring
in
soc
ial
scie
nc
e
s
a
nd
busi
ne
ss
-
re
late
d
fie
lds
re
pre
s
e
nted
the
lar
ge
st
s
ubgro
up,
followe
d
by
those
in
e
n
ginee
ring
a
nd
tec
hnolog
y,
a
nd
subseque
ntl
y
those
in
e
duc
a
ti
on
a
nd
the
h
umaniti
e
s.
Rega
rding
tec
hnology
e
n
ga
ge
ment,
most
re
sponde
nts
re
porte
d
re
gul
a
r
use
o
f
digi
tal
tool
s
a
nd
AI
a
pp
li
c
a
ti
ons
to
support
their
a
c
a
d
e
mi
c
tasks.
This
high
leve
l
of
tec
hnologi
c
a
l
e
ng
a
ge
ment
sugge
st
s
that
the
sample
wa
s
we
ll
posi
ti
one
d for
e
xa
m
ini
ng lea
rning be
ha
viors
withi
n AI
-
suppo
rte
d e
du
c
a
ti
ona
l conte
xts
.
As
re
po
rte
d
in
T
a
ble
1,
the
me
a
sure
ment
re
sul
t
s
indi
c
a
te
that
a
ll
c
onst
r
uc
ts
we
r
e
me
a
sure
d
wit
h
a
c
c
e
ptable
qu
a
li
ty.
All
o
uter
loadings
e
xc
e
e
d
0.7
0,
indi
c
a
ti
ng
a
d
e
qua
te
indi
c
a
tor
r
e
li
a
bil
it
y.
Cronba
c
h’s
a
lph
a
a
nd
Rho
_A
v
a
lues
a
re
a
bove
r
e
c
omm
e
nde
d
thre
shol
ds,
c
onfir
mi
ng
int
e
r
na
l
c
onsi
st
e
nc
y.
A
ve
ra
g
e
va
ria
nc
e
e
xtra
c
ted
(
AVE
)
v
a
lues
surpa
ss
0.50,
supporting
c
onve
rge
nt
va
li
dit
y,
wh
il
e
va
ria
nc
e
infl
a
ti
on
fa
c
tor
(
V
I
F
)
va
lues
be
low
3.0
indi
c
a
te
no
c
oll
inea
rity
is
sue
s.
Additi
ona
ll
y,
the
he
ter
otra
it
-
monot
ra
it
(H
TMT)
r
a
ti
os
a
re
be
low
0.85,
c
onfir
mi
ng
dis
c
rimi
na
nt
va
li
dit
y.
The
se
r
e
sul
ts
va
li
da
te
th
e
mea
sur
e
ment
model
a
n
d
support
proc
e
e
ding
to
st
ru
c
tura
l
a
na
lys
is
.
Ac
a
de
mi
c
pr
oc
ra
st
ination
si
gnific
a
ntl
y
pre
dicts
a
c
a
de
mi
c
a
c
hieve
ment
(H
1:
β=0.551,
p<
0
.001
),
indi
c
a
ti
ng
a
si
gnific
a
nt
posi
ti
ve
re
lations
hip
be
twe
e
n
a
c
a
d
e
mi
c
proc
ra
st
i
na
ti
on
a
nd
a
c
a
d
e
mi
c
a
c
hieve
m
e
nt
,
c
onsi
st
e
nt
with
prior
re
sea
rc
h
[14
],
[30]
.
S
e
lf
-
r
e
gulate
d
lea
rning
(H
2)
is
a
st
rong
ne
ga
ti
ve
pre
dicto
r
(β=
-
0
.800,
p<
0
.001)
,
indi
c
a
ti
ng
that
st
ude
nts
who
e
ff
e
c
ti
ve
ly
plan
a
nd
moni
tor
their
lea
rning a
r
e
less li
ke
ly t
o pro
c
ra
st
inate
[16]
, a
s
sh
own
in
Ta
ble 2.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J Eva
l &
Res Edu
c
I
S
S
N:
2252
-
8822
Ac
ade
mic
pro
c
rast
inat
ion and achie
v
e
me
nt amon
g unive
rsi
ty students unde
r AI … (
T
ang M
y
Sang
)
3305
Ta
ble 1. Me
a
su
re
ment
m
ode
l re
sul
ts
I
te
m
O
ut
e
r
l
oa
di
ng
C
r
onba
c
h
’
s
a
lp
ha
R
ho_A
AVE
V
I
F
D
C
1
0.804
0.874
0.887
0.635
1.045
D
C
2
0.801
1.524
D
C
3
0.812
1.719
D
C
4
0.832
2.363
D
C
5
0.733
2.764
A
P
1
0.782
0.907
0.908
0.645
2.050
A
P
2
0.862
2.818
A
P
3
0.861
2.108
A
P
4
0.756
2.003
A
P
5
0.804
2.233
A
P
6
0.778
2.245
A
P
7
0.770
2.058
AO1
0.916
0.858
0.882
0.644
2.290
AO2
0.898
2.244
AO3
0.936
2.660
AO4
0.898
1.011
AO5
0.964
2.922
AO6
0.847
2.410
AO7
0.808
1.312
AO8
0.742
2.372
AO9
0.721
2.564
D
L1
0.794
0.759
0.804
0.669
1.512
D
L2
0.786
1.556
D
L3
0.872
1.524
S
L1
0.876
0.874
0.877
0.636
1.666
S
L2
0.817
2.939
S
L3
0.844
2.187
S
L4
0.771
2.450
S
L5
0.786
2.325
S
L6
0.826
2.391
S
L7
0.861
1.723
S
L8
0.885
2.392
S
L9
0.890
2.145
S
L10
0.895
2.833
S
L11
0.888
2.052
S
L12
0.892
2.360
S
L13
0.860
1.309
S
L14
0.878
1.243
S
L15
0.887
2.665
F
S
1
0.844
0.808
0.809
0.631
2.503
F
S
2
0.879
2.916
F
S
3
0.795
2.547
F
S
4
0.908
2.713
F
S
5
0.845
2.076
S
A
1
0.876
0.802
0.803
0.650
2.168
S
A
2
0.878
1.871
S
A
3
0.887
2.368
S
A
4
0.845
2.142
S
A
5
0.845
2.901
AA1
0.734
0.736
0.761
0.651
1.413
AA2
0.855
1.591
AA3
0.826
1.427
Ta
ble 2. St
ruc
tura
l
model
re
sul
ts
H
ypot
he
si
s
R
e
la
ti
onshi
ps
O
r
ig
in
a
l
s
a
mpl
e
t
-
va
lu
e
p
-
va
lu
e
R
e
sul
ts
H1
A
c
a
d
e
mi
c
pr
o
c
r
a
st
in
a
ti
on → a
c
a
de
mi
c
a
c
hi
e
v
e
me
nt
0.551
12.920
0.000
C
onf
irm
H2
S
e
lf
-
r
e
gul
a
te
d
le
a
r
ni
ng → a
c
a
d
e
mi
c
pr
oc
r
a
st
in
a
ti
on
-
0.800
10.367
0.000
C
onf
irm
H3
D
ig
it
a
l
c
ompe
te
nc
e
s → a
c
a
d
e
mi
c
pr
oc
r
a
st
in
a
ti
on
-
0.441
8.442
0.000
C
onf
irm
H4
D
ig
it
a
l
li
te
r
a
c
y → a
c
a
d
e
mi
c
pr
oc
r
a
st
in
a
ti
on
-
0.047
2.105
0.035
C
onf
irm
H5
F
a
mi
ly
suppor
t
→ a
c
a
de
mi
c
p
r
oc
r
a
st
in
a
ti
on
-
0.085
2.138
0.033
C
onf
irm
H6
S
c
hool
a
tt
a
c
hme
nt
→ a
c
a
d
e
mi
c
pr
oc
r
a
st
in
a
ti
on
-
0.803
10.575
0.000
C
onf
irm
H7
A
I
ove
r
r
e
li
a
n
c
e
→
a
c
a
de
mi
c
p
r
oc
r
a
st
in
a
ti
on
0.430
8.251
0.000
C
onf
irm
S
im
il
a
rly,
digi
tal
c
ompete
nc
e
(H
3)
re
du
c
e
s
p
roc
r
a
st
ination
(β=
-
0.441,
p
<
0
.001)
,
li
ke
ly
by
lowe
ring
tec
hnica
l
ba
rr
ier
s
in
te
c
hnology
-
ba
sed
lea
rning
[17]
.
Digit
a
l
li
ter
a
c
y
(H
4)
shows
a
sm
a
ll
e
r
but
si
gnific
a
nt
ne
ga
ti
ve
e
ff
e
c
t
(β=
-
0.04
7,
p<
0
.05),
sugg
e
st
ing
that
c
riti
c
a
l
digi
tal
ski
ll
s
he
lp
st
ude
nts
mana
ge
infor
mation
a
nd
maintain
foc
us
[18]
.
F
a
mi
ly
support
(H
5)
sho
ws
a
sm
a
ll
but
si
gnific
a
n
t
ne
ga
ti
ve
e
f
fect
on
proc
r
a
st
ination
(β=
-
0.085,
p<
0
.05),
sug
ge
st
ing
that
supportive
home
e
nvironmen
ts
he
lp
re
duc
e
a
voidan
c
e
,
though
less
Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
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8822
I
nt
J Eva
l &
Res Edu
c
,
V
ol.
15
, No.
4
,
August
20
26
:
3
30
1
-
3309
3306
st
rongly
than
indi
vidual
a
nd
ins
ti
tut
ional
fa
c
tors
[
10]
.
S
c
hool
a
tt
a
c
hment
(
H6)
is
a
st
rong
n
e
ga
ti
ve
pre
dictor
(β=
-
0.803,
p
<
0
.001)
,
ind
ica
ti
ng
that
st
ude
nts
wh
o
fe
e
l
c
onne
c
ted
to
th
e
ir
univer
si
ty
a
r
e
mor
e
e
ng
a
ge
d
a
nd
less
li
ke
ly
to
proc
ra
st
i
na
te
[7]
.
I
n
c
ont
ra
st
,
A
I
ove
r
re
li
a
nc
e
(
H7)
i
nc
re
a
s
e
s
pro
c
ra
st
ination
(β=
0.430,
p<
0
.001)
,
a
s
he
a
vy
de
pe
nde
nc
e
on
A
I
may
e
nc
o
ura
ge
task
de
lay
a
nd
re
d
uc
e
e
nga
ge
m
e
nt
[9]
.
I
m
porta
ntl
y,
thi
s st
udy is
a
mong t
he
fi
rst to i
ntegr
a
te A
I
ove
rr
e
l
ianc
e
int
o a
c
a
de
mi
c
pro
c
ra
st
ination m
ode
ls
.
The
findings
indi
c
a
te
that
self
-
re
gulat
e
d
lea
rnin
g
a
nd
schoo
l
a
tt
a
c
hment
a
re
the
most
influe
nti
a
l
fa
c
tors
in
re
duc
ing
a
c
a
de
mi
c
proc
r
a
st
ination,
followe
d
by
digi
tal
c
ompete
nc
e
a
nd
A
I
ov
e
rr
e
li
a
n
c
e
.
Th
e
s
e
re
sul
ts
sugge
st
th
a
t
tec
hnologi
c
a
l
support
doe
s
not
re
plac
e
the
ne
e
d
for
self
-
re
gulation;
ra
t
he
r,
we
a
k
re
gulation
be
c
om
e
s
mor
e
proble
matic
in
A
I
-
int
e
gra
ted
le
a
rning
e
nviron
ments.
S
e
ve
ra
l
li
mi
tations
shoul
d
be
a
c
knowle
dg
e
d.
The
st
udy
re
li
e
s
on
self
-
re
porte
d
da
ta,
whic
h
may
int
rod
uc
e
re
sponse
bias.
I
n
a
d
dit
ion,
the
sample
c
onsi
st
s
of
st
ude
nts
fr
om
priva
te
univer
si
ti
e
s,
whic
h
may
li
mi
t
th
e
ge
ne
r
a
li
z
a
bil
it
y
of
the
findings.
The
c
ross
-
se
c
ti
ona
l
de
si
gn
a
ls
o
re
st
ric
ts
c
a
usa
l
int
e
rpr
e
tation.
F
utur
e
re
s
e
a
rc
h
shoul
d
e
mpl
oy
longi
tudi
na
l
de
si
gns
a
nd
broa
de
r
ins
ti
tut
ional
samples
to
fur
th
e
r
e
xa
mi
ne
how
A
I
-
r
e
lat
e
d
lea
rning
be
ha
vio
rs
de
ve
lop
ove
r
ti
me.
5.
TH
EO
RET
ICA
L CO
NTRIB
UTIO
NS
This
st
udy
c
ontribut
e
s
to
a
c
a
d
e
mi
c
proc
ra
st
ination
re
sea
rc
h
by
posi
ti
oning
proc
ra
st
ination
a
s
a
ke
y
proc
e
ss
li
nking
indi
vidual
a
bil
it
ies,
c
ontextua
l
f
a
c
tors,
a
nd
A
I
-
r
e
late
d
infl
ue
nc
e
s
to
a
c
a
d
e
mi
c
a
c
hi
e
ve
ment.
The
findings
show
th
a
t,
in
A
I
-
int
e
gr
a
ted
le
a
rning
e
nvironmen
ts
,
self
-
re
gul
a
ti
on
fa
il
ure
s
re
main
c
riti
c
a
l
r
a
the
r
than
be
c
omi
ng
less
r
e
le
va
nt.
The
st
rong
e
ff
e
c
t
of
schoo
l
a
tt
a
c
hm
e
nt
sugge
st
s
that
ins
ti
tut
ional
c
onne
c
ti
on
c
onti
nue
s
to
mot
ivate
st
ude
nts
e
ve
n
in
fl
e
xibl
e
,
tec
hnology
-
ri
c
h
setti
ng
s,
c
ha
ll
e
nging
a
ssum
pti
ons
a
bout
re
duc
e
d
c
ontextua
l
influe
nc
e
.
I
n
a
ddit
ion,
A
I
o
ve
rr
e
li
a
n
c
e
is
identifie
d
a
s
a
tec
hnologi
c
a
l
risk
that
may
e
nc
oura
g
e
de
lay
e
d
e
ff
o
r
t,
he
lpi
ng
e
xplain
why
A
I
-
supporte
d
le
a
rning
le
a
ds
to
diff
e
re
nt
outcom
e
s
a
c
ross
st
ude
nts
.
6.
M
AN
AGE
RIA
L I
M
PL
ICA
TI
ONS
The
re
sul
ts
sugge
st
that
e
ff
orts
to
re
duc
e
a
c
a
de
mi
c
proc
ra
st
ination
in
AI
-
supporte
d
lea
rning
e
nvironmen
ts
shoul
d
be
gin
with
st
re
ngthening
st
ude
nts
’
self
-
r
e
gulate
d
le
a
rning.
Tr
a
ini
ng
ini
ti
a
ti
ve
s
shoul
d
go
be
yond
ge
ne
ri
c
ti
me
-
mana
ge
ment
a
dvic
e
a
nd
foc
us
more
dire
c
tl
y
on
goa
l
setti
ng,
planning,
a
nd
e
ff
ort
re
gulation.
The
st
rong
e
ff
e
c
t
of
schoo
l
a
tt
a
c
h
ment
point
s
to
the
im
porta
nc
e
of
ins
ti
tut
ional
c
onne
c
ti
on.
Unive
rsiti
e
s
shoul
d
not
a
ssum
e
that
fle
xibl
e
o
r
tec
hnology
-
ric
h
lea
rni
ng
e
nvironmen
ts
na
tura
ll
y
sust
a
in
st
ude
nt
e
nga
ge
m
e
nt.
I
n
st
e
a
d,
foste
ring
re
gul
a
r
int
e
ra
c
ti
on
with
facult
y,
buil
ding
supportive
a
c
a
d
e
mi
c
c
omm
unit
ies,
a
nd
c
re
a
t
ing
spa
c
e
s
whe
re
st
ud
e
nts
fe
e
l
r
e
c
ogniz
e
d
a
nd
c
onne
c
ted
may
h
e
l
p
re
duc
e
dis
e
nga
ge
ment
a
nd
t
a
sk
de
lay.
This
is
e
spe
c
i
a
ll
y
re
leva
nt
in
priva
t
e
univer
si
ti
e
s,
whe
re
a
utonom
y
is
high
a
nd
e
xter
na
l s
truc
tur
e
is
ofte
n
li
mi
ted.
The
findings
a
ls
o
indi
c
a
te
that
ope
r
a
ti
ona
l
digi
tal
c
ompete
nc
e
pl
a
ys
a
more
im
media
te
role
i
n
re
duc
ing
pro
c
ra
st
ination
than
higher
-
lev
e
l
digi
tal
li
ter
a
c
y
a
lon
e
.
I
nst
it
uti
ons
shoul
d
e
nsure
that
st
ud
e
nts
c
a
n
use
lea
rning
tec
hnologi
e
s
e
ff
icie
ntl
y
a
nd
c
onfide
nt
ly.
Reduc
ing
tec
hnica
l
fr
iction
in
e
ve
ryda
y
a
c
a
de
mi
c
tasks
may
lowe
r
a
voidan
c
e
a
nd
make
it
e
a
si
e
r
for
st
ude
nts
to
st
a
rt
wo
rk
on
ti
me.
A
I
ov
e
rr
e
li
a
nc
e
e
mer
ge
s
a
s
a
pra
c
ti
c
a
l
c
onc
e
rn
ra
the
r
than
a
pure
ly
theor
e
ti
c
a
l
is
sue
.
Unive
rsiti
e
s
shoul
d
not
only
promote
AI
a
dopti
on
but
a
ls
o
set
c
lea
r
e
xpe
c
t
a
ti
ons
a
bout
a
pprop
ria
te
use
.
Guide
li
ne
s
that
c
lar
ify
whe
n
AI
tool
s
a
re
a
c
c
e
ptable
,
c
ombi
ne
d
with
a
ssessment
de
si
gns
that
re
quire
a
c
ti
ve
e
nga
ge
ment
a
nd
original
thi
nking, m
a
y
he
lp
p
re
ve
nt
A
I
fr
om bec
omi
ng a
shortc
u
t t
ha
t enc
oura
g
e
s t
a
sk de
l
a
y.
Although
fa
mi
ly
support
showe
d
a
we
a
ke
r
d
ire
c
t
e
f
fe
c
t,
it
shoul
d
not
be
ignore
d.
F
a
mi
l
y
e
xpe
c
tations
a
nd
support
may
st
il
l
sha
pe
st
ude
nts
’
mot
ivation
a
nd
c
opin
g
pa
tt
e
rns
in
indi
re
c
t
wa
ys.
Cl
e
a
r
c
omm
unica
ti
on
a
bout
a
c
a
de
mi
c
d
e
mands
a
nd
e
nc
oura
g
e
ment
of
st
ude
nt
a
utonom
y
may
c
o
mpl
e
ment
ins
ti
tut
ional
e
ff
orts
to
a
ddre
ss
proc
r
a
st
ination.
The
findings
im
ply
that
mana
ging
a
c
a
d
e
mi
c
proc
ra
st
ination
re
quire
s
c
oo
rdina
ted
a
c
ti
on.
I
mproving
indi
vidual
lea
rning
ski
ll
s,
st
re
ngthening
ins
ti
tut
ional
c
onne
c
ti
ons,
a
nd
setti
ng
c
lea
r
bounda
rie
s
for
A
I
use
a
ppe
a
r
more
e
ff
e
c
ti
ve
than
is
olate
d
int
e
rve
nti
ons
foc
use
d
on
tec
hnology
a
lone.
7.
CONC
LUS
IO
N
This
st
udy
e
xa
mi
ne
d
a
c
a
de
mi
c
proc
ra
st
ination
a
s
a
ke
y
mec
ha
nis
m
li
nking
self
-
re
gulate
d
le
a
rning,
digi
tal
c
ompete
nc
e
,
digi
tal
li
ter
a
c
y,
fa
mi
ly
supp
ort,
schoo
l
a
tt
a
c
hment,
a
nd
A
I
ove
rr
e
li
a
n
c
e
to
a
c
a
d
e
mi
c
a
c
hieve
ment
in
A
I
-
int
e
g
ra
ted
highe
r
e
du
c
a
ti
on.
T
he
r
e
sul
ts
show
th
a
t
self
-
re
gul
a
ted
le
a
rning
a
n
d
schoo
l
a
tt
a
c
hment
re
duc
e
proc
r
a
st
ination,
while
AI
ove
rr
e
li
a
nc
e
incr
e
a
ses
it
.
I
n
turn,
proc
ra
st
ination
si
gnific
a
ntl
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J Eva
l &
Res Edu
c
I
S
S
N:
2252
-
8822
Ac
ade
mic
pro
c
rast
inat
ion and achie
v
e
me
nt amon
g unive
rsi
ty students unde
r AI … (
T
ang M
y
Sang
)
3307
a
ff
e
c
ts
a
c
a
de
mi
c
a
c
hiev
e
ment.
The
st
udy
c
ontribut
e
s
by
int
e
gra
ti
ng
A
I
ove
rr
e
li
a
nc
e
with
indi
vidual
a
nd
c
ontextua
l
fa
c
tors
in
a
unifie
d
model,
off
e
ring
a
more
c
ompre
h
e
nsi
ve
e
xplana
ti
on
of
proc
r
a
st
ination
in
AI
-
supporte
d
le
a
rning.
F
indi
ngs
indi
c
a
te
that
a
dva
nc
e
d
te
c
hnologi
e
s
do
not
re
plac
e
s
e
lf
-
r
e
gulation;
ins
tea
d,
we
a
k
self
-
re
gulation
be
c
omes
more
proble
matic
with
he
a
vy
AI
re
li
a
n
c
e
.
P
ra
c
ti
c
a
ll
y,
univer
si
ti
e
s
shoul
d
st
re
ngthen
st
ude
nts
’
self
-
re
gulate
d
lea
rning
a
nd
promote
re
sponsi
ble
AI
use
through
tra
ini
ng
a
nd
c
lea
r
guidelines.
How
e
ve
r,
the
c
ross
-
sec
ti
ona
l
de
si
gn
li
mi
ts
c
a
usa
l
c
onc
lus
ions,
a
nd
A
I
ove
rr
e
li
a
nc
e
wa
s
mea
sure
d
broa
dly.
F
uture
r
e
sea
rc
h
shoul
d
use
longi
tudi
na
l
o
r
e
xpe
rimenta
l
de
si
gns,
include
diver
se
c
ontexts,
a
nd
a
pply
more
de
tailed me
a
sure
s o
f A
I
use
to bette
r und
e
rst
a
nd it
s i
mpac
t on proc
ra
s
ti
na
ti
on a
nd a
c
hieve
ment
.
AC
KNOWL
EDG
M
ENT
Dur
ing
the
pre
p
a
ra
ti
on
o
f
thi
s
wor
k,
the
a
uthors
use
d
ChatGP
T
to
im
prove
gra
mm
a
r,
punc
tuation
,
a
nd
langua
ge
flue
n
c
y
in
thi
s
manusc
ript.
Af
ter
usi
ng
thi
s
tool
,
the
a
uthors
re
view
e
d
a
nd
e
dit
e
d
the
c
ontent
a
s
ne
e
de
d
a
nd take
s full r
e
sponsi
bil
it
y for
the c
ontent of
the publica
ti
on.
FUN
DIN
G INFORM
A
TI
ON
This
re
sea
rc
h
w
a
s
pa
rtia
ll
y
funde
d
by
Ho
Chi
Mi
nh
Unive
rsity
of
Ban
king,
Ho
Chi
Mi
nh
Ci
t
y,
Vie
tnam.
This
re
sea
rc
h
is
pa
rtially
funde
d
by
Ho
Chi
Mi
nh
Ci
ty
Uni
ve
rsity
of
Ec
onomi
c
s
a
nd
F
inanc
e
(U
EF
), H
o Chi
Mi
nh Ci
t
y, Vie
tnam.
AU
TH
OR CONTRIBUT
IO
NS S
TA
TE
M
ENT
This
journa
l
use
s
the
Cont
ributor
Rol
e
s
Ta
xonomy
(CRediT)
to
re
c
ognize
indi
vidual
a
utho
r
c
ontribut
ions,
re
duc
e
a
uthorship di
sput
e
s, a
nd fa
c
i
li
tate
c
oll
a
bora
ti
on.
Nam
e
of A
u
thor
C
M
So
Va
Fo
I
R
D
O
E
Vi
Su
P
Fu
Ta
ng My S
a
ng
✓
✓
✓
✓
✓
✓
Le
Quoc
Th
a
ng
✓
✓
✓
✓
✓
✓
✓
✓
✓
C
:
C
onc
e
pt
ua
li
z
a
ti
on
M
:
M
e
th
odol
ogy
So
:
So
f
twa
r
e
Va
:
Va
li
da
ti
on
Fo
:
Fo
r
ma
l
a
na
ly
si
s
I
:
I
nve
st
ig
a
ti
on
R
:
R
e
sour
c
e
s
D
:
D
a
ta
C
ur
a
ti
on
O
:
W
r
it
in
g
-
O
r
ig
in
a
l
D
r
a
f
t
E
:
W
r
it
in
g
-
R
e
vi
e
w
&
E
di
ti
ng
Vi
:
Vi
sua
li
z
a
ti
on
Su
:
Su
pe
r
vi
si
on
P
:
P
r
oj
e
c
t
a
dmi
ni
st
r
a
ti
on
Fu
:
Fu
ndi
ng a
c
qui
si
ti
on
CONF
LI
CT O
F INTE
RES
T S
TA
TE
M
ENT
The
a
uthors r
e
port ther
e
a
re
no c
omp
e
ti
ng int
e
re
st
s.
ET
HI
CA
L APPR
OVAL
The
st
udy
protoc
ol
wa
s
re
view
e
d
a
nd
a
pprov
e
d
by
Ho
Chi
Mi
nh
Unive
r
si
ty
of
Banking
Revie
w
Boar
d
or
Ethi
c
s
Com
m
it
tee
,
e
nsuring
c
ompl
ian
c
e
with
e
thi
c
a
l
st
a
nda
r
ds
for
r
e
sea
rc
h
invol
vi
ng
human
pa
rticipa
nts
.
DA
TA AV
AILAB
IL
IT
Y
The
da
t
a
that
suppo
rt
th
e
findings
of
thi
s
st
udy
a
re
a
va
il
a
ble
on
re
que
st
fr
om
th
e
c
o
rr
e
spondi
ng
a
uthor,
[L
QT]
.
Th
e
da
t
a
,
whic
h
c
ontain
infor
mation
that
c
ould
c
ompromi
se
the
priva
c
y
of
re
sea
rc
h
pa
rticipa
nts
, a
r
e
not publ
icly a
va
il
a
ble due
to
c
e
rta
in re
st
ric
ti
ons.
REFE
RENC
ES
[
1]
E.
A
ly
a
hy
a
n
a
nd
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D
üşt
e
g
ör
,
“
P
r
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di
c
ti
ng
a
c
a
d
e
mi
c
su
c
c
e
ss
in
hi
gh
e
r
e
duc
a
ti
on:
li
te
r
a
tu
r
e
r
e
vi
e
w
a
nd
be
st
p
r
a
c
ti
c
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s,
”
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nt
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rnat
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J
ournal
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is
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ubl
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C
he
n,
D
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Zou,
H
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X
ie
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G
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C
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nd
C
.
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“
Tw
o
de
c
a
d
e
s
of
a
r
ti
f
ic
ia
l
in
te
ll
ig
e
nc
e
in
e
d
uc
a
ti
on,”
Educ
at
io
nal
T
e
c
hnol
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&
Soc
ie
ty
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–
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7, 2022
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
S
S
N
:
2252
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8822
I
nt
J Eva
l &
Res Edu
c
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ol.
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August
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3
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1
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J.
S
ong,
Y
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Le
i,
Y
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Zha
ng,
a
nd
X
.
H
u,
“
C
hr
onot
yp
e
a
nd
a
c
a
de
mi
c
pr
oc
r
a
st
in
a
ti
on:
th
e
c
h
a
in
me
di
a
ti
ng
r
ol
e
o
f
f
u
tu
r
e
se
lf
-
c
ont
in
ui
ty
a
nd se
lf
-
c
ont
r
ol
,
”
BM
C
Psy
c
hol
ogy
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A
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C
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K
oo,
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H
e
w
,
“
S
e
lf
-
r
e
gul
a
te
d
le
a
r
ni
ng
st
r
a
te
gi
e
s
a
nd
non
-
a
c
a
de
mi
c
out
c
ome
s
in
hi
ghe
r
e
duc
a
ti
on
bl
e
nde
d
le
a
r
ni
ng
e
nvi
r
onm
e
nt
s:
a
one
de
c
a
d
e
r
e
vi
e
w
,
”
Educ
a
ti
on
and
I
nf
ormati
on
T
e
c
hnol
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e
s
,
vol
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F
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S
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F
a
yda
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in
ik
,
“
Th
e
im
pa
c
t
of
di
gi
ta
l
c
ompe
te
n
c
e
s
on
a
c
a
de
mi
c
pr
o
c
r
a
st
in
a
ti
on
in
hi
g
he
r
e
duc
a
ti
on:
a
st
r
uc
tu
r
a
l
e
qu
a
ti
on
mode
li
ng
a
ppr
oa
c
h,
”
Pe
g
e
m
J
ournal
of
Educ
at
io
n
and
I
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ruc
ti
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[
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X
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Tia
n,
X
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Liu,
Z.
X
ia
o,
a
nd
Q
.
Lin,
“
U
nde
r
g
r
a
du
a
te
s’
ne
g
a
ti
ve
e
mot
io
n
a
nd
a
c
a
d
e
mi
c
pr
o
c
r
a
st
in
a
ti
on
dur
in
g
C
O
V
I
D
-
19:
li
f
e
a
ut
onomy a
s a
me
di
a
to
r
a
nd se
nse
of
sc
hool
be
lo
ngi
ng a
s a
mode
r
a
to
r
,
”
Psy
c
hol
ogy
Re
s
e
arc
h and Be
hav
io
r M
anage
m
e
nt
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un,
J.
Li,
X
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C
he
n,
M.
C
ui
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a
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Y
a
n,
“
The
im
pa
c
t
of
ma
la
da
pt
iv
e
pe
r
f
e
c
ti
oni
sm
on
A
I
d
e
pe
nde
n
c
e
a
mong
c
ol
le
ge
st
ude
nt
s:
th
e
me
di
a
ti
ng
r
ol
e
of
se
lf
-
c
ont
r
ol
a
nd
th
e
mode
r
a
ti
ng
r
ol
e
of
a
c
a
d
e
mi
c
e
ng
a
ge
m
e
nt
,”
Ac
ta
Psy
c
hol
ogi
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a
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t
al
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a
r
e
o
f
me
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ti
ve
l
a
z
in
e
ss:
e
f
f
e
c
ts
of
g
e
n
e
r
a
ti
ve
a
r
ti
f
ic
i
a
l
in
te
ll
ig
e
nc
e
on
le
a
r
ni
ng mot
iv
a
ti
on, pr
oc
e
ss
e
s,
a
nd
pe
r
f
o
r
ma
nc
e
,”
Bri
ti
sh J
ournal
of
Educ
at
io
nal
T
e
c
hnol
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A
di
yono,
S
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N
ur
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ya
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N
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Mu
ti
’
a
h,
A
bdur
r
ohi
m,
E.
R
ie
novi
ta
,
a
nd
S
.
A
r
ia
nt
i,
“
S
e
lf
-
e
f
f
ic
a
c
y
a
s
a
m
e
di
a
to
r
:
how
se
lf
-
r
e
gu
la
te
d
le
a
r
ni
ng
a
nd
f
a
mi
ly
suppor
t
r
e
duc
e
a
c
a
d
e
mi
c
pr
oc
r
a
st
in
a
ti
on
a
m
ong
I
ndone
si
a
n
Engli
sh
a
s
a
f
or
e
ig
n
la
ngua
ge
(
EF
L)
st
ude
nt
s
?
”
I
nt
e
rnat
io
nal
J
ournal
of
T
ESO
L
St
udi
e
s
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A
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K
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G
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d
e
H
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A
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F
r
e
i
r
e
s,
a
n
d
P
.
N
.
da
F
onse
c
a
,
“
P
syc
h
ome
tric
pr
op
e
r
ti
e
s
of
th
e
a
c
a
de
mi
c
pr
oc
r
a
st
in
a
ti
on
sc
a
l
e
(
A
P
S
)
in
B
r
a
z
il
,”
J
ournal
of
Psy
c
hoe
d
uc
at
io
nal
Asse
ssme
nt
,
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S
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Lyna
m
,
M.
C
a
c
hi
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,
a
nd
R
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S
to
c
k,
“
A
n
e
va
lu
a
ti
on
of
th
e
f
a
c
to
r
s
th
a
t
in
f
lu
e
nc
e
a
c
a
d
e
mi
c
suc
c
e
ss
a
s
de
f
in
e
d
by
e
n
ga
ge
d
st
ude
nt
s,”
Educ
at
io
nal
Re
v
i
e
w
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in
de
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va
n
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lp
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n,
“
A
c
a
d
e
mi
c
buoya
nc
y:
ove
r
c
omi
ng
te
st
a
nxi
e
ty
a
nd
se
tb
a
c
ks,”
J
ourn
al
of
I
nt
e
ll
ig
e
nc
e
, vol
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A
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R
a
gusa
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t
al
.
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E
f
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e
c
ts
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a
c
a
de
mi
c
se
lf
-
r
e
gul
a
ti
on
on
p
r
o
c
r
a
st
in
a
ti
on,
a
c
a
de
mi
c
st
r
e
ss
a
nd
a
nxi
e
ty
,
r
e
si
li
e
nc
e
a
nd
a
c
a
d
e
mi
c
pe
r
f
o
r
ma
nc
e
in
a
s
a
mpl
e
of
S
pa
ni
sh
se
c
onda
r
y
sc
hool
st
u
de
nt
s,”
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rs
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Psy
c
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N
. A
. A
lb
e
lb
is
i,
A
. S
. A
l
-
A
dw
a
n, a
nd A
. H
a
bi
bi
, “
S
e
lf
-
r
e
gul
a
te
d l
e
a
r
ni
ng a
nd sa
ti
sf
a
c
ti
on:
a
ke
y de
te
r
mi
na
nt
s of
MOO
C
suc
c
e
ss,”
Educ
at
io
n and I
nf
ormati
on T
e
c
hnol
ogi
e
s
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M.
X
a
vi
e
r
a
nd
J.
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ne
s
e
s,
“
P
e
r
si
st
e
nc
e
a
nd
ti
me
c
ha
ll
e
ng
e
s
in
a
n
ope
n
onl
in
e
uni
ve
r
si
ty
:
a
c
a
s
e
st
udy
of
th
e
e
xpe
r
ie
n
c
e
s
of
f
irst
-
ye
a
r
le
a
r
n
e
r
s,”
I
nt
e
rnat
io
nal
J
ournal
of
Educ
at
io
nal
T
e
c
hnol
ogy
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ig
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e
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A
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I
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nt
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s,
M
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A
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G
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C
a
r
va
lh
o,
C
.
M.
V
. S
ol
ór
z
a
no,
a
nd L.
S
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Ma
r
r
oni
,
“
The
di
gi
ta
l
c
ompe
te
nc
e
o
f
a
c
a
d
e
mi
c
s
in
hi
ghe
r
e
duc
a
ti
on:
is
th
e
g
la
ss
ha
lf
e
mpt
y
or
ha
lf
f
ul
l?
”
I
nt
e
r
nat
io
nal
J
ournal
o
f
Educ
at
io
n
al
T
e
c
hnol
ogy
in
H
ig
he
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Educ
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[
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Z.
A
r
di
,
G
a
ne
f
r
i,
H
.
H
id
a
ya
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A
.
H
id
a
ya
ti
,
a
nd
A
.
H
.
P
ut
r
a
,
“
I
nt
e
gr
a
ti
ng
c
r
it
ic
a
l
th
in
ki
ng
a
nd
di
gi
ta
l
li
te
r
a
c
y
in
to
te
c
hnol
ogy
a
c
c
e
pt
a
n
c
e
f
o
r
onl
in
e
c
ounse
li
ng:
a
P
LS
-
S
EM
st
udy
a
mong
Musl
im
uni
ve
r
si
ty
st
ude
nt
s
,”
I
sl
am
ic
G
ui
danc
e
and
C
ouns
e
li
ng
J
ournal
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[
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M.
La
ndoni,
T.
H
ui
be
r
s,
E.
M
ur
gi
a
,
a
nd
M.
S
.
P
e
r
a
,
“
Ethi
c
a
l
im
pl
ic
a
ti
ons
f
or
c
hi
ld
r
e
n’
s
us
e
of
s
e
a
r
c
h
to
ol
s
in
a
n
e
duc
a
ti
ona
l
se
tt
in
g,”
I
nt
e
rnat
io
nal
J
ournal
of
C
hi
ld
-
C
om
put
e
r I
nt
e
rac
ti
on
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:
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.i
jc
c
i.
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[
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J.
H
ua
ng,
Z.
Y
a
ng,
Q
.
W
a
ng,
J.
Liu,
W
.
X
ie
,
a
nd
Y
.
S
un,
“
Th
e
r
e
la
ti
onshi
p
be
twe
e
n
f
a
mi
ly
c
ohe
si
on
a
nd
be
dt
im
e
pr
oc
r
a
st
in
a
ti
on
a
mong
C
hi
ne
se
c
ol
le
ge
st
ude
n
ts
:
th
e
c
ha
in
me
di
a
ti
ng
e
f
f
e
c
t
of
c
opi
ng
st
yl
e
s
a
nd
mobi
le
p
hone
a
ddi
c
ti
on,”
BM
C
Psy
c
hi
at
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L.
G
.
H
il
l
a
nd
N
.
E.
W
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r
ne
r
,
“
A
f
f
il
ia
ti
ve
mot
iv
a
ti
on,
sc
hool
a
tt
a
c
hme
nt
,
a
nd
a
gg
r
e
ssi
on
in
sc
hool
,”
Psy
c
hol
og
y
in
th
e
Sc
hool
s
,
vol
. 43, no. 2, pp. 231
–
246, F
e
b. 2006, doi:
10.1002/pi
ts
.20140.
[
22]
Y
.
Liu,
B
.
Ze
ng,
a
nd
L.
C
h
a
ng,
“
Ex
a
mi
ni
ng
th
e
li
nks
b
e
twe
e
n
se
ns
e
of
be
lo
ngi
ng,
c
onf
li
c
t
r
e
sol
ut
io
n
ski
ll
s,
e
mot
io
na
l
in
te
ll
ig
e
nc
e
,
a
nd
li
f
e
sa
ti
sf
a
c
ti
on
in
C
hi
ne
se
uni
ve
r
si
ti
e
s,”
BM
C
Psy
c
hol
og
y
,
vol
.
13,
no.
1,
p.
431,
A
pr
.
2025,
doi
:
10.1186/s
40359
-
025
-
02742
-
9.
[
23]
Z.
A
lp
te
ki
n
a
nd
A
.
Ta
ne
r
i,
“
Te
c
hnol
ogy
i
nt
e
gr
a
ti
on
in
pe
d
a
gogi
c
a
l
pr
o
c
e
sse
s:
di
gi
ta
l
c
ompe
te
nc
e
a
nd
te
a
c
hi
ng
pr
a
c
ti
c
e
s
of
pr
im
a
r
y sc
hool
t
e
a
c
h
e
r
s i
n Tur
k
e
y,”
D
is
c
o
v
e
r Edu
c
at
io
n
, vol
. 4, no. 1, p. 351, S
e
p. 2025, doi:
10.1007/s
44217
-
025
-
00646
-
9.
[
24]
W
.
H
ua
ng
a
nd
W
.
Zhu,
“
P
e
r
c
e
iv
e
d
te
a
c
h
e
r
suppo
r
t
a
nd
a
c
a
de
mi
c
pr
o
c
r
a
st
in
a
ti
on
a
mong
e
le
me
nt
a
r
y
sc
hool
st
ude
nt
s:
th
e
me
di
a
ti
ng
e
f
f
e
c
t
of
a
c
a
de
m
ic
se
lf
-
e
f
f
i
c
a
c
y
a
nd
mod
e
r
a
ti
ng
e
f
f
e
c
t
o
f
ge
nd
e
r
,”
Ac
ta
Ps
y
c
h
ol
ogi
c
a
,
vol
.
261,
p.
105779,
N
ov.
2025, doi
:
10.1016/j
.a
c
tp
sy.2025.105779.
[
25]
C
.
S
.
A
ndr
e
a
sse
n,
T.
Tor
sh
e
im
,
G
.
S
.
B
r
unbor
g,
a
nd
S
.
P
a
ll
e
se
n,
“
D
e
ve
lo
pme
nt
o
f
a
F
a
c
e
b
ook
a
ddi
c
ti
on
sc
a
l
e
,”
Ps
y
c
hol
o
gi
c
al
Re
port
s
, vol
. 110, no. 2, pp. 501
–
517, Apr
. 2012, doi:
10.2466/02.09.18.P
R
0.110.2.501
-
517.
[
26]
C
.
Zha
i,
S
.
W
ib
ow
o,
a
nd
L.
D
.
Li,
“
The
e
f
f
e
c
ts
of
ove
r
-
r
e
li
a
nc
e
on
A
I
d
ia
lo
gue
syst
e
ms
on
s
tu
de
nt
s’
c
ogni
ti
ve
a
bi
li
ti
e
s:
a
syst
e
ma
ti
c
r
e
vi
e
w
,
”
Sm
art
L
e
arni
ng Env
ir
onm
e
nt
s
, vol
. 11, no. 1, p. 28, Jun. 2024, doi
:
10.1
186/
s40561
-
024
-
00316
-
7.
[
27]
K
.
Tz
a
f
il
kou,
M.
P
e
r
i
f
a
nou,
a
nd
A
.
A
.
Ec
onomi
d
e
s,
“
D
e
ve
lo
pme
nt
a
nd
va
li
da
ti
on
of
st
ude
nt
s’
di
gi
ta
l
c
ompe
te
nc
e
sc
a
le
(
S
D
iC
oS
)
,
”
I
nt
e
rnat
io
nal
J
ou
rnal
of
Educ
at
io
nal
T
e
c
hnol
ogy
in
H
ig
he
r
Educ
at
io
n
,
vol
.
19,
no.
1,
p.
30,
D
e
c
.
2022,
doi
:
10.1186/s
41239
-
022
-
00330
-
0.
[
2
8
]
T
.
S
h
e
n,
A
.
E
.
O
s
o
r
i
o,
a
n
d
A
.
S
e
tt
l
e
s
,
“
Th
e
in
f
l
u
e
n
c
e
of
su
pp
o
r
t
f
a
c
t
or
s
o
n
e
nt
r
e
pr
e
n
e
u
r
i
a
l
a
tt
it
u
d
e
s
a
nd
i
nt
e
nt
i
ons
o
f
c
ol
l
e
g
e
s
tu
d
e
nt
s,
”
A
c
ad
e
m
y
of
M
a
na
g
e
m
e
nt
Pro
c
e
e
di
ng
s
,
v
ol
.
2
01
7,
n
o.
1,
p
.
10
90
1,
A
ug
.
20
17
,
do
i
:
10
.
54
65/
A
M
B
P
P
.
20
17
.1
09
01
a
bst
r
a
c
t
.
[
29]
B
.
H
.
C
he
n,
W
.
-
C
.
C
hi
u,
a
nd
C
.
-
C
.
W
a
ng,
“
The
r
e
la
ti
onshi
p
a
mong
a
c
a
d
e
mi
c
se
lf
-
c
onc
e
pt
,
le
a
r
ni
ng
st
r
a
te
gi
e
s,
a
nd
a
c
a
d
e
mi
c
a
c
hi
e
v
e
me
nt
:
a
c
a
se
st
udy
of
n
a
ti
ona
l
voc
a
ti
ona
l
c
ol
le
g
e
st
ud
e
nt
s
in
Ta
iw
a
n
vi
a
S
EM,”
T
he
Asi
a
-
Pac
if
ic
Edu
c
at
io
n
Re
s
e
arc
he
r
,
vol
. 24, no. 2, pp. 419
–
431, Jun. 2015, doi
:
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40299
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014
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0194
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1.
[
30]
D
.
R
.
Je
ba
si
ngh,
N
.
A
hma
d,
S
.
R
.
S
hi
mra
y,
a
nd
A
.
S
ub
a
v
e
e
r
a
pa
ndi
y
a
n,
“
P
e
r
c
e
iv
e
d
im
p
a
c
t
of
pr
oc
r
a
st
in
a
ti
on
on
a
c
a
d
e
mi
c
pe
r
f
o
r
ma
nc
e
a
mong
st
ude
nt
s
a
nd
th
e
r
ol
e
of
A
I
to
ol
s
,”
L
ib
ri
,
vol
.
75,
no.
4,
pp.
355
–
373,
D
e
c
.
2025,
doi
:
10.1515/l
ib
r
i
-
2025
-
0093.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
nt
J Eva
l &
Res Edu
c
I
S
S
N:
2252
-
8822
Ac
ade
mic
pro
c
rast
inat
ion and achie
v
e
me
nt amon
g unive
rsi
ty students unde
r AI … (
T
ang M
y
Sang
)
3309
BI
OG
RA
PHIE
S
OF AU
TH
ORS
Tang
My
Sang
is
cur
rently
working
as
a
full
-
ti
me
lecturer
at
Ho
Chi
Mi
nh
University
of
Banking,
Viet
nam.
She
has
practical
as
w
ell
as
theoretical
expertise
i
n
the
field
of
education,
business
admi
nistration,
accounting
,
and
sustainable
development.
H
er
research
interests
include
education
,
finance
and
banking,
acc
ountin
g
and
auditin
g
,
and
sustain
able
development.
She
can
be
co
ntacted
at
email:
sangtm@h
ub.
edu.
vn
.
Le
Quoc
Thang
rec
eived
the
doctor
degree
fr
om
European
University
in
Business
Administra
tion
(D
BA).
He
has
over
20
years
of
experie
nce
as
a
manage
r
and
lecture
r
in
many
universities
includi
ng
state
and
private
ones
.
H
e
used
to
be
a
Vice
Director
of
Qualit
y
Assurance
Department
,
D
i
rector
of
Academic
Depar
tment
,
Vice
D
irector
o
f
I
nstitute
of
I
nternational
Education
and
now
he
is
the
D
irector
of
Testing
D
epartment
and
Vi
ce
D
irector
of
Graduate
Education
I
nstitute
as
well.
Beside
he
is
als
o
a
lecturer
in
Business
Ad
ministration
Are
a.
His
research
rega
rd
to
education
with
students’
learning,
graduate
progra
ms,
testing,
support
service,
and
e
-
learni
ng.
He
can
be
contacted
at
e
mail:
thanglq@
uef.
edu
.
vn
.
Evaluation Warning : The document was created with Spire.PDF for Python.