I
nte
rna
t
io
na
l J
o
urna
l o
f
E
v
a
lua
t
io
n a
nd
Resea
rc
h in E
du
ca
t
io
n (
I
J
E
RE
)
Vo
l.
15
,
No
.
4
,
A
u
g
u
s
t
20
26
,
p
p
.
3
1
7
2
~
3
1
8
1
I
SS
N:
2
2
5
2
-
8
8
2
2
,
DOI
: 1
0
.
1
1
5
9
1
/
ijer
e
.
v
15
i
4
.
3
9
9
1
5
3172
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ere.
ia
esco
r
e.
co
m
Cha
tGPT a
s sca
ff
o
ld:
quiz
perf
o
rm
a
nce acro
ss
sess
io
n
co
mplexit
y
F
a
t
im
a
E
zz
a
hra
K
a
bb
a
1
,2
,
Z
o
uh
a
ir
E
j
ba
ri
2
1
H
i
g
h
e
r
I
n
t
e
r
n
a
t
i
o
n
a
l
I
n
st
i
t
u
t
e
o
f
T
o
u
r
i
sm (
I
S
I
TT),
M
i
n
i
st
r
y
o
f
T
o
u
r
i
sm,
H
a
n
d
i
c
r
a
f
t
s,
a
n
d
S
o
c
i
a
l
a
n
d
S
o
l
i
d
a
r
i
t
y
E
c
o
n
o
my
,
Ta
n
g
i
e
r
,
M
o
r
o
c
c
o
2
D
e
p
a
r
t
me
n
t
o
f
Ec
o
n
o
m
i
c
s
a
n
d
M
a
n
a
g
e
m
e
n
t
,
F
a
c
u
l
t
y
o
f
Le
g
a
l
a
n
d
E
c
o
n
o
m
i
c
S
c
i
e
n
c
e
s
o
f
T
a
n
g
i
e
r
,
A
b
d
e
l
ma
l
e
k
E
ssaa
d
i
U
n
i
v
e
r
s
i
t
y
,
Ta
n
g
i
e
r
,
M
o
r
o
c
c
o
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Ap
r
12
,
2
0
2
6
R
ev
is
ed
J
u
l
11
,
2
0
2
6
Acc
ep
ted
J
u
l
20
,
2
0
2
6
M
a
n
y
st
u
d
ies
e
x
a
m
in
e
t
h
e
u
se
o
f
Ch
a
tG
P
T
in
e
d
u
c
a
ti
o
n
,
b
u
t
m
o
st
m
e
a
su
re
stu
d
e
n
t
p
e
rc
e
p
ti
o
n
s,
n
o
t
p
e
rfo
r
m
a
n
c
e
,
a
n
d
fe
w
trac
k
p
e
rfo
rm
a
n
c
e
a
c
ro
ss
m
u
lt
ip
le
se
ss
io
n
s
o
f
d
iffere
n
t
c
o
m
p
lex
it
y
.
In
p
a
rti
c
u
lar,
n
o
st
u
d
y
h
a
s
trac
k
e
d
wh
e
th
e
r
th
is
a
ss
o
c
iatio
n
v
a
ries
a
c
ro
ss
se
ss
io
n
s
o
f
d
iffere
n
t
c
o
g
n
i
ti
v
e
c
o
m
p
lex
it
y
.
Us
i
n
g
a
q
u
a
si
-
e
x
p
e
rime
n
tal
d
e
sig
n
,
f
irst
-
y
e
a
r
u
n
d
e
r
g
ra
d
u
a
tes
(N
=
1
9
3
)
a
t
t
h
e
Hi
g
h
e
r
I
n
tern
a
ti
o
n
a
l
In
st
it
u
te
o
f
To
u
rism
(I
S
ITT
)
i
n
Tan
g
ier,
M
o
ro
c
c
o
we
re
fo
ll
o
we
d
a
c
ro
ss
se
v
e
n
in
tr
o
d
u
c
to
ry
sta
ti
stics
se
ss
io
n
s.
On
e
g
ro
u
p
h
a
d
a
c
c
e
ss
to
C
h
a
tG
P
T
d
u
ri
n
g
lea
rn
in
g
a
c
ti
v
it
ies
,
wh
i
le
th
e
o
th
e
r
fo
ll
o
we
d
th
e
sa
m
e
in
stru
c
ti
o
n
with
o
u
t
a
rti
ficia
l
i
n
telli
g
e
n
c
e
(
AI
)
a
c
c
e
s
s.
P
e
rfo
rm
a
n
c
e
wa
s
m
e
a
su
re
d
th
ro
u
g
h
e
n
d
-
of
-
se
ss
io
n
q
u
izz
e
s
(1
,
1
3
6
o
b
se
rv
a
ti
o
n
s)
a
n
d
a
n
a
ly
z
e
d
u
s
in
g
a
li
n
e
a
r
m
ix
e
d
-
e
ffe
c
ts
m
o
d
e
l.
No
c
o
n
siste
n
t
o
v
e
ra
ll
a
d
v
a
n
tag
e
wa
s
a
ss
o
c
iate
d
with
e
it
h
e
r
c
o
n
d
it
i
o
n
.
Ho
we
v
e
r,
a
sig
n
ifi
c
a
n
t
i
n
tera
c
ti
o
n
b
e
twe
e
n
c
o
n
d
it
io
n
a
n
d
se
ss
io
n
wa
s
id
e
n
ti
fie
d
(χ
²
(6
)
=
6
1
.
5
0
,
p
<
0
.
0
0
1
).
T
h
e
m
o
st
p
ro
n
o
u
n
c
e
d
d
i
v
e
rg
e
n
c
e
o
c
c
u
rre
d
i
n
se
ss
io
n
6
,
wh
ich
in
v
o
l
v
e
d
m
u
l
ti
-
ste
p
c
o
m
p
u
tati
o
n
(h
a
rm
o
n
ic
m
e
a
n
a
n
d
g
ro
u
p
e
d
-
d
a
ta
m
o
d
e
in
terp
o
latio
n
),
w
h
e
re
th
e
AI
-
p
e
rm
it
ted
g
r
o
u
p
sc
o
re
d
h
ig
h
e
r
(9
.
1
5
v
s.
7
.
1
8
,
d
=
1
.
2
4
).
Ac
ro
ss
th
e
re
m
a
in
in
g
six
se
ss
io
n
s,
e
ffe
c
t
siz
e
s
ra
n
g
e
d
fro
m
d
=
−
0
.
2
0
t
o
d
=
+
0
.
1
9
.
O
u
r
fi
n
d
i
n
g
s
s
u
g
g
e
st
th
a
t
AI
in
teg
ra
ti
o
n
sh
o
u
l
d
b
e
se
lec
ti
v
e
,
u
se
d
d
u
r
in
g
c
o
m
p
lex
p
r
o
c
e
d
u
ra
l
se
ss
io
n
s
ra
th
e
r
th
a
n
u
n
ifo
rm
ly
a
c
ro
ss
a
ll
c
o
u
rse
c
o
n
ten
t.
K
ey
w
o
r
d
s
:
C
h
atGPT
Gen
er
ativ
e
AI
Hig
h
er
ed
u
ca
tio
n
Qu
asi
-
ex
p
er
im
en
tal
d
esig
n
Statis
t
ics ed
u
ca
tio
n
Stu
d
en
t p
er
f
o
r
m
an
ce
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Fatim
a
E
zz
ah
r
a
Kab
b
a
Hig
h
er
I
n
ter
n
atio
n
al
I
n
s
titu
te
o
f
T
o
u
r
is
m
(
I
SIT
T
)
Min
is
tr
y
o
f
T
o
u
r
is
m
,
Han
d
icr
af
ts
,
an
d
So
cial
an
d
So
lid
ar
ity
E
co
n
o
m
y
T
an
g
ier
,
Mo
r
o
cc
o
E
m
ail: k
ab
b
a.
f
atim
a.
ez
za
h
r
a
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
Gen
er
ativ
e
ar
tific
ial
in
tellig
en
ce
(
AI
)
to
o
ls
s
u
ch
as
C
h
atGP
T
ar
e
b
ec
o
m
in
g
in
cr
ea
s
in
g
ly
c
o
m
m
o
n
in
h
ig
h
er
ed
u
ca
tio
n
,
as
th
ey
ca
n
h
elp
s
tu
d
en
ts
in
m
an
y
wa
y
s
:
g
en
er
atin
g
e
x
p
lan
atio
n
s
,
ex
a
m
p
les,
an
d
s
tep
-
by
-
s
tep
g
u
id
an
ce
in
r
esp
o
n
s
e
to
p
r
o
b
lem
s
th
ey
f
ac
e
in
lear
n
in
g
[
1
]
–
[
4
]
.
Desp
ite
th
is
g
r
o
win
g
u
s
e,
teac
h
er
s
s
till
lack
clea
r
g
u
i
d
an
ce
o
n
wh
en
a
n
d
h
o
w
to
u
s
e
th
ese
to
o
ls
in
t
h
eir
co
u
r
s
es.
A
p
r
ac
tical
q
u
esti
o
n
r
em
ain
s
lar
g
ely
u
n
r
eso
lv
ed
:
u
n
d
er
wh
at
c
o
n
d
itio
n
s
,
if
a
n
y
,
ca
n
th
ese
to
o
l
s
s
u
p
p
o
r
t
s
tu
d
en
t
lear
n
in
g
w
h
en
u
s
ed
alo
n
g
s
id
e
r
eg
u
lar
class
r
o
o
m
i
n
s
tr
u
ctio
n
?
M
o
s
t
e
x
is
t
i
n
g
s
t
u
d
i
es
f
o
c
u
s
o
n
s
t
u
d
e
n
t
p
e
r
c
e
p
ti
o
n
s
,
e
t
h
i
ca
l
d
eb
a
t
e
s
,
o
r
i
n
s
t
i
t
u
t
i
o
n
a
l
p
o
l
i
ci
e
s
,
w
i
t
h
f
e
w
er
e
x
a
m
i
n
i
n
g
a
c
t
u
a
l
l
e
a
r
n
i
n
g
o
u
t
c
o
m
e
s
a
c
r
o
s
s
m
u
lt
i
p
l
e
s
es
s
i
o
n
s
[
2
]
,
[
5
]
–
[
7
]
.
T
h
e
s
t
u
d
i
es
t
h
a
t
d
o
m
e
as
u
r
e
p
e
r
f
o
r
m
a
n
c
e
t
e
n
d
t
o
r
e
l
y
o
n
s
i
n
g
l
e
s
e
s
s
i
o
n
s
,
s
m
a
ll
s
a
m
p
l
es
,
o
r
s
e
l
f
-
r
e
p
o
r
t
e
d
d
a
t
a
[
8
]
.
L
o
n
g
i
t
u
d
i
n
a
l
c
l
ass
r
o
o
m
-
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
C
h
a
tGP
T a
s
s
ca
ffo
ld
:
q
u
iz
p
erfo
r
ma
n
ce
a
cro
s
s
s
ess
io
n
co
mp
lexity
(
F
a
tima
E
z
z
a
h
r
a
K
a
b
b
a
)
3173
b
a
s
e
d
e
v
i
d
e
n
c
e
,
t
r
a
c
k
i
n
g
r
e
a
l
s
t
u
d
e
n
t
p
e
r
f
o
r
m
a
n
c
e
a
s
c
o
u
r
s
e
co
n
t
e
n
t
g
r
o
w
s
i
n
c
o
m
p
l
e
x
i
t
y
,
r
em
a
i
n
s
li
m
i
t
e
d
.
T
h
is
g
a
p
m
a
t
t
e
r
s
i
n
q
u
a
n
t
i
ta
t
i
v
e
d
is
c
i
p
li
n
e
s
s
u
c
h
a
s
s
t
a
t
is
ti
c
s
,
wh
e
r
e
l
e
a
r
n
i
n
g
b
u
i
l
d
s
c
u
m
u
l
a
tiv
e
l
y
a
n
d
p
r
o
c
e
d
u
r
a
l
d
e
m
a
n
d
s
i
n
c
r
e
a
s
e
f
r
o
m
o
n
e
s
e
s
s
i
o
n
t
o
t
h
e
n
e
x
t
.
T
o
o
u
r
k
n
o
w
l
e
d
g
e
,
n
o
p
r
i
o
r
s
t
u
d
y
h
a
s
e
x
a
m
i
n
e
d
w
h
e
t
h
e
r
C
h
a
t
GP
T
s
u
p
p
o
r
t
i
s
m
o
r
e
s
t
r
o
n
g
l
y
a
s
s
o
c
i
at
e
d
w
i
t
h
s
t
u
d
e
n
t
p
e
r
f
o
r
m
a
n
c
e
i
n
p
r
o
c
e
d
u
r
a
l
l
y
c
o
m
p
l
e
x
s
e
s
s
i
o
n
s
t
h
a
n
i
n
c
o
n
c
e
p
t
u
a
l
o
n
e
s
,
o
r
h
o
w
t
h
is
a
s
s
o
ci
a
t
i
o
n
v
a
r
ie
s
a
c
r
o
s
s
s
es
s
io
n
s
o
f
d
i
f
f
e
r
i
n
g
c
o
g
n
i
t
i
v
e
c
o
m
p
l
e
x
i
t
y
.
T
h
is
g
ap
is
esp
ec
ial
ly
r
e
le
v
a
n
t
i
n
N
o
r
th
Af
r
i
ca
n
c
o
u
n
tr
i
es
li
k
e
M
o
r
o
c
c
o
,
w
h
e
r
e
d
i
g
i
tal
a
cc
ess
is
u
n
e
q
u
al
a
n
d
i
n
s
ti
tu
ti
o
n
al
A
I
p
o
li
cies
d
o
n
o
t
y
et
e
x
is
t.
St
u
d
e
n
ts
a
n
d
t
ea
c
h
er
s
n
a
v
i
g
ate
A
I
i
n
te
g
r
a
ti
o
n
w
it
h
o
u
t
p
e
d
a
g
o
g
ic
al
g
u
i
d
a
n
c
e
o
r
i
n
s
ti
t
u
ti
o
n
al
f
r
am
ew
o
r
k
s
[
9
]
,
[
1
0
]
.
A
r
ec
en
t
r
e
v
ie
w
c
o
n
f
ir
m
s
th
at
wh
i
le
C
h
a
tGPT
h
as
g
ai
n
ed
wi
d
e
r
e
co
g
n
it
io
n
am
o
n
g
s
t
u
d
en
ts
,
its
li
m
i
tat
io
n
s
r
e
q
u
ir
e
c
ar
e
f
u
l
at
te
n
ti
o
n
,
es
p
ec
i
all
y
i
n
s
e
tti
n
g
s
wit
h
lim
i
te
d
i
n
s
tit
u
t
i
o
n
al
s
u
p
p
o
r
t
[
1
1
]
.
T
h
e
s
p
e
ci
f
ic
it
y
o
f
t
h
is
s
t
u
d
y
als
o
lies
in
i
ts
i
n
s
tit
u
t
io
n
al
a
n
d
p
ed
ag
o
g
i
ca
l
co
n
t
ex
t.
Ma
n
y
s
t
u
d
e
n
ts
at
Hi
g
h
e
r
I
n
t
e
r
n
ati
o
n
al
I
n
s
t
it
u
te
o
f
T
o
u
r
is
m
(
I
S
I
T
T
)
b
e
g
i
n
t
h
e
d
es
cr
ip
ti
v
e
s
t
atis
tics
co
u
r
s
e
wi
th
litt
le
o
r
n
o
p
r
i
o
r
s
tat
is
tic
al
b
a
ck
g
r
o
u
n
d
,
p
a
r
ti
cu
la
r
l
y
t
h
o
s
e
w
h
o
c
o
m
e
f
r
o
m
a
h
u
m
a
n
iti
es
b
a
cc
a
la
u
r
ea
te
t
r
a
c
k
.
D
esc
r
i
p
t
iv
e
s
tat
is
ti
cs
is
a
m
a
n
d
a
to
r
y
f
i
r
s
t
-
s
e
m
est
er
co
u
r
s
e
,
m
a
k
i
n
g
it
a
c
o
g
n
i
ti
v
el
y
d
e
m
a
n
d
i
n
g
co
m
p
o
n
en
t o
f
th
ei
r
a
ca
d
e
m
ic
t
r
a
n
s
i
ti
o
n
.
Ha
v
i
n
g
t
au
g
h
t
t
h
is
s
u
b
j
ec
t
f
o
r
m
o
r
e
t
h
a
n
a
d
ec
ad
e,
t
h
e
f
i
r
s
t
au
t
h
o
r
o
b
s
e
r
v
e
d
th
at
s
t
u
d
e
n
ts
o
f
te
n
r
eq
u
i
r
e
s
u
b
s
ta
n
ti
al
s
u
p
p
o
r
t
to
m
o
v
e
f
r
o
m
in
tu
iti
v
e
r
ea
s
o
n
in
g
t
o
s
tat
is
ti
ca
l
th
i
n
k
i
n
g
.
F
u
r
t
h
e
r
m
o
r
e
,
t
h
e
s
t
u
d
y
was
c
o
n
d
u
c
te
d
i
n
th
e
a
b
s
e
n
c
e
o
f
a
f
o
r
m
al
i
n
s
tit
u
t
i
o
n
al
A
I
p
o
lic
y
,
a
s
it
u
at
i
o
n
th
a
t
r
e
f
l
ec
ts
t
h
e
b
r
o
a
d
er
u
n
ce
r
ta
in
ty
s
u
r
r
o
u
n
d
i
n
g
t
h
e
g
o
v
er
n
a
n
c
e
o
f
g
e
n
er
ati
v
e
A
I
u
s
e
i
n
Mo
r
o
c
ca
n
p
u
b
lic
h
i
g
h
e
r
e
d
u
c
ati
o
n
.
R
es
ea
r
c
h
f
r
o
m
M
id
d
l
e
E
ast
a
n
d
No
r
t
h
Af
r
i
ca
(
M
E
NA
)
te
ac
h
e
r
s
co
n
f
i
r
m
s
th
a
t
A
I
a
d
o
p
t
io
n
i
n
th
e
r
e
g
i
o
n
f
a
ce
s
u
n
iq
u
e
c
h
all
e
n
g
es
r
ela
te
d
to
i
n
s
ti
tu
ti
o
n
al
r
e
ad
i
n
ess
an
d
t
r
ai
n
i
n
g
[
1
2
]
.
A
g
l
o
b
al
s
u
r
v
e
y
o
f
o
v
er
2
3
,
0
0
0
s
t
u
d
e
n
ts
f
r
o
m
1
0
9
c
o
u
n
tr
i
es
f
o
u
n
d
th
at
m
o
s
t
C
h
atGP
T
r
ese
ar
ch
c
o
m
es
f
r
o
m
W
est
er
n
co
n
t
ex
ts
[
1
3
]
.
W
h
ile
t
h
es
e
s
t
u
d
ies
d
esc
r
i
b
e
w
h
o
u
s
es C
h
at
GPT
a
n
d
h
o
w
it
is
p
e
r
ce
i
v
e
d
,
t
h
e
y
d
o
n
o
t
ex
p
l
ai
n
wh
en
A
I
h
el
p
s
a
n
d
w
h
e
n
it
d
o
es n
o
t.
A
f
r
am
ew
o
r
k
f
r
o
m
m
at
h
e
m
a
tics
ed
u
c
ati
o
n
h
e
lp
s
a
d
d
r
ess
th
is
q
u
est
io
n
.
H
ie
b
e
r
t
a
n
d
L
e
f
e
v
r
e
[
1
4
]
d
i
f
f
er
e
n
ti
ate
b
et
wee
n
c
o
n
c
ep
tu
al
k
n
o
wle
d
g
e
(
u
n
d
er
s
ta
n
d
i
n
g
wh
at
i
d
ea
s
m
e
an
)
a
n
d
p
r
o
ce
d
u
r
al
k
n
o
w
le
d
g
e
(
t
h
e
a
b
i
lit
y
t
o
c
ar
r
y
o
u
t
s
t
ep
-
by
-
s
t
e
p
ac
ti
o
n
s
)
.
Fo
r
e
x
a
m
p
le
,
u
n
d
e
r
s
t
an
d
i
n
g
wh
y
t
h
e
m
e
d
ia
n
is
p
r
e
f
e
r
r
ed
f
o
r
s
k
ewe
d
d
is
tr
i
b
u
tio
n
s
is
c
o
n
ce
p
t
u
a
l.
A
p
p
l
y
i
n
g
t
h
e
i
n
te
r
p
o
lat
io
n
f
o
r
m
u
la
to
f
i
n
d
t
h
e
m
o
d
e
o
f
g
r
o
u
p
e
d
d
a
ta
is
p
r
o
c
ed
u
r
a
l.
S
t
ar
[
1
5
]
a
d
d
s
t
h
at
p
r
o
c
ed
u
r
al
k
n
o
wl
ed
g
e
c
an
r
a
n
g
e
f
r
o
m
r
o
te
e
x
e
cu
ti
o
n
t
o
f
le
x
i
b
l
e
ap
p
li
ca
ti
o
n
.
I
n
t
h
is
s
tu
d
y
,
co
n
c
ep
tu
al
tas
k
s
a
r
e
t
h
o
s
e
w
h
e
r
e
s
t
u
d
e
n
ts
d
e
f
i
n
e
,
class
if
y
,
o
r
i
n
te
r
p
r
et
s
ta
tis
ti
ca
l
co
n
c
e
p
ts
.
P
r
o
ce
d
u
r
al
tas
k
s
a
r
e
th
o
s
e
w
h
e
r
e
s
t
u
d
e
n
ts
s
el
ec
t
a
n
d
a
p
p
ly
f
o
r
m
u
las
t
h
r
o
u
g
h
m
u
l
t
i
-
s
t
ep
c
o
m
p
u
t
ati
o
n
.
I
n
e
d
u
ca
t
io
n
,
s
c
af
f
o
l
d
i
n
g
r
e
f
er
s
t
o
t
em
p
o
r
ar
y
i
n
s
t
r
u
ct
i
o
n
al
s
u
p
p
o
r
t
t
h
at
h
el
p
s
s
t
u
d
e
n
ts
c
o
m
p
le
te
t
as
k
s
th
e
y
ca
n
n
o
t y
e
t d
o
i
n
d
e
p
e
n
d
e
n
tly
,
an
d
th
at
is
r
e
d
u
ce
d
s
te
p
b
y
s
te
p
as
t
h
e
s
t
u
d
en
t b
e
co
m
es
m
o
r
e
ca
p
a
b
l
e.
W
h
e
n
u
s
e
d
t
o
v
e
r
i
f
y
i
n
t
e
r
m
ed
iat
e
s
tep
s
o
r
b
r
ea
k
d
o
w
n
c
o
m
p
le
x
p
r
o
b
l
em
s
,
C
h
atGP
T
ca
n
f
u
n
cti
o
n
as
a
f
o
r
m
o
f
s
ca
f
f
o
l
d
i
n
g
t
h
at
s
u
p
p
o
r
ts
l
ea
r
n
e
r
s
at
m
o
m
e
n
ts
o
f
d
i
f
f
ic
u
lt
y
[
1
6
]
.
T
h
is
k
i
n
d
o
f
s
u
p
p
o
r
t
m
ay
b
e
m
o
s
t
r
el
ev
a
n
t
d
u
r
i
n
g
p
r
o
ce
d
u
r
al
t
r
a
n
s
it
io
n
s
,
wh
e
r
e
s
t
u
d
en
ts
m
u
s
t
m
o
v
e
f
r
o
m
u
n
d
e
r
s
t
an
d
i
n
g
c
o
n
c
ep
ts
t
o
ap
p
l
y
i
n
g
f
o
r
m
u
l
as,
co
n
s
is
t
e
n
t
wit
h
a
cti
v
e
lea
r
n
i
n
g
a
p
p
r
o
ac
h
es
t
h
a
t
em
p
h
as
ize
v
e
r
i
f
ic
ati
o
n
a
n
d
r
e
f
o
r
m
u
la
ti
o
n
[
1
7
]
.
R
ec
e
n
t
r
ese
ar
ch
in
d
ic
at
es
t
h
at
g
en
er
ati
v
e
A
I
m
ay
a
ct
as
a
‘
m
o
r
e
k
n
o
wle
d
g
e
a
b
le
o
t
h
e
r
’
i
n
V
y
g
o
ts
k
y
’
s
f
r
a
m
ewo
r
k
,
s
c
af
f
o
l
d
i
n
g
lea
r
n
i
n
g
wit
h
i
n
t
h
e
zo
n
e
o
f
p
r
o
x
im
al
d
e
v
e
lo
p
m
e
n
t
[
1
8
]
.
Yet
,
c
o
n
ti
n
u
o
u
s
AI
av
ail
a
b
ili
ty
m
a
y
als
o
l
ea
d
t
o
o
v
e
r
-
s
ca
f
f
o
l
d
i
n
g
,
li
m
it
in
g
s
tu
d
en
ts
’
d
e
v
e
lo
p
m
e
n
t
o
f
in
d
ep
e
n
d
en
t
p
r
o
b
le
m
-
s
o
lv
in
g
s
k
i
lls
[
1
9
]
.
T
h
is
r
a
is
es
a
k
e
y
q
u
esti
o
n
:
d
o
es
A
I
s
u
p
p
o
r
t l
ea
r
n
i
n
g
p
r
im
ar
i
ly
w
h
e
n
tas
k
s
a
r
e
b
e
y
o
n
d
wh
at
s
t
u
d
en
ts
c
a
n
d
o
wit
h
o
u
t
h
el
p
,
o
r
d
o
es
it
c
r
e
ate
d
ep
en
d
en
c
y
e
v
e
n
i
n
l
ess
d
em
a
n
d
in
g
t
as
k
s
?
T
h
i
s
s
tu
d
y
tes
ts
w
h
et
h
er
C
h
a
tG
PT
a
cc
ess
m
atte
r
s
d
i
f
f
er
e
n
tl
y
a
cr
o
s
s
s
ess
i
o
n
s
o
f
v
ar
y
i
n
g
c
o
m
p
l
e
x
it
y
.
T
h
e
id
ea
is
s
i
m
p
le
:
C
h
atGP
T
a
cc
ess
m
ay
h
el
p
m
o
r
e
i
n
s
o
m
e
s
ess
io
n
s
t
h
a
n
o
t
h
er
s
,
d
ep
e
n
d
in
g
o
n
h
o
w
d
if
f
i
cu
lt
t
h
e
tas
k
is
.
Fig
u
r
e
1
s
h
o
ws t
h
is
c
o
n
c
ep
tu
al
m
o
d
el
.
Fig
u
r
e
1
.
A
s
s
o
ciatio
n
b
etwe
en
in
s
tr
u
ctio
n
al
co
n
d
itio
n
an
d
p
e
r
f
o
r
m
a
n
ce
,
m
o
d
er
ated
b
y
task
co
m
p
lex
ity
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
15
,
No
.
4
,
Au
g
u
s
t
20
26
:
3
1
7
2
-
3
1
8
1
3174
T
h
e
s
tu
d
y
ex
am
in
es
s
tu
d
en
t
p
er
f
o
r
m
a
n
ce
ac
r
o
s
s
s
ev
en
s
ess
i
o
n
s
in
wh
ich
o
n
e
g
r
o
u
p
u
s
ed
C
h
atGPT
alo
n
g
s
id
e
teac
h
er
-
le
d
in
s
tr
u
c
tio
n
d
u
r
i
n
g
lear
n
i
n
g
ac
tiv
iti
es,
wh
ile
a
s
ec
o
n
d
g
r
o
u
p
f
o
llo
wed
th
e
s
am
e
in
s
tr
u
ctio
n
with
o
u
t
AI
ac
c
ess
.
T
o
th
e
au
t
h
o
r
s
’
k
n
o
wled
g
e,
n
o
class
r
o
o
m
-
b
ased
q
u
asi
-
ex
p
er
im
en
tal
s
tu
d
y
o
n
C
h
atGPT
an
d
s
tu
d
en
t
p
er
f
o
r
m
an
ce
h
as
b
ee
n
co
n
d
u
cted
i
n
a
Mo
r
o
cc
an
h
ig
h
er
ed
u
c
atio
n
in
s
titu
tio
n
.
T
h
is
p
ap
er
p
r
o
v
id
es
class
r
o
o
m
-
b
as
ed
lo
n
g
itu
d
in
al
ev
i
d
en
ce
f
r
o
m
a
co
n
tex
t
wh
er
e
s
u
ch
em
p
ir
ic
al
r
esear
ch
r
em
ain
s
s
ca
r
ce
.
T
h
e
n
o
v
elty
o
f
th
is
s
tu
d
y
lies
in
th
r
ee
asp
ec
ts
.
First,
it
is
,
to
o
u
r
k
n
o
wled
g
e,
th
e
f
ir
s
t
q
u
asi
-
ex
p
er
im
en
tal
l
o
n
g
itu
d
in
al
s
t
u
d
y
t
r
ac
k
in
g
th
e
ass
o
ciatio
n
b
etwe
en
C
h
atGPT
ac
ce
s
s
an
d
s
tu
d
en
t
q
u
iz
p
er
f
o
r
m
an
ce
ac
r
o
s
s
s
ess
io
n
s
o
f
d
if
f
er
e
n
t
c
o
g
n
itiv
e
co
m
p
lex
ity
.
Seco
n
d
,
u
n
lik
e
s
tu
d
ies
th
at
m
ea
s
u
r
e
p
er
ce
p
tio
n
s
o
r
r
ely
o
n
s
in
g
le
-
s
ess
io
n
d
esig
n
s
,
th
is
s
tu
d
y
p
r
o
v
id
es
em
p
ir
ical
ev
id
e
n
ce
th
a
t
th
e
ass
o
ciatio
n
is
s
ess
io
n
-
s
p
ec
if
ic,
em
er
g
in
g
s
p
ec
if
ically
at
a
p
r
o
ce
d
u
r
al
co
m
p
lex
ity
th
r
esh
o
ld
.
T
h
ir
d
,
it
co
n
tr
ib
u
tes
class
r
o
o
m
-
b
ased
ev
id
en
ce
f
r
o
m
a
Mo
r
o
c
ca
n
h
ig
h
e
r
ed
u
ca
tio
n
in
s
titu
tio
n
,
wh
er
e
s
u
ch
em
p
ir
ical
r
esear
ch
r
em
ain
s
s
ca
r
ce
.
2.
M
E
T
H
O
D
T
h
is
s
ec
tio
n
d
escr
ib
es
th
e
r
esear
ch
d
esig
n
,
p
a
r
ticip
an
ts
,
teac
h
in
g
ap
p
r
o
ac
h
,
an
d
d
at
a
an
aly
s
is
p
r
o
ce
d
u
r
es
u
s
ed
in
th
e
s
tu
d
y
.
T
h
e
s
tu
d
y
ad
o
p
ted
a
q
u
asi
-
ex
p
er
im
en
tal
class
r
o
o
m
-
b
ased
d
esig
n
to
ex
am
in
e
s
tu
d
en
t
q
u
iz
p
e
r
f
o
r
m
an
ce
ac
r
o
s
s
s
ev
en
in
s
tr
u
ctio
n
al
s
ess
io
n
s
.
All
p
r
o
ce
d
u
r
es
wer
e
co
n
d
u
cted
u
n
d
er
n
o
r
m
al
teac
h
in
g
co
n
d
itio
n
s
at
I
SIT
T
i
n
T
an
g
ier
,
Mo
r
o
cc
o
.
2
.
1
.
Study
des
ig
n
T
h
is
s
tu
d
y
ad
o
p
te
d
a
q
u
asi
-
ex
p
er
im
en
tal,
class
r
o
o
m
-
b
ased
d
esig
n
co
n
d
u
cted
u
n
d
er
n
o
r
m
al
teac
h
in
g
co
n
d
itio
n
s
.
I
n
s
tr
u
ctio
n
al
co
n
d
itio
n
s
wer
e
d
eter
m
in
e
d
b
y
p
r
e
-
ex
is
tin
g
class
o
r
g
an
izatio
n
r
ath
er
th
a
n
r
a
n
d
o
m
ass
ig
n
m
en
t.
T
h
e
s
tu
d
y
was
co
n
d
u
cte
d
with
in
r
eg
u
lar
c
o
u
r
s
e
d
eliv
er
y
an
d
d
id
n
o
t
in
v
o
l
v
e
ch
an
g
es
to
th
e
in
s
titu
tio
n
al
tim
etab
le
o
r
ex
ter
n
al
ass
ess
m
en
ts
.
T
h
e
s
tu
d
y
ex
am
in
es
ass
o
ciatio
n
s
b
etwe
en
in
s
tr
u
ctio
n
al
co
n
d
itio
n
a
n
d
p
er
f
o
r
m
an
ce
r
ath
er
th
an
m
ak
in
g
ca
u
s
al
claim
s
.
T
h
e
s
tu
d
y
was
co
n
d
u
cted
o
v
e
r
s
ev
en
c
o
n
s
ec
u
tiv
e
s
ess
io
n
s
b
eg
in
n
in
g
o
n
No
v
em
b
er
21
s
t,
2
0
2
4
,
ea
ch
ad
d
r
ess
in
g
a
d
is
tin
ct
s
et
o
f
in
tr
o
d
u
cto
r
y
s
tatis
tical
co
n
ce
p
ts
an
d
c
o
n
clu
d
in
g
with
a
s
h
o
r
t
in
-
class
q
u
iz.
E
ac
h
s
ess
io
n
f
o
cu
s
ed
o
n
a
d
if
f
er
e
n
t
s
et
o
f
in
tr
o
d
u
cto
r
y
s
tatis
ti
ca
l
co
n
ce
p
ts
,
alig
n
ed
with
t
h
e
co
u
r
s
e
s
y
llab
u
s
.
Ses
s
io
n
s
f
o
l
l
o
w
e
d
a
c
o
n
s
is
te
n
t
s
t
r
u
c
t
u
r
e
:
i
n
t
r
o
d
u
c
t
i
o
n
o
f
c
o
n
c
ep
t
s
,
g
u
i
d
e
d
p
r
a
c
t
i
ce
,
a
n
d
a
n
e
n
d
-
of
-
s
e
s
s
i
o
n
q
u
iz.
2
.
2
.
P
a
rt
icipa
nts
Par
ticip
an
ts
wer
e
f
ir
s
t
-
y
ea
r
s
tu
d
en
ts
en
r
o
lled
in
a
n
in
tr
o
d
u
cto
r
y
s
tatis
tics
co
u
r
s
e
at
th
e
I
SIT
T
in
T
an
g
ier
,
Mo
r
o
cc
o
.
Stu
d
en
ts
wer
e
o
r
g
an
ized
in
to
f
iv
e
p
r
e
-
ex
is
tin
g
class
e
s
.
On
e
clas
s
w
as
d
iv
id
ed
in
to
two
s
ep
ar
ate
g
r
o
u
p
s
,
p
r
o
d
u
cin
g
s
ix
g
r
o
u
p
s
,
th
r
ee
f
o
llo
win
g
AI
-
p
e
r
m
itted
in
s
tr
u
ctio
n
a
n
d
th
r
ee
f
o
llo
win
g
AI
-
not
-
p
e
r
m
itted
in
s
tr
u
ctio
n
.
T
ab
le
1
s
u
m
m
ar
izes th
e
a
r
r
an
g
em
en
t.
T
h
e
co
n
d
itio
n
s
r
ep
r
esen
t
p
er
m
is
s
io
n
-
b
ased
lear
n
in
g
en
v
ir
o
n
m
en
ts
,
n
o
t
v
er
if
ied
AI
to
o
l
ad
o
p
tio
n
.
T
h
e
s
tu
d
y
d
id
n
o
t
m
ea
s
u
r
e
o
r
v
e
r
if
y
w
h
eth
er
in
d
iv
id
u
al
s
tu
d
en
ts
ac
tu
ally
u
s
ed
C
h
at
GPT.
An
aly
s
es
ar
e
in
ter
p
r
eted
as
ass
o
ciatio
n
s
b
etwe
en
co
n
d
itio
n
an
d
p
e
r
f
o
r
m
an
ce
.
Acr
o
s
s
s
ev
en
q
u
iz
s
ess
io
n
s
,
1
9
3
u
n
iq
u
e
s
tu
d
en
ts
s
u
b
m
itted
at
least o
n
e
q
u
iz,
y
ield
i
n
g
1
,
1
3
6
o
b
s
er
v
atio
n
s
.
T
ab
le
1
.
Stu
d
y
d
esig
n
: c
lass
an
d
g
r
o
u
p
ar
r
an
g
em
en
t
C
l
a
s
s
AI
-
p
e
r
mi
t
t
e
d
(
3
g
r
o
u
p
s)
AI
-
not
-
p
e
r
m
i
t
t
e
d
(
3
g
r
o
u
p
s)
C
l
a
s
s
1
F
u
l
l
c
l
a
ss
a
ss
i
g
n
e
d
—
C
l
a
s
s
2
F
u
l
l
c
l
a
ss
a
ss
i
g
n
e
d
—
C
l
a
s
s
3
—
F
u
l
l
c
l
a
ss
a
ss
i
g
n
e
d
C
l
a
s
s
4
—
F
u
l
l
c
l
a
ss
a
ss
i
g
n
e
d
C
l
a
s
s
5
(
sp
l
i
t
)
G
r
o
u
p
a
–
s
e
p
a
r
a
t
e
d
G
r
o
u
p
b
–
s
e
p
a
r
a
t
e
d
To
t
a
l
o
b
ser
v
a
t
i
o
n
s
5
6
3
5
7
3
N
=
1
9
3
u
n
i
q
u
e
st
u
d
e
n
t
s,
1
,
1
3
6
q
u
i
z
o
b
serv
a
t
i
o
n
s a
c
r
o
ss
se
v
e
n
s
e
ssi
o
n
s.
2
.
3
.
T
ea
ching
a
pp
ro
a
ch
a
nd
us
e
o
f
Cha
t
G
P
T
All
class
es
f
o
llo
wed
th
e
s
am
e
p
lan
n
e
d
c
o
n
ten
t,
s
lid
es,
an
d
ex
e
r
cises
.
I
n
AI
-
p
er
m
itt
ed
class
es,
s
tu
d
en
ts
co
u
ld
co
n
s
u
lt
C
h
atGPT
d
u
r
in
g
lear
n
in
g
ac
tiv
ities
o
n
ly
.
Stu
d
en
ts
wer
e
r
e
q
u
ir
ed
to
r
ewr
ite
all
ex
p
lan
atio
n
s
in
th
eir
o
wn
wo
r
d
s
.
T
h
e
in
s
tr
u
cto
r
m
o
n
i
to
r
ed
in
ter
ac
tio
n
s
an
d
co
r
r
e
cted
AI
-
g
en
er
ate
d
in
ac
cu
r
ac
ies wh
en
o
b
s
er
v
ed
.
I
n
AI
-
not
-
p
er
m
itted
class
es,
s
tu
d
en
ts
r
elied
o
n
lectu
r
e
m
ater
ia
ls
an
d
in
d
ep
en
d
en
t
r
ea
s
o
n
in
g
.
C
h
atGPT
was n
o
t a
llo
wed
d
u
r
in
g
q
u
izze
s
in
an
y
c
lass
.
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
C
h
a
tGP
T a
s
s
ca
ffo
ld
:
q
u
iz
p
erfo
r
ma
n
ce
a
cro
s
s
s
ess
io
n
co
mp
lexity
(
F
a
tima
E
z
z
a
h
r
a
K
a
b
b
a
)
3175
2
.
4
.
Q
uizzes
At
th
e
en
d
o
f
ea
ch
s
ess
io
n
,
s
tu
d
en
ts
co
m
p
leted
a
q
u
iz
alig
n
e
d
with
t
h
at
s
ess
io
n
’
s
lear
n
in
g
o
b
jectiv
es.
Sco
r
es
wer
e
r
ec
o
r
d
e
d
o
n
a
0
–
1
0
s
ca
le.
Qu
izze
s
d
if
f
er
ed
i
n
co
n
ten
t
a
n
d
co
g
n
itiv
e
d
e
m
a
n
d
s
ac
r
o
s
s
s
ess
io
n
s
.
T
h
e
m
o
d
el
in
clu
d
es
a
s
ep
ar
ate
ter
m
f
o
r
ea
ch
s
ess
io
n
,
wh
ich
co
n
tr
o
ls
f
o
r
th
e
f
ac
t
th
at
s
o
m
e
q
u
izze
s
wer
e
h
ar
d
er
t
h
an
o
t
h
er
s
.
T
h
r
ee
e
x
am
p
les
illu
s
tr
ate
th
e
r
an
g
e
.
I
n
q
u
iz
2
(
c
o
n
ce
p
tu
al)
,
s
tu
d
en
ts
d
is
tin
g
u
is
h
ed
b
etwe
en
p
o
p
u
latio
n
,
s
am
p
le
,
s
tatis
tica
l
u
n
it,
a
n
d
v
ar
iab
le,
a
task
t
h
at
p
r
o
v
ed
ch
allen
g
in
g
b
ec
a
u
s
e
m
an
y
s
tu
d
en
ts
in
ter
p
r
eted
'
p
o
p
u
latio
n
'
o
n
ly
in
th
e
ev
er
y
d
ay
s
en
s
e.
I
n
q
u
iz
4
(
p
r
o
ce
d
u
r
al
)
,
s
tu
d
en
ts
co
m
p
u
ted
ab
s
o
lu
te
an
d
r
elativ
e
f
r
eq
u
en
cies
f
r
o
m
a
r
aw
d
ataset.
I
n
q
u
iz
6
(
co
m
p
l
ex
p
r
o
ce
d
u
r
al)
,
s
tu
d
e
n
ts
ca
lcu
lated
th
e
h
ar
m
o
n
ic
m
ea
n
f
r
o
m
a
f
r
eq
u
en
cy
tab
l
e
u
s
in
g
H
=
N/Σ
(
n
_
i/x
_
i)
,
an
d
d
eter
m
in
ed
th
e
m
o
d
e
o
f
a
g
r
o
u
p
ed
c
o
n
tin
u
o
u
s
v
ar
iab
le
b
y
c
o
m
p
u
tin
g
d
en
s
ity
f
o
r
ea
c
h
class
,
id
en
tif
y
in
g
th
e
m
o
d
al
class
,
an
d
ap
p
ly
in
g
th
e
in
ter
p
o
latio
n
f
o
r
m
u
la.
T
h
e
f
u
ll
q
u
iz
6
item
s
ar
e
r
ep
o
r
ted
in
Ap
p
en
d
i
x
.
2
.
5
.
Da
t
a
a
na
ly
s
is
A
lin
ea
r
m
ix
ed
-
ef
f
ec
ts
m
o
d
el
was
u
s
ed
with
f
ix
ed
ef
f
ec
ts
f
o
r
in
s
tr
u
ctio
n
al
co
n
d
itio
n
,
s
ess
io
n
(
ca
teg
o
r
ical)
,
a
n
d
th
eir
i
n
ter
a
ctio
n
,
an
d
a
r
an
d
o
m
in
ter
ce
p
t
f
o
r
s
tu
d
en
t
I
D
.
T
h
e
m
o
d
el
is
s
p
ec
if
ied
in
(
1
)
.
A
lin
ea
r
m
ix
ed
-
ef
f
ec
ts
m
o
d
el
was
ch
o
s
en
b
ec
au
s
e
s
tu
d
en
ts
co
n
tr
ib
u
ted
b
etwe
en
o
n
e
a
n
d
s
ev
en
o
b
s
er
v
atio
n
s
d
ep
en
d
i
n
g
o
n
atten
d
a
n
ce
,
p
r
o
d
u
cin
g
a
n
u
n
b
alan
ce
d
r
ep
ea
te
d
-
m
ea
s
u
r
es
s
tr
u
ctu
r
e
[
2
0
]
.
T
h
is
m
o
d
el
ac
co
u
n
ts
f
o
r
in
d
iv
id
u
al
d
if
f
er
e
n
ce
s
th
r
o
u
g
h
a
r
an
d
o
m
in
ter
ce
p
t
an
d
d
o
es
n
o
t
r
eq
u
ir
e
eq
u
al
n
u
m
b
er
s
o
f
o
b
s
er
v
atio
n
s
p
er
s
tu
d
en
t.
T
h
is
ap
p
r
o
ac
h
was
p
r
ef
er
r
ed
o
v
er
r
ep
ea
ted
-
m
e
asu
r
es
a
n
aly
s
is
o
f
v
ar
ian
ce
(
ANOVA
)
b
ec
au
s
e
ANOV
A
r
eq
u
ir
es
co
m
p
lete
d
ata
f
o
r
all
s
ess
io
n
s
f
r
o
m
ea
ch
s
tu
d
en
t,
wh
ich
was
n
o
t
a
v
ail
ab
le
d
u
e
to
n
atu
r
al
atten
d
an
ce
v
ar
iatio
n
.
T
h
e
m
i
x
ed
-
ef
f
ec
ts
m
o
d
el
u
s
es
all
av
ailab
le
o
b
s
er
v
atio
n
s
with
o
u
t
ex
clu
d
in
g
s
tu
d
en
ts
wh
o
m
is
s
ed
o
n
e
o
r
m
o
r
e
s
ess
i
o
n
s
.
=
0
+
1
(
)
+
2
(
)
+
3
(
×
)
+
_
+
_
(
1
)
Her
e,
_
d
en
o
tes
th
e
r
an
d
o
m
in
ter
ce
p
t
f
o
r
s
tu
d
en
t
,
an
d
_
is
t
h
e
r
esid
u
al
er
r
o
r
f
o
r
o
b
s
er
v
at
io
n
j
with
in
s
tu
d
en
t i.
W
e
u
s
ed
Py
th
o
n
(
An
ac
o
n
d
a
)
with
th
e
s
tats
m
o
d
els
l
ib
r
ar
y
an
d
r
estricte
d
m
ax
im
u
m
lik
elih
o
o
d
(
R
E
ML
)
esti
m
atio
n
.
T
h
e
in
tr
ac
lass
co
r
r
elatio
n
co
ef
f
icien
t
(
I
C
C
)
f
r
o
m
th
e
u
n
co
n
d
itio
n
al
m
o
d
el
was
0
.
0
3
4
,
in
d
icatin
g
th
at
ap
p
r
o
x
im
ately
3
%
o
f
th
e
to
tal
v
ar
ian
ce
in
q
u
iz
s
co
r
es
was
at
tr
ib
u
tab
le
to
s
tab
le
d
if
f
er
en
ce
s
b
etwe
en
s
tu
d
en
ts
.
T
h
e
r
em
ain
in
g
9
7
%
r
ef
lecte
d
with
in
-
s
t
u
d
en
t
v
ar
iatio
n
ac
r
o
s
s
s
es
s
io
n
s
.
T
h
e
m
u
ltil
ev
el
s
tr
u
ctu
r
e
is
war
r
an
ted
to
ac
co
u
n
t f
o
r
r
ep
ea
ted
o
b
s
er
v
atio
n
s
w
ith
in
s
tu
d
en
ts
.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
is
s
ec
tio
n
p
r
esen
ts
th
e
d
esc
r
ip
tiv
e
s
tatis
tic
s
,
m
o
d
el
esti
m
ates,
an
d
s
ess
io
n
-
lev
el
f
in
d
in
g
s
f
r
o
m
th
e
lin
ea
r
m
i
x
e
d
-
e
f
f
e
c
t
s
a
n
a
l
y
s
i
s
.
R
es
u
l
ts
a
r
e
o
r
g
a
n
i
z
e
d
f
r
o
m
o
v
e
r
a
l
l
g
r
o
u
p
-
l
e
v
e
l
p
a
t
t
e
r
n
s
t
o
s
p
ec
i
f
i
c
s
e
s
s
i
o
n
ef
f
ec
ts
,
with
a
f
o
cu
s
o
n
t
h
e
in
te
r
ac
tio
n
b
etwe
en
in
s
tr
u
ctio
n
al
c
o
n
d
itio
n
an
d
s
ess
io
n
c
o
m
p
lex
it
y
.
T
h
e
d
is
cu
s
s
io
n
in
teg
r
ates th
ese
f
in
d
in
g
s
with
ex
is
tin
g
liter
atu
r
e
an
d
ad
d
r
ess
es th
eir
p
r
ac
tical
an
d
t
h
eo
r
etic
al
im
p
licatio
n
s
.
3
.
1
.
Descript
iv
e
o
v
e
rv
iew
T
ab
le
2
p
r
esen
ts
th
e
d
escr
ip
ti
v
e
s
tatis
tics
f
o
r
b
o
th
g
r
o
u
p
s
,
i
n
clu
d
in
g
s
am
p
le
s
ize,
m
ea
n
q
u
iz
s
co
r
e,
an
d
s
tan
d
ar
d
d
ev
iatio
n
(
SD)
.
T
h
e
two
g
r
o
u
p
s
s
h
o
wed
s
im
ilar
o
v
er
all
p
e
r
f
o
r
m
an
ce
wh
en
s
co
r
es
wer
e
co
m
b
in
ed
ac
r
o
s
s
all
s
ev
en
s
e
s
s
io
n
s
.
T
h
ese
ag
g
r
eg
ate
f
ig
u
r
es
p
r
o
v
id
e
a
b
aselin
e
b
ef
o
r
e
ex
am
in
in
g
s
ess
io
n
-
lev
el
v
ar
iatio
n
in
s
u
b
s
eq
u
en
t s
u
b
s
ec
tio
n
s
.
T
h
e
two
g
r
o
u
p
s
h
ad
s
im
ilar
m
ea
n
s
co
r
es
(
7
.
3
0
v
s
.
7
.
0
6
)
a
n
d
s
im
ilar
v
ar
iab
ilit
y
(
SD
=
2
.
3
9
v
s
.
2
.
2
9
)
wh
en
p
er
f
o
r
m
an
ce
was
co
m
b
i
n
ed
ac
r
o
s
s
all
s
e
s
s
io
n
s
.
T
h
ese
ag
g
r
eg
ate
av
er
a
g
es
m
ay
m
ask
im
p
o
r
tan
t
s
ess
io
n
-
lev
el
v
ar
iatio
n
,
wh
ich
is
ex
am
in
ed
in
th
e
f
o
llo
win
g
s
ec
tio
n
s
.
T
h
e
co
m
p
a
r
ab
le
g
r
o
u
p
-
l
ev
el
s
tatis
t
ics
al
s
o
in
d
icate
th
at
an
y
o
b
s
er
v
ed
d
if
f
er
en
ce
s
ar
e
u
n
lik
ely
to
r
esu
lt
f
r
o
m
a
g
e
n
er
al
p
er
f
o
r
m
a
n
ce
g
a
p
b
etwe
en
th
e
two
g
r
o
u
p
s
.
T
ab
le
2
.
Descr
ip
tiv
e
s
tatis
tics
b
y
in
s
tr
u
ctio
n
al
g
r
o
u
p
(
N
=
1
,
1
3
6
)
G
r
o
u
p
n
M
e
a
n
SD
C
h
a
t
G
P
T
-
p
e
r
mi
t
t
e
d
5
6
3
7
.
3
0
2
.
3
9
N
o
C
h
a
t
G
P
T
5
7
3
7
.
0
6
2
.
2
9
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
15
,
No
.
4
,
Au
g
u
s
t
20
26
:
3
1
7
2
-
3
1
8
1
3176
3
.
2
.
O
v
er
a
ll e
f
f
ec
t
s
A
jo
in
t
W
ald
test
(
wh
ich
ev
al
u
ates
wh
eth
er
a
s
et
o
f
m
o
d
el
c
o
ef
f
icien
ts
is
s
ig
n
if
ican
tly
d
if
f
er
en
t
f
r
o
m
ze
r
o
)
s
h
o
wed
n
o
s
ig
n
if
ica
n
t
o
v
er
all
ef
f
ec
t
o
f
in
s
tr
u
cti
o
n
al
g
r
o
u
p
(
χ²(
1
)
=
1
.
0
7
,
p
=0
.
3
0
1
)
.
Ho
wev
e
r
,
th
e
in
ter
ac
tio
n
b
etwe
en
g
r
o
u
p
an
d
s
ess
io
n
was
s
tatis
tically
s
ig
n
if
ican
t
(
χ²(
6
)
=
6
1
.
5
0
,
p
<0
.
0
0
1
)
,
i
n
d
icatin
g
t
h
at
th
e
ass
o
ciatio
n
was n
o
t th
e
s
am
e
in
ev
er
y
s
ess
io
n
.
T
ab
le
3
r
ep
o
r
ts
th
e
f
ix
e
d
-
ef
f
ec
ts
esti
m
ates.
T
ab
le
3
.
Fix
ed
-
ef
f
ec
ts
esti
m
ates f
r
o
m
th
e
lin
ea
r
m
ix
ed
-
ef
f
ec
ts
m
o
d
el
Ef
f
e
c
t
Est
i
m
a
t
e
SE
z
p
I
n
t
e
r
c
e
p
t
4
.
7
1
0
.
1
9
2
5
.
0
6
<
0
.
0
0
1
G
r
o
u
p
(
C
h
a
t
G
P
T)
0
.
2
7
0
.
2
6
1
.
0
4
0
.
3
0
1
S
e
ssi
o
n
(
o
v
e
r
a
l
l
)
—
—
—
<
0
.
0
0
1
G
r
o
u
p
×
S
e
ss
i
o
n
—
—
—
<
0
.
0
0
1
3
.
3
.
Ses
s
io
n
-
lev
el
re
s
ults
T
a
b
le
4
p
r
ese
n
ts
t
h
e
m
ea
n
q
u
i
z
s
c
o
r
es,
s
am
p
l
e
s
iz
es,
an
d
C
o
h
e
n
’
s
d
ef
f
e
ct
s
i
ze
s
f
o
r
ea
c
h
g
r
o
u
p
ac
r
o
s
s
all
s
e
v
e
n
s
ess
i
o
n
s
.
T
h
es
e
r
es
u
l
ts
al
l
o
w
d
i
r
e
ct
c
o
m
p
ar
is
o
n
o
f
b
o
t
h
a
g
g
r
e
g
a
te
a
n
d
s
ess
io
n
-
s
p
ec
i
f
ic
p
e
r
f
o
r
m
a
n
c
e
p
atter
n
s
b
etwe
en
co
n
d
itio
n
s
.
F
ig
u
r
e
2
v
is
u
alize
s
th
e
s
co
r
e
tr
a
jecto
r
ies f
o
r
b
o
th
g
r
o
u
p
s
ac
r
o
s
s
s
es
s
io
n
s
.
T
ab
le
4
.
Me
an
q
u
iz
s
co
r
es,
s
a
m
p
le
s
izes,
an
d
ef
f
ec
t sizes b
y
s
ess
io
n
S
To
p
i
c
n
(
A
I
)
M
(
A
I
)
n
(
N
o
)
M
(
N
o
)
d
Ty
p
e
1
D
e
scri
p
t
i
v
e
v
s.
i
n
f
e
r
e
n
t
i
a
l
81
4
.
9
9
80
4
.
7
5
+
0
.
1
8
C
o
n
c
e
p
t
u
a
l
2
S
t
a
t
i
st
i
c
a
l
v
o
c
a
b
u
l
a
r
y
78
7
.
6
2
81
7
.
6
8
−
0
.
0
3
C
o
n
c
e
p
t
u
a
l
3
V
a
r
i
a
b
l
e
t
y
p
e
s
83
8
.
3
1
86
8
.
4
2
−
0
.
0
5
C
o
n
c
e
p
t
u
a
l
4
F
r
e
q
u
e
n
c
i
e
s
80
9
.
6
5
85
9
.
4
8
+
0
.
1
9
P
r
o
c
e
d
u
r
a
l
5
A
r
i
t
h
m
e
t
i
c
/
g
e
o
met
r
i
c
mea
n
s
81
5
.
2
3
83
5
.
5
9
−
0
.
2
0
P
r
o
c
e
d
u
r
a
l
6
H
a
r
mo
n
i
c
me
a
n
a
n
d
m
o
d
e
78
9
.
1
5
83
7
.
1
8
+
1
.
2
4
C
o
m
p
l
e
x
p
r
o
c
e
d
u
r
a
l
7
G
r
a
p
h
s
a
n
d
me
d
i
a
n
82
6
.
2
7
75
6
.
0
5
+
0
.
1
2
A
p
p
l
i
c
a
t
i
o
n
d
=
C
o
h
e
n
’
s
d
(
p
o
s
i
t
i
v
e
=
A
I
g
r
o
u
p
h
i
g
h
e
r
)
.
C
l
a
ss
i
f
i
c
a
t
i
o
n
f
o
l
l
o
w
s
[
1
4
]
.
Fig
u
r
e
2
.
Me
an
q
u
iz
s
co
r
es a
c
r
o
s
s
s
ev
en
s
ess
io
n
s
f
o
r
b
o
th
g
r
o
u
p
s
.
T
h
e
two
lin
es o
v
er
la
p
cl
o
s
ely
in
s
ess
io
n
s
1
–
5
an
d
7
,
d
iv
er
g
in
g
o
n
ly
in
s
ess
io
n
6
3
.
4
.
Ses
s
io
n 6
div
er
g
ence
T
h
e
lar
g
est
d
if
f
er
e
n
ce
was
in
s
ess
io
n
6
:
th
e
AI
-
p
er
m
itted
g
r
o
u
p
s
co
r
e
d
9
.
1
5
co
m
p
ar
ed
with
7
.
1
8
(β
=
1
.
6
7
,
s
tan
d
ar
d
er
r
o
r
(
SE
)
=
0
.
3
4
,
z
=
4
.
8
9
,
p
<
0
.
0
0
1
)
.
T
h
e
s
tan
d
ar
d
ized
ef
f
ec
t
s
ize
was
d
=
1
.
2
4
,
ca
lcu
lated
as
th
e
r
aw
m
ea
n
d
i
f
f
er
en
ce
(
1
.
9
7
)
d
iv
id
e
d
b
y
th
e
p
o
o
led
with
in
-
s
ess
io
n
SD
(
1
.
5
9
)
.
Fo
llo
wi
n
g
C
o
h
en
[
2
1
]
,
th
is
r
ep
r
esen
ts
a
lar
g
e
ef
f
ec
t.
T
h
is
ef
f
ec
t
em
er
g
e
d
in
o
n
ly
o
n
e
o
f
s
ev
en
s
ess
io
n
s
;
ac
r
o
s
s
th
e
r
em
ain
in
g
s
ix
,
ef
f
ec
t
s
izes r
an
g
ed
f
r
o
m
d
=
−0
.
2
0
t
o
d
=
+0
.
1
9
.
Fig
u
r
e
3
s
h
o
ws th
e
e
f
f
ec
t sizes f
o
r
all
s
ess
io
n
s
.
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
C
h
a
tGP
T a
s
s
ca
ffo
ld
:
q
u
iz
p
erfo
r
ma
n
ce
a
cro
s
s
s
ess
io
n
co
mp
lexity
(
F
a
tima
E
z
z
a
h
r
a
K
a
b
b
a
)
3177
Ses
s
io
n
6
r
ep
r
esen
ts
th
e
h
ig
h
e
s
t
lev
el
o
f
p
r
o
ce
d
u
r
al
d
em
an
d
in
th
e
co
u
r
s
e.
Stu
d
en
ts
h
ad
to
s
elec
t
th
e
co
r
r
ec
t
f
o
r
m
u
la
,
co
m
p
u
te
d
e
n
s
ity
f
o
r
ea
ch
class
,
id
en
tif
y
th
e
m
o
d
al
class
,
an
d
a
p
p
l
y
an
in
ter
p
o
latio
n
p
r
o
ce
d
u
r
e.
T
h
e
h
i
g
h
er
s
co
r
es
ap
p
ea
r
ed
at
th
is
m
o
m
e
n
t
o
f
ac
cu
m
u
lated
p
r
o
ce
d
u
r
al
c
o
m
p
le
x
ity
,
n
o
t
u
n
if
o
r
m
ly
ac
r
o
s
s
th
e
co
u
r
s
e
.
Fig
u
r
e
3
.
C
o
h
e
n
’
s
d
ef
f
ec
t sizes b
y
s
ess
io
n
.
Dash
ed
lin
e
=
lar
g
e
-
ef
f
ec
t th
r
esh
o
l
d
(
0
.
8
0
)
3
.
5
.
Dis
cus
s
io
n
I
n
s
tr
u
ctio
n
al
co
n
d
itio
n
s
wer
e
p
er
m
is
s
io
n
-
b
ased
an
d
n
o
t
ex
p
er
im
en
tally
co
n
tr
o
lled
.
All
f
in
d
in
g
s
ar
e
th
er
ef
o
r
e
in
ter
p
r
eted
as
co
n
d
itio
n
al
ass
o
ciatio
n
s
r
ath
er
th
an
ca
u
s
al
ef
f
ec
ts
.
T
h
e
f
o
llo
win
g
d
is
cu
s
s
io
n
co
n
s
id
er
s
wh
at
th
e
o
b
s
er
v
ed
p
atter
n
s
s
u
g
g
est,
wh
ile
ac
k
n
o
wled
g
in
g
th
e
d
esig
n
lim
itatio
n
s
in
h
er
en
t
to
th
is
class
r
o
o
m
-
b
ased
s
tu
d
y
.
T
h
e
f
ir
s
t
f
iv
e
s
ess
io
n
s
f
o
cu
s
ed
o
n
f
o
u
n
d
ati
o
n
al
co
n
ce
p
ts
an
d
b
o
th
g
r
o
u
p
s
p
er
f
o
r
m
ed
s
im
ilar
ly
.
I
n
s
ess
io
n
6
,
s
tu
d
en
ts
f
ac
e
d
m
u
lti
-
s
tep
co
m
p
u
tatio
n
,
i
d
en
tify
in
g
a
m
o
d
al
class
b
ased
o
n
d
e
n
s
ity
,
ap
p
ly
i
n
g
a
n
in
ter
p
o
latio
n
f
o
r
m
u
la,
an
d
s
eq
u
en
cin
g
s
ev
er
al
co
m
p
u
tatio
n
a
l
s
tep
s
.
Un
d
er
th
ese
co
n
d
itio
n
s
,
th
e
AI
-
p
er
m
itted
g
r
o
u
p
s
co
r
ed
n
o
ta
b
ly
h
ig
h
e
r
(
d
=
1
.
2
4
)
.
T
h
is
f
in
d
in
g
is
co
n
s
is
ten
t
with
Aln
ey
ad
i
an
d
W
ar
d
at
[
2
2
]
,
wh
o
r
ep
o
r
ted
p
o
s
itiv
e
ef
f
ec
ts
o
f
C
h
atGPT
o
n
s
tu
d
en
t
ac
h
iev
e
m
en
t
in
a
p
r
o
ce
d
u
r
ally
d
em
a
n
d
in
g
s
cien
ce
u
n
it.
A
r
ec
en
t
q
u
asi
-
ex
p
e
r
im
en
tal
s
tu
d
y
i
n
a
to
u
r
is
m
s
tatis
tic
s
co
u
r
s
e
s
im
ilar
ly
f
o
u
n
d
th
at
C
h
atGPT
’
s
ass
o
ciatio
n
with
p
er
f
o
r
m
an
ce
d
e
p
en
d
s
o
n
th
e
s
p
ec
if
ic
task
co
n
tex
t [
2
3
]
.
T
h
e
s
co
r
e
d
r
o
p
-
in
s
ess
io
n
5
p
r
o
v
id
es
im
p
o
r
tan
t
co
n
tex
t.
B
o
t
h
g
r
o
u
p
s
ex
p
e
r
ien
ce
d
a
s
co
r
e
d
r
o
p
wh
en
th
e
co
u
r
s
e
s
h
if
ted
f
r
o
m
d
e
f
in
itio
n
al
co
n
ten
t
to
f
o
r
m
u
la
-
d
r
iv
e
n
co
m
p
u
tatio
n
.
Yet
t
h
e
g
r
o
u
p
s
d
id
n
o
t
d
iv
e
r
g
e
in
s
ess
io
n
5
,
th
e
d
iv
er
g
en
ce
ca
m
e
o
n
ly
in
s
ess
io
n
6
.
I
n
o
th
er
wo
r
d
s
,
C
h
atGPT
m
ay
n
o
t
h
elp
wh
en
s
tu
d
en
ts
f
ir
s
t
en
co
u
n
ter
f
o
r
m
u
las,
b
u
t
it
m
ay
s
tar
t
to
m
atter
wh
en
th
e
f
o
r
m
u
las
b
ec
o
m
e
to
o
c
o
m
p
lex
to
h
an
d
le
with
o
u
t
s
u
p
p
o
r
t.
I
n
c
o
n
tr
ast,
Yan
g
et
a
l
.
[
2
4
]
f
o
u
n
d
th
at
u
n
s
u
p
er
v
is
ed
C
h
atGPT
u
s
e
d
ec
r
ea
s
ed
s
elf
-
ef
f
icac
y
an
d
ac
h
iev
em
en
t
in
p
r
o
g
r
am
m
i
n
g
.
T
h
e
d
if
f
er
en
ce
m
ay
b
e
ex
p
la
in
ed
b
y
th
e
lev
el
o
f
in
s
tr
u
ct
o
r
o
v
er
s
ig
h
t:
in
th
eir
s
tu
d
y
,
s
tu
d
en
ts
u
s
ed
AI
in
d
ep
en
d
en
tly
,
wh
e
r
ea
s
in
th
e
p
r
esen
t
s
tu
d
y
,
u
s
e
was
m
o
n
ito
r
ed
an
d
s
tu
d
en
ts
wer
e
r
eq
u
ir
ed
to
r
ef
o
r
m
u
late
AI
r
esp
o
n
s
es in
th
eir
o
w
n
wo
r
d
s
.
Xin
g
[
2
5
]
s
h
o
we
d
th
at
C
h
atG
PT
p
er
f
o
r
m
s
well
o
n
c
o
n
ce
p
t
u
al
q
u
esti
o
n
s
.
Oth
er
s
tu
d
ies
h
a
v
e
r
ep
o
r
ted
p
o
s
itiv
e
ef
f
ec
ts
in
s
p
ec
if
ic
s
u
b
ject
ar
ea
s
,
in
clu
d
in
g
r
em
o
te
le
ar
n
in
g
in
m
ed
ical
e
d
u
ca
tio
n
[
2
6
]
an
d
k
n
o
wled
g
e
g
ain
s
in
m
u
s
ic
ed
u
ca
tio
n
[
2
7
]
.
Ou
r
s
tu
d
y
g
o
es
f
u
r
th
er
b
y
s
h
o
win
g
th
at
th
e
ass
o
ciatio
n
b
et
wee
n
AI
ac
ce
s
s
an
d
s
tu
d
en
t
p
er
f
o
r
m
an
ce
a
p
p
ea
r
s
s
p
ec
if
ically
d
u
r
in
g
p
r
o
ce
d
u
r
al
s
ess
io
n
s
,
n
o
t
d
u
r
in
g
c
o
n
ce
p
tu
al
o
n
es.
T
h
e
co
n
ce
r
n
s
ab
o
u
t A
I
b
y
p
ass
in
g
s
tan
d
ar
d
p
r
o
ce
d
u
r
es [
2
8
]
r
em
ai
n
r
elev
an
t,
i
n
th
is
s
tu
d
y
,
in
s
tr
u
cto
r
o
v
er
s
ig
h
t m
a
y
h
av
e
lim
ited
th
is
r
is
k
.
T
h
e
b
r
o
ad
er
liter
atu
r
e
s
u
g
g
ests
th
at
s
tr
u
ctu
r
ed
AI
u
s
e
is
m
o
r
e
lik
ely
t
o
s
u
p
p
o
r
t
lear
n
in
g
th
an
u
n
r
estricte
d
ac
ce
s
s
[
2
9
]
,
[
3
0
]
.
T
h
e
s
ess
io
n
-
s
p
ec
if
ic
p
a
tter
n
m
ay
also
b
e
u
n
d
e
r
s
to
o
d
th
r
o
u
g
h
co
g
n
itiv
e
lo
ad
th
eo
r
y
,
wh
ich
d
escr
ib
es
h
o
w
th
e
m
en
tal
ef
f
o
r
t
r
e
q
u
ir
e
d
b
y
a
task
af
f
ec
ts
lear
n
in
g
[
3
1
]
.
Ses
s
io
n
s
1
–
3
r
eq
u
ir
ed
s
tu
d
e
n
ts
to
r
em
em
b
er
d
ef
in
itio
n
s
an
d
class
if
y
co
n
ce
p
ts
,
task
s
th
at
d
o
n
o
t
d
em
an
d
m
u
ch
m
e
n
tal
ef
f
o
r
t.
Ses
s
io
n
6
r
e
q
u
ir
ed
m
u
l
ti
-
s
tep
co
m
p
u
tatio
n
with
s
ev
er
al
f
o
r
m
u
las
ap
p
lied
in
s
eq
u
e
n
ce
,
a
task
with
h
ig
h
m
en
tal
ef
f
o
r
t,
wh
e
r
e
C
h
atGPT
m
ay
h
av
e
h
el
p
ed
b
y
b
r
ea
k
i
n
g
th
e
p
r
o
b
lem
in
to
s
m
aller
s
tep
s
[
3
2
]
.
Ho
wev
e
r
,
co
n
s
tan
t
AI
av
ailab
ilit
y
also
r
aises
co
n
ce
r
n
s
.
Stu
d
en
ts
m
ay
s
to
p
tr
y
in
g
to
s
o
lv
e
p
r
o
b
lem
s
o
n
th
eir
o
wn
if
AI
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
15
,
No
.
4
,
Au
g
u
s
t
20
26
:
3
1
7
2
-
3
1
8
1
3178
alwa
y
s
g
iv
es
th
em
th
e
a
n
s
wer
[
1
9
]
.
I
n
th
is
s
tu
d
y
,
C
h
atGPT
ac
ce
s
s
d
id
n
o
t
im
p
r
o
v
e
s
co
r
es
in
s
ess
io
n
s
1
–
3
,
wh
ich
m
ea
n
s
s
tu
d
en
ts
d
i
d
n
o
t
b
ec
o
m
e
d
e
p
en
d
e
n
t
o
n
AI
f
o
r
task
s
th
ey
co
u
ld
h
an
d
le
alo
n
e.
A
r
ec
en
t
m
eta
-
an
aly
s
is
co
n
f
ir
m
s
th
at
C
h
atGPT
’
s
im
p
ac
t
o
n
ac
a
d
em
ic
ac
h
i
ev
em
en
t
is
n
o
t
u
n
if
o
r
m
b
u
t
v
a
r
ies
b
y
co
u
r
s
e
ty
p
e
an
d
d
u
r
atio
n
[
3
3
]
.
T
h
ese
r
esu
lts
ch
allen
g
e
th
e
ass
u
m
p
tio
n
th
at
AI
p
r
o
d
u
ce
s
u
n
iv
er
s
al
b
e
n
ef
its
in
ed
u
ca
tio
n
.
T
h
e
p
r
esen
t stu
d
y
ad
d
s
th
at
e
v
en
with
in
a
s
in
g
le
co
u
r
s
e,
th
e
ass
o
ciatio
n
v
ar
ies b
y
s
ess
io
n
.
Fo
r
s
tat
is
ti
cs
i
n
s
tr
u
ct
o
r
s
,
t
h
e
a
p
p
r
o
ac
h
u
s
e
d
i
n
t
h
is
s
t
u
d
y
o
f
f
e
r
s
a
co
n
cr
ete
m
o
d
el:
ex
p
l
ai
n
t
h
e
p
r
o
ce
d
u
r
e
w
it
h
o
u
t
A
I
,
all
o
w
C
h
atGP
T
d
u
r
i
n
g
p
r
ac
t
ic
e
f
o
r
s
te
p
v
er
if
i
ca
ti
o
n
,
r
eq
u
i
r
e
r
e
f
o
r
m
u
lat
io
n
i
n
th
e
s
tu
d
e
n
t
’
s
o
w
n
wo
r
d
s
,
a
n
d
p
r
o
h
ib
i
t A
I
d
u
r
i
n
g
t
h
e
q
u
i
z.
T
h
is
s
e
q
u
e
n
c
e
w
as
ass
o
cia
te
d
wit
h
s
tr
o
n
g
er
p
e
r
f
o
r
m
an
ce
at
th
e
p
o
i
n
t
o
f
h
ig
h
est
p
r
o
ce
d
u
r
al
d
e
m
a
n
d
.
I
t s
h
o
u
l
d
b
e
t
r
e
ate
d
as
a
p
r
el
im
in
ar
y
s
te
p
,
n
o
t
a
v
er
i
f
i
ed
m
et
h
o
d
.
W
h
en
all
s
ev
en
s
ess
io
n
s
wer
e
co
n
s
id
er
ed
to
g
eth
er
,
n
o
co
n
s
is
ten
t
ad
v
an
tag
e
was
ass
o
ciate
d
with
AI
av
ailab
ilit
y
.
T
h
e
ef
f
ec
t
was
l
im
ited
to
s
ess
io
n
6
.
Fo
r
s
ess
io
n
s
f
o
cu
s
ed
o
n
d
ef
i
n
itio
n
s
a
n
d
class
if
icatio
n
s
,
teac
h
er
-
led
in
s
tr
u
ctio
n
with
o
u
t
AI
ap
p
ea
r
e
d
eq
u
ally
ef
f
ec
tiv
e
.
AI
in
teg
r
atio
n
s
h
o
u
ld
b
e
s
ele
ctiv
e,
n
o
t u
n
if
o
r
m
.
3
.
6
.
L
im
it
a
t
io
ns
a
nd
f
uture
re
s
ea
rc
h
Sev
er
al
d
esig
n
f
ea
tu
r
es lim
it th
e
co
n
clu
s
io
n
s
.
First,
th
e
g
r
o
u
p
s
r
ef
lecte
d
p
er
m
is
s
io
n
-
b
ased
co
n
d
itio
n
s
r
ath
er
th
a
n
v
er
if
ied
AI
u
s
e
—
th
e
s
tu
d
y
d
id
n
o
t
co
llect
p
r
o
m
p
t
lo
g
s
o
r
s
cr
ee
n
r
ec
o
r
d
in
g
s
t
o
co
n
f
ir
m
wh
eth
er
s
tu
d
en
ts
ac
tu
ally
u
s
ed
C
h
atGPT
o
r
h
o
w
o
f
ten
.
Seco
n
d
,
th
e
s
p
lit
-
class
ar
r
an
g
em
en
t
in
o
n
e
class
m
ea
n
s
s
o
m
e
in
f
o
r
m
al
cr
o
s
s
-
co
n
d
itio
n
in
ter
ac
tio
n
ca
n
n
o
t
b
e
f
u
lly
ex
clu
d
ed
,
th
o
u
g
h
an
y
c
o
n
tam
in
atio
n
wo
u
ld
b
e
ex
p
ec
te
d
to
r
ed
u
ce
r
ath
er
th
a
n
in
f
lat
e
o
b
s
er
v
ed
d
if
f
er
e
n
ce
s
.
T
h
i
r
d
,
th
e
f
r
ee
ly
av
ailab
le
v
er
s
io
n
o
f
C
h
atGPT
o
cc
asio
n
ally
p
r
o
d
u
ce
d
i
n
ac
cu
r
ate
ex
p
lan
atio
n
s
th
at
r
eq
u
ir
e
d
in
s
tr
u
cto
r
co
r
r
ec
tio
n
,
wh
ich
r
ef
lects
r
ea
l
-
wo
r
ld
co
n
s
tr
ain
ts
b
u
t
i
n
tr
o
d
u
ce
s
v
ar
i
atio
n
th
at
was
n
o
t
s
y
s
tem
atica
lly
r
ec
o
r
d
ed
.
Fo
u
r
th
,
th
e
s
tu
d
y
was
co
n
d
u
cted
at
a
s
in
g
le
in
s
titu
tio
n
in
Mo
r
o
cc
o
with
a
s
p
ec
if
ic
cu
r
r
icu
lu
m
,
a
s
in
g
le
in
s
tr
u
cto
r
,
an
d
f
ir
s
t
-
y
e
ar
s
tu
d
en
ts
,
lim
itin
g
g
en
er
aliza
b
ilit
y
to
o
th
er
in
s
titu
tio
n
s
,
d
is
cip
lin
es,
o
r
s
tu
d
en
t
p
o
p
u
latio
n
s
.
Fu
tu
r
e
r
esear
ch
s
h
o
u
ld
in
clu
d
e
d
ir
ec
t
m
ea
s
u
r
es
o
f
AI
in
ter
ac
tio
n
s
u
ch
as
p
r
o
m
p
t
lo
g
s
co
llected
with
s
tu
d
en
t
c
o
n
s
en
t,
a
n
d
s
h
o
u
ld
u
s
e
ex
ter
n
al
ex
p
er
ts
to
r
ate
s
ess
io
n
co
m
p
le
x
ity
in
d
ep
e
n
d
en
tly
.
4.
CO
NCLU
SI
O
N
T
h
is
s
tu
d
y
ex
am
in
e
d
th
e
ass
o
ciatio
n
b
etwe
en
C
h
atGPT
ac
ce
s
s
an
d
s
tu
d
en
t
q
u
iz
p
er
f
o
r
m
a
n
ce
ac
r
o
s
s
s
ev
en
s
ess
io
n
s
in
an
in
t
r
o
d
u
cto
r
y
s
tatis
tics
co
u
r
s
e
at
th
e
I
SI
T
T
in
T
a
n
g
ier
,
Mo
r
o
cc
o
.
A
s
ig
n
if
ican
t
in
te
r
ac
tio
n
b
etwe
en
g
r
o
u
p
a
n
d
s
ess
io
n
was
id
en
tifie
d
,
in
d
icatin
g
th
a
t
th
e
ass
o
ciatio
n
was
s
ess
io
n
-
s
p
ec
if
ic
r
ath
er
th
a
n
u
n
if
o
r
m
.
I
t
co
n
tr
i
b
u
tes
class
r
o
o
m
-
b
ased
lo
n
g
itu
d
in
al
ev
i
d
en
ce
f
r
o
m
a
Mo
r
o
cc
an
h
i
g
h
er
ed
u
ca
tio
n
in
s
titu
tio
n
,
a
co
n
tex
t w
h
er
e
s
u
ch
em
p
ir
ical
r
esear
ch
r
em
ain
s
s
ca
r
ce
.
T
h
e
clea
r
est
p
atter
n
e
m
er
g
e
d
in
s
ess
io
n
6
,
w
h
er
e
s
tu
d
en
ts
with
C
h
atGPT
ac
ce
s
s
s
co
r
ed
h
ig
h
e
r
o
n
a
p
r
o
ce
d
u
r
ally
co
m
p
lex
q
u
iz
(
d
=
1
.
2
4
)
.
Six
o
u
t
o
f
s
ev
en
s
ess
io
n
s
s
h
o
wed
n
o
m
ea
n
in
g
f
u
l
b
etwe
en
-
g
r
o
u
p
d
if
f
er
en
ce
.
T
h
e
f
in
d
in
g
is
in
ter
p
r
eted
as
a
co
n
d
itio
n
al
ass
o
ciatio
n
at
a
p
o
in
t
o
f
ac
cu
m
u
lated
p
r
o
ce
d
u
r
al
d
em
an
d
,
n
o
t a
s
ev
id
e
n
ce
o
f
a
g
en
er
al
AI
a
d
v
an
tag
e
.
T
h
ese
f
in
d
in
g
s
s
u
g
g
est th
at
th
e
r
elatio
n
s
h
ip
b
etwe
en
AI
ac
ce
s
s
an
d
s
tu
d
en
t p
er
f
o
r
m
a
n
ce
m
ay
d
ep
en
d
o
n
wh
e
n
AI
is
m
ad
e
a
v
ailab
l
e
an
d
wh
at
k
i
n
d
o
f
task
s
tu
d
e
n
ts
f
ac
e.
Fo
r
co
u
r
s
e
d
esig
n
,
t
h
ese
r
esu
lts
s
u
g
g
est
th
at
teac
h
er
s
co
u
ld
id
en
tify
wh
ich
s
ess
io
n
s
in
v
o
lv
e
th
e
h
ig
h
est
p
r
o
ce
d
u
r
al
d
em
an
d
s
an
d
p
lan
AI
ac
ce
s
s
s
p
ec
if
ically
f
o
r
th
o
s
e
s
ess
io
n
s
,
wh
ile
m
ain
tain
in
g
tr
a
d
itio
n
al
in
s
tr
u
ctio
n
f
o
r
co
n
ce
p
tu
al
co
n
t
en
t.
T
h
is
ap
p
r
o
ac
h
tr
ea
ts
AI
as
a
tar
g
eted
s
u
p
p
o
r
t
to
o
l,
n
o
t
a
p
er
m
a
n
en
t
f
ea
tu
r
e
o
f
ev
er
y
s
ess
io
n
.
AI
m
ay
h
el
p
m
o
r
e
in
co
m
p
lex
s
ess
io
n
s
.
W
h
eth
er
th
is
p
atter
n
h
o
ld
s
in
o
th
e
r
co
u
r
s
es a
n
d
in
s
titu
tio
n
s
n
ee
d
s
to
b
e
test
ed
in
f
u
tu
r
e
r
esear
ch
.
ACK
NO
WL
E
DG
M
E
N
T
S
T
h
e
au
t
h
o
r
s
th
a
n
k
Ad
n
an
e
Af
q
u
ir
e,
De
p
u
ty
Dir
ec
to
r
in
C
h
a
r
g
e
o
f
Ped
a
g
o
g
ical
Af
f
air
s
at
th
e
Hig
h
er
I
n
ter
n
atio
n
al
I
n
s
titu
te
o
f
T
o
u
r
is
m
,
T
an
g
ier
,
Mo
r
o
cc
o
f
o
r
ad
m
in
is
tr
ativ
e
s
u
p
p
o
r
t
an
d
p
er
m
is
s
io
n
to
co
n
d
u
c
t
th
is
r
esear
ch
.
T
h
e
f
ir
s
t
au
th
o
r
also
th
an
k
s
L
a
y
a
Aziz
f
o
r
h
e
r
co
n
s
tan
t
s
u
p
p
o
r
t.
T
h
e
au
th
o
r
s
ar
e
also
g
r
atef
u
l
to
th
e
p
ar
ticip
atin
g
s
tu
d
e
n
ts
f
o
r
t
h
eir
co
o
p
er
atio
n
a
n
d
e
n
g
ag
em
en
t th
r
o
u
g
h
o
u
t th
e
s
tu
d
y
.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
Au
th
o
r
s
s
tate
n
o
f
u
n
d
in
g
in
v
o
lv
ed
.
AUTHO
R
CO
NT
RI
B
UT
I
O
NS ST
A
T
E
M
E
N
T
T
h
is
jo
u
r
n
al
u
s
es
th
e
C
o
n
t
r
ib
u
to
r
R
o
les
T
a
x
o
n
o
m
y
(
C
R
ed
iT)
to
r
ec
o
g
n
ize
in
d
iv
i
d
u
al
au
th
o
r
co
n
tr
ib
u
tio
n
s
,
r
ed
u
ce
au
th
o
r
s
h
ip
d
is
p
u
tes,
an
d
f
ac
ilit
ate
co
llab
o
r
atio
n
.
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
C
h
a
tGP
T a
s
s
ca
ffo
ld
:
q
u
iz
p
erfo
r
ma
n
ce
a
cro
s
s
s
ess
io
n
co
mp
lexity
(
F
a
tima
E
z
z
a
h
r
a
K
a
b
b
a
)
3179
Na
m
e
o
f
Aut
ho
r
C
M
So
Va
Fo
I
R
D
O
E
Vi
Su
P
Fu
Fatim
a
E
zz
ah
r
a
Kab
b
a
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Z
o
u
h
air
E
j
b
ar
i
✓
✓
✓
✓
C
:
C
o
n
c
e
p
t
u
a
l
i
z
a
t
i
o
n
M
:
M
e
t
h
o
d
o
l
o
g
y
So
:
So
f
t
w
a
r
e
Va
:
Va
l
i
d
a
t
i
o
n
Fo
:
Fo
r
mal
a
n
a
l
y
s
i
s
I
:
I
n
v
e
s
t
i
g
a
t
i
o
n
R
:
R
e
so
u
r
c
e
s
D
:
D
a
t
a
C
u
r
a
t
i
o
n
O
:
W
r
i
t
i
n
g
-
O
r
i
g
i
n
a
l
D
r
a
f
t
E
:
W
r
i
t
i
n
g
-
R
e
v
i
e
w
&
E
d
i
t
i
n
g
Vi
:
Vi
su
a
l
i
z
a
t
i
o
n
Su
:
Su
p
e
r
v
i
s
i
o
n
P
:
P
r
o
j
e
c
t
a
d
mi
n
i
st
r
a
t
i
o
n
Fu
:
Fu
n
d
i
n
g
a
c
q
u
i
si
t
i
o
n
CO
NF
L
I
C
T
O
F
I
N
T
E
R
E
S
T
ST
A
T
E
M
E
NT
Au
th
o
r
s
s
tate
n
o
co
n
f
lict o
f
in
t
er
est.
I
NF
O
RM
E
D
CO
NS
E
N
T
Stu
d
en
ts
wer
e
in
f
o
r
m
e
d
ab
o
u
t
th
e
p
u
r
p
o
s
e
o
f
th
e
s
tu
d
y
a
n
d
co
n
s
en
ted
to
th
e
u
s
e
o
f
th
eir
a
n
o
n
y
m
ize
d
q
u
iz
d
ata
f
o
r
r
esear
c
h
p
u
r
p
o
s
es.
No
p
e
r
s
o
n
ally
id
e
n
tifia
b
le
in
f
o
r
m
atio
n
is
r
ep
o
r
ted
i
n
th
is
m
an
u
s
cr
ip
t.
T
h
e
s
tu
d
y
was
co
n
d
u
cted
i
n
co
m
p
lian
ce
with
ap
p
licab
le
in
s
titu
tio
n
al
s
tan
d
ar
d
s
an
d
th
e
He
ls
in
k
i
Dec
lar
atio
n
p
r
in
cip
les f
o
r
r
esear
ch
in
v
o
lv
i
n
g
h
u
m
an
p
ar
ticip
an
ts
.
E
T
H
I
CAL AP
P
RO
V
AL
Stu
d
en
ts
wer
e
in
f
o
r
m
ed
ab
o
u
t
th
e
s
tu
d
y
an
d
co
n
s
en
ted
to
th
e
u
s
e
o
f
an
o
n
y
m
ized
q
u
iz
d
ata.
T
h
e
s
tu
d
y
was c
o
n
d
u
cte
d
with
in
s
titu
tio
n
al
k
n
o
wled
g
e
an
d
ap
p
r
o
v
al.
Qu
iz
s
co
r
es d
id
n
o
t in
f
l
u
e
n
ce
f
in
al
g
r
ad
es.
DATA AV
AI
L
AB
I
L
I
T
Y
T
h
e
d
ata
th
at
s
u
p
p
o
r
ts
th
e
f
in
d
in
g
s
o
f
th
is
s
tu
d
y
ar
e
av
ailab
le
f
r
o
m
th
e
c
o
r
r
esp
o
n
d
in
g
a
u
th
o
r
,
[
FEK]
,
u
p
o
n
r
ea
s
o
n
ab
le
r
eq
u
est.
RE
F
E
R
E
NC
E
S
[
1
]
R
.
M
i
c
h
e
l
-
V
i
l
l
a
r
r
e
a
l
,
E.
V
i
l
a
l
t
a
-
P
e
r
d
o
mo
,
D
.
E.
S
a
l
i
n
a
s
-
N
a
v
a
r
r
o
,
R
.
T
h
i
e
r
r
y
-
A
g
u
i
l
e
r
a
,
a
n
d
F
.
S
.
G
e
r
a
r
d
o
u
,
“
C
h
a
l
l
e
n
g
e
s
a
n
d
o
p
p
o
r
t
u
n
i
t
i
e
s
o
f
g
e
n
e
r
a
t
i
v
e
A
I
f
o
r
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
a
s
e
x
p
l
a
i
n
e
d
b
y
C
h
a
t
G
P
T,
”
Ed
u
c
a
t
i
o
n
S
c
i
e
n
c
e
s
,
v
o
l
.
1
3
,
n
o
.
9
,
p
.
8
5
6
,
A
u
g
.
2
0
2
3
,
d
o
i
:
1
0
.
3
3
9
0
/
e
d
u
c
sc
i
1
3
0
9
0
8
5
6
.
[
2
]
H
.
C
r
o
mp
t
o
n
a
n
d
D
.
B
u
r
k
e
,
“
T
h
e
e
d
u
c
a
t
i
o
n
a
l
a
f
f
o
r
d
a
n
c
e
s
a
n
d
c
h
a
l
l
e
n
g
e
s
o
f
C
h
a
t
G
P
T
:
st
a
t
e
o
f
t
h
e
f
i
e
l
d
,”
T
e
c
h
T
re
n
d
s
,
v
o
l
.
6
8
,
n
o
.
2
,
p
p
.
3
8
0
–
3
9
2
,
M
a
r
.
2
0
2
4
,
d
o
i
:
1
0
.
1
0
0
7
/
s
1
1
5
2
8
-
0
2
4
-
0
0
9
3
9
-
0.
[
3
]
A
.
Ze
b
,
R
.
U
l
l
a
h
,
a
n
d
R
.
K
a
r
i
m,
“
Ex
p
l
o
r
i
n
g
t
h
e
r
o
l
e
o
f
C
h
a
t
G
P
T
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
:
o
p
p
o
r
t
u
n
i
t
i
e
s,
c
h
a
l
l
e
n
g
e
s
a
n
d
e
t
h
i
c
a
l
c
o
n
si
d
e
r
a
t
i
o
n
s,
”
T
h
e
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
I
n
f
o
rm
a
t
i
o
n
a
n
d
L
e
a
r
n
i
n
g
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
4
1
,
n
o
.
1
,
p
p
.
9
9
–
1
1
1
,
J
a
n
.
2
0
2
4
,
d
o
i
:
1
0
.
1
1
0
8
/
I
JI
LT
-
04
-
2
0
2
3
-
0
0
4
6
.
[
4
]
R
.
G
.
L
u
c
i
a
n
o
,
“
Th
e
d
u
a
l
i
m
p
a
c
t
o
f
C
h
a
t
G
P
T
o
n
l
e
a
r
n
i
n
g
a
n
d
e
t
h
i
c
s a
m
o
n
g
b
a
c
h
e
l
o
r
o
f
sc
i
e
n
c
e
i
n
i
n
f
o
r
m
a
t
i
o
n
t
e
c
h
n
o
l
o
g
y
(
B
S
I
T)
st
u
d
e
n
t
s
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
L
e
a
r
n
i
n
g
,
T
e
a
c
h
i
n
g
a
n
d
E
d
u
c
a
t
i
o
n
a
l
R
e
se
a
rc
h
,
v
o
l
.
2
3
,
n
o
.
1
2
,
p
p
.
7
8
–
9
5
,
D
e
c
.
2
0
2
4
,
d
o
i
:
1
0
.
2
6
8
0
3
/
i
j
l
t
e
r
.
2
3
.
1
2
.
5
.
[
5
]
M
.
S
u
l
l
i
v
a
n
,
A
.
K
e
l
l
y
,
a
n
d
P
.
M
c
La
u
g
h
l
a
n
,
“
C
h
a
t
G
P
T
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
:
c
o
n
s
i
d
e
r
a
t
i
o
n
s
f
o
r
a
c
a
d
e
m
i
c
i
n
t
e
g
r
i
t
y
a
n
d
s
t
u
d
e
n
t
l
e
a
r
n
i
n
g
,
”
J
o
u
r
n
a
l
o
f
A
p
p
l
i
e
d
L
e
a
r
n
i
n
g
a
n
d
T
e
a
c
h
i
n
g
,
v
o
l
.
6
,
n
o
.
1
,
p
p
.
3
1
–
4
0
,
M
a
r
.
2
0
2
3
,
d
o
i
:
1
0
.
3
7
0
7
4
/
j
a
l
t
.
2
0
2
3
.
6
.
1
.
1
7
.
[
6
]
J.
R
u
d
o
l
p
h
,
S
.
Ta
n
,
a
n
d
S
.
Ta
n
,
“
C
h
a
t
G
P
T:
b
u
l
l
s
h
i
t
sp
e
w
e
r
o
r
t
h
e
e
n
d
o
f
t
r
a
d
i
t
i
o
n
a
l
a
ss
e
ssm
e
n
t
s
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
?
”
J
o
u
r
n
a
l
o
f
Ap
p
l
i
e
d
L
e
a
r
n
i
n
g
a
n
d
T
e
a
c
h
i
n
g
,
v
o
l
.
6
,
n
o
.
1
,
p
p
.
3
4
2
–
3
6
3
,
Ja
n
.
2
0
2
3
,
d
o
i
:
1
0
.
3
7
0
7
4
/
j
a
l
t
.
2
0
2
3
.
6
.
1
.
9
.
[
7
]
M
.
M
.
A
sa
d
a
n
d
A
.
A
j
a
z
,
“
I
mp
a
c
t
o
f
C
h
a
t
G
P
T
a
n
d
g
e
n
e
r
a
t
i
v
e
A
I
o
n
l
i
f
e
l
o
n
g
l
e
a
r
n
i
n
g
a
n
d
u
p
s
k
i
l
l
i
n
g
l
e
a
r
n
e
r
s
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
:
u
n
v
e
i
l
i
n
g
t
h
e
c
h
a
l
l
e
n
g
e
s a
n
d
o
p
p
o
r
t
u
n
i
t
i
e
s
g
l
o
b
a
l
l
y
,
”
T
h
e
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
I
n
f
o
rm
a
t
i
o
n
a
n
d
L
e
a
r
n
i
n
g
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
4
1
,
n
o
.
5
,
p
p
.
5
0
7
–
5
2
3
,
N
o
v
.
2
0
2
4
,
d
o
i
:
1
0
.
1
1
0
8
/
I
JI
LT
-
06
-
2
0
2
4
-
0
1
0
3
.
[
8
]
S
.
M
.
J.
U
d
d
i
n
,
A
.
A
l
b
e
r
t
,
A
.
O
v
i
d
,
a
n
d
A
.
A
l
s
h
a
r
e
f
,
“
Le
v
e
r
a
g
i
n
g
C
h
a
t
G
P
T
t
o
a
i
d
c
o
n
st
r
u
c
t
i
o
n
h
a
z
a
r
d
r
e
c
o
g
n
i
t
i
o
n
a
n
d
s
u
p
p
o
r
t
safet
y
e
d
u
c
a
t
i
o
n
a
n
d
t
r
a
i
n
i
n
g
,
”
S
u
s
t
a
i
n
a
b
i
l
i
t
y
,
v
o
l
.
1
5
,
n
o
.
9
,
p
.
7
1
2
1
,
A
p
r
.
2
0
2
3
,
d
o
i
:
1
0
.
3
3
9
0
/
su
1
5
0
9
7
1
2
1
.
[
9
]
O
.
A
.
O
j
u
b
a
n
i
r
e
,
S
.
A
.
O
l
a
l
e
y
e
,
M
.
A
.
M
a
r
h
r
a
o
u
i
,
M
.
W
.
K
a
m
i
h
a
n
d
a
,
O
.
I
.
O
k
e
,
a
n
d
O
.
A
.
O
j
u
b
a
n
i
r
e
,
“
A
w
a
r
e
n
e
ss,
p
e
r
c
e
p
t
i
o
n
,
a
n
d
a
d
o
p
t
i
o
n
o
f
C
h
a
t
G
P
T
i
n
A
f
r
i
c
a
n
H
EI
s:
a
m
u
l
t
i
-
d
i
m
e
n
s
i
o
n
a
l
a
n
a
l
y
si
s
,
”
T
h
e
I
n
t
e
rn
e
t
a
n
d
H
i
g
h
e
r
Ed
u
c
a
t
i
o
n
,
v
o
l
.
6
5
,
p
.
1
0
0
9
9
9
,
A
p
r
.
2
0
2
5
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
i
h
e
d
u
c
.
2
0
2
5
.
1
0
0
9
9
9
.
[
1
0
]
N
.
E
l
t
a
i
b
a
,
S
.
H
o
sse
i
n
i
,
a
n
d
K
.
O
k
o
y
e
,
“
B
e
n
e
f
i
t
s
a
n
d
i
mp
a
c
t
o
f
t
e
c
h
n
o
l
o
g
y
-
e
n
h
a
n
c
e
d
l
e
a
r
n
i
n
g
a
p
p
l
i
c
a
t
i
o
n
s
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
i
n
M
i
d
d
l
e
E
a
st
a
n
d
N
o
r
t
h
A
f
r
i
c
a
:
a
s
y
s
t
e
ma
t
i
c
r
e
v
i
e
w
,
”
G
l
o
b
a
l
T
ra
n
si
t
i
o
n
s
,
v
o
l
.
7
,
p
p
.
3
5
0
–
3
7
4
,
2
0
2
5
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
g
l
t
.
2
0
2
5
.
0
6
.
0
0
4
.
[
1
1
]
P
.
B
h
a
s
k
a
r
a
n
d
C
.
K
.
Ti
w
a
r
i
,
“
C
h
a
r
mi
n
g
o
r
c
h
i
l
l
i
n
g
?
A
c
o
m
p
r
e
h
e
n
si
v
e
r
e
v
i
e
w
o
f
C
h
a
t
G
P
T’
s
i
n
e
d
u
c
a
t
i
o
n
se
c
t
o
r
,
”
T
h
e
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
I
n
f
o
rm
a
t
i
o
n
a
n
d
L
e
a
r
n
i
n
g
T
e
c
h
n
o
l
o
g
y
,
M
a
r
.
2
0
2
5
,
d
o
i
:
1
0
.
1
1
0
8
/
I
J
I
LT
-
05
-
2
0
2
4
-
0
0
9
7
.
[
1
2
]
H
.
A
l
-
M
u
g
h
a
i
r
i
a
n
d
P
.
B
h
a
s
k
a
r
,
“
Ex
p
l
o
r
i
n
g
t
h
e
f
a
c
t
o
r
s
a
f
f
e
c
t
i
n
g
t
h
e
a
d
o
p
t
i
o
n
A
I
t
e
c
h
n
i
q
u
e
s
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
:
i
n
s
i
g
h
t
s
f
r
o
m
t
e
a
c
h
e
r
s’
p
e
r
s
p
e
c
t
i
v
e
s
o
n
C
h
a
t
G
P
T,
”
J
o
u
rn
a
l
o
f
Re
s
e
a
r
c
h
i
n
I
n
n
o
v
a
t
i
v
e
T
e
a
c
h
i
n
g
&
L
e
a
rn
i
n
g
,
v
o
l
.
1
8
,
n
o
.
2
,
p
p
.
2
3
2
–
2
4
7
,
S
e
p
.
2
0
2
5
,
d
o
i
:
1
0
.
1
1
0
8
/
JR
I
T
-
09
-
2
0
2
3
-
0
1
2
9
.
[
1
3
]
D
.
R
a
v
šel
j
e
t
a
l
.
,
“
H
i
g
h
e
r
e
d
u
c
a
t
i
o
n
st
u
d
e
n
t
s’
p
e
r
c
e
p
t
i
o
n
s
o
f
C
h
a
t
G
P
T:
a
g
l
o
b
a
l
s
t
u
d
y
o
f
e
a
r
l
y
r
e
a
c
t
i
o
n
s
,
”
PL
o
S
O
N
E
,
v
o
l
.
2
0
,
n
o
.
2
,
p
.
e
0
3
1
5
0
1
1
,
F
e
b
.
2
0
2
5
,
d
o
i
:
1
0
.
1
3
7
1
/
j
o
u
r
n
a
l
.
p
o
n
e
.
0
3
1
5
0
1
1
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
8
2
2
I
n
t
J
E
v
al
&
R
es E
d
u
c
,
Vo
l
.
15
,
No
.
4
,
Au
g
u
s
t
20
26
:
3
1
7
2
-
3
1
8
1
3180
[
1
4
]
J.
H
i
e
b
e
r
t
a
n
d
P
.
L
e
f
e
v
r
e
,
“
C
o
n
c
e
p
t
u
a
l
a
n
d
p
r
o
c
e
d
u
r
a
l
k
n
o
w
l
e
d
g
e
i
n
ma
t
h
e
mat
i
c
s
:
a
n
i
n
t
r
o
d
u
c
t
o
r
y
a
n
a
l
y
s
i
s
,”
i
n
C
o
n
c
e
p
t
u
a
l
a
n
d
Pro
c
e
d
u
r
a
l
K
n
o
w
l
e
d
g
e
:
T
h
e
C
a
s
e
o
f
Ma
t
h
e
m
a
t
i
c
s
,
1
st
e
d
.
,
J.
H
i
e
b
e
r
t
,
Ed
.
,
N
e
w
Y
o
r
k
,
N
Y
:
R
o
u
t
l
e
d
g
e
,
1
9
8
6
,
p
p
.
1
–
27
.
[
1
5
]
J.
R
.
S
t
a
r
,
“
R
e
c
o
n
c
e
p
t
u
a
l
i
z
i
n
g
p
r
o
c
e
d
u
r
a
l
k
n
o
w
l
e
d
g
e
,
”
J
o
u
r
n
a
l
f
o
r
R
e
se
a
rc
h
i
n
M
a
t
h
e
m
a
t
i
c
s
E
d
u
c
a
t
i
o
n
,
v
o
l
.
3
6
,
n
o
.
5
,
p
p
.
4
0
4
–
4
1
1
,
2
0
0
5
.
[
1
6
]
L.
S
.
V
y
g
o
t
s
k
y
,
Mi
n
d
i
n
s
o
c
i
e
t
y
:
t
h
e
d
e
v
e
l
o
p
m
e
n
t
o
f
h
i
g
h
e
r
p
syc
h
o
l
o
g
i
c
a
l
p
ro
c
e
ss
e
s
.
C
a
mb
r
i
d
g
e
,
M
A
:
H
a
r
v
a
r
d
U
n
i
v
e
r
si
t
y
P
r
e
ss
,
1
9
7
8
,
d
o
i
:
1
0
.
2
3
0
7
/
j
.
c
t
v
j
f
9
v
z
4
.
[
1
7
]
M
.
P
r
i
n
c
e
,
“
D
o
e
s
a
c
t
i
v
e
l
e
a
r
n
i
n
g
w
o
r
k
?
A
r
e
v
i
e
w
o
f
t
h
e
r
e
sea
r
c
h
,
”
J
o
u
rn
a
l
o
f
E
n
g
i
n
e
e
r
i
n
g
E
d
u
c
a
t
i
o
n
,
v
o
l
.
9
3
,
n
o
.
3
,
p
p
.
2
2
3
–
2
3
1
,
Ju
l
.
2
0
0
4
,
d
o
i
:
1
0
.
1
0
0
2
/
j
.
2
1
6
8
-
9
8
3
0
.
2
0
0
4
.
t
b
0
0
8
0
9
.
x
.
[
1
8
]
M
.
Tr
a
n
,
C
.
B
a
l
a
s
o
o
r
i
y
a
,
C
.
S
e
mm
l
e
r
,
a
n
d
J
.
R
h
e
e
,
“
G
e
n
e
r
a
t
i
v
e
a
r
t
i
f
i
c
i
a
l
i
n
t
e
l
l
i
g
e
n
c
e
:
t
h
e
‘
m
o
r
e
k
n
o
w
l
e
d
g
e
a
b
l
e
o
t
h
e
r
’
i
n
a
so
c
i
a
l
c
o
n
st
r
u
c
t
i
v
i
s
t
f
r
a
m
e
w
o
r
k
o
f
m
e
d
i
c
a
l
e
d
u
c
a
t
i
o
n
,
”
n
p
j
D
i
g
i
t
a
l
M
e
d
i
c
i
n
e
,
v
o
l
.
8
,
n
o
.
1
,
p
.
4
3
0
,
Ju
l
.
2
0
2
5
,
d
o
i
:
1
0
.
1
0
3
8
/
s4
1
7
4
6
-
025
-
0
1
8
2
3
-
8.
[
1
9
]
P
.
Z
h
a
n
g
a
n
d
G
.
T
u
r
,
“
A
s
y
st
e
ma
t
i
c
r
e
v
i
e
w
o
f
C
h
a
t
G
P
T
u
se
i
n
K
-
1
2
e
d
u
c
a
t
i
o
n
,
”
E
u
ro
p
e
a
n
J
o
u
r
n
a
l
o
f
E
d
u
c
a
t
i
o
n
,
v
o
l
.
5
9
,
n
o
.
2
,
p.
e
1
2
5
9
9
,
Ju
n
.
2
0
2
4
,
d
o
i
:
1
0
.
1
1
1
1
/
e
j
e
d
.
1
2
5
9
9
.
[
2
0
]
S
.
W
.
R
a
u
d
e
n
b
u
sh
a
n
d
A
.
S
.
B
r
y
k
,
H
i
e
r
a
rc
h
i
c
a
l
l
i
n
e
a
r
m
o
d
e
l
s:
a
p
p
l
i
c
a
t
i
o
n
s
a
n
d
d
a
t
a
a
n
a
l
y
s
i
s
m
e
t
h
o
d
s
,
2
n
d
e
d
.
Th
o
u
sa
n
d
O
a
k
s,
C
A
:
S
A
G
E
P
u
b
l
i
c
a
t
i
o
n
s,
I
n
c
.
,
2
0
0
2
.
[
2
1
]
J.
C
o
h
e
n
,
S
t
a
t
i
s
t
i
c
a
l
p
o
w
e
r
a
n
a
l
y
si
s
f
o
r t
h
e
b
e
h
a
v
i
o
r
a
l
sc
i
e
n
c
e
s
,
2
n
d
e
d
.
H
i
l
l
sd
a
l
e
,
N
J:
La
w
r
e
n
c
e
Er
l
b
a
u
m
A
sso
c
i
a
t
e
s,
1
9
8
8
.
[
2
2
]
S
.
A
l
n
e
y
a
d
i
a
n
d
Y
.
W
a
r
d
a
t
,
“
C
h
a
t
G
P
T:
R
e
v
o
l
u
t
i
o
n
i
z
i
n
g
st
u
d
e
n
t
a
c
h
i
e
v
e
m
e
n
t
i
n
t
h
e
e
l
e
c
t
r
o
n
i
c
ma
g
n
e
t
i
sm
u
n
i
t
f
o
r
e
l
e
v
e
n
t
h
-
g
r
a
d
e
st
u
d
e
n
t
s
i
n
Emi
r
a
t
e
s
sc
h
o
o
l
s,”
C
o
n
t
e
m
p
o
r
a
ry
Ed
u
c
a
t
i
o
n
a
l
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
1
5
,
n
o
.
4
,
p
.
e
p
4
4
8
,
O
c
t
.
2
0
2
3
,
d
o
i
:
1
0
.
3
0
9
3
5
/
c
e
d
t
e
c
h
/
1
3
4
1
7
.
[
2
3
]
K
.
M
.
S
e
l
e
m
,
E
.
G
.
S
a
g
h
i
e
r
,
S
.
H
.
A
.
K
h
r
e
i
s
,
a
n
d
C
.
C
.
Ta
n
,
“
C
h
a
t
G
P
T
-
r
e
l
a
t
e
d
r
i
s
k
p
a
t
t
e
r
n
s
a
n
d
st
u
d
e
n
t
s’
c
r
e
a
t
i
v
e
t
h
i
n
k
i
n
g
t
o
w
a
r
d
t
o
u
r
i
sm
st
a
t
i
s
t
i
c
s
c
o
u
r
se
:
p
r
e
t
e
st
a
n
d
p
o
s
t
t
e
st
q
u
a
s
i
-
e
x
p
e
r
i
m
e
n
t
a
t
i
o
n
,”
J
o
u
r
n
a
l
o
f
H
o
s
p
i
t
a
l
i
t
y
&
T
o
u
r
i
sm
E
d
u
c
a
t
i
o
n
,
v
o
l
.
3
7
,
n
o
.
3
,
p
p
.
3
1
3
–
3
2
8
,
J
u
l
.
2
0
2
5
,
d
o
i
:
1
0
.
1
0
8
0
/
1
0
9
6
3
7
5
8
.
2
0
2
5
.
2
4
5
6
6
3
8
.
[
2
4
]
T.
-
C
.
Y
a
n
g
,
Y
.
-
C
.
H
su
,
a
n
d
J.
-
Y
.
W
u
,
“
T
h
e
e
f
f
e
c
t
i
v
e
n
e
ss
o
f
C
h
a
t
G
P
T
i
n
a
ssi
st
i
n
g
h
i
g
h
sc
h
o
o
l
st
u
d
e
n
t
s
i
n
p
r
o
g
r
a
mm
i
n
g
l
e
a
r
n
i
n
g
:
e
v
i
d
e
n
c
e
f
r
o
m
a
q
u
a
s
i
-
e
x
p
e
r
i
m
e
n
t
a
l
r
e
sea
r
c
h
,
”
I
n
t
e
ra
c
t
i
v
e
L
e
a
r
n
i
n
g
E
n
v
i
ro
n
m
e
n
t
s
,
v
o
l
.
3
3
,
n
o
.
6
,
p
p
.
3
7
2
6
–
3
7
4
3
,
Ju
l
.
2
0
2
5
,
d
o
i
:
1
0
.
1
0
8
0
/
1
0
4
9
4
8
2
0
.
2
0
2
5
.
2
4
5
0
6
5
9
.
[
2
5
]
Y
.
X
i
n
g
,
“
Ex
p
l
o
r
i
n
g
t
h
e
u
se
o
f
C
h
a
t
G
P
T
i
n
l
e
a
r
n
i
n
g
a
n
d
i
n
s
t
r
u
c
t
i
n
g
st
a
t
i
st
i
c
s
a
n
d
d
a
t
a
a
n
a
l
y
t
i
c
s,
”
T
e
a
c
h
i
n
g
S
t
a
t
i
s
t
i
c
s
,
v
o
l
.
4
6
,
n
o
.
2
,
p
p
.
9
5
–
1
0
4
,
A
p
r
.
2
0
2
4
,
d
o
i
:
1
0
.
1
1
1
1
/
t
e
s
t
.
1
2
3
6
7
.
[
2
6
]
N
.
A
l
n
a
i
m
e
t
a
l
.
,
“
Ef
f
e
c
t
i
v
e
n
e
ss
o
f
C
h
a
t
G
P
T
i
n
r
e
m
o
t
e
l
e
a
r
n
i
n
g
e
n
v
i
r
o
n
m
e
n
t
s:
a
n
e
mp
i
r
i
c
a
l
s
t
u
d
y
w
i
t
h
m
e
d
i
c
a
l
st
u
d
e
n
t
s
i
n
S
a
u
d
i
A
r
a
b
i
a
,
”
N
u
t
r
i
t
i
o
n
a
n
d
H
e
a
l
t
h
,
v
o
l
.
3
1
,
n
o
.
3
,
p
p
.
1
0
3
5
–
1
0
4
6
,
Ju
l
.
2
0
2
5
,
d
o
i
:
1
0
.
1
1
7
7
/
0
2
6
0
1
0
6
0
2
4
1
2
7
3
5
9
6
.
[
2
7
]
W
.
Z
h
o
u
a
n
d
Y
.
K
i
m
,
“
I
n
n
o
v
a
t
i
v
e
mu
s
i
c
e
d
u
c
a
t
i
o
n
:
a
n
e
mp
i
r
i
c
a
l
a
ss
e
ssm
e
n
t
o
f
C
h
a
t
G
P
T
-
4
’
s
i
m
p
a
c
t
o
n
st
u
d
e
n
t
l
e
a
r
n
i
n
g
e
x
p
e
r
i
e
n
c
e
s
,
”
E
d
u
c
a
t
i
o
n
a
n
d
I
n
f
o
rm
a
t
i
o
n
T
e
c
h
n
o
l
o
g
i
e
s
,
v
o
l
.
2
9
,
n
o
.
1
6
,
p
p
.
2
0
8
5
5
–
2
0
8
8
1
,
N
o
v
.
2
0
2
4
,
d
o
i
:
1
0
.
1
0
0
7
/
s1
0
6
3
9
-
024
-
1
2
7
0
5
-
z.
[
2
8
]
J.
S
c
h
w
a
r
z
,
“
Th
e
u
se
o
f
g
e
n
e
r
a
t
i
v
e
A
I
i
n
st
a
t
i
st
i
c
a
l
d
a
t
a
a
n
a
l
y
s
i
s
a
n
d
i
t
s
i
m
p
a
c
t
o
n
t
e
a
c
h
i
n
g
st
a
t
i
st
i
c
s
a
t
u
n
i
v
e
r
si
t
i
e
s
o
f
a
p
p
l
i
e
d
sci
e
n
c
e
s,
”
T
e
a
c
h
i
n
g
S
t
a
t
i
st
i
c
s
,
v
o
l
.
4
7
,
n
o
.
2
,
p
p
.
1
1
8
–
1
2
8
,
M
a
y
2
0
2
5
,
d
o
i
:
1
0
.
1
1
1
1
/
t
e
st
.
1
2
3
9
8
.
[
2
9
]
D
.
T
h
ü
s
,
S
.
M
a
l
o
n
e
,
a
n
d
R
.
B
r
ü
n
k
e
n
,
“
E
x
p
l
o
r
i
n
g
g
e
n
e
r
a
t
i
v
e
A
I
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
:
a
R
A
G
s
y
s
t
e
m
t
o
e
n
h
a
n
c
e
s
t
u
d
e
n
t
e
n
g
a
g
e
me
n
t
w
i
t
h
s
c
i
e
n
t
i
f
i
c
l
i
t
e
r
a
t
u
r
e
,
”
Fr
o
n
t
i
e
rs
i
n
Ps
y
c
h
o
l
o
g
y
,
v
o
l
.
1
5
,
p
.
1474892,
O
c
t
.
2
0
2
4
,
d
o
i
:
1
0
.
3
3
8
9
/
f
p
s
y
g
.
2
0
2
4
.
1
4
7
4
8
9
2
.
[
3
0
]
N
.
M
o
u
ssa
,
R
.
B
e
n
t
o
u
mi
,
a
n
d
T.
S
a
a
l
i
,
“
P
r
o
m
o
t
i
n
g
st
u
d
e
n
t
s
u
c
c
e
ss
w
i
t
h
n
e
u
t
r
o
s
o
p
h
i
c
set
s:
a
r
t
i
f
i
c
i
a
l
i
n
t
e
l
l
i
g
e
n
c
e
a
n
d
s
t
u
d
e
n
t
e
n
g
a
g
e
m
e
n
t
i
n
h
i
g
h
e
r
e
d
u
c
a
t
i
o
n
c
o
n
t
e
x
t
,
”
I
n
t
e
r
n
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
N
e
u
t
r
o
so
p
h
i
c
S
c
i
e
n
c
e
,
v
o
l
.
2
3
,
n
o
.
1
,
p
p
.
2
3
8
–
2
4
8
,
2
0
2
4
,
d
o
i
:
1
0
.
5
4
2
1
6
/
I
JN
S
.
2
3
0
1
2
1
.
[
3
1
]
L.
P
.
P
a
t
a
c
a
n
d
A
.
V
.
P
a
t
a
c
,
“
U
s
i
n
g
C
h
a
t
G
P
T
f
o
r
a
c
a
d
e
m
i
c
s
u
p
p
o
r
t
:
m
a
n
a
g
i
n
g
c
o
g
n
i
t
i
v
e
l
o
a
d
a
n
d
e
n
h
a
n
c
i
n
g
l
e
a
r
n
i
n
g
e
f
f
i
c
i
e
n
c
y
–
a
p
h
e
n
o
m
e
n
o
l
o
g
i
c
a
l
a
p
p
r
o
a
c
h
,
”
S
o
c
i
a
l
S
c
i
e
n
c
e
s
&
H
u
m
a
n
i
t
i
e
s
O
p
e
n
,
v
o
l
.
1
1
,
p
.
1
0
1
3
0
1
,
2
0
2
5
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
s
sa
h
o
.
2
0
2
5
.
1
0
1
3
0
1
.
[
3
2
]
D
.
K
a
y
a
a
n
d
S
.
Y
a
v
u
z
,
“
C
a
n
g
e
n
e
r
a
t
i
v
e
A
I
a
n
d
C
h
a
t
G
P
T
b
r
e
a
k
h
u
m
a
n
s
u
p
r
e
mac
y
i
n
ma
t
h
e
ma
t
i
c
s
a
n
d
r
e
s
h
a
p
e
c
o
mp
e
t
e
n
c
e
i
n
c
o
g
n
i
t
i
v
e
-
d
e
ma
n
d
i
n
g
p
r
o
b
l
e
m
-
s
o
l
v
i
n
g
t
a
s
k
s
?
”
J
o
u
r
n
a
l
o
f
I
n
t
e
l
l
i
g
e
n
c
e
,
v
o
l
.
1
3
,
n
o
.
4
,
p
.
4
3
,
A
p
r
.
2
0
2
5
,
d
o
i
:
1
0
.
3
3
9
0
/
j
i
n
t
e
l
l
i
g
e
n
c
e
1
3
0
4
0
0
4
3
.
[
3
3
]
Z.
L
i
u
,
H
.
Z
u
o
,
a
n
d
Y
.
L
u
,
“
T
h
e
i
m
p
a
c
t
o
f
C
h
a
t
G
P
T
o
n
st
u
d
e
n
t
s’
a
c
a
d
e
mi
c
a
c
h
i
e
v
e
m
e
n
t
:
a
me
t
a
-
a
n
a
l
y
s
i
s,
”
J
o
u
rn
a
l
o
f
C
o
m
p
u
t
e
r
Assi
st
e
d
L
e
a
r
n
i
n
g
,
v
o
l
.
4
1
,
n
o
.
4
,
p
.
e
7
0
0
9
6
,
A
u
g
.
2
0
2
5
,
d
o
i
:
1
0
.
1
1
1
1
/
j
c
a
l
.
7
0
0
9
6
.
AP
P
E
NDI
X
Ass
es
s
m
ent
des
ig
n,
in
s
t
ruct
i
o
na
l c
o
nte
x
t
,
a
nd
s
up
po
rt
ing
m
a
t
er
i
a
ls
T
h
is
ap
p
en
d
i
x
p
r
o
v
id
es
s
u
p
p
o
r
tin
g
in
f
o
r
m
atio
n
o
n
th
e
ass
ess
m
en
t
d
esig
n
,
in
s
tr
u
ctio
n
al
co
n
d
itio
n
s
,
an
d
q
u
iz
m
ater
ials
u
s
ed
in
th
e
s
tu
d
y
.
I
ns
t
ruct
io
na
l c
o
nte
x
t
a
nd
us
e
o
f
dig
it
a
l t
o
o
ls
Dig
ital
to
o
ls
,
in
clu
d
i
n
g
g
en
e
r
ativ
e
tex
t
-
b
ased
ap
p
licatio
n
s
,
wer
e
p
er
m
itted
o
n
ly
d
u
r
in
g
lear
n
i
n
g
ac
tiv
ities
in
d
esig
n
ated
class
es
an
d
we
r
e
n
o
t
allo
wed
d
u
r
in
g
ass
ess
m
en
t.
Du
r
in
g
lear
n
in
g
ac
tiv
ities
,
s
tu
d
en
ts
in
th
e
AI
-
p
er
m
itted
co
n
d
itio
n
wer
e
allo
wed
to
ask
co
n
ce
p
tu
al
q
u
esti
o
n
s
s
u
ch
as
d
ef
in
itio
n
s
an
d
in
ter
p
r
etatio
n
s
,
r
eq
u
est
clar
if
icatio
n
o
f
p
r
o
ce
d
u
r
es
d
is
cu
s
s
ed
in
class
,
co
m
p
ar
e
ex
p
lan
atio
n
s
with
lectu
r
e
s
lid
es,
an
d
r
ef
o
r
m
u
late
c
o
n
te
n
t
in
th
eir
o
wn
w
o
r
d
s
.
Du
r
in
g
q
u
izze
s
,
n
o
d
ig
ital
to
o
ls
o
r
ex
ter
n
al
ass
is
tan
ce
wer
e
p
er
m
itted
.
Qu
izze
s
wer
e
co
m
p
leted
in
d
iv
id
u
ally
u
n
d
e
r
s
tan
d
ar
d
class
r
o
o
m
s
u
p
er
v
is
io
n
an
d
ad
m
in
is
ter
ed
at
th
e
en
d
o
f
ea
ch
s
ess
io
n
.
O
v
er
v
iew
o
f
qu
izze
s
a
nd
lea
rning
o
bje
ct
iv
es
Qu
iz
1
:
r
o
le
o
f
s
tatis
tic
s
(
co
n
ce
p
tu
al
)
.
Qu
iz
2
:
s
tatis
tical
v
o
ca
b
u
lar
y
(
c
o
n
ce
p
t
u
al
)
.
Qu
iz
3
:
ty
p
es
o
f
v
ar
iab
les
(
co
n
ce
p
tu
al
)
.
Qu
iz
4
:
f
r
eq
u
e
n
cies
(
p
r
o
ce
d
u
r
al/ap
p
l
icatio
n
)
.
Qu
iz
5
:
m
ea
n
s
(
p
r
o
c
ed
u
r
al/ap
p
licatio
n
)
.
Qu
iz
6
:
h
ar
m
o
n
ic
m
ea
n
an
d
m
o
d
e
(
p
r
o
ce
d
u
r
al/ap
p
licatio
n
)
.
Qu
iz
7
:
m
ed
ian
a
n
d
g
r
ap
h
s
(
a
p
p
licatio
n
).
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
C
h
a
tGP
T a
s
s
ca
ffo
ld
:
q
u
iz
p
erfo
r
ma
n
ce
a
cro
s
s
s
ess
io
n
co
mp
lexity
(
F
a
tima
E
z
z
a
h
r
a
K
a
b
b
a
)
3181
P
eda
g
o
g
ica
l sig
na
ls
f
ro
m
a
s
s
ess
m
ent
perf
o
rm
a
nce
Acr
o
s
s
s
e
s
s
io
n
s
,
ce
r
tain
co
n
ce
p
ts
an
d
p
r
o
ce
d
u
r
es
co
n
s
is
ten
tl
y
g
en
er
ated
s
tu
d
en
t
d
if
f
ic
u
lty
.
I
n
q
u
iz
1
,
s
tu
d
en
ts
o
f
ten
in
ter
p
r
eted
d
escr
ip
tiv
e
s
tatis
tics
a
s
d
ata
r
ath
er
th
an
as
m
eth
o
d
s
.
I
n
q
u
iz
2
,
d
ef
in
in
g
s
tatis
tical
p
o
p
u
latio
n
s
b
ey
o
n
d
t
h
e
co
m
m
o
n
u
n
d
er
s
tan
d
i
n
g
o
f
'
p
eo
p
l
e'
p
r
o
v
ed
c
h
allen
g
in
g
.
I
n
q
u
iz
3
,
ju
s
tify
in
g
th
e
class
if
icatio
n
o
f
o
r
d
in
al
v
ar
ia
b
les
in
s
ati
s
f
ac
tio
n
s
ca
les
was
a
r
ec
u
r
r
in
g
s
o
u
r
ce
o
f
co
n
f
u
s
io
n
.
Qu
iz
4
r
ev
ea
led
d
if
f
icu
lties
in
co
m
p
u
tin
g
a
n
d
in
ter
p
r
etin
g
f
r
eq
u
e
n
cy
d
is
tr
ib
u
tio
n
s
co
r
r
ec
tly
.
I
n
q
u
iz
5
,
ca
lcu
latin
g
th
e
g
eo
m
etr
ic
m
ea
n
p
r
esen
ted
p
e
r
s
is
ten
t
ch
allen
g
es.
I
n
q
u
iz
7
,
s
elec
tin
g
ap
p
r
o
p
r
iate
g
r
ap
h
i
ca
l
r
ep
r
esen
tatio
n
s
alo
n
g
s
id
e
d
eter
m
i
n
in
g
th
e
m
e
d
ian
r
eq
u
ir
ed
ju
d
g
m
e
n
t th
at
s
tu
d
en
ts
f
o
u
n
d
d
em
an
d
i
n
g
.
Ver
ba
t
im
a
s
s
ess
m
ent
it
em
s
f
o
r
qu
iz
6
T
o
en
s
u
r
e
tr
an
s
p
ar
e
n
cy
r
e
g
ar
d
in
g
th
e
ass
ess
m
en
t
as
s
o
ciate
d
with
s
ess
io
n
6
,
th
is
ap
p
en
d
i
x
r
ep
o
r
ts
th
e
ex
ac
t
wo
r
d
in
g
a
n
d
s
tr
u
ctu
r
e
o
f
th
e
item
s
ad
m
in
is
ter
ed
in
q
u
iz
6
.
T
h
ese
item
s
wer
e
id
en
tical
ac
r
o
s
s
all
clas
s
e
s
an
d
co
n
d
itio
n
s
.
−
I
tem
1
:
h
ar
m
o
n
ic
m
ea
n
(
d
is
cr
e
te
d
ata
with
f
r
eq
u
en
cies
)
C
alcu
late
th
e
h
ar
m
o
n
ic
m
ea
n
f
o
r
th
e
f
o
llo
win
g
d
ata:
s
p
ee
d
(
k
m
/h
)
:
2
0
,
3
0
,
4
0
,
5
0
,
6
0
with
f
r
eq
u
e
n
cy
:
4
,
6
,
8
,
2
,
1
.
R
esp
o
n
s
e
o
p
tio
n
s
:
A)
3
1
.
9
8
k
m
/h
,
B
)
3
5
.
4
k
m
/h
,
C
)
3
6
.
2
k
m
/
h
,
D)
I
d
o
n
o
t
k
n
o
w.
T
h
is
item
r
eq
u
ir
ed
co
r
r
ec
t a
p
p
licatio
n
o
f
th
e
h
ar
m
o
n
ic
m
ea
n
f
o
r
m
u
la
with
f
r
eq
u
en
cy
weig
h
ts
.
−
I
tem
2
:
m
o
d
e
(
d
is
cr
ete
v
a
r
iab
l
e
)
Dete
r
m
in
e
th
e
m
o
d
e
f
o
r
th
e
f
o
llo
win
g
d
ata:
R
ass
i
(
2
c
h
ild
r
en
)
,
B
elab
ass
e
(
5
)
,
Aze
r
o
u
al
(
6
)
,
B
o
lif
(
5
)
.
R
esp
o
n
s
e
o
p
tio
n
s
:
A)
R
ass
i,
B
)
B
elab
ass
e,
C
)
Aze
r
o
u
al
,
D)
I
d
o
n
o
t
k
n
o
w.
T
h
is
item
ass
ess
ed
co
n
ce
p
tu
al
u
n
d
er
s
tan
d
in
g
o
f
t
h
e
m
o
d
e
as th
e
m
o
s
t f
r
e
q
u
en
tl
y
o
cc
u
r
r
in
g
v
alu
e.
−
I
tem
3
:
m
o
d
e
f
o
r
g
r
o
u
p
e
d
co
n
tin
u
o
u
s
d
ata
(
u
n
e
q
u
al
class
wid
th
s
)
Dete
r
m
in
e
th
e
m
o
d
e
f
o
r
th
e
f
o
llo
win
g
c
o
n
tin
u
o
u
s
v
ar
iab
le:
Salar
y
i
n
ter
v
al
[
0
;
3
0
0
0
)
Fre
q
=1
0
,
0
0
0
W
id
th
=3
,
0
0
0
Den
s
ity
=3
.
3
3
;
[
3
0
0
0
;
6
0
0
0
)
Fre
q
=
2
5
,
0
0
0
W
id
th
=3
,
0
0
0
Den
s
ity
=8
.
3
3
;
[
6
0
0
0
;
7
0
0
0
)
Fre
q
=3
0
,
0
0
0
W
id
th
=1
,
0
0
0
D
en
s
ity
=3
0
.
0
0
;
[
7
0
0
0
;
9
0
0
0
)
Fre
q
=2
0
,
0
0
0
W
id
th
=2
,
0
0
0
De
n
s
ity
=1
0
.
0
0
;
[
9
0
0
0
;
1
2
0
0
0
)
Fre
q
=1
5
,
0
0
0
W
id
th
=
3
,
0
0
0
De
n
s
ity
=5
.
0
0
;
[
1
2
0
0
0
;
1
5
0
0
0
)
Fre
q
=5
,
0
0
0
W
id
th
=3
,
0
0
0
De
n
s
ity
=1
.
6
7
.
R
esp
o
n
s
e
o
p
tio
n
s
: A
)
3
0
0
0
.
6
6
,
B
)
5
3
9
0
.
3
5
,
C
)
6
3
3
3
.
3
3
,
D)
I
d
o
n
o
t k
n
o
w.
I
tem
3
r
eq
u
ir
ed
id
e
n
tific
atio
n
o
f
th
e
m
o
d
al
class
b
ased
o
n
d
en
s
ity
r
ath
er
th
an
r
aw
f
r
eq
u
en
c
y
,
f
o
llo
wed
b
y
a
p
p
licatio
n
o
f
th
e
in
ter
p
o
latio
n
f
o
r
m
u
la
f
o
r
g
r
o
u
p
ed
co
n
tin
u
o
u
s
d
ata.
T
o
g
et
h
er
,
th
e
th
r
ee
item
s
r
eq
u
ir
ed
m
u
lti
-
s
tep
co
m
p
u
ta
tio
n
,
co
r
r
ec
t
f
o
r
m
u
la
s
elec
tio
n
,
an
d
p
r
o
ce
d
u
r
al
s
eq
u
en
cin
g
,
r
ef
lectin
g
a
s
u
b
s
tan
tially
h
ig
h
er
co
g
n
itiv
e
an
d
co
m
p
u
tatio
n
al
lo
a
d
th
an
a
s
s
es
s
m
en
ts
u
s
ed
in
ea
r
lier
s
ess
io
n
s
.
E
t
hica
l a
nd
re
po
rt
ing
co
ns
id
er
a
t
io
ns
No
r
aw
s
tu
d
en
t
r
esp
o
n
s
es
ar
e
d
is
clo
s
ed
an
d
n
o
in
d
i
v
id
u
al
in
ter
ac
tio
n
lo
g
s
wer
e
c
o
llected
.
All
r
esu
lts
ar
e
r
ep
o
r
ted
at
th
e
g
r
o
u
p
lev
e
l
to
p
r
eser
v
e
s
tu
d
en
t
co
n
f
id
e
n
tiality
.
C
h
atGPT
was
av
ailab
l
e
to
s
tu
d
en
ts
in
th
e
AI
-
p
er
m
itted
class
es o
n
ly
d
u
r
i
n
g
lear
n
in
g
ac
tiv
ities
an
d
was
n
o
t p
er
m
itted
d
u
r
i
n
g
q
u
izze
s
in
an
y
class
.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
Fa
tim
a
Ez
z
a
h
r
a
K
a
b
b
a
h
o
l
d
s
a
P
h
.
D.
in
Ec
o
n
o
m
ics
a
n
d
M
a
n
a
g
e
m
e
n
t
(2
0
2
4
)
a
n
d
a
m
a
ste
r’s
d
e
g
re
e
in
F
in
a
n
c
e
.
S
h
e
is
a
lec
tu
re
r
a
t
th
e
Hig
h
e
r
In
tern
a
ti
o
n
a
l
I
n
stit
u
te
o
f
To
u
rism
,
M
o
ro
c
c
o
,
w
h
e
re
sh
e
tea
c
h
e
s
e
c
o
n
o
m
ics
a
n
d
m
a
n
a
g
e
m
e
n
t,
a
n
d
a
n
a
ffil
iate
d
re
se
a
rc
h
e
r
with
th
e
F
a
c
u
l
ty
o
f
Le
g
a
l,
Eco
n
o
m
ic
a
n
d
S
o
c
ial
S
c
ie
n
c
e
s
o
f
Tan
g
ier,
Ab
d
e
lma
lek
Essa
â
d
i
Un
iv
e
rsity
.
S
h
e
a
lso
h
o
l
d
s
th
e
G
o
o
g
le
Da
ta
An
a
ly
ti
c
s
P
ro
fe
ss
io
n
a
l
Ce
rti
fica
te.
He
r
re
se
a
rc
h
in
tere
sts
fo
c
u
s
o
n
th
e
i
m
p
a
c
t
o
f
a
rti
ficia
l
in
telli
g
e
n
c
e
o
n
lea
rn
i
n
g
a
n
d
d
a
ta
-
d
ri
v
e
n
d
e
c
isio
n
-
m
a
k
i
n
g
i
n
e
d
u
c
a
ti
o
n
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
:
k
a
b
b
a
.
fa
ti
m
a
.
e
z
z
a
h
ra
@g
m
a
il
.
c
o
m
.
Zo
u
h
a
ir
Ejb
a
r
i
h
o
l
d
s
a
P
h
.
D.
in
Eco
n
o
m
ics
a
n
d
M
a
n
a
g
e
m
e
n
t.
He
is
a
se
n
io
r
p
ro
fe
ss
o
r
a
t
th
e
F
a
c
u
lt
y
o
f
Leg
a
l,
Eco
n
o
m
ic
a
n
d
S
o
c
ial
S
c
ien
c
e
s
o
f
Tan
g
ier,
Ab
d
e
lma
lek
Essa
â
d
i
Un
iv
e
rsity
,
M
o
r
o
c
c
o
.
H
is
tea
c
h
in
g
a
n
d
re
se
a
rc
h
fo
c
u
s
o
n
p
u
b
li
c
m
a
n
a
g
e
m
e
n
t
a
n
d
h
ig
h
e
r
e
d
u
c
a
ti
o
n
.
His
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
g
o
v
e
rn
a
n
c
e
,
p
u
b
li
c
p
o
li
c
y
,
a
n
d
d
a
ta
-
d
riv
e
n
a
n
a
ly
sis
in
e
d
u
c
a
ti
o
n
a
l
a
n
d
i
n
stit
u
t
io
n
a
l
c
o
n
tex
ts.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
z
e
jb
a
ri@u
a
e
.
a
c
.
m
a
.
Evaluation Warning : The document was created with Spire.PDF for Python.