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s
[
1
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2
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p
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tech
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[
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Fo
r
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Face
b
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k
g
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ates
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ata
ar
e
g
en
er
ated
f
r
o
m
a
s
s
es
s
m
en
t.
Ass
es
s
m
en
t
b
ig
d
ata
r
ef
er
s
to
lear
n
er
d
ata
th
at
is
d
ee
p
an
d
b
r
o
ad
[
9
,
1
0
]
.
T
h
is
b
r
o
ad
d
ata
co
m
es
f
r
o
m
i
n
ter
n
a
l
ex
a
m
i
n
atio
n
s
an
d
ass
es
s
m
en
t
;
e
-
f
ee
d
b
ac
k
o
f
s
tu
d
en
t
s
’
e
v
al
u
atio
n
;
o
n
-
l
in
e
en
d
o
f
ter
m
r
esu
lts
o
f
s
t
u
d
en
t;
teac
h
er
-
m
ad
e
f
o
r
m
ati
v
e
tes
t
s
co
r
es;
an
d
p
er
f
o
r
m
an
ce
te
s
t
i
n
d
icato
r
f
r
o
m
class
r
o
o
m
ass
e
s
s
m
e
n
t
tec
h
n
i
q
u
e.
Fo
r
s
tu
d
en
t
s
’
ass
es
s
m
en
t
to
b
e
ea
s
il
y
ac
ce
s
s
ed
an
d
co
n
ti
n
u
all
y
m
o
n
ito
r
e
d
,
o
n
-
li
n
e
lear
n
in
g
p
lat
f
o
r
m
i
s
th
er
ef
o
r
e
r
eq
u
ir
ed
.
T
h
r
o
u
g
h
co
n
tin
u
o
u
s
as
s
es
s
m
en
t
o
f
s
t
u
d
en
t
lear
n
i
n
g
an
d
t
h
e
s
u
b
s
eq
u
e
n
t
f
ee
d
b
ac
k
i
n
f
o
r
m
o
f
as
s
es
s
m
e
n
t
r
esu
lt
s
,
ass
e
s
s
m
en
t b
ig
d
ata
ar
e
g
en
er
ated
in
q
u
an
t
u
m
[
1
1
,
1
2
]
.
Desp
ite
th
e
q
u
a
n
t
u
m
d
ata
g
e
n
er
ated
f
r
o
m
ass
e
s
s
m
e
n
t
in
e
d
u
ca
tio
n
,
ass
e
s
s
m
e
n
t
b
ig
d
ata
ar
e
f
ac
ed
w
it
h
v
ar
io
u
s
c
h
alle
n
g
e
s
w
h
ic
h
i
n
cl
u
d
es
s
t
u
d
en
t’
s
p
r
iv
ac
y
,
d
if
f
ic
u
lt
y
i
n
ac
ce
s
s
i
n
g
r
eq
u
ir
e
d
d
ata,
ac
cu
r
ac
y
o
f
d
ata
an
d
ti
m
eli
n
ess
o
f
f
ee
d
b
ac
k
,
in
s
u
f
f
icie
n
t
n
u
m
b
er
o
f
t
r
ain
ed
p
er
s
o
n
n
el
to
u
s
e
b
ig
d
ata,
in
teg
r
atio
n
o
f
s
tr
u
ct
u
r
ed
an
d
u
n
s
tr
u
ct
u
r
ed
d
ata
f
r
o
m
d
i
f
f
er
en
t
s
o
u
r
ce
s
,
a
n
d
co
s
t
o
f
lear
n
i
n
g
a
n
al
y
tic
s
s
o
f
t
w
ar
e
[
1
3
-
15
]
.
I
n
Nig
er
ia,
th
e
g
e
n
er
ated
b
ig
d
ata
f
r
o
m
ass
e
s
s
m
en
t
ar
e
n
o
t
co
r
r
elate
d
to
p
r
o
v
id
e
f
ee
d
b
ac
k
f
o
r
en
h
an
c
in
g
s
tu
d
e
n
ts
’
lear
n
i
n
g
a
n
d
p
er
f
o
r
m
an
ce
[
1
6
-
1
8
]
.
Stu
d
en
ts
’
r
es
p
o
n
s
es
in
as
s
ig
n
m
e
n
ts
an
d
ex
a
m
in
at
io
n
s
m
ai
n
l
y
s
er
v
e
as
a
m
ea
s
u
r
e
m
e
n
t
o
f
s
t
u
d
en
ts
’
p
er
f
o
r
m
a
n
ce
s
in
a
n
ar
e
a
r
ath
er
th
a
n
to
aid
i
n
d
ata
-
b
as
ed
d
ec
is
io
n
m
a
k
i
n
g
in
Nig
er
ia
[
19
].
On
e
m
a
y
w
o
n
d
er
w
h
e
th
er
ed
u
ca
to
r
s
,
p
o
licy
m
a
k
er
s
,
g
o
v
er
n
m
e
n
t
a
g
en
c
y
,
etc.
,
a
r
e
aw
ar
e
o
f
th
e
s
o
u
r
ce
s
,
t
y
p
es,
p
r
o
p
o
r
tio
n
s
,
u
s
es,
a
n
d
f
u
t
u
r
e
o
f
as
s
ess
m
e
n
t
b
ig
d
ata
i
n
Ni
g
er
ia.
R
esear
c
h
o
n
id
en
tific
atio
n
,
g
en
er
atio
n
an
d
u
s
e
s
o
f
ass
e
s
s
m
en
t
b
ig
d
ata
in
ed
u
ca
tio
n
is
a
r
ec
en
t
d
ev
elo
p
m
e
n
t
t
h
at
n
ee
d
s
m
o
r
e
w
o
r
k
.
I
t
is
s
ca
r
ce
,
if
n
o
t
co
m
p
letel
y
u
n
a
v
ailab
le.
T
h
u
s
,
th
is
s
tu
d
y
th
at
s
ee
k
s
to
f
i
n
d
o
u
t
as
s
ess
m
e
n
t
b
i
g
d
ata
in
Ni
g
er
ia
its
id
en
ti
f
icatio
n
,
g
e
n
er
atio
n
a
n
d
p
r
o
ce
s
s
in
g
i
n
t
h
e
o
p
in
io
n
s
o
f
t
h
e
e
x
p
er
ts
w
i
ll
co
n
tr
ib
u
te
t
o
th
e
li
ter
atu
r
e
o
n
ass
es
s
m
en
t b
i
g
d
ata.
T
h
is
s
tu
d
y
is
d
eli
m
ited
to
f
i
n
d
in
g
o
u
t t
h
e
o
p
in
io
n
o
f
a
s
s
e
s
s
m
en
t e
x
p
er
ts
o
n
s
o
u
r
ce
s
o
f
as
s
es
s
m
e
n
t b
ig
d
ata;
t
y
p
es
an
d
p
r
o
p
o
r
tio
n
s
o
f
ass
e
s
s
m
e
n
t
b
ig
d
ata;
p
r
o
b
lem
s
i
n
g
e
n
er
ati
n
g
a
n
d
p
r
o
ce
s
s
in
g
a
s
s
e
s
s
m
en
t
b
ig
d
ata;
an
d
th
e
f
u
t
u
r
e
o
f
as
s
ess
m
en
t b
ig
d
ata
in
Ni
g
er
ia.
2.
RE
S
E
ARC
H
M
E
T
H
O
D
T
h
e
s
tu
d
y
e
m
p
lo
y
ed
d
escr
ip
ti
v
e
s
u
r
v
e
y
d
esi
g
n
.
Su
r
v
e
y
r
e
s
e
ar
ch
d
esig
n
i
s
o
n
e
i
n
w
h
ic
h
a
g
r
o
u
p
o
f
ite
m
s
o
r
p
eo
p
le
ar
e
s
tu
d
ied
b
y
co
llectin
g
a
n
d
an
al
y
zi
n
g
d
ata
f
r
o
m
o
n
l
y
a
f
e
w
p
eo
p
le
o
r
item
s
co
n
s
id
er
ed
to
b
e
r
ep
r
esen
tativ
e
o
f
t
h
e
e
n
tire
g
r
o
u
p
[
2
0
,
2
1
]
.
T
h
is
d
esig
n
i
s
c
o
n
s
id
er
ed
ap
p
r
o
p
r
iate
f
o
r
th
e
p
r
esen
t
s
t
u
d
y
a
s
it
s
o
u
g
h
t
to
f
i
n
d
o
u
t
ass
e
s
s
m
en
t
b
ig
d
ata
in
Nig
er
ia
its
id
en
t
if
i
ca
tio
n
,
g
en
er
atio
n
an
d
p
r
o
ce
s
s
in
g
i
n
th
e
o
p
in
io
n
s
o
f
th
e
e
x
p
er
ts
.
T
h
e
p
o
p
u
latio
n
o
f
th
e
s
tu
d
y
co
n
s
is
ted
o
f
e
x
p
er
ts
in
ed
u
ca
tio
n
al
m
ea
s
u
r
e
m
en
t
an
d
e
v
al
u
atio
n
,
ed
u
ca
tio
n
r
esear
ch
an
d
s
tatis
t
ics.
P
u
r
p
o
s
iv
e
s
a
m
p
lin
g
tech
n
iq
u
e
w
as
u
s
ed
to
s
elec
t
f
o
r
t
y
-
f
i
v
e
(
4
5
)
ex
p
er
ts
f
r
o
m
1
0
u
n
i
v
er
s
itie
s
(
7
Fed
er
al;
3
State)
i
n
f
iv
e
g
eo
-
p
o
liti
ca
l
zo
n
es
i
n
Ni
g
er
ia.
T
h
ese
4
5
ex
p
er
ts
co
n
s
is
ted
o
f
20
m
a
les
a
n
d
2
5
f
e
m
ales
.
A
s
e
m
i
-
s
tr
u
ctu
r
ed
i
n
ter
v
ie
w
s
ch
ed
u
le
a
n
d
d
o
cu
m
e
n
t
s
wer
e
u
s
ed
to
co
llect
th
e
n
ec
e
s
s
ar
y
d
ata.
T
h
e
ex
p
er
ts
w
er
e
ask
ed
to
p
r
o
v
id
e
an
s
w
er
s
to
t
h
e
q
u
es
tio
n
s
p
o
s
ed
t
o
th
e
m
a
n
d
to
ass
i
g
n
r
ates
to
th
e
d
escr
ib
ed
an
s
w
er
s
in
a
s
ca
le
o
f
1
-
5
b
ased
o
n
its
r
elev
an
ce
.
T
h
e
h
ig
h
er
th
e
n
u
m
b
er
,
th
e
m
o
r
e
r
elev
an
ce
/
i
m
p
o
r
tan
ce
attac
h
ed
to
it.
T
h
e
q
u
an
titati
v
e
d
ata
wer
e
an
al
y
s
ed
u
s
i
n
g
f
r
eq
u
en
c
y
,
p
er
ce
n
tag
e,
m
ea
n
an
d
s
tan
d
ar
d
d
ev
iatio
n
,
w
h
ile
th
e
m
es
i
n
th
e
q
u
alitati
v
e
d
ata
w
er
e
id
en
t
if
ied
a
n
d
u
s
ed
to
s
u
p
p
o
r
t
q
u
an
titati
v
e
d
ata
g
at
h
er
ed
.
T
h
e
r
esu
lts
w
er
e
d
escr
ib
ed
an
d
p
r
esen
ted
.
3.
RE
SU
L
T
S
AND
D
I
SCU
SS
I
O
N
3
.
1
.
Resea
rc
h
qu
e
s
t
io
n
1
:
Wha
t
a
re
t
he
s
o
urce
s
o
f
a
s
s
ess
m
e
nt
big
da
t
a
in Nig
er
ia
?
T
ab
le
1
p
r
esen
ts
s
o
u
r
ce
s
o
f
a
s
s
es
s
m
en
t
b
ig
d
ata
in
s
ec
o
n
d
ar
y
s
c
h
o
o
ls
as
id
en
tifie
d
b
y
th
e
ex
p
er
ts
in
ter
v
ie
w
ed
.
T
h
r
ee
s
o
u
r
ce
s
o
f
ass
e
s
s
m
e
n
t
b
ig
d
ata
in
s
ec
o
n
d
ar
y
s
c
h
o
o
ls
w
er
e
m
e
n
tio
n
ed
b
y
m
o
r
e
th
a
n
h
al
f
(
≥
2
3
)
o
f
th
e
ex
p
er
ts
in
ter
v
ie
w
ed
.
I
n
T
ab
le
2
,
th
e
id
en
tifie
d
s
o
u
r
ce
s
o
f
as
s
es
s
m
en
t
b
i
g
d
ata
in
u
n
i
v
er
s
itie
s
ac
co
r
d
in
g
to
ex
p
er
ts
’
o
p
in
io
n
ar
e
p
r
esen
ted
.
Fo
u
r
o
u
t
o
f
s
ix
s
o
u
r
ce
s
id
en
ti
f
ied
w
er
e
m
en
ti
o
n
ed
b
y
m
o
r
e
th
a
n
h
al
f
(
≥
2
3
)
o
f
th
e
ex
p
er
ts
i
n
ter
v
ie
w
ed
.
C
o
u
r
s
e
w
o
r
k
r
esu
l
ts
w
er
e
m
en
t
io
n
ed
b
y
all
t
h
e
in
te
r
v
ie
w
ee
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
E
v
al
&
R
e
s
E
d
u
c
.
I
SS
N:
2252
-
8822
A
s
s
es
s
men
t b
ig
d
a
ta
in
N
ig
eria
:
I
d
e
n
tif
ica
tio
n
,
g
e
n
era
tio
n
a
n
d
…
(
N
ke
ch
i P
a
tr
icia
-
Ma
r
y
E
s
o
mo
n
u
)
347
T
ab
le
1
.
So
u
r
ce
s
o
f
ass
es
s
m
e
n
t b
ig
d
ata
in
s
ec
o
n
d
ar
y
s
ch
o
o
l
s
f
r
o
m
e
x
p
er
ts
’
o
p
in
io
n
s
S
/
N
D
e
scri
p
t
i
o
n
F
r
e
q
u
e
n
c
y
P
e
r
c
e
n
t
a
g
e
1
I
n
t
e
r
n
a
l
a
n
d
Ex
t
e
r
n
a
l
Ex
a
m
i
n
a
t
i
o
n
s
a
n
d
A
sse
ssm
e
n
t
s
43
9
5
.
5
%
2
e
-
f
e
e
d
b
a
c
k
o
f
st
u
d
e
n
t
s
e
v
a
l
u
a
t
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s
s
io
n
p
r
o
ce
s
s
es,
s
tu
d
e
n
ts
p
r
o
v
id
e
th
eir
b
io
d
ata
b
y
f
i
lli
n
g
i
n
f
o
r
m
s
i
n
h
a
r
d
co
p
ies.
B
io
m
etr
ic
s
o
f
s
t
u
d
en
t
s
ar
e
also
ca
p
tu
r
ed
o
n
lin
e.
A
t
t
h
e
B
asic
E
d
u
ca
tio
n
an
d
Seco
n
d
ar
y
Sc
h
o
o
l
lev
els,
s
t
u
d
en
ts
d
o
m
id
ter
m
test
s
,
co
n
tin
u
o
u
s
ass
e
s
s
m
en
t
an
d
ter
m
l
y
ex
a
m
i
n
atio
n
s
.
T
h
is
is
d
o
n
e
th
r
ee
ti
m
es
a
y
ea
r
.
I
n
N
ig
er
ia,
th
e
s
e
ar
e
p
r
ed
o
m
i
n
an
tl
y
ca
r
r
ied
o
u
t
u
s
in
g
p
ap
er
an
d
p
en
cil
test
.
B
u
t
th
e
ter
m
l
y
ex
a
m
i
n
atio
n
r
esu
l
ts
ar
e
p
u
b
lis
h
ed
o
n
li
n
e.
A
t
th
e
en
d
o
f
Se
n
io
r
Seco
n
d
ar
y
i
n
Ni
g
er
ia,
s
tu
d
e
n
ts
s
ea
t
f
o
r
e
x
ter
n
al
ex
a
m
i
n
ati
o
n
s
co
n
d
u
cted
b
y
d
i
f
f
er
en
t
e
x
a
m
in
at
io
n
b
o
d
ies.
So
m
e
o
f
t
h
e
m
ar
e
W
est
Af
r
i
ca
n
E
x
a
m
i
n
atio
n
C
o
u
n
cil
(
W
A
E
C
)
,
Natio
n
al
E
x
a
m
i
n
atio
n
C
o
u
n
c
il
(
NE
C
O)
,
Natio
n
al
B
u
s
i
n
es
s
a
n
d
T
ec
h
n
ical
E
d
u
ca
tio
n
B
o
ar
d
(
NA
B
T
E
B
)
.
Fo
r
th
e
ex
a
m
i
n
atio
n
s
c
o
n
d
u
cted
b
y
t
h
e
s
es
b
o
d
ies,
th
e
ca
n
d
id
ates
r
e
g
is
te
r
o
n
lin
e,
ta
k
e
t
h
e
p
ap
er
an
d
p
en
cil
ex
a
m
i
n
atio
n
b
u
t
th
e
ir
r
esu
lt
s
s
co
r
es
ar
e
ca
p
tu
r
ed
o
n
lin
e
f
r
o
m
w
h
ich
b
i
g
ass
e
s
s
m
e
n
t d
ata
ar
e
g
en
er
ate
d
.
A
cc
o
r
d
in
g
l
y
,
i
n
s
tit
u
tio
n
s
g
e
n
er
ate
b
ig
d
ata
th
r
o
u
g
h
th
e
c
o
n
d
u
ct
o
f
co
m
p
u
ter
-
b
ased
e
x
a
m
in
at
io
n
[
2
2
,
2
3
]
.
T
h
e
J
o
in
t
A
d
m
i
s
s
io
n
an
d
Ma
tr
icu
latio
n
B
o
ar
d
(
J
A
MB
)
w
h
ic
h
is
th
e
Ni
g
er
ian
en
tr
an
ce
ex
a
m
in
at
io
n
b
o
ar
d
f
o
r
ter
tiar
y
le
v
el,
r
eg
i
s
ter
ca
n
d
id
ates
o
n
lin
e,
d
o
co
m
p
u
ter
-
b
ased
ex
a
m
i
n
atio
n
an
d
r
esu
lts
ca
p
t
u
r
ed
o
n
lin
e.
Mo
s
t
u
n
iv
er
s
ities
i
n
Nig
er
ia
also
co
n
d
u
ct
P
o
s
t
Un
i
f
ied
T
er
tiar
y
Ma
tr
icu
la
ti
o
n
E
x
a
m
in
at
io
n
as
a
f
u
r
t
h
er
s
cr
ee
n
i
n
g
f
o
r
ca
n
d
id
ates
s
ee
k
i
n
g
ad
m
is
s
io
n
i
n
t
o
th
e
u
n
i
v
er
s
i
ties
.
I
n
m
an
y
o
f
th
e
u
n
i
v
er
s
itie
s
,
th
e
ca
n
d
id
ates
r
e
g
is
ter
o
n
lin
e,
th
e
y
d
o
co
m
p
u
ter
-
b
ased
ex
a
m
in
at
io
n
an
d
t
h
e
r
es
u
lts
ar
e
ca
p
tu
r
ed
an
d
p
u
b
lis
h
ed
o
n
li
n
e.
C
a
n
d
id
ates
w
h
o
ar
e
ad
m
itted
s
u
p
p
l
y
th
ei
r
b
io
d
ata
o
n
lin
e
d
u
r
i
n
g
t
h
e
f
i
r
s
t
an
d
s
u
b
s
eq
u
e
n
t
r
eg
is
tr
atio
n
s
.
T
h
er
e
ar
e
p
h
y
s
i
ca
l
clea
r
an
ce
p
r
o
ce
s
s
es
w
h
er
e
b
io
m
etr
ics
i
s
ap
p
lied
.
I
n
li
n
e
w
ith
th
is
A
w
o
r
a
n
ti
in
h
is
s
tu
d
ie
s
n
o
ted
t
h
ese
u
n
iv
er
s
ities
t
h
at
ar
e
i
m
p
le
m
e
n
ti
n
g
th
e
e
-
ex
a
m
i
n
atio
n
in
s
cr
ee
n
i
n
g
an
d
as
s
es
s
m
en
t o
f
th
eir
s
t
u
d
en
t
s
[
2
4
,
2
5
]
.
Ho
w
e
v
er
,
m
o
s
t
o
f
th
e
ac
ad
e
m
ic
o
r
lear
n
in
g
as
s
es
s
m
e
n
t
o
f
t
h
e
s
tu
d
en
t
s
is
t
h
r
o
u
g
h
class
r
o
o
m
co
n
tacts,
u
s
e
p
ap
e
r
an
d
p
en
cil
i
n
i
n
-
co
u
r
s
e
a
s
s
ess
m
en
t
s
a
n
d
ex
a
m
i
n
atio
n
s
a
r
e
d
o
n
e.
Stu
d
en
ts
p
r
esen
t
s
e
m
i
n
ar
s
,
ca
r
r
y
o
u
t
a
n
d
d
ef
en
d
t
h
eir
p
r
o
jects,
th
es
es
an
d
d
is
s
er
tatio
n
s
.
B
u
t,
m
an
y
o
f
t
h
e
s
u
m
m
ati
v
e
ev
alu
a
tio
n
d
ata
ar
e
g
en
er
ated
an
d
p
u
b
lis
h
ed
o
n
lin
e.
A
d
m
i
n
is
tr
ati
v
e
s
ta
f
f
teac
h
er
s
an
d
lectu
r
er
s
d
o
a
lo
t
o
f
d
o
cu
m
en
tatio
n
d
u
r
i
n
g
e
m
p
lo
y
m
en
t.
T
h
er
e
ar
e
an
n
u
al
ap
p
r
aisals
o
f
s
ta
f
f
in
ed
u
ca
tio
n
in
s
tit
u
tio
n
s
a
n
d
a
lo
t
o
f
d
ata
ar
e
g
en
er
ated
.
3
.
4
.
Resea
rc
h
qu
e
s
t
io
n
4
:
H
o
w
is
a
s
s
ess
m
ent
big
da
t
a
us
ed
in
Nig
er
ia
?
I
n
T
ab
le
6
,
th
e
id
en
ti
f
ied
u
s
es
o
f
a
s
s
es
s
m
en
t
b
ig
d
ata
i
n
Nig
er
ia
ac
co
r
d
in
g
to
ex
p
er
t
s
’
o
p
in
io
n
s
ar
e
p
r
esen
ted
.
E
ig
h
t
o
u
t
o
f
t
en
u
s
e
s
id
en
ti
f
ied
w
er
e
m
e
n
t
io
n
ed
b
y
m
o
r
e
t
h
an
h
al
f
(
≥
2
3
)
o
f
th
e
ex
p
er
ts
in
ter
v
ie
w
ed
.
T
ab
le
6
.
Uses
o
f
ass
es
s
m
en
t b
i
g
d
ata
in
N
i
g
er
ia
f
r
o
m
e
x
p
er
ts
’
o
p
in
io
n
s
S
/
N
I
n
N
i
g
e
r
i
a
a
sse
ssm
e
n
t
b
i
g
d
a
t
a
i
s
u
se
d
f
o
r
…
F
r
e
q
u
e
n
c
y
P
e
r
c
e
n
t
a
g
e
1
a
d
m
i
ssi
o
n
p
u
r
p
o
se
s
30
6
6
.
7
%
2
P
r
o
mo
t
i
o
n
s
25
5
5
.
6
%
3
mo
n
i
t
o
r
i
n
g
s
t
u
d
e
n
t
s’
l
e
a
r
n
i
n
g
40
8
8
.
8
%
4
st
u
d
e
n
t
s
c
e
r
t
i
f
i
c
a
t
i
o
n
45
1
0
0
%
5
c
u
r
r
i
c
u
l
u
m
mo
d
i
f
i
c
a
t
i
o
n
s
20
4
4
.
4
%
6
e
a
r
n
i
n
g
a
w
a
r
d
s
35
7
7
.
7
%
7
a
ssi
g
n
me
n
t
o
f
g
r
a
d
e
s
43
9
5
.
6
%
8
sch
o
o
l
c
o
mp
a
r
i
so
n
35
7
7
.
7
%
9
su
p
e
r
v
i
si
o
n
i
n
a
d
j
u
st
i
n
g
t
e
a
c
h
i
n
g
a
n
d
l
e
a
r
n
i
n
g
30
6
6
.
7
%
10
g
o
v
e
r
n
me
n
t
d
e
c
i
si
o
n
m
a
k
i
n
g
21
4
6
.
7
%
S
o
u
rc
e
:
A
u
t
h
o
rs
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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t J
E
v
al
&
R
e
s
E
d
u
c
.
I
SS
N:
2252
-
8822
A
s
s
es
s
men
t b
ig
d
a
ta
in
N
ig
eria
:
I
d
e
n
tif
ica
tio
n
,
g
e
n
era
tio
n
a
n
d
…
(
N
ke
ch
i P
a
tr
icia
-
Ma
r
y
E
s
o
mo
n
u
)
349
3
.
5
.
Resea
rc
h
qu
e
s
t
io
n
5
:
H
o
w
a
re
big
da
t
a
in a
s
s
ess
m
e
nt
pr
o
ce
s
s
ed?
C
u
r
r
en
tl
y
i
n
Nig
er
ia,
p
r
o
ce
s
s
in
g
o
f
ass
e
s
s
m
e
n
t
d
ata
-
d
ata
co
llectio
n
,
en
ter
in
g
,
an
al
y
s
i
n
g
an
d
r
ep
o
r
tin
g
o
f
t
h
e
f
in
d
i
n
g
s
–
a
r
e
d
o
n
e
o
n
lin
e
a
n
d
also
p
u
b
l
is
h
ed
o
n
l
in
e.
E
x
a
m
in
a
tio
n
b
o
d
ies
lik
e
W
A
E
C
,
NE
C
O,
N
A
B
T
E
B
an
d
J
A
MB
d
o
o
n
lin
e
r
eg
i
s
tr
atio
n
o
f
th
e
ir
ca
n
d
id
ates.
T
h
e
y
p
r
o
ce
s
s
an
d
p
u
b
lis
h
th
eir
r
es
u
lt
s
o
n
lin
e.
Ma
n
y
u
n
i
v
er
s
it
ies
u
s
e
b
io
m
e
tr
ics
i
n
h
an
d
li
n
g
t
h
e
s
tu
d
e
n
ts
’
b
io
lo
g
ical
d
ata.
S
o
m
e
in
s
tit
u
tio
n
s
d
o
en
g
a
g
e
t
h
e
s
er
v
ices
o
f
co
m
p
a
n
ies
o
r
f
ir
m
s
i
n
p
r
o
ce
s
s
i
n
g
th
eir
ass
es
s
m
e
n
t
d
ata.
Ho
w
ev
er
,
in
ca
lcu
la
tin
g
a
n
d
r
ep
o
r
tin
g
o
f
ass
ess
m
e
n
t
b
ig
d
ata
in
Nig
er
ia
s
i
m
p
le
d
escr
ip
t
iv
e
s
tati
s
tics
ar
e
m
ai
n
l
y
u
s
ed
.
C
u
r
r
en
tl
y
,
lack
o
f
s
u
b
s
ta
n
tial
d
ata
b
ase
i
s
a
p
r
o
b
le
m
.
T
h
e
ex
i
s
ti
n
g
b
ig
d
ata
ar
e
m
o
s
tl
y
co
m
p
r
e
s
s
ed
,
i
n
f
er
en
tial
s
tati
s
tics
ar
e
m
o
s
tl
y
u
s
ed
to
ca
lcu
late
co
n
f
id
en
ce
i
n
ter
v
al
an
d
esti
m
a
to
r
s
ar
e
u
s
ed
to
h
an
d
le
p
o
p
u
latio
n
p
ar
a
m
eter
s
.
W
ith
th
e
s
e,
m
a
n
y
d
ata
ar
e
n
o
t
an
al
y
s
ed
an
d
a
lo
t o
f
in
f
o
r
m
at
i
o
n
ar
e
lo
s
t.
3
.
6
.
Resea
rc
h
qu
estio
n
6
:
Wha
t
a
re
t
he
pro
ble
m
s
in
g
ener
a
t
i
ng
a
nd
pro
ce
s
s
ing
a
s
s
es
s
m
e
nt
big
da
t
a
i
n
Nig
er
ia
?
T
ab
le
7
s
h
o
w
s
t
h
e
m
ea
n
a
n
d
s
tan
d
ar
d
d
ev
iatio
n
o
f
ex
p
er
ts
’
o
p
in
io
n
s
r
ati
n
g
s
o
n
p
r
o
b
lem
s
i
n
g
en
er
ati
n
g
an
d
p
r
o
ce
s
s
i
n
g
a
s
s
ess
m
en
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scri
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Resea
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:
Wha
t
is
t
he
f
uture
o
f
a
s
s
ess
m
e
nt
bi
g
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t
a
in Nig
er
ia
?
T
ab
le
8
s
h
o
w
s
t
h
e
m
ea
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an
d
s
tan
d
ar
d
d
ev
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n
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f
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p
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in
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g
s
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ir
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ce
iv
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f
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t
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r
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o
f
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e
s
s
m
e
n
t
b
ig
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ata
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n
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g
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ia.
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h
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m
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s
r
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ed
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m
2
.
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3
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d
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n
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i
m
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s
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t
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s
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ab
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.
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h
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fu
t
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r
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s
s
m
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t b
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d
ata
in
N
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as r
ated
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I
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S
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:
A
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rs
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T
h
e
s
co
r
es
g
en
er
ated
w
er
e
m
o
s
tl
y
u
s
ed
f
o
r
s
elec
tio
n
,
p
r
o
m
o
tio
n
an
d
p
lace
m
en
t
as
o
b
s
er
v
ed
in
T
ab
le
6
.
R
esear
ch
e
s
o
n
m
o
d
elli
n
g
f
o
r
p
r
ed
ictin
g
f
u
t
u
r
e
b
eh
av
io
u
r
o
f
s
tu
d
en
t
s
,
an
d
i
m
p
r
o
v
e
m
en
t
i
n
ac
h
iev
e
m
e
n
t
w
h
ic
h
ar
e
th
e
h
al
l
m
ar
k
o
f
b
u
ild
in
g
d
atab
ase
ar
e
g
r
o
s
s
l
y
n
e
g
lecte
d
[
2
4
,
2
6
,
2
7
]
.
T
h
e
ex
p
er
ts
ar
e
n
o
t d
o
in
g
t
h
e
n
ee
d
f
u
l
b
ec
au
s
e
w
h
a
t p
eo
p
le
d
o
n
o
t k
n
o
w
,
t
h
e
y
ca
n
n
o
t
m
ea
s
u
r
e,
w
h
at
th
e
y
d
o
n
o
t
m
ea
s
u
r
e,
th
e
y
c
an
n
o
t j
u
d
g
e.
As
o
b
s
er
v
ed
i
n
T
ab
le
7
,
lo
w
a
w
ar
e
n
es
s
o
n
t
h
e
n
ee
d
/ad
v
a
n
tag
e
s
o
f
as
s
ess
m
e
n
t
b
i
g
d
at
a,
s
ec
u
r
it
y
is
s
u
es
in
co
n
tr
ac
t
in
g
d
ata
an
al
y
s
t
an
d
lo
w
le
v
el
o
f
in
f
r
as
tr
u
c
tu
r
al
d
ev
elo
p
m
e
n
t
an
d
tech
n
ic
al
k
n
o
w
h
o
w
w
er
e
id
en
ti
f
ied
as
th
e
m
aj
o
r
p
r
o
b
le
m
i
n
g
e
n
er
atin
g
an
d
p
r
o
ce
s
s
in
g
ass
es
s
m
en
t
b
ig
d
ata.
T
h
is
is
in
ag
r
ee
m
en
t
w
it
h
p
o
ten
tial
ch
alle
n
g
e
s
in
g
en
er
a
tin
g
an
d
an
al
y
s
i
n
g
b
ig
d
ata
s
tip
u
lated
b
y
Ha
m
m
er
et
al
an
d
Ma
cf
ad
y
e
n
et
al
in
g
en
er
ati
n
g
a
n
d
an
al
y
s
i
n
g
b
ig
d
ata
[
2
8
,
2
9
]
.
I
t
is
also
in
li
n
e
w
i
th
R
aj
ag
o
p
alan
,
a
n
d
C
o
p
e
an
d
Kala
n
tzis
w
h
o
p
r
o
p
o
s
es
th
at
f
o
r
an
ea
s
y
g
e
n
e
r
atin
g
a
n
d
p
r
o
ce
s
s
i
n
g
o
f
as
s
es
s
m
e
n
t
b
i
g
d
at
a,
ef
f
ec
ti
v
e
i
n
s
ti
t
u
tio
n
al
tech
n
o
lo
g
y
in
f
r
astru
ct
u
r
e
is
r
eq
u
ir
ed
[
3
0
,
3
1
]
.
I
n
Nig
er
ia,
it
is
h
o
p
ed
th
at
t
h
er
e
w
ill
b
e
an
in
cr
ea
s
e
in
t
h
e
co
m
p
u
ter
-
b
ased
lear
n
in
g
en
v
ir
o
n
m
en
t
w
h
ic
h
w
ill
in
cr
ea
s
e
p
o
w
er
an
d
ab
ilit
y
to
lo
g
f
i
n
e
-
g
r
ai
n
ed
d
ata
ab
o
u
t
s
t
u
d
en
t
s
’
lear
n
i
n
g
.
W
ith
t
h
e
tr
ain
i
n
g
an
d
r
etr
ain
in
g
o
f
I
n
f
o
r
m
at
io
n
an
d
C
o
m
m
u
n
ica
tio
n
T
ec
h
n
o
lo
g
y
(
I
C
T
)
o
f
f
icer
s
,
b
ig
d
ata
in
ed
u
c
atio
n
w
ill
b
e
b
etter
h
an
d
led
.
T
h
e
f
u
ll
b
en
e
f
it
o
f
b
ig
d
ata
in
th
e
s
y
s
te
m
w
ill
b
eg
in
to
m
an
i
f
e
s
t
w
h
e
n
cr
itical
d
ec
is
io
n
s
ar
e
tak
e
n
b
ased
o
n
r
e
s
u
lt
s
o
f
d
ata
a
n
al
y
s
is
a
n
d
w
h
e
n
t
h
e
as
s
es
s
m
e
n
t
b
ig
d
ata
in
f
o
r
m
p
o
lic
y
.
T
h
er
e
s
h
o
u
ld
b
e
s
tr
ateg
ic
p
lan
s
f
o
r
co
llectin
g
d
ata,
r
ec
o
r
d
cr
ea
tin
g
in
all
ed
u
ca
t
io
n
ac
tiv
itie
s
.
T
h
er
e
s
h
o
u
ld
b
e
ed
u
ca
tio
n
h
is
to
r
y
f
o
r
p
u
p
ils
a
n
d
s
t
u
d
en
t
s
.
T
h
is
w
i
l
l
h
elp
i
n
d
esi
g
n
i
n
g
m
o
d
els
f
o
r
ex
p
lain
i
n
g
lear
n
er
s
’
b
e
h
av
io
u
r
,
attit
u
d
e,
an
d
ac
h
iev
e
m
e
n
t
an
d
s
o
o
n
.
T
h
e
n
ec
es
s
ar
y
in
f
r
astr
u
ct
u
r
e
f
o
r
g
en
er
atin
g
an
d
an
al
y
s
i
n
g
co
m
p
l
ex
d
ata
n
ee
d
s
to
b
e
p
u
t in
p
lace
.
4.
CO
NCLU
SI
O
N
T
h
e
r
esear
ch
er
s
f
r
o
m
th
e
f
i
n
d
in
g
s
o
f
t
h
is
s
t
u
d
y
co
n
c
lu
d
e
th
at
t
h
er
e
ex
i
s
ts
lo
w
a
war
en
ess
o
n
th
e
ad
v
an
tag
e
s
o
f
ass
e
s
s
m
e
n
t
b
ig
d
ata
f
r
o
m
th
e
p
ar
t
o
f
p
o
licy
m
a
k
er
s
i
n
Nig
er
ia.
T
h
e
a
m
a
s
s
ed
ass
es
s
m
en
t
b
ig
d
ata
m
a
in
l
y
en
d
s
u
p
in
s
t
u
d
en
ts
’
p
lace
m
e
n
t
a
n
d
ce
r
tif
ic
a
tio
n
.
W
ith
a
d
ev
elo
p
ed
d
ata
b
ase
s
y
s
te
m
,
ea
s
y
g
en
er
ati
n
g
,
p
r
o
ce
s
s
in
g
an
d
ac
ce
s
s
i
n
g
o
f
a
s
s
es
s
m
en
t
b
i
g
d
ata
m
a
y
b
e
estab
lis
h
ed
.
T
h
en
th
e
f
u
ll
b
en
e
f
it
o
f
ass
es
s
m
en
t b
i
g
d
ata
w
i
ll
m
a
n
i
f
est as c
r
itical
d
ec
is
io
n
s
ta
k
en
ar
e
b
ased
o
n
r
esu
lts
o
f
d
ata
an
al
y
s
i
s
.
T
h
er
e
is
n
ee
d
f
o
r
th
e
s
tak
e
h
o
ld
er
s
to
cr
ea
te
aw
ar
en
e
s
s
o
n
t
h
e
i
m
p
o
r
tan
ce
o
f
b
ig
d
ata
in
th
e
m
o
d
er
n
ed
u
ca
tio
n
s
y
s
te
m
to
i
m
p
r
o
v
e
l
ea
r
n
er
s
’
p
er
f
o
r
m
a
n
ce
.
T
h
er
e
s
h
o
u
ld
b
e
a
s
tr
ate
g
ic
p
la
n
i
n
b
u
ild
in
g
o
u
r
d
atab
ase
to
g
ain
th
e
ad
v
a
n
ta
g
es
o
f
b
ig
d
ata.
T
h
e
in
f
r
astr
u
ct
u
r
al
an
d
tech
n
o
lo
g
ical
m
ater
ials
n
ec
ess
ar
y
f
o
r
b
ig
d
ata
o
p
er
atio
n
s
h
o
u
ld
b
e
p
u
t
in
p
lace
.
T
h
er
e
is
n
ee
d
t
o
im
p
r
o
v
e
th
e
in
ter
n
et
co
n
n
ec
ti
v
it
y
,
an
d
elec
tr
ic
p
o
w
er
s
u
p
p
l
y
in
i
n
s
tit
u
tio
n
s
.
T
r
ai
n
in
g
a
n
d
r
etr
ain
i
n
g
ar
e
i
m
p
er
ativ
e
to
m
a
k
e
t
h
e
o
p
er
ato
r
s
an
d
s
ta
f
f
o
f
ed
u
ca
tio
n
e
n
ter
p
r
is
e
co
m
p
u
te
r
an
d
in
ter
n
et
co
m
p
lia
n
t
an
d
ef
f
icien
t.
B
io
m
etr
ic
d
ata
ca
p
tu
r
in
g
n
ee
d
to
b
e
ex
p
an
d
ed
in
h
a
n
d
li
n
g
lear
n
er
s
’
is
s
u
e
s
i
n
ad
m
i
s
s
io
n
,
r
eg
i
s
t
r
atio
n
an
d
p
r
ed
ictin
g
lear
n
er
s
’
f
u
tu
r
e
b
eh
a
v
io
u
r
an
d
p
er
f
o
r
m
an
ce
.
RE
F
E
R
E
NC
E
S
[1
]
S
.
M
u
k
h
e
rjee
a
n
d
R
.
S
h
o
w
,
“
B
ig
d
a
ta
-
Co
n
c
e
p
ts,
A
p
p
li
c
a
ti
o
n
s,
c
h
a
ll
e
n
g
e
s
a
n
d
F
u
t
u
re
S
c
o
p
e
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
A
d
v
a
n
c
e
d
Res
e
a
rc
h
in
Co
mp
u
ter
a
n
d
Co
mm
u
n
ica
ti
o
n
E
n
g
i
n
e
e
rin
g
,
v
o
l.
5
,
n
o
.
2
,
p
p
.
6
6
-
7
4
,
2
0
1
6
.
[2
]
M
.
A
k
taru
z
z
a
m
a
n
,
M
.
R.
H.
S
h
a
m
i
m
,
a
n
d
C.
K.
Clem
e
n
t,
“
T
re
n
d
s
a
n
d
issu
e
s
to
i
n
teg
ra
te
ICT
in
tea
c
h
in
g
lea
rn
in
g
f
o
r
th
e
f
u
tu
re
w
o
rld
o
f
e
d
u
c
a
ti
o
n
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
En
g
in
e
e
rin
g
&
T
e
c
h
n
o
lo
g
y
IJ
ET
-
IJ
ENS
,
v
o
l.
1
1
,
n
o
.
3
,
pp
.
1
1
4
-
1
1
9
,
2
0
1
1
.
[3
]
M.
V.
A
d
e
g
b
ij
a
,
M
.
A
.
F
a
k
o
m
o
g
b
o
n
,
a
n
d
F
.
O.
Da
ra
m
o
la,
“
T
h
e
n
e
w
tec
h
n
o
lo
g
ies
a
n
d
th
e
c
o
n
d
u
c
t
o
f
e
-
e
x
a
m
in
a
ti
o
n
s:
A
c
a
se
stu
d
y
o
f
Na
ti
o
n
a
l
Op
e
n
Un
iv
e
rsity
o
f
Nig
e
ria,”
Brit
ish
J
o
u
rn
a
l
o
f
S
c
ien
c
e
,
v
o
l.
3
,
n
o
.
5
9
,
2
0
1
2
.
[4
]
UN
ES
CO
In
stit
u
te
f
o
r
S
tatisti
c
s
(UIS)
,
“
I
n
tern
a
ti
o
n
a
l
S
tan
d
a
rd
Clas
sif
ica
ti
o
n
o
f
E
d
u
c
a
ti
o
n
:
IS
CED
2
0
1
1
,
”
M
o
n
trea
l:
UN
ES
CO
In
stit
u
te
f
o
r
S
tatisti
c
s,
2
0
1
2
.
[
O
n
li
n
e
]
.
A
v
a
il
a
b
le:
h
tt
p
:
//
ww
w
.
u
is.u
n
e
sc
o
.
o
rg
/E
d
u
c
a
ti
o
n
/D
o
c
u
m
e
n
ts/i
sc
e
d
-
2
0
1
1
-
e
n
.
p
d
f
[5
]
P
.
Nit
h
y
a
,
B.
Um
a
m
a
h
e
s
w
a
ri,
a
n
d
A
.
Um
a
d
e
ri,
“
A
su
rv
e
y
o
n
e
d
u
c
a
ti
o
n
a
l
d
a
t
a
m
in
in
g
i
n
f
ield
o
f
e
d
u
c
a
ti
o
n
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
A
d
v
a
n
c
e
Res
e
a
rc
h
in
C
o
mp
u
ter
En
g
in
e
e
rin
g
a
n
d
T
e
c
h
n
o
l
o
g
y
(
IJ
AR
CET
),
v
o
l.
5
,
n
o
.
1
,
p
p
.
6
9
-
7
8
,
2
0
1
6
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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&
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.
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s
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a
tr
icia
-
Ma
r
y
E
s
o
mo
n
u
)
351
[6
]
L
.
I.
El
e
je,
N.P
.
M
.
Eso
m
o
n
u
,
a
n
d
F
.
N.
Uf
e
a
ro
,
“
T
re
n
d
s
in
in
f
o
rm
a
t
io
n
a
n
d
c
o
m
m
u
n
ica
ti
o
n
tec
h
n
o
lo
g
y
a
n
d
lea
rn
in
g
a
ss
e
ss
m
e
n
t:
th
e
a
p
p
li
c
a
ti
o
n
a
n
d
i
m
p
li
c
a
ti
o
n
,
”
In
ter
n
a
ti
o
n
a
l
E
d
u
c
a
ti
o
n
a
l
Ap
p
li
e
d
Res
e
a
rc
h
J
o
u
rn
a
l
(
IEA
RJ)
,
v
o
l.
0
3
,
n
o
.
1
1
,
2
0
1
9
.
[7
]
L
.
F
.
G
u
l,
“
T
h
e
c
h
a
n
g
i
n
g
tren
d
s
i
n
e
d
u
c
a
ti
o
n
,
”
IC
T
,
v
o
l.
2
,
n
o
.
1
2
0
1
5
.
[
On
l
in
e
]
.
A
v
a
il
a
b
le:
h
tt
p
s:/
/www
.
f
ro
n
ti
e
rsin
.
o
rg
/article
s/1
0
.
3
3
8
9
/f
ict.
2
0
1
5
.
0
0
0
0
1
/f
u
ll
[8
]
N.
G
u
,
L
.
F
.
G
ü
l,
A
.
W
il
li
a
m
s,
a
n
d
W
.
Na
k
a
p
a
n
,
“
Co
n
q
u
e
ri
n
g
n
e
w
w
o
rld
s,”
Pro
c
e
e
d
in
g
s
o
f
th
e
1
4
th
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
C
o
mp
u
ter
Ai
d
e
d
Arc
h
it
e
c
tu
ra
l
De
sig
n
Res
e
a
rc
h
in
Asia
/Y
u
n
li
n
(
T
a
i
wa
n
),
Betw
e
e
n
M
a
n
a
n
d
M
a
c
h
in
e
?
I
n
teg
r
a
ti
o
n
,
I
n
t
u
it
io
n
,
I
n
telli
g
e
n
c
e
2
0
0
9
,
T
a
iwa
n
,
p
p
.
1
5
3
-
1
6
4
,
2
0
0
9
.
[9
]
Un
it
e
d
Na
ti
o
n
s
Ed
u
c
a
ti
o
n
a
l,
S
c
i
e
n
ti
f
ic
a
n
d
Cu
lt
u
ra
l
Org
a
n
iza
ti
o
n
,
T
h
e
d
a
t
a
re
v
o
lu
ti
o
n
i
n
e
d
u
c
a
ti
o
n
.
Ca
n
a
d
a
:
S
u
c
c
u
rsa
le Cen
tre
-
V
i
ll
e
M
o
n
trea
l
,
Qu
e
b
e
c
,
2
0
1
7
.
[1
0
]
C.
T
h
il
le,
E.
S
c
h
n
e
id
e
r,
R.
F
.
Ki
z
il
e
e
c
,
C.
P
iec
h
,
S
.
A
.
Ha
la
w
a
,
a
n
d
D.
K.
G
re
e
n
e
,
“
T
h
e
f
u
tu
re
o
f
d
a
ta
-
e
n
rich
e
d
a
ss
e
ss
m
e
n
t,
”
In
J
.
Br
o
w
n
(Ed
.
),
Res
e
a
rc
h
a
n
d
Pra
c
ti
c
e
i
n
Asse
ss
me
n
t.
S
p
e
c
ia
l
Iss
u
e
:
Bi
g
d
a
ta
a
n
d
lea
rn
in
g
a
n
a
lytics
,
v
o
l.
9
,
p
p
.
5
-
1
4
,
2
0
1
4
.
[1
1
]
J
.
M
u
sk
in
,
“
T
h
e
d
a
ta
re
v
o
lu
ti
o
n
a
n
d
e
d
u
c
a
ti
o
n
p
o
st
-
2
0
1
5
:
C
o
n
si
d
e
rin
g
th
e
p
r
o
m
ise
a
n
d
t
h
e
risk
s
,
”
2
0
1
5
.
[
On
l
in
e
].
Av
a
il
a
b
le:
h
tt
p
s://
w
ww
.
b
ro
o
k
in
g
s.e
d
u
/
b
lo
g
/ed
u
c
a
ti
o
n
-
p
lu
s
-
d
e
v
e
lo
p
m
e
n
t/
2
0
1
5
/
0
3
/3
1
/t
h
e
-
d
a
ta
-
re
v
o
lu
ti
o
n
-
a
n
d
-
e
d
u
c
a
ti
o
n
-
p
o
st
-
2
0
1
5
-
c
o
n
si
d
e
rin
g
-
th
e
-
p
ro
m
ise
-
a
n
d
-
th
e
-
risk
s/
[1
2
]
J.
Cre
ss
w
e
ll
,
U.
S
c
h
w
a
n
tn
e
r,
a
n
d
C.
W
a
ters
,
A
r
e
v
iew
o
f
in
ter
n
a
ti
o
n
a
l
la
r
g
e
-
sc
a
le
a
ss
e
ss
me
n
ts
in
e
d
u
c
a
t
i
o
n
:
a
ss
e
ss
in
g
c
o
m
p
o
n
e
n
t
sk
il
ls
a
n
d
c
o
ll
e
c
ti
n
g
c
o
n
tex
tu
a
l
d
a
ta
.
P
a
ris
:
Org
a
n
isa
ti
o
n
f
o
r
Eco
n
o
m
ic
Co
-
o
p
e
ra
ti
o
n
a
n
d
De
v
e
lo
p
m
e
n
t,
2
0
1
5
.
[1
3
]
S
.
A
n
irb
a
n
,
“
Big
d
a
ta
a
n
a
ly
ti
c
s
in
th
e
e
d
u
c
a
ti
o
n
se
c
to
r:
Ne
e
d
s
,
o
p
p
o
rtu
n
it
ies
a
n
d
c
h
a
ll
e
n
g
e
s,”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
Re
se
a
rc
h
i
n
Co
m
p
u
ter
a
n
d
Co
mm
u
n
ica
ti
o
n
T
e
c
h
n
o
lo
g
y
,
v
o
l
.
3
,
n
o
.
1
1
,
p
p
.
1
2
-
2
0
,
2
0
1
4
.
[1
4
]
A
.
G
.
P
icc
ian
o
,
“
Big
d
a
ta
a
n
d
lea
rn
in
g
a
n
a
ly
ti
c
s
in
b
le
n
d
e
d
l
e
a
rn
in
g
e
n
v
iro
n
m
e
n
ts:
Be
n
e
f
it
s
a
n
d
c
o
n
c
e
rn
s,”
In
ter
a
c
ti
v
e
J
o
u
rn
a
l
o
f
Art
if
icia
l
I
n
telli
g
e
n
c
e
a
n
d
In
ter
a
c
ti
v
e
M
u
l
ti
me
d
ia
,
v
o
l
.
2
,
n
o
.
7
,
p
p
.
3
5
-
4
3
,
2
0
1
4
.
[1
5
]
K.
J.
Ih
e
c
h
u
a
n
d
N.
Ug
w
u
o
ji
,
“
Ev
a
lu
a
ti
o
n
o
f
th
e
a
p
p
li
c
a
ti
o
n
o
f
ICT
in
c
o
n
ti
n
u
o
u
s
a
ss
e
ss
m
e
n
t
b
y
a
c
a
d
e
m
i
c
sta
ff
o
f
u
n
iv
e
rsiti
e
s
i
n
A
b
ia
S
tate
,
Nig
e
ria
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
S
c
i
e
n
ti
fi
c
Res
e
a
rc
h
i
n
E
d
u
c
a
ti
o
n
,
v
o
l.
1
0
,
n
o
.
1
,
p
p
.
1
0
2
-
1
1
1
,
2
0
1
7
.
[1
6
]
K.
S
a
li
su
,
“
E
-
g
o
v
e
rn
m
e
n
t
a
d
o
p
ti
o
n
a
n
d
f
ra
m
e
w
o
rk
f
o
r
b
ig
d
a
ta
a
n
a
l
y
ti
c
s
in
Nig
e
ria,”
N
a
ti
o
n
a
l
In
f
o
rm
a
ti
o
n
T
e
c
h
n
o
lo
g
y
De
v
e
lo
p
m
e
n
t
A
a
g
e
n
c
y
(NITD
A
).
2
0
1
5
.
[1
7
]
C.
A
.
Ug
o
d
u
l
u
n
w
a
a
n
d
C.
M
.
An
ik
w
e
z
e
,
“
Big
d
a
ta
a
n
d
a
ss
e
ss
m
e
n
t
f
o
r
lea
rn
in
g
i
n
Nig
e
ria
u
n
iv
e
rsiti
e
s:
P
r
o
sp
e
c
ts
a
n
d
c
h
a
ll
e
n
g
e
s
,
”
2
0
1
9
.
[1
8
]
UN
ICEF
,
“
M
o
n
it
o
rin
g
Ed
u
c
a
ti
o
n
P
a
rti
c
ip
a
ti
o
n
:
F
ra
m
e
w
o
rk
f
o
r
M
o
n
it
o
ri
n
g
C
h
il
d
re
n
a
n
d
A
d
o
les
c
e
n
t
s
W
h
o
A
re
o
u
t
o
f
S
c
h
o
o
l
o
r
a
t
Risk
o
f
Dro
p
p
in
g
o
u
t,
”
G
e
n
e
v
a
:
UN
ICEF
,
2
0
1
6
.
[1
9
]
K.
S
c
h
il
d
k
a
m
p
,
M
.
Eh
re
n
,
a
n
d
M
.
K.
L
a
i,
“
Ed
it
o
r
ial
a
rti
c
le
f
o
r
th
e
sp
e
c
ial
issu
e
o
n
d
a
ta
-
b
a
se
d
d
e
c
isio
n
m
a
k
in
g
a
ro
u
n
d
t
h
e
w
o
rld
:
F
ro
m
p
o
li
c
y
to
p
ra
c
ti
c
e
to
re
su
l
ts
,
”
S
c
h
o
o
l
Ef
fec
ti
v
e
n
e
ss
a
n
d
S
c
h
o
o
l
Imp
r
o
v
e
me
n
t,
v
o
l.
2
3
,
n
o
.
2
,
p
p
.
1
2
3
-
1
3
1
,
2
0
1
2
.
[2
0
]
B.
G
.
Nw
o
rg
u
,
E
d
u
c
a
t
io
n
a
l
r
e
se
a
rc
h
:
Ba
sic
issu
e
s
a
n
d
me
t
h
o
d
o
l
o
g
y
,
(2
n
d
e
d
).
E
n
u
g
u
:
U
n
iv
e
rsity
tru
st
p
u
b
li
sh
e
rs
,
2
0
1
5
.
[2
1
]
C.
R.
Ko
th
a
ri
a
n
d
G
.
G
a
r
g
,
Res
e
a
rc
h
me
th
o
d
o
l
o
g
y
:
M
e
th
o
d
s
a
n
d
tec
h
n
iq
u
e
s.
De
lh
i
In
d
ia:
Ne
w
A
g
e
In
tern
a
ti
o
n
a
l
(P
)
L
td
,
P
u
b
l
ish
e
rs,
2
0
1
4
.
[2
2
]
D.A
.
Do
ti
m
i,
a
n
d
J
-
T
.
Ha
m
il
to
n
-
Ek
e
k
e
,
“
In
f
o
r
m
a
ti
o
n
a
n
d
C
o
m
m
u
n
ica
ti
o
n
T
e
c
h
n
o
l
o
g
y
(IC
T
)
–
E
-
L
e
a
rn
in
g
in
Nig
e
rian
T
e
rti
a
r
y
In
stit
u
ti
o
n
s,”
T
h
e
L
ib
r
a
ria
n
a
n
d
In
f
o
rm
a
ti
o
n
M
a
n
a
g
e
r,
v
o
l.
6
,
n
o
.
1
,
p
p
.
4
4
-
5
9
,
2
0
1
3
.
[2
3
]
J
-
T
.
Ha
m
il
to
n
-
Ek
e
k
e
a
n
d
C.
E.
M
b
a
c
h
u
,
“
T
h
e
P
lac
e
o
f
In
f
o
rm
a
ti
o
n
,
Co
m
m
u
n
ica
ti
o
n
a
n
d
T
e
c
h
n
o
lo
g
y
(IC
T
)
in
T
e
a
c
h
in
g
a
n
d
L
e
a
rn
in
g
in
Nig
e
rian
T
e
rti
a
ry
In
stit
u
ti
o
n
s,”
Ame
ric
a
n
J
o
u
r
n
a
l
o
f
E
d
u
c
a
ti
o
n
a
l
Res
e
a
rc
h
,
v
o
l.
3
,
n
o
.
3
,
p
p
.
3
4
0
-
3
4
7
,
2
0
1
5
.
[2
4
]
O.
A
.
Aw
o
ra
n
ti
,
“
T
ra
n
s
f
o
r
m
in
g
p
u
b
li
c
e
x
a
m
in
in
g
s
y
ste
m
th
ro
u
g
h
th
e
a
p
p
l
ica
ti
o
n
o
f
late
n
t
trait
m
o
d
e
ls,”
2
n
d
In
stit
u
te
o
f
Ed
u
c
a
ti
o
n
in
tern
a
ti
o
n
a
l
c
o
n
f
e
re
n
c
e
,
Un
iv
e
r
sit
y
o
f
Ib
a
d
a
n
,
I
b
a
d
a
n
,
Nig
e
ria,
2
0
1
3
.
[2
5
]
O.
A
.
Aw
o
ra
n
ti
,
“
I
n
f
o
rm
a
ti
o
n
a
n
d
c
o
m
m
u
n
ica
ti
o
n
s
tec
h
n
o
l
o
g
y
(ICT
)
in
Nig
e
ria
e
d
u
c
a
ti
o
n
a
l
a
ss
e
ss
m
e
n
t
sy
ste
m
-
e
m
e
rg
in
g
c
h
a
ll
e
n
g
e
s,”
Un
ive
rs
a
l
J
o
u
rn
a
l
o
f
E
d
u
c
a
t
io
n
a
l
Res
e
a
rc
h
,
v
o
l.
4
,
n
o
.
6
,
p
p
.
1
3
5
1
-
1
3
5
6
,
2
0
1
6
.
[2
6
]
C.
M
.
Be
u
k
e
s
-
Am
iss
a
n
d
E.
R.
T
.
Ch
iw
a
re
,
“
T
h
e
i
m
p
a
c
t
o
f
d
iff
u
sio
n
o
f
ICT
‟
s
in
to
e
d
u
c
a
ti
o
n
a
l
p
ra
c
ti
c
e
s,
h
o
w
g
o
o
d
o
r
h
o
w
b
a
d
?
A
re
v
ie
w
o
f
th
e
Na
m
ib
ia situ
a
ti
o
n
,
”
2
0
0
6
.
[2
7
]
C.
Ca
m
p
b
e
ll
a
n
d
B.
L
e
v
in
,
“
Us
in
g
d
a
ta
to
su
p
p
o
rt
e
d
u
c
a
ti
o
n
a
l
im
p
ro
v
e
m
e
n
t
,”
Ed
u
c
a
ti
o
n
a
l
Asse
ss
me
n
t
,
Ev
a
lu
a
ti
o
n
a
n
d
Acc
o
u
n
ta
b
il
i
ty,
v
o
l.
2
1
,
p
p
.
4
7
-
6
5
,
2
0
0
9
.
[2
8
]
C.
L
.
Ha
m
m
e
r,
D.
C.
Ko
stro
c
h
,
G
.
Qu
ird
,
a
n
d
S
ta
In
tern
a
l
G
ro
u
p
,
“
Big
d
a
ta:
P
o
ten
ti
a
l,
c
h
a
ll
e
n
g
e
s
a
n
d
sta
ti
stica
l
im
p
li
c
a
ti
o
n
s,”
2
0
1
7
.
[2
9
]
L
.
P
.
M
a
c
f
a
d
y
e
n
,
S
.
Da
w
so
n
,
A.
P
a
r
d
o
,
a
n
d
D.
G
a
s
e
v
i,
“
E
m
b
ra
c
in
g
b
ig
d
a
ta
in
c
o
m
p
lex
e
d
u
c
a
ti
o
n
a
l
sy
ste
m
s:
T
h
e
lea
rn
in
g
a
n
a
l
y
ti
c
s
i
m
p
e
r
a
ti
v
e
a
n
d
th
e
p
o
li
c
y
c
h
a
n
g
e
,
”
Res
e
a
rc
h
a
n
d
Pr
a
c
ti
c
e
in
Asse
ss
me
n
t
,
v
o
l.
9
,
n
o
.
2
,
p
p
.
1
7
-
2
8
,
2
0
1
4
.
[3
0
]
M
.
R.
Ra
jag
o
p
a
lan
,
NRC
-
F
OSS
,
“
Big
Da
ta
F
ra
m
e
w
o
rk
f
o
r
Na
ti
o
n
a
l
e
-
G
o
v
e
rn
a
n
c
e
P
lan
b
y
El
e
v
e
n
th
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
ICT
a
n
d
Kn
o
w
le
d
g
e
En
g
in
e
e
rin
g
,
”
Ce
n
tre
f
o
r
De
v
e
lo
p
m
e
n
t
o
f
A
d
v
a
n
c
e
d
Co
m
p
u
ti
n
g
Ch
e
n
n
a
i,
In
d
ia,
2
0
1
3
.
[3
1
]
B.
Co
p
e
a
n
d
M
.
Ka
lan
tzis,
“
Big
d
a
ta co
m
e
s to
sc
h
o
o
l:
Im
p
li
c
a
ti
o
n
s
f
o
r
lea
r
n
in
g
,
a
ss
e
ss
m
e
n
t,
a
n
d
re
se
a
rc
h
,
”
2
0
1
6
.
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