Efektivitas Strategi Ta’bir Mushawwar dalam Pembelajaran Bahasa Arab di Madrasah Ibtidaiyah
Abstract
Speaking proficiency is one of the main skills in Arabic language learning, but fourth grade students of MI TPI Keramat face difficulties in assembling mufradat and practicing active conversation, mainly due to the lack of varied learning strategies. This study aims to analyze the effectiveness of the ta'bir mushawwar strategy, which uses picture as a media to facilitate students in constructing sentences and telling stories, in improving Arabic speaking skills. With a quantitative approach and pre-experiment design, this study involved 18 students of class IV-C. Data were collected through tests, observations, and interviews, then analyzed descriptively and N-Gain test. The posttest average was 83.06 (very good category) with 88.9% completeness, and the N-Gain score was 0.6398 which showed effectiveness in the medium category. The ta'bir mushawwar strategy offers a solution in the form of a visual and hands-on learning approach that can significantly improve students' speaking skills and make learning more interesting and interactive.
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"""Bisection algorithms."""
def insort_right(a, x, lo=0, hi=None):
"""Insert item x in list a, and keep it sorted assuming a is sorted.
If x is already in a, insert it to the right of the rightmost x.
Optional args lo (default 0) and hi (default len(a)) bound the
slice of a to be searched.
"""
lo = bisect_right(a, x, lo, hi)
a.insert(lo, x)
def bisect_right(a, x, lo=0, hi=None):
"""Return the index where to insert item x in list a, assuming a is sorted.
The return value i is such that all e in a[:i] have e <= x, and all e in
a[i:] have e > x. So if x already appears in the list, a.insert(x) will
insert just after the rightmost x already there.
Optional args lo (default 0) and hi (default len(a)) bound the
slice of a to be searched.
"""
if lo < 0:
raise ValueError('lo must be non-negative')
if hi is None:
hi = len(a)
while lo < hi:
mid = (lo+hi)//2
# Use __lt__ to match the logic in list.sort() and in heapq
if x < a[mid]: hi = mid
else: lo = mid+1
return lo
def insort_left(a, x, lo=0, hi=None):
"""Insert item x in list a, and keep it sorted assuming a is sorted.
If x is already in a, insert it to the left of the leftmost x.
Optional args lo (default 0) and hi (default len(a)) bound the
slice of a to be searched.
"""
lo = bisect_left(a, x, lo, hi)
a.insert(lo, x)
def bisect_left(a, x, lo=0, hi=None):
"""Return the index where to insert item x in list a, assuming a is sorted.
The return value i is such that all e in a[:i] have e < x, and all e in
a[i:] have e >= x. So if x already appears in the list, a.insert(x) will
insert just before the leftmost x already there.
Optional args lo (default 0) and hi (default len(a)) bound the
slice of a to be searched.
"""
if lo < 0:
raise ValueError('lo must be non-negative')
if hi is None:
hi = len(a)
while lo < hi:
mid = (lo+hi)//2
# Use __lt__ to match the logic in list.sort() and in heapq
if a[mid] < x: lo = mid+1
else: hi = mid
return lo
# Overwrite above definitions with a fast C implementation
try:
from _bisect import *
except ImportError:
pass
# Create aliases
bisect = bisect_right
insort = insort_right
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