Efektivitas Strategi Ta’bir Mushawwar dalam Pembelajaran Bahasa Arab di Madrasah Ibtidaiyah
Keywords:
Arabic; speaking skill; ta’bir mushawwar
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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from collections.abc import Sequence, Iterable
from functools import total_ordering
import fnmatch
import linecache
import os.path
import pickle
# Import types and functions implemented in C
from _tracemalloc import *
from _tracemalloc import _get_object_traceback, _get_traces
def _format_size(size, sign):
for unit in ('B', 'KiB', 'MiB', 'GiB', 'TiB'):
if abs(size) < 100 and unit != 'B':
# 3 digits (xx.x UNIT)
if sign:
return "%+.1f %s" % (size, unit)
else:
return "%.1f %s" % (size, unit)
if abs(size) < 10 * 1024 or unit == 'TiB':
# 4 or 5 digits (xxxx UNIT)
if sign:
return "%+.0f %s" % (size, unit)
else:
return "%.0f %s" % (size, unit)
size /= 1024
class Statistic:
"""
Statistic difference on memory allocations between two Snapshot instance.
"""
__slots__ = ('traceback', 'size', 'count')
def __init__(self, traceback, size, count):
self.traceback = traceback
self.size = size
self.count = count
def __hash__(self):
return hash((self.traceback, self.size, self.count))
def __eq__(self, other):
if not isinstance(other, Statistic):
return NotImplemented
return (self.traceback == other.traceback
and self.size == other.size
and self.count == other.count)
def __str__(self):
text = ("%s: size=%s, count=%i"
% (self.traceback,
_format_size(self.size, False),
self.count))
if self.count:
average = self.size / self.count
text += ", average=%s" % _format_size(average, False)
return text
def __repr__(self):
return ('<Statistic traceback=%r size=%i count=%i>'
% (self.traceback, self.size, self.count))
def _sort_key(self):
return (self.size, self.count, self.traceback)
class StatisticDiff:
"""
Statistic difference on memory allocations between an old and a new
Snapshot instance.
"""
__slots__ = ('traceback', 'size', 'size_diff', 'count', 'count_diff')
def __init__(self, traceback, size, size_diff, count, count_diff):
self.traceback = traceback
self.size = size
self.size_diff = size_diff
self.count = count
self.count_diff = count_diff
def __hash__(self):
return hash((self.traceback, self.size, self.size_diff,
self.count, self.count_diff))
def __eq__(self, other):
if not isinstance(other, StatisticDiff):
return NotImplemented
return (self.traceback == other.traceback
and self.size == other.size
and self.size_diff == other.size_diff
and self.count == other.count
and self.count_diff == other.count_diff)
def __str__(self):
text = ("%s: size=%s (%s), count=%i (%+i)"
% (self.traceback,
_format_size(self.size, False),
_format_size(self.size_diff, True),
self.count,
self.count_diff))
if self.count:
average = self.size / self.count
text += ", average=%s" % _format_size(average, False)
return text
def __repr__(self):
return ('<StatisticDiff traceback=%r size=%i (%+i) count=%i (%+i)>'
% (self.traceback, self.size, self.size_diff,
self.count, self.count_diff))
def _sort_key(self):
return (abs(self.size_diff), self.size,
abs(self.count_diff), self.count,
self.traceback)
def _compare_grouped_stats(old_group, new_group):
statistics = []
for traceback, stat in new_group.items():
previous = old_group.pop(traceback, None)
if previous is not None:
stat = StatisticDiff(traceback,
stat.size, stat.size - previous.size,
stat.count, stat.count - previous.count)
else:
stat = StatisticDiff(traceback,
stat.size, stat.size,
stat.count, stat.count)
statistics.append(stat)
for traceback, stat in old_group.items():
stat = StatisticDiff(traceback, 0, -stat.size, 0, -stat.count)
statistics.append(stat)
return statistics
@total_ordering
class Frame:
"""
Frame of a traceback.
"""
__slots__ = ("_frame",)
def __init__(self, frame):
# frame is a tuple: (filename: str, lineno: int)
self._frame = frame
@property
def filename(self):
return self._frame[0]
@property
def lineno(self):
return self._frame[1]
def __eq__(self, other):
if not isinstance(other, Frame):
return NotImplemented
return (self._frame == other._frame)
def __lt__(self, other):
if not isinstance(other, Frame):
return NotImplemented
return (self._frame < other._frame)
def __hash__(self):
return hash(self._frame)
def __str__(self):
return "%s:%s" % (self.filename, self.lineno)
def __repr__(self):
return "<Frame filename=%r lineno=%r>" % (self.filename, self.lineno)
@total_ordering
class Traceback(Sequence):
"""
Sequence of Frame instances sorted from the oldest frame
to the most recent frame.
"""
__slots__ = ("_frames", '_total_nframe')
def __init__(self, frames, total_nframe=None):
Sequence.__init__(self)
# frames is a tuple of frame tuples: see Frame constructor for the
# format of a frame tuple; it is reversed, because _tracemalloc
# returns frames sorted from most recent to oldest, but the
# Python API expects oldest to most recent
self._frames = tuple(reversed(frames))
self._total_nframe = total_nframe
@property
def total_nframe(self):
return self._total_nframe
def __len__(self):
return len(self._frames)
def __getitem__(self, index):
if isinstance(index, slice):
return tuple(Frame(trace) for trace in self._frames[index])
else:
return Frame(self._frames[index])
def __contains__(self, frame):
return frame._frame in self._frames
def __hash__(self):
return hash(self._frames)
def __eq__(self, other):
if not isinstance(other, Traceback):
return NotImplemented
return (self._frames == other._frames)
def __lt__(self, other):
if not isinstance(other, Traceback):
return NotImplemented
return (self._frames < other._frames)
def __str__(self):
return str(self[0])
def __repr__(self):
s = f"<Traceback {tuple(self)}"
if self._total_nframe is None:
s += ">"
else:
s += f" total_nframe={self.total_nframe}>"
return s
def format(self, limit=None, most_recent_first=False):
lines = []
if limit is not None:
if limit > 0:
frame_slice = self[-limit:]
else:
frame_slice = self[:limit]
else:
frame_slice = self
if most_recent_first:
frame_slice = reversed(frame_slice)
for frame in frame_slice:
lines.append(' File "%s", line %s'
% (frame.filename, frame.lineno))
line = linecache.getline(frame.filename, frame.lineno).strip()
if line:
lines.append(' %s' % line)
return lines
def get_object_traceback(obj):
"""
Get the traceback where the Python object *obj* was allocated.
Return a Traceback instance.
Return None if the tracemalloc module is not tracing memory allocations or
did not trace the allocation of the object.
"""
frames = _get_object_traceback(obj)
if frames is not None:
return Traceback(frames)
else:
return None
class Trace:
"""
Trace of a memory block.
"""
__slots__ = ("_trace",)
def __init__(self, trace):
# trace is a tuple: (domain: int, size: int, traceback: tuple).
# See Traceback constructor for the format of the traceback tuple.
self._trace = trace
@property
def domain(self):
return self._trace[0]
@property
def size(self):
return self._trace[1]
@property
def traceback(self):
return Traceback(*self._trace[2:])
def __eq__(self, other):
if not isinstance(other, Trace):
return NotImplemented
return (self._trace == other._trace)
def __hash__(self):
return hash(self._trace)
def __str__(self):
return "%s: %s" % (self.traceback, _format_size(self.size, False))
def __repr__(self):
return ("<Trace domain=%s size=%s, traceback=%r>"
% (self.domain, _format_size(self.size, False), self.traceback))
class _Traces(Sequence):
def __init__(self, traces):
Sequence.__init__(self)
# traces is a tuple of trace tuples: see Trace constructor
self._traces = traces
def __len__(self):
return len(self._traces)
def __getitem__(self, index):
if isinstance(index, slice):
return tuple(Trace(trace) for trace in self._traces[index])
else:
return Trace(self._traces[index])
def __contains__(self, trace):
return trace._trace in self._traces
def __eq__(self, other):
if not isinstance(other, _Traces):
return NotImplemented
return (self._traces == other._traces)
def __repr__(self):
return "<Traces len=%s>" % len(self)
def _normalize_filename(filename):
filename = os.path.normcase(filename)
if filename.endswith('.pyc'):
filename = filename[:-1]
return filename
class BaseFilter:
def __init__(self, inclusive):
self.inclusive = inclusive
def _match(self, trace):
raise NotImplementedError
class Filter(BaseFilter):
def __init__(self, inclusive, filename_pattern,
lineno=None, all_frames=False, domain=None):
super().__init__(inclusive)
self.inclusive = inclusive
self._filename_pattern = _normalize_filename(filename_pattern)
self.lineno = lineno
self.all_frames = all_frames
self.domain = domain
@property
def filename_pattern(self):
return self._filename_pattern
def _match_frame_impl(self, filename, lineno):
filename = _normalize_filename(filename)
if not fnmatch.fnmatch(filename, self._filename_pattern):
return False
if self.lineno is None:
return True
else:
return (lineno == self.lineno)
def _match_frame(self, filename, lineno):
return self._match_frame_impl(filename, lineno) ^ (not self.inclusive)
def _match_traceback(self, traceback):
if self.all_frames:
if any(self._match_frame_impl(filename, lineno)
for filename, lineno in traceback):
return self.inclusive
else:
return (not self.inclusive)
else:
filename, lineno = traceback[0]
return self._match_frame(filename, lineno)
def _match(self, trace):
domain, size, traceback, total_nframe = trace
res = self._match_traceback(traceback)
if self.domain is not None:
if self.inclusive:
return res and (domain == self.domain)
else:
return res or (domain != self.domain)
return res
class DomainFilter(BaseFilter):
def __init__(self, inclusive, domain):
super().__init__(inclusive)
self._domain = domain
@property
def domain(self):
return self._domain
def _match(self, trace):
domain, size, traceback, total_nframe = trace
return (domain == self.domain) ^ (not self.inclusive)
class Snapshot:
"""
Snapshot of traces of memory blocks allocated by Python.
"""
def __init__(self, traces, traceback_limit):
# traces is a tuple of trace tuples: see _Traces constructor for
# the exact format
self.traces = _Traces(traces)
self.traceback_limit = traceback_limit
def dump(self, filename):
"""
Write the snapshot into a file.
"""
with open(filename, "wb") as fp:
pickle.dump(self, fp, pickle.HIGHEST_PROTOCOL)
@staticmethod
def load(filename):
"""
Load a snapshot from a file.
"""
with open(filename, "rb") as fp:
return pickle.load(fp)
def _filter_trace(self, include_filters, exclude_filters, trace):
if include_filters:
if not any(trace_filter._match(trace)
for trace_filter in include_filters):
return False
if exclude_filters:
if any(not trace_filter._match(trace)
for trace_filter in exclude_filters):
return False
return True
def filter_traces(self, filters):
"""
Create a new Snapshot instance with a filtered traces sequence, filters
is a list of Filter or DomainFilter instances. If filters is an empty
list, return a new Snapshot instance with a copy of the traces.
"""
if not isinstance(filters, Iterable):
raise TypeError("filters must be a list of filters, not %s"
% type(filters).__name__)
if filters:
include_filters = []
exclude_filters = []
for trace_filter in filters:
if trace_filter.inclusive:
include_filters.append(trace_filter)
else:
exclude_filters.append(trace_filter)
new_traces = [trace for trace in self.traces._traces
if self._filter_trace(include_filters,
exclude_filters,
trace)]
else:
new_traces = self.traces._traces.copy()
return Snapshot(new_traces, self.traceback_limit)
def _group_by(self, key_type, cumulative):
if key_type not in ('traceback', 'filename', 'lineno'):
raise ValueError("unknown key_type: %r" % (key_type,))
if cumulative and key_type not in ('lineno', 'filename'):
raise ValueError("cumulative mode cannot by used "
"with key type %r" % key_type)
stats = {}
tracebacks = {}
if not cumulative:
for trace in self.traces._traces:
domain, size, trace_traceback, total_nframe = trace
try:
traceback = tracebacks[trace_traceback]
except KeyError:
if key_type == 'traceback':
frames = trace_traceback
elif key_type == 'lineno':
frames = trace_traceback[:1]
else: # key_type == 'filename':
frames = ((trace_traceback[0][0], 0),)
traceback = Traceback(frames)
tracebacks[trace_traceback] = traceback
try:
stat = stats[traceback]
stat.size += size
stat.count += 1
except KeyError:
stats[traceback] = Statistic(traceback, size, 1)
else:
# cumulative statistics
for trace in self.traces._traces:
domain, size, trace_traceback, total_nframe = trace
for frame in trace_traceback:
try:
traceback = tracebacks[frame]
except KeyError:
if key_type == 'lineno':
frames = (frame,)
else: # key_type == 'filename':
frames = ((frame[0], 0),)
traceback = Traceback(frames)
tracebacks[frame] = traceback
try:
stat = stats[traceback]
stat.size += size
stat.count += 1
except KeyError:
stats[traceback] = Statistic(traceback, size, 1)
return stats
def statistics(self, key_type, cumulative=False):
"""
Group statistics by key_type. Return a sorted list of Statistic
instances.
"""
grouped = self._group_by(key_type, cumulative)
statistics = list(grouped.values())
statistics.sort(reverse=True, key=Statistic._sort_key)
return statistics
def compare_to(self, old_snapshot, key_type, cumulative=False):
"""
Compute the differences with an old snapshot old_snapshot. Get
statistics as a sorted list of StatisticDiff instances, grouped by
group_by.
"""
new_group = self._group_by(key_type, cumulative)
old_group = old_snapshot._group_by(key_type, cumulative)
statistics = _compare_grouped_stats(old_group, new_group)
statistics.sort(reverse=True, key=StatisticDiff._sort_key)
return statistics
def take_snapshot():
"""
Take a snapshot of traces of memory blocks allocated by Python.
"""
if not is_tracing():
raise RuntimeError("the tracemalloc module must be tracing memory "
"allocations to take a snapshot")
traces = _get_traces()
traceback_limit = get_traceback_limit()
return Snapshot(traces, traceback_limit)
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