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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#! /usr/bin/env python3
"""Python interface for the 'lsprof' profiler.
Compatible with the 'profile' module.
"""
__all__ = ["run", "runctx", "Profile"]
import _lsprof
import profile as _pyprofile
# ____________________________________________________________
# Simple interface
def run(statement, filename=None, sort=-1):
return _pyprofile._Utils(Profile).run(statement, filename, sort)
def runctx(statement, globals, locals, filename=None, sort=-1):
return _pyprofile._Utils(Profile).runctx(statement, globals, locals,
filename, sort)
run.__doc__ = _pyprofile.run.__doc__
runctx.__doc__ = _pyprofile.runctx.__doc__
# ____________________________________________________________
class Profile(_lsprof.Profiler):
"""Profile(timer=None, timeunit=None, subcalls=True, builtins=True)
Builds a profiler object using the specified timer function.
The default timer is a fast built-in one based on real time.
For custom timer functions returning integers, timeunit can
be a float specifying a scale (i.e. how long each integer unit
is, in seconds).
"""
# Most of the functionality is in the base class.
# This subclass only adds convenient and backward-compatible methods.
def print_stats(self, sort=-1):
import pstats
pstats.Stats(self).strip_dirs().sort_stats(sort).print_stats()
def dump_stats(self, file):
import marshal
with open(file, 'wb') as f:
self.create_stats()
marshal.dump(self.stats, f)
def create_stats(self):
self.disable()
self.snapshot_stats()
def snapshot_stats(self):
entries = self.getstats()
self.stats = {}
callersdicts = {}
# call information
for entry in entries:
func = label(entry.code)
nc = entry.callcount # ncalls column of pstats (before '/')
cc = nc - entry.reccallcount # ncalls column of pstats (after '/')
tt = entry.inlinetime # tottime column of pstats
ct = entry.totaltime # cumtime column of pstats
callers = {}
callersdicts[id(entry.code)] = callers
self.stats[func] = cc, nc, tt, ct, callers
# subcall information
for entry in entries:
if entry.calls:
func = label(entry.code)
for subentry in entry.calls:
try:
callers = callersdicts[id(subentry.code)]
except KeyError:
continue
nc = subentry.callcount
cc = nc - subentry.reccallcount
tt = subentry.inlinetime
ct = subentry.totaltime
if func in callers:
prev = callers[func]
nc += prev[0]
cc += prev[1]
tt += prev[2]
ct += prev[3]
callers[func] = nc, cc, tt, ct
# The following two methods can be called by clients to use
# a profiler to profile a statement, given as a string.
def run(self, cmd):
import __main__
dict = __main__.__dict__
return self.runctx(cmd, dict, dict)
def runctx(self, cmd, globals, locals):
self.enable()
try:
exec(cmd, globals, locals)
finally:
self.disable()
return self
# This method is more useful to profile a single function call.
def runcall(self, func, /, *args, **kw):
self.enable()
try:
return func(*args, **kw)
finally:
self.disable()
def __enter__(self):
self.enable()
return self
def __exit__(self, *exc_info):
self.disable()
# ____________________________________________________________
def label(code):
if isinstance(code, str):
return ('~', 0, code) # built-in functions ('~' sorts at the end)
else:
return (code.co_filename, code.co_firstlineno, code.co_name)
# ____________________________________________________________
def main():
import os
import sys
import runpy
import pstats
from optparse import OptionParser
usage = "cProfile.py [-o output_file_path] [-s sort] [-m module | scriptfile] [arg] ..."
parser = OptionParser(usage=usage)
parser.allow_interspersed_args = False
parser.add_option('-o', '--outfile', dest="outfile",
help="Save stats to <outfile>", default=None)
parser.add_option('-s', '--sort', dest="sort",
help="Sort order when printing to stdout, based on pstats.Stats class",
default=-1,
choices=sorted(pstats.Stats.sort_arg_dict_default))
parser.add_option('-m', dest="module", action="store_true",
help="Profile a library module", default=False)
if not sys.argv[1:]:
parser.print_usage()
sys.exit(2)
(options, args) = parser.parse_args()
sys.argv[:] = args
# The script that we're profiling may chdir, so capture the absolute path
# to the output file at startup.
if options.outfile is not None:
options.outfile = os.path.abspath(options.outfile)
if len(args) > 0:
if options.module:
code = "run_module(modname, run_name='__main__')"
globs = {
'run_module': runpy.run_module,
'modname': args[0]
}
else:
progname = args[0]
sys.path.insert(0, os.path.dirname(progname))
with open(progname, 'rb') as fp:
code = compile(fp.read(), progname, 'exec')
globs = {
'__file__': progname,
'__name__': '__main__',
'__package__': None,
'__cached__': None,
}
try:
runctx(code, globs, None, options.outfile, options.sort)
except BrokenPipeError as exc:
# Prevent "Exception ignored" during interpreter shutdown.
sys.stdout = None
sys.exit(exc.errno)
else:
parser.print_usage()
return parser
# When invoked as main program, invoke the profiler on a script
if __name__ == '__main__':
main()
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