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ESTIMATION AND COMPUTATION ABILITIES OF MRSM STUDENTS ON ITEMS
                  INVOLVING WHOLE NUMBERS


                               Noraini Noordin
                       Universiti Teknologi Mara, Perlis
                      noraininoordin@perlis.uitm.edu.my

                             Fadzilah Abdol Razak
                       Universiti Teknologi Mara, Perlis
                       fadzilah.ar@perak.uitm.edu.my

                                   Nooraini Ali
                       Universiti Teknologi Mara, Perlis
                       noorainiali@perlis.uitm.edu.my


                                    Abstract


        It is a well established fact that estimation and number sense are
        closely related. Number sense is the ability to understand and use
        the meaning of numbers in communicating, processing and
        interpreting information.       However, students are found to
        demonstrate little understanding of numerical situations in which
        they solve number problems and this has been the concern of
        mathematics educators. This lack of number sense is usually
        brought about by not understanding the mathematical exercises
        they learned in schools. Students can normally manipulate and
        follow symbolic rules better than at making sense of these
        numerical practices. Estimation allows the students to find an
        approximate answer before carrying out the calculation, thus helps
        to determine whether an answer is reasonable or not. This paper
        discusses the relationship between the estimation and computation
        skills of Form One students at Maktab Rendah Sains Mara (MRSM)
        in Malaysia on items involving Whole Numbers.


        Keywords: Estimation; Number Sense; Numerical Situations
INTRODUCTION


In any estimation exercise, a student selects simple numbers to operate on mentally
to produce an approximate answer (Reys, 1984; Segovia & Castro, 2009). This
definitive characteristic of an estimation exercise indicates the close relationship
between estimation and mental computation. However, mental computation is not an
inborn or inherent trait. Experiences and practice are required before one is able to
develop strategies that are more sophisticated than traditional written methods
(McIntosh, 2002; Asplin, Frid & Sparrow, 2006). This development can be
experienced in many ways and need not necessarily be in the form of a test
(Heirdsfield, 2002).


Ahmad Zanzali and Ghazali (2002) stated that out of five strands of number sense
(understanding the meaning of size and numbers, understanding the use of
equivalent forms and representations of numbers, understanding the meaning and
effect of operations, understanding the use of equivalent expressions and computing
and counting strategies), students demonstrated having difficulties in all strands
except the last two strands of number sense. It was found that although Year One to
Year Three students were not formerly exposed to addition and subtraction mental
calculation strategies, they were able to demonstrate intuitive mental computation
strategies to solve addition and subtraction problems varying from an inefficient
strategy of counting on their fingers to more sophisticated and simpler strategies
such as using doubles, bridging through ten, separation and wholistic strategy
(Ghazali, Alias, Anuar Ariffin & Ayub, 2010).


These studies indicated the need to understand how students think when they solve
mathematics problem. In another study, Ghazali, Abdul Rahman, Ismail, Idros and
Salleh (2003) identified three types of strategies employed by Year One to Year
Three students:


i)     Emergent strategies to refer to immature strategies of doing mathematics
       problems
ii)    Beginning strategies to refer to methods that exhibit some indication of
       thinking and employment of strategies of solving the problem that gives the
       correct answer but with no expert-like strategies
iii)   Competent strategies to refer to expert-like method of doing the mathematics.

These categories were used to formulate a matrix that will be able to define different
levels of strategies employed by students as well as classify the levels of the
students.
Students undergo six years of learning Mathematics at primary schools in Malaysia.
The section “points to note” in the Integrated Curriculum for Primary School specifies
that mental computation is to be emphasized in Primary School Mathematics at Year
One and Year Two (Mathematics Year 1, 2002; Mathematics Year 2, 2003).
However, mental computation is not formally taught in schools.

As for estimation and approximation, students are exposed to these vocabularies at
Year Three under the topic Numbers. By the end of Year Three, students will be able
to estimate quantities of objects up to 1000 beginning with smaller values to higher
values and round whole numbers less than 10000 to the nearest ten. Students are
also taught to ensure the reasonableness of any estimates made. They are also
exposed to estimates in topics like Mass and Volume of Liquid (Mathematics Year 3,
2003). At Year Five, estimation can be found in some other learning areas such as
Whole Numbers, Decimals, Integers, Basic Measurements, Perimeter and Area, and
Solid Geometry (Mathematics Year 5, 2006).


Estimation is a significant topic in school mathematics. It is a process rather than
content knowledge in the mathematics curriculum, and it applies to several strands
(Bana & Dolma, 2006). According to the National Research Council (2001), being
able to do quick and accurate mental computations and estimations has two
advantages:


i)     Students are able to check the reasonableness of an answer
ii)    Students are able to better appreciate the knowledge of place value,
       mathematical operations and general number sense.


However, studies found that a great number of students have encountered difficulties
doing simple mental calculation or estimating answers to a problem, causing them to
form a significant barrier to using mathematics in their everyday life (Case & Sowder,
1990; Star, Lee, Chang & Glasser, 2007).


This paper will discuss the results of a study carried out to assess the estimation and
computation abilities of Form One students. The study focused on four major areas in
the curriculum, namely, Whole Numbers, Decimals, Money and Fractions. This
paper will only focus on the results obtained with respect to only one area, namely,
Whole Numbers.


METHODOLOGY


Selected samples were from MRSMs in the North Zone of Malaysia, namely MRSM
Beseri in Perlis, MRSM Kubang Pasu in Kedah and MRSM Gerik and MRSM
Pengkalan Hulu in Perak. Data were collected in the first semester of 2010 at the
respective colleges. A three-phase procedure was carried out on these samples of
students, beginning with a short test on estimation that had a time limit of 30 seconds
  per item to minimize any precise calculations. Students were also not permitted to
  write anything on the test paper, other than their responses. This was followed by a
  short test on computation with a slightly longer time limit, namely three minutes for
  each item. Students were allowed to use any method/s of their choice, but
  calculators were not permitted in the computation test. After the test sessions, a
  selection of three male and three female students were interviewed using the Probing
  Interview and the interview sessions were audio-taped.


  The instruments used had 15 similar stemmed items which were constructed based
  on the topics in the curriculum for Mathematics Year Three to Year Six covering four
  areas: Whole Numbers (5 items – 33.33%), Fractions (4 items – 26.67%), Decimals
  (4 items – 26.67%), and Money (2 items – 13.33%). The multiple-choice format was
  chosen for the Estimation Test to safeguard against students doing precise
  calculations (Bana and Dolma, 2006).


  Rasch Measurement Model was used to analyze the responses to both tests. Table 1
  summarizes statistics of measures of reliability and correlation for both tests:


          TABLE 1: Summary Statistics of Measures of Reliability and Correlation
                                                      TYPE OF TEST
                   ITEMS
                                           Computation Test Estimation Test
Item Reliability                                  0.98                 0.98
Person Reliability                                0.44                 0.64
Item Raw Score-To-Measure Correlation                 -0.96                -0.94
Person Raw Score-To-Measure Correlation               0.97                  0.98


  The person and item reliability indices were rated using the rating scale instrument
  quality criteria. It reported the same index of 0.98 (> 0.94) for item reliability of both
  tests, thus the instrument measured an excellent item reliability rating. Since item
  reliability was not dependent on the length of a test, the recorded indices implied that
  both tests had a wide difficulty range, both tests were administered on a large sample
  and inferences were expected to be consistent. In addition, item ordering had a very
  high probability of being replicated if these same items were given to a different
  group of students (Bond & Fox, 2007).


  High reliability values also implied that the number of ranges in the scale that can be
  distinguished with confidence across samples also increased. Studies indicated that
  measures with reliabilities of 0.67 will tend to vary within two groups that can be
  separated with 95% confidence, measures of reliabilities of 0.80 will vary within three
  groups; of 0.90, four groups; of 0.94, five groups; of 0.96, six groups; of 0.97, seven
  groups, and so on (Fisher Jr., Elbaum & Coulter, 2010). However, the person
  reliability indices reported low values of 0.44 and 0.64 on the Computation Test and
the Estimation Test, respectively. Since person reliability does not depend on
sample ability variance, this paper can confidently say that this low value may imply
that there was not much difference between the students’ abilities. It was also not
possible to discriminate the samples into different levels, thus, this sample did not
demonstrate a hierarchy of ability (Bond & Fox, 2007). In addition, a very high
positive person raw score-to-measure correlation and very low negative item raw
score-to-item correlation implied a low proportion of very high and very low scores
(Winsteps, 2011). These values also confirmed the earlier finding that there was no
distinct ability difference between the selected students from these colleges.


RESULTS


How students think cannot be observed directly, but can be evaluated from the work
that they produced. These evaluations can help identify their level of conceptual
understanding or highlight misconceptions (Wong, Evans & Anderson, 2006). This
paper will focus its discussion on only five items on Whole Numbers, namely items 4,
5, 7, 8 and 11. Table 2 summarizes the objectives of these items:


      TABLE 2: Distribution of Items according to Topics and Objectives
TOPIC     ITEM       OBJECTIVES
            4        Develop number sense up to 1000000
            5        Develop number sense up to 1000000
WHOLE       7        Develop number sense up to 1000000
NUMBERS              Understand and use the vocabulary of estimation and
            8
                     approximation
            11       Multiply any two numbers with the highest product of 100000


Item maps of the responses to both tests were built to determine the hierarchy of
difficulty among these items according to the type of test. The item maps found item
7 to be the easiest Whole Number item on both tests. The items ordered from
easiest to most difficult were items 7, 5, 4, 8, and 11 for the Estimation Test, and
items 7, 11, 5, 8 and 4 for the Computation Test. The maps also found items 5 and 8
on the Computation Test to lie on the same ability level.
DISCUSSION


Table 3 displays items and percentage measures for items on Whole Numbers:

        TABLE 3: Item and Percentage Measures for Items on Whole Numbers

                    Estimation Test                       Computation Test
Item No.
               Item           Percentage
                                               Item Measure Percentage Measure
              Measure          Measure
    4           294                76               156                   41
    5           338                88               304                   79
    7           381                99               352                   91
    8           260                68               299                   78
   11           238                62               333                   86


As can be seen, students were more able to handle items 4, 5 and 7 in the
Estimation Test than on the Computation Test. From among these three items,
students found item 7 to be the easiest and item 4 to be the most difficult. In
particular, item 4 measured the largest range in percentage measure between both
tests. The small range in percentage measure for item 7 suggested that students
had no problem finding the place value for a digit in a number up to 1000000 in both
tests. The level of performance shown on item 5 indicated that they have achieved
the first strand in number sense; they were able to understand and use the meaning
and size of numbers. However, they were not able to utilize their mastery of the
ability achieved in item 5, on item 4; item 4 presented a situation that required a
higher thinking capability from the students to enable them to manipulate the
knowledge of the size of numbers.


These three items involved the recognition of place values under different
circumstances. Students first recognized the place of a digit of a number at Year
One for numbers up to 20, at Year Two for numbers up to 1000, and the number of
digits increased as they progressed through primary school, thus they should be able
to determine what value a digit represented in any number (Mathematics Year 2,
2003). More than 90% of the students were found able to associate the digit “6” in
the given number for item 7 to 6000. This paper wishes to emphasize that better
student performances in the Estimation Test can be accounted for by the presence of
four solution alternatives A, B, C and D provided in these items, as shown in Table 4.
TABLE 4: Items 4, 5 and 7 in the Computation and Estimation Tests
Item          Computation Test                           Estimation Test
  4  Find the missing numbers in the     Find the missing numbers in the sequence given
     sequence given below:               below:

      917 158, _____, _____, 887 158       917 158, ____, ____, 887 158

                                           A        927 158, 937 158
                                           B        927 158, 907 158
                                           C        907 158, 897 158
                                           D        897 158, 892 158
 5    Round up the following numbers to    Which of the following numbers when rounded
      the nearest ten thousand.            off to the nearest thousand becomes 580 000?

      579 324                              A       579 324       C       580 516
      580 516                              B       579 562       D       581 105
      579 562
      581 105

 7    The value of the digit 6 in the The value of the digit 6 in the number
      number 856 943 is               856 943 is

                                           A       60            C       6 000
                                           B       600           D       60 000


The students demonstrated having more problems rounding up numbers to the
nearest ten thousand in item 5 of the Computation Test than rounding up to the
nearest thousand in item 5 of the Estimation Test. It was perhaps much easier in
the Estimation Test because the solution alternatives given in the test may have
provided the students with better chances of determining if the thousands in the
number was equal or greater than 5, or smaller than 5 to enable rounding off to the
nearest 10000 (Mathematics Year 5, 2006). Since the third digit in the number
579562 was “5”, an increment of one was added to the fourth digit “9”, thus the
solution alternative 579562 qualified to be rounded off to the nearest thousand as
580000. In terms of frequency of students failing item 5 of the Estimation Test,
581805 ranked the highest followed by 579324 and 580516. However, these
answers did not suggest any particular rule used by the students in the estimation
process. Similarly, item 5 of the Computation Test showed that the fourth digit
exceeded 5 in the first and the third numbers, thus all the given numbers should
round off to 580000. In order to better understand the mistakes that may have been
performed by students in recognizing and applying the place value of digits in a
number, this paper will take a look at the wrong answers given by students for item 5
of the Computation Test, as displayed in Table 5.
TABLE 5: Wrong Answers for Item 5 of the Computation Test
    NUMBER                          WRONG ANSWERS
    579 324         579 000, 578 000, 590 000, 600 000, 579 320, 58 000
    580 516         581 000, 680 516, 580 500, 580 520, 600 000, 58 000
    579 562         581 000, 579 560, 600 000, 58 000
    581 105         581 000, 590 000, 581 110, 590 000, 600 000, 58 000



To be more precise, this paper will take a look at how students rounded off 579324 to
the nearest ten thousand. Analysis of answers to this item revealed that the most
prominent wrong answer given was 579000. This could only mean that students
associated the place value for the third digit to 10000 instead of 1000. The wrong
answer 600000 could be attributed to students wrongly associating the fifth digit to
the place value of 10000 instead of 100000. Further research has to be done to
investigate the flaws behind the incorrect answers like 570000 and 579320. Was it
possible for students to have overlooked the process of determining if the selected
digit was smaller or greater than 5 thus coming up with the incorrect answer of
570000? Could it be that the students did not understand the need to identify the
digit with the correct place value, hence giving the answer 579320?

In item 4, the students had more difficulty finding the missing numbers in a sequence
of numbers up to 1000000 in the Computation Test than the Estimation Test. The
item in the Estimation Test was much easier because students could see that there
was a common difference of 10000 between the numbers in the series by just
comparing the solution alternatives given to the blanks in the sequence of numbers in
the item. By looking at the construct of item 4 in Table 3, almost 90% of students
were able to eliminate solution alternatives A) 927158, 937158 and B) 927158,
907158 as answers for this particular item because these alternatives did not fit the
decreasing pattern of the given sequence. The 294 students who passed this item
chose the solution alternative C) 907158, 897158 over D) 897158, 892158 as the
answer because both these numbers exhibited a common difference of 10000
between them and also from the first and fourth number in the sequence. However,
this pattern was definitely not obvious to some students, causing them to opt for a
different solution than C) and almost 11% of them did not attempt to answer this item.
Unlike the Estimation Test, students who attempted this item in the Computation Test
had to come up with their own counting and computing strategies for this item.
However, it is important to take note that there were some students who passed this
item in the Estimation Test but failed in the Computation Test.


Contrasting items 4, 5 and 7, the students were found to demonstrate less ability on
items 8 and 11 on the Estimation Test than on the Computation Test. Item 8
required students to determine the best estimate of the total number of sweets that
Aishah bought given that she bought 7 packets with an average value of 106 to 120
sweets per packet. Both tests provided four solution alternatives for the students to
choose from in this item. The construct of item 8 was almost similar for both tests.
The Computation Test required an answer to the question “Which of the following
values would be the best estimate of the total number of sweets that she bought?”
while the Estimation Test wanted students to “Estimate the total number of sweets
that she bought.” Contrary to the paper’s earlier perception that performances in
both tests should be almost the same for this item, analysis of answers to this item
noted a 10% difference in percentage measure between both tests as displayed in
Table 3. Thus, students were better at finding the correct counting and computing
strategies; hence demonstrating they were less competent and had lower number
sense at estimation than computation. The paper wishes to point out that the nature
of the construct in the Computation Test may have had some influence on how
students should think. Unlike item 8, the construct of item 11 was the same for both
tests. Surprisingly, Table 3 indicates that there was a 24% difference in percentage
measure between performances on both tests.


In tackling item 11 in the Computation Test, students had to find all the products for
750×45, 833×25, 961×40 and 1025×27, then round them up before deciding which
among these products lie between 30000 and 35000. These computations took time
to finish. However, analysis of answers indicates that this was easier for the students
to do than to eliminate the products 833×25 and 1025×27 because they were smaller
than 30000, and 961×40 because it was larger than 35000 in the Estimation Test
before deciding that 750×45 would be the most appropriate answer. This paper
wishes to emphasize that the performance on this item may be taken as a cue that
students were not equipped with the knowledge on how to estimate product of
numbers, thus causing 38% of the students to fail this item in the Estimation Test.
Students may not understand the mathematical exercises they learned in schools,
and may have approached mathematics as a set of rules to memorize. Thus this
explains the lack of number sense shown by the students for this item.


IMPLICATIONS OF THE STUDY


In this study, Rasch Measurement Model was used to build item maps that generated
a preference item schedule for items on estimation and computation which would
help suggest significant differences in the estimation and computation abilities of
students. Item measures helped to identify problematic items in both tests. In
particular, this study was also able to list some issues on estimation and computation
abilities of students with respect to numbers.


LIMITATIONS OF THE STUDY


Firstly, samples were selected Form One students of only four MRSMs in the North
Zone of Malaysia. Data were collected in the first semester of schooling in 2010.
Two instruments, a Computation Test and an Estimation Test were developed by the
researchers. Both tests had 15 similar stemmed items based on four topics in the
curriculum for Mathematics Year Three to Year Six, namely, Whole Numbers,
Fractions, Decimals, and Money.


Secondly, the tests were conducted in classrooms or halls provided by the college,
thus there was no control on the space between the students when they sat for the
tests. Thirdly, the Estimation Test was given first, with a time limit of 30 seconds per
item to minimize any precise calculations. To further enhance the estimation aspect
of the test, students were not permitted to write anything on the test paper, other than
their responses and the items was structured using the multiple-choice format to
safeguard against students doing precise calculations (Bana & Dolma, 2006).
Fourthly, the Computation Test was given after a short break, with a three-minute
time limit for each item to enable analysis of computation abilities. In addition,
students were instructed that the computations could be done using any method/s of
their choice, but calculators were not permitted. Lastly, three male and three female
students were selected for an interview right after completing the test sessions in
rooms allocated by the colleges. There was no possibility of barring off sound from
the interview sessions. The interview sessions were audio-taped.


CONCLUSIONS


Table 6 displays the distribution of scores on both tests. As can be seen, students
performed better on the Computation Test than on the Estimation Test. However,
the percentage difference in the performance distribution was not large.

                    TABLE 6: Distribution of Scores on Both Tests

                        Computation Test                  Estimation Test
   SCORES           Number of                      Number of
                                  % students                       % students
                     Students                       Students
 Above Mean
                        208            54.03           202              52.47
    Score
 Below Mean
                        177            45.97           183              47.53
    Score
                        385             100            385               100


Rasch Measurement Model was used to analyze the responses to both tests.
Summary statistics of the responses concluded that the students performed better on
the Computation Test with a mean of 11.4 as compared to a mean of 10.3 on the
Estimation Test. Both tests indicated the same maximum score (15) and minimum
score (3). Interestingly, there were however four more students with a maximum
score on the Estimation Test than there were on the Computation Test.
i)     Relationship between Computation and Estimation Abilities


Estimation helps students to not only approximate answers before carrying out the
calculations but it also helps them to determine whether an answer is reasonable or
not, hence developing number sense in the students (Segovia & Castro, 2009). It
requires mental computation, thinking and making sense of the computation and
does not rely on rules or mechanical procedures. However, students are usually
more successful on written computations than on number sense (Bana & Dolma,
2006). Therefore, if the scores on the Estimation Test can be taken as the
benchmark for the development of number sense in students, then this paper posits
that only 52.47% of the students have developed number sense in thinking.

Analysis of the responses found that students were better at computation than
estimation in ten out of 15 items, including items 8 and 11 under the topic of Whole
Numbers. Table 6 indicates that there was a small range of difference between the
students’ abilities. Thus, further investigation of these scores has to be done in order
to assess and understand the strong relationship between computation and
estimation abilities of these students. There is also a need to compare the items on
both tests that involved learning areas other than Whole Numbers in order to identify
problematic items. There is also a need to look into those items that have students
performing better on the Estimation Test than the Computation Test.


ii)    Problematic Items on the Computation Test


If a percentage measure of 60% can be taken as benchmark for identifying items
that students had little ability to handle, then there were more items on the Estimation
Test that need to be given extra focus by the educators than the Computation Test.
Items 2, 6, and 14 under the topic Fractions and 15 under the topic Money were
identified as problematic on the Estimation Test. On the other hand, only items 4 and
6 were found to be problematic on the Computation Test. In particular, there were no
items under Whole Numbers identified as problematic to the students in the
Estimation Test. On the contrary, item 4 on Whole Numbers with a percentage
measure of 41% fell into this category for the Computation Test. This paper tends to
believe that students were not exposed to methods of estimation that can enable
them to develop the number sense needed in the finding of possible strategies to
tackle this item. Analysis of answers to this item indicated that they were not only
unable to see the pattern in the sequence of numbers given in this item; they were
also not able to make sense of the end numbers 917158 and 887158.
iii) Items Students Performed Better on Estimation Test than Computation Test


The students were found to perform better on the Estimation Test in only five out of
15 items, which included items 4, 5 and 7 under the topic on Whole Numbers. Items
4, 5 and 7 involved the identification of place values under different circumstances.
Item 7 was a very straight forward problem. Item 5 involved a bigger set of numbers
than item 7. Item 4 was the most difficult since it involved a higher hierarchy of
thinking strategies of finding missing items.

High percentage measures for item 7 in both tests indicated that students had no
problem finding the place value for a digit in a number up to 1000000 in both tests,
which meant that they have developed the first strand in number sense by being able
to understand and use the meaning and size of numbers. Their understanding of the
effect of rounding up and rounding down to the nearest 10000 made it easier for
them to find the number that would be nearest to 580000 in item 5, indicating they
had also developed the first strand of number sense in this item. The multiple
choices provided a clear identification of the common difference between the
numbers, thus, they were better at finding counting and computing strategies for this
item in the Estimation Test than they were in the Computation Test.

 Mental computation can be characterized by it ability to produce exact answers.
When mental computation is used in an estimation procedure, simple numbers are
selected and operated on mentally to bring about approximate answers, emphasizing
the close relationship between estimation and mental computation; hence it is very
important to teach students to do mental computation at school (Reys, 1984; Segovia
& Castro, 2009). In particular, the students’ proficiency to compute in the other 10
items would be a great advantage for them in their estimation procedures. However,
teaching approaches must be improved in order to upgrade students’ achievements
since percentages below 85% were recorded for some of these items.


Emphasis on computational skills may produce high computational scores; however,
the extent to which these processes transfer to students’ understanding is still
unknown (Ghazali et al, 2003). The samples used in this study were selected for
admission into the MRSM schooling system, thus, higher expectations were
expected in their achievements. However, there was no distinct difference between
54.03% passes in the Computation Test and 52.47% passes in the Estimation Test.
In addition, the study has established that students were better at computation than
estimation. Furthermore, students who can do estimation should be able to
approximate answers before doing any computation and to determine the
reasonableness of an answer (Segovia & Castro, 2009). Therefore, if scores on the
Estimation Test can benchmark the development of number sense in students, then
only 52.47% of the students have developed number sense in thinking and the highly
developed number sense was observed in item 7 of the Estimation Test with 99%
passes. Since item 7 dealt with the recognition of place values for numbers up to
1000000, these meant that these students have understood and were able to use the
meaning and size of numbers.
The findings of this study have shown that it is important for mathematics educators
to pay attention to the development of number sense in the teaching of mathematics
in schools. Item 4 was identified as one of the items students performed better at
estimation than computation, but it recorded percentage passes of only 76%. That
means that 24% of the students had problems with higher order thinking in problem
solving, thus it was impossible for them to come up with the correct strategies to find
missing numbers in the sequence 917158, _________, ___________, 887158. Lack
of number sense can be felt more in item 15 with only 52% passes in the Estimation
test.


This paper wishes to point out that failure to succeed at item 15 may have taken
place because analysis of answers given suggests the possibility that students may
have misread the question. However, if it were not due to misreading, then attention
should be given to help students with mixed operations on numbers in solving
mathematics problem in real life. What might be the best approach to teach mixed
operations? To conclude, this study has opened our eyes to some details in the
learning of Whole Numbers that should be given more focus in order to increase
number sense in thinking and to develop estimation capabilities. It is hoped that this
study has contributed ideas to mathematics educators on improving the approaches
in teaching these items.
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FACTORS AFFECTING ORGANIZATIONAL COMMITMENT AMONG LECTURERS IN
           HIGHER EDUCATIONAL INSTITUTION IN MALAYSIA


                                   Munirah Salim
                      Kolej Profesional MARA Bandar Melaka
                             munirahsalim@yahoo.com


                              Halimahton Kamarudin
                      Kolej Profesional MARA Bandar Melaka
                            halimahton@yahoo.com.my


                            Mumtaz Begam Abdul Kadir
                      Kolej Profesional MARA Bandar Melaka
                          mumtazabdulkadir@yahoo.com


                                       Abstract


      A study was conducted to determine MARA Professional Colleges lecturers’
      perception on organizational commitment. The study builds on social
      exchange theory and organizational model to identify the factors influencing
      the organizational commitment of these lecturers. The study analyzes
      whether or not there is a significant relationship between job satisfaction,
      job involvement, perceived organizational support and organizational
      commitment among lecturers in MARA Professional Colleges. Data were
      collected via questionnaires from 132 lecturers of three different MARA
      Professional Colleges. The study utilizes correlation and regression
      statistics to analyze the data. The findings of the survey show there is a
      significant relationship between job satisfaction (r=0.307), job involvement
      (r=0.536) and perceived organizational support (r=0.489). Job involvement
      contributed the most which is 28.8%, followed by perceived organizational
      support 23.9% and job satisfaction contributed 9.4% towards organizational
      commitment among MARA Professional College lectures. The study
      focuses on MARA Professional Colleges and concentrates only on the
      organizational commitment among academicians. The results suggest an
      improvement of social change by increasing job involvement, perceived
      organizational support and job satisfaction is an efficient way of obtaining
      highly committed human resource. The results of the study have valuable
      implications for policy makers in MARA Higher Education Division, college
      administrators and educators.


      Keywords: Organizational Commitment, Job Satisfaction, Job
      Involvement, Perceived Organizational Support
INTRODUCTION


Committed human resources are organization’s greatest assets. In order to ensure excellent
and experienced academic staff always attached with the educational institutions.
Committed employee should receive superior attention. Moreover, when committed lecturer
quits, the college will be burden with high cost and implications for the education system.
Committed and quality lecturer will take with them their teaching skills and experience.


Meyer and Allen (1993) have recognized that organizational commitment as a leading factor
impacting the level of achievement in many organizations. A lot of studies have been
conducted on the relationship of organizational commitment either towards job satisfaction,
job involvement or perceived organizational support only. However, only few have been
carried out on the collaboration of these three factors towards the organizational
commitment. Besides, there is very little research done to identify factors that impact
organizational commitment among academics (Chang & Choi, 2007; Chen et al., 2007;
Freund, 2005; Obeng & Ugboro, 2003).


LITERATURE REVIEW


Organizational commitment is as “a strong belief in and acceptance of the organization’s
goals and values; a willingness to exert considerable effort on behalf of the organization; and
a strong desire to maintain membership in the organization” (Mowday, R.T., Steers, R.M., &
Porter, L.W. (1979). The concept of organizational commitment has been conceptualized
from various perspectives. In this current study, the concept of organizational commitment
will be discussed from the behavioral approach and psychological approach. From the
behavioral approach, organizational commitment has been studied from the output of
rewards/ contribution exchange processes between employers and employees (Morris &
Sherman, 1981). On the other hand, the psychological approach looks at organizational
commitment from the view of the attachment or identification of employees with the
organization at which they work.


The model of Meyer and Allen (1997) used in this current study proposed a three-component
model of organizational commitment according to the nature of the bond that exists between
an employee and employer as below:


1. Affective commitment is employee’s emotional attachment to, identification with and
   involvement in the organization (Meyer et.al., 1993; Shore and Tetrick, 1991; Romzek,
   1990)
2. Continuance commitment that is based on the costs that the employee links with leaving
   the organization or on a perceived lack of alternative employment
   opportunities.(Buitendach and De Witte, 2005;Reichers, 1985; Murray, Gregoire, &
   Downey,1991)
3. Normative commitment that involves the employee’s feelings of obligation to stay with
   the organization.(Meyer & Allen, 1991; Wiener and Gechman, 1977; Roussenau, 1995)


Job satisfaction is one of the most regularly measured organizational variables and
frequently referred to as an employee’s global attitudinal or affective response to their job.
Makanjee et al. (2006) explained that job satisfaction was basically the way individuals
thought and felt about their multifaceted work experience. Loui (1995) examined the
relationship between job satisfaction and organizational commitment among 109 workers
and reported that there are positive relationship between organizational commitment and job
satisfaction. Another study by Coleman & Cooper (1997) explained that job satisfaction was
positively related to both affective and normative commitment. A study by Rajendran and
Raduan (2005) also showed the same result that is job satisfaction has a positive influence
on affective and normative commitment


Mathieu and Zajac (1990) define job involvement as a belief descriptive of an employee’s
relationship with the present job. Joiner and Bakalis (2006) suggested that job involvement
describes how interested, enmeshed, and engrossed the worker is in the goals, culture, and
tasks of a given organization. A study by Uygur and Kilic (2009) involving employees
working in the central Organization of the Ministry of Health revealed that there is a positive
correlation between organizational commitment and job involvements.


In organization researchers, the social exchange theory (Blau, 1964), and the concept of
perceived organizational support (POS) have been applied to explain the psychological
process underlying the employee attitudes and behaviors (Settoon, Bennet & Liden , 1996;
Wayne et al.,2002). Exchanges between an employee and employing organization are
called POS. Review of POS literature uses social exchange theory interpretation of
organizational commitment to explain how an employee’s commitment to an organization is
influenced by the organization’s commitment to employee (Jackson et al, 2004). Many
researchers have investigated the effects of POS on important work outcomes such as
affective commitment and turnover intention (Eisenberger et al., 1986; Eisenberger et al.,
1990; Setton et al., 1996; Wayne et.al., 1997).


PROBLEM STATEMENT


Educational institution is considered as a service industry playing key role in developing
smart, well educated with first class mentality human capital required in vision 2020.
Therefore, the main player is academicians who are responsible to produce future human
capital needed by the nation. As per Atan (2007), academic staffs that are committed to
improve teaching and learning methods, strengthening research and innovation are the main
factor in order to turn Malaysia into leading education hub.
Majlis Amanah Rakyat (MARA) through Bahagian Pendidikan Tinggi (BPT) has taken many
steps to strengthen its education sector in order to support Malaysia into a leading education
hub. Since, committed human resources are organization’s greatest assets, therefore
identifying factors that help to foster organizational commitment among MARA lecturers is
important. Moreover, when committed lecturer quits, MARA will be burden with high cost and
implications for the education system. Committed and quality lecturer will take with them
their teaching skills and experiences.


Due to this, there is a desire to conduct a study focussing on factors that will influence
organizational commitment among lecturers in MARA Professional Colleges. This study will
investigate whether or not job satisfaction, job involvement and perceived organizational
influence organizational commitment among MARA lecturers.


PURPOSE OF THE STUDY


The purpose of this study is to examine the relationship between job satisfaction, job
involvement, and perceived organizational support towards organizational commitment
among academicians. It is hoped that the findings of the study will provide empirical
evidences in the aspects of factor impacting organizational commitment among academics
and fulfil the research gap due to lack of studies conducted among academicians on
organizational commitment. At the same time, the findings from this research will be useful
to policy makers in MARA Higher Education Division and college administrator in order to
maximize the capacity and capability of its lecturers by increasing their level of commitment.


RESEARCH QUESTIONS

The current study is thus conducted to address the following research questions:


1. Does job satisfaction contribute towards organizational commitment (Affective,
   continuance and normative)
2. Does job involvement contribute towards organizational commitment (Affective,
   continuance and normative)
3. Does perceived organizational support contribute towards organizational commitment
   (Affective, continuance and normative)


METHODOLOGY


This study was carried out through a survey method using questionnaires as the main
instrument. The sample consists of respondents among lecturers from three MARA
Professional Colleges.
The conceptual framework for this current study is suggested in Figure 1. This framework
was imitative from earlier theories on antecedents and consequences of organizational
commitment such as social exchange theory (Blau, 1964) and model of organisational
commitment by Meyer & Allen (1997). The concept of exchange says that individual
becomes attached to the organization in return for gains provided by the organization.


This conceptual framework explains that organizational commitment among academics is
influenced by job satisfaction, job involvement and perceived organizational support .The
dependent variable in this research is organizational commitment. Organizational
commitment can be defined through the strength of employee’s identification with, and
involvement, in a particular organization. The independent variables are job satisfaction, job
involvement, and perceived organizational support.




             JOB SATISFACTION
                                                       ORGANIZATIONAL
                                                        COMMITMENT

                                                            AFFECTIVE
             JOB INVOLVEMENT
                                                            CONTINUANCE

                                                            NORMATIVE
               PERCEIVED
             ORGANIZATIONAL
                SUPPORT




                         Figure 1: Research Conceptual Framework

The questionnaires consist of five parts to measure the studied elements, where the
independent variables are job satisfaction (Spector, 1997), job involvement (Kanugo, 1982)
and perceived organizational support (Eisenberger et al., 1986). The dependent variable
was organizational commitment with three subscales that are affective, continuance and
normative commitment.


The method used to measure job satisfaction in this current study is Job Satisfaction Survey
(JSS) (Spector, 1997). No modification was made on the current questionnaires. The survey
uses a faceted approach to the measurement of satisfaction in terms of specific identifiable
characteristics related to the job (Luthans, 1998). It measures nine aspects of an employee’s
satisfaction: Pay, Promotion, Supervision, Fringe Benefits, Contingent Rewards
(performance based rewards), Operating Procedures (required rules and procedures),
Coworkers, Nature of Work, and Communication (Spector, 1997). The JSS consist of 36
items, and there are 4 items for each facet.
To measure the job involvement, 10 items from the Job Involvement Questionnaire (JIQ)
developed by Kanugo (1982) is used. However, modification was made by the current
researcher due to a reliability test. Therefore, in the current study only 9 items were used.
Perceived organizational support is measured using Survey of Perceived Organizational
Support adapted from Eisenberger et al., (1986). Modifications were made by the
researchers in terms of rewording the construct in order to fit with a particular sample. The
shorter version which consists of 8 items was used in the current study. Organizational
commitment survey developed by Meyer and Allen (1997) was used. Modifications were also
done by the researchers in terms of the construct in order to fit with a particular sample. It
identifies 24 items that can be broken into 3 subscales based on the definition of
organizational commitment that is affective commitment, continuance commitment and
normative commitment. A likert scale format with 7 choices per item is used ranging from
"strongly disagree" to "strongly agree”.


A pilot study was carried out to revise the questionnaires and for item analysis. The validity
and reliability of the questionnaires were measured. The internal consistencies of scale were
assessed through computing Cronbach’s Alpha. The components of factor affecting
organizational commitment show the reliability value ranging from 0.6 to 0.9. Implication from
these values indicates that all of the items used for each component in the questionnaire
have a high and consistent reliability values.


FINDINGS


i)   The relationship between job satisfaction, job involvement, perceived
     organizational support and organizational commitment (Affective, continuance
     and normative).


Correlations were calculated to determine to what extent job satisfaction, job involvement
and perceived organizational support correlated with organizational commitment. As can
be seen in Table 1, significant positive correlations (p < .05) were formed for all three
variables. Correlations ranged from 0.307 for job satisfaction, 0.489 for perceived
organizational support to 0.536 for job involvement.

                    Table 1: Analysis of Pearson Correlation-Zero Order

                                  Job          Job                 Perceived
                              Satisfaction Involvement        Organizational Support
Organizational                 0.307           0.536                   0.489
Commitment                     (132)           (132)                   (132)
                              P=0.00          P=0.00                  P=0.00
Job Satisfaction               1.000           0.150                   0.512
                                (0)            (132)                   (132)
                              P=0.00          P=0.087                 P=0.00
Job Involvement               0.150            1.000                  0.422
                              (132)             (0)                   (132)
                             P=0.087          P=0.00                 P=0.00
Perceived                      0.512           0.422                  1.000
Organizational Support         (132)           (132)                   (0)
                              P=0.00          P=0.00                   P=

                                          *p<0.05


The correlation coefficient value gained from this analysis shows a solid relationship
between the variables (Davies in Baharom, 2004). This results show that there is a
relationship between job satisfaction, job involvement and perceived organizational support
towards organizational commitment among MARA Professional Colleges lecturers.


ii) Contribution of job satisfaction, job involvement, perceived organizational support
    towards organizational commitment (Affective, continuance and normative)


The result from the correlation as shown in Table 1 fulfils the required conditions for
regression analysis. The correlation analysis shows that the studied dependent variable
does not have a high correlation. Tabachnik and Fidell (1996) in Pallant (2001) stated that
regression analysis can only be done if the correlation value between studied enabler is <
0.7. Thus, the regression analysis can be carried out. Linear regression analysis was used to
determine the contribution of the independent variable which is job satisfaction, job
involvement and perceived organizational support towards organizational commitment
among lecturers in MARA Professional College as stated in hypothesis below:


H1: There is significant contribution from job satisfaction towards organizational commitment
      (affective, continuance and normative commitment).
H2: There is significant contribution from job involvement towards organizational
      commitment (affective, continuance and normative commitment).
H3: There is significant contribution from perceived organizational support towards
     organizational commitment (affective, continuance and normative commitment).
Table 2 and 3 show the results of linear regression analysis for the influence of job
satisfaction towards organizational commitment. The linear regression analysis shows that
the independent enabler which is job satisfaction is the indicator with correlation (β=0.346,
t=3.679 and p=0.000) (p<0.05) and the value of R² (R²=0.094) contributes 9.4% towards
organizational commitment among MARA Professional College lecturers. Thus H1 will be
accepted.
Table 2: Analysis of Linear Regression between Job Satisfactions towards Organizational
                                        Commitment
Independent         β          Beta          t         Sig.-t          R²     Contribution
  Variable                      (β)                                               (%)
Job              0.346         0.307       3.679      0.000          0.094        9.4
Satisfaction
Constant         2.926                     7.035      0.000
R                                                 0.307a
R squared                                         0.094
Adjusted R squared                                0.087
Standard Error                                    0.671


                                Table 3: Analysis of Variance
                      Sum of
      Source          Squares          df      Mean Square        F           Sig.
       Regression       6.098          1          6.098         13.533       .000a
       Residual        58.573         130          .451
       Total           64.670         131


The contribution of job satisfaction towards organizational commitment among MARA
Professional College lecturers forms the linear regression as below:


Y= 2.926 + 0.346X1 + 0.671
Y= Organizational Commitment
X1= Job Satisfaction
Constant             2.926
Standard Error       0.416


The result of linear regression analysis for the influence of job involvement towards
organizational commitment is shown in Tables 4 and 5. The linear regression analysis shows
that the independent enabler which is job involvement is the indicator with correlation
(β=0.419, t=7.246 and p=0.000) (p<0.05) and the value of R² (R²=0.288) contributes 28.8%
towards organizational commitment among MARA Professional College lecturers. Thus H2
will be accepted.

  Table 4: Analysis of Linear Regression between Job Involvements towards Organizational
                                        Commitment
Independent         β          Beta           t        Sig.-t         R²     Contribution
  Variable                      (β)                                              (%)
Job               0.419        0.536        7.246      0.000        0.288       28.8
Involvement
Constant          2.604                    10.066      0.000
R                                                  0.536a
R squared                                          0.288
Adjusted R squared                                   0.282
Standard Error                                       0.595


                                Table 5: Analysis of Variance
                       Sum of
      Source           Squares         df         Mean Square      F          Sig.
       Regression      18.607          1             18.607      52.512       .000a
       Residual        46.064         130             .354
       Total           64.670         131


The contribution of job involvement towards organizational commitment among MARA
Professional College lecturers forms the linear regression as below:


Y= 2.604 + 0.419X1 + 0.595
Y= Organizational Commitment
X1= Job Involvement
Constant             2.604
Standard Error       0.259


The regression linear analysis in Tables 6 and 7 show that the independent enabler which is
perceived organizational support is the indicator which has the correlation of (β=0.332,
t=6.386 and p=0.000) (p<0.05) and the value of R² (R²=0.239) contributes 23.9% towards
organizational commitment among MARA Professional College lecturers. Thus H3 will be
accepted.

Table 6: Analysis of Linear Regression between Perceived Organizational Supports towards
                                Organizational Commitment

 Independent       β          Beta            t         Sig.-t      R²       Contribution
   Variable                    (β)                                              (%)
Perceived        0.332        0.489         6.386       0.000     0.239         23.9
Organizational
Support
Constant         3.080                      14.012      0.000
R                                                    0.489a
R squared                                            0.239
Adjusted R squared                                   0.233
Standard Error                                       0.615
Table 7: Analysis of Variance
                        Sum of
      Source            Squares          df    Mean Square          F             Sig.
       Regression        15.444          1         15.444         40.786          .000a
       Residual          49.226         130         .379
       Total             64.670         131


The contribution of perceived organizational support towards organizational commitment
among MARA Professional College lecturers forms the linear regression as below:


Y= 3.080 + 0.332X1 + 0.615
Y= Organizational Commitment
X1= Perceived Organizational Support
Constant             3.080
Standard Error       0.220


From the linear regression analysis can be concluded that job involvement contributed the
most which is 28.8%, followed by perceived organizational support 23.9% and job
satisfaction contributed 9.4% towards organizational commitment among lecturers in MARA
Professional Colleges.


DISCUSSION & PRACTICAL IMPLICATIONS


Social exchange theory is the driving force that primarily influences employee organizational
commitment specifically; job satisfaction, job involvement and perceived organizational
support were identified as key drivers of organizational commitment.

In the current study, job involvement was found to have a strong positively linked with
organizational commitment. Job involvement also was identified as a major contributor to
organizational commitment among lecturers in MARA Professional Colleges. Research by
Janis (1982) and Loui (1995) also support these findings. Literature review regarding job
involvement provided evidence of job involvement as significant predictor of organizational
commitment (Kanugo, 1982; Hafer &Martin, 2006; Wegge et al., 2007; Uygur & Kilic, 2009).

Since job involvement is a strong predictor of organizational commitment, Higher
Educational Division and college administrator must take action to increase job involvement
of the lecturers. The multidimensional model of job involvement by Yoshimura (1996),
suggests that the individual variable which affect the job involvement can be divided into
individual personality and organizational variables. Individual personality such as locus of
control, growth needs, working values, way of being socialized, career stage and successful
job experience whereas for organizational variables are like participation in decision making,
job type and human resource management (Yoshimura,1996). Therefore, people who are
very involved in their job will not feel the need to leave the organization. Thus, by increasing
the degree of employees’ self-esteem will enrich job involvement and may lead to higher
commitment.


Job satisfaction is said to have direct impact on organizational commitment even though it is
not a strong predictor. It reflects that when the level of job satisfaction increases, the level of
organizational commitment also increases slightly. Therefore, this factor should be increased
to improve an employee’s commitment to an organization. Findings from the current study in
relation to facets of job satisfaction revealed that most of the lecturers are satisfied with the
nature of work and least satisfied with operating condition and promotion. Results from the
current study is consistent with the study conducted by Clay-Warner et al.,(2005) on
organizational justice and job satisfaction. Procedural justice and the level of fairness in the
methods by which rewards were distributed among employees by the organization directly
impacted an employee’s level of satisfaction. Therefore, it is recommended that the
institution’s rules, policies and procedures should be fair and equitable According to McFarlin
and Sweeney (1992), the fairness of an institution’s procedures defines the institution’s
capacity to treat its employees fairly. Thus, if employees see the procedures as fair, they are
likely to view the organization positively, which in turn would motivate them to remain
committed to their respective institutions. Therefore, higher authorities in MARA Higher
Education Division should make an intensive effort to improve procedures and reward
distributions at MARA Professional Colleges.


Since most of the lecturers are satisfied with the nature of work, the current jobs should be
enriched so as to make them more interesting, challenging, and motivating. Furthermore,
most research indicated that the presence of certain core job dimensions such as autonomy
(Dunham et al., 1994), job challenge (Meyer et al., 1997), variety (Steers, 1977) and positive
feedback (Hutchison & Garstka, 1996) direct to greater commitment. As a result, it is
recommended that MARA Higher Education Division should give more autonomy to teachers
such as giving them more freedom to choose text books, determine the teaching
methodology, set grading and evaluation criteria for their courses and also be given some
discretion in scheduling their classes. Besides autonomy, current jobs can be enriched by
adding variety to their work like giving a right balance between teaching and research.
Presently, conducting research in their respective areas of specialization is not a
requirement for lecturers in MARA Professional Colleges. If there is a right blend of teaching
and research, the lecturers will not only have a greater variety of work to do but will also get
a chance to upgrade their skills and abilities.
The present study shows a moderately significant relationship between perceived
organizational support and organizational commitment. In line with the current studies, Tek
(2009) found evidence that perceived organizational support has a direct influence on
organizational commitment based on research amongst 134 academicians in four private
universities in Malaysia. Several studies have provided evidence that perceived
organizational support plays a critical role in enhancing organizational commitment
(Eisenberger et al., 1986; Mottaz, 1988; Vancouver et al., 1994). As perceived organizational
support is related to organizational commitment, organizations should find ways to promote
higher perceived organizational support employees. Hence, the organizations should always
recognize the academician’s contributions and care for their well being in order to achieve
the organization’s mission so that the academicians can deliver high quality teaching and
support Malaysia into a leading education hub.


Job satisfaction, job involvement and perceived organizational support have been identified
as significant factors that influence organizational commitment among academicians.
Director of each MARA Professional Colleges may use this useful information as an
opportunity to create committed team of lecturers. This is because lecturers are part of an
influential force that plays a key role in the success of students which at the end shows the
success of the institution.


CONCLUSION


From the above discussion, it is clear that fostering commitment among faculty members
has important implications for educational institutions. Therefore, highly committed lecturers
would make a positive contribution to their respective institutions and may lead to increase
the effectiveness of the educational institutions. Thus, institutions which seek to retain their
lecturers by building strong organizational commitment are in a better position to reap the
benefits of a more dedicated, motivated, and reliable teaching staff.


In total, this study contributes to the limited body of knowledge underlying the formation of
organizational commitment among academicians through the perspectives of social
exchange theory. Besides, it justifies the importance of creating organizational commitment
among academicians in order to turn Malaysia into a leading educational hub.
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KESAN MODEL STAD TERHADAP SIKAP DAN KEMAHIRAN BERKOMUNIKASI
          PELAJAR DALAM MATA PELAJARAN SEJARAH


                              Azwani bin Ismail
                       Bahagian Sumber Manusia MARA
                           azwaniha@yahoo.com

                       Prof. Madya Dr .Datin Zahara Aziz
                        Universiti Kebangsaan Malaysia

                             Dr. Sharifah Nor Puteh
                         Universiti Kebangsaan Malaysia

                     Prof. Madya Dato’ Abdul Razaq Ahmad
                        Universiti Kebangsaan Malaysia

                                      Abstrak

     Kajian ini bertujuan untuk mengkaji keberkesanan Pembelajaran Koperatif
     model Student Team Achievement Division (STAD) terhadap sikap dan
     kemahiran berkomunikasi pelajar terhadap mata pelajaran Sejarah. Reka
     bentuk kajian ini ialah kuasi-eksperimen dengan reka bentuk ujian pra-
     pasca kumpulan-kumpulan tidak serupa, (Pre Test-Post Test, Non-
     equivalent Control Group Design). Sampel kajian ialah pelajar-pelajar
     Tingkatan 2 daripada sebuah sekolah di Selangor iaitu seramai 158 orang.
     Bagi Kumpulan Rawatan adalah seramai 78 orang pelajar manakala
     Kumpulan Kawalan seramai 80 orang. Kajian ini menggunakan pendekatan
     kuantitatif dan disokong oleh data kualitatif. Dua kaedah digunakan dalam
     pemilihan sampel iaitu pensampelan bertujuan (purposive sampling) bagi
     memilih sekolah dan pensampelan rawak mudah (simple random sampling)
     bagi memilih kelas untuk membentuk kumpulan. Alat kajian yang digunakan
     adalah soal selidik pelajar (ujian pra-pasca), pemerhatian dan temu bual
     atas pelajar. Kajian ini dijalankan selama 14 minggu. Dapatan kajian
     menunjukkan terdapat perbezaan min yang signifikan antara kumpulan bagi
     ujian pasca bagi sikap pelajar terhadap mata pelajaran Sejarah t(133) = -
     2.40, p = 0.02. Terdapat perbezaan min yang signifikan antara kumpulan
     bagi ujian pasca bagi kemahiran berkomunikasi pelajar dalam mata
     pelajaran Sejarah t(156) = -2.47, p = 0.02. Hasil kajian ini telah menjawab
     persoalan kajian bahawa kaedah Pembelajaran Koperatif model STAD
     berkesan menerapkan sikap yang positif dan kemahiran berkomunikasi
     yang berkesan dalam mata pelajaran Sejarah. Berdasarkan analisis temu
     bual dengan pelajar dari pelbagai bangsa, jelas menunjukkan para pelajar
     menunjukkan perkembangan yang positif setelah menggunakan model
     STAD.

     Kata kunci: pembelajaran koperatif model STAD, kaedah kuasi-
     eksperimen, sikap, kemahiran berkomunikasi.
PENDAHULUAN


Sejarah ialah mata pelajaran teras dalam Kurikulum Bersepadu Sekolah Menengah (KBSM)
yang wajib dipelajari oleh semua pelajar secara berterusan selama lima tahun. Penyemakan
kurikulum Sejarah Kurikulum Bersepadu Sekolah Menengah (KBSM) (2000) bertujuan
memantapkan Akta Pendidikan 1996, memenuhi semangat Falsafah Pendidikan
Kebangsaan (FPK) dan menyediakan warganegara Malaysia untuk menghadapi cabaran
pendidikan pada abad ke-21. Proses pengajaran dan pembelajaran (P&P) Sejarah
seharusnya menjadi sesuatu yang hidup dan boleh menarik minat pelajar. menurut Anuar
Ahmad, Siti Haishah Abd Rahman & Nur Atiqah T. Abdullah. (2009).


Dua prinsip utama yang ditekankan dalam model STAD adalah persandaran positif dan
tanggungjawab individu. Idea utama di sebalik penggunaan model STAD adalah untuk
memberi motivasi kepada pelajar supaya memberi galakan dan bantuan kepada rakan-
rakannya (Effandi 2005). Slavin (2000) menjelaskan bahawa terdapat dua komponen
penting dalam semua kaedah pembelajaran koperatif iaitu struktur insentif koperatif (pelajar
diberi ganjaran berdasarkan pencapaian kumpulan) dan struktur tugasan koperatif (pelajar
menyelesaikan tugasan secara berkumpulan).


Slavin (2006) juga menyatakan kaedah pengajaran yang berpusatkan pelajar yang menarik
akan menyebabkan pengajaran dan pembelajaran dalam kelas akan lebih menyeronokkan,
malah mengikut Carr (2007) pelajar hendaklah didedahkan dengan pembelajaran yang
berbentuk kumpulan kerana ini akan membantu pelajar untuk belajar membuat keputusan
sendiri. Pembelajaran yang efektif ini akan melahirkan pelajar yang celik sejarah, bersikap
positif, mempertingkatkan kemahiran berkomunikasi sesama rakan, daya pemikiran dan
seterusnya boleh mengambil iktibar daripada pengalaman sejarah.


PERNYATAAN MASALAH


Kebanyakan pelajar mempunyai tanggapan awal bahawa mata pelajaran Sejarah ialah mata
pelajaran yang membosankan. Tanggapan awal ini akan menyebabkan pelajar kurang
tumpuan dan kurang bermotivasi untuk mempelajari Sejarah. Menurut Abdul Razak dan Ali
(2000) dan Anuar Ahmad, Siti Haishah Abd Rahman & Nur Atiqah T. Abdullah. (2009), mata
pelajaran Sejarah kurang diminati pelajar dan membosankan. Kajian oleh Abdul Razak dan
Abdullah (2000) terhadap 240 pelajar di daerah Petaling Jaya dan Kuala Selangor
mendapati pelajar-pelajar menganggap mata pelajaran Sejarah sebagai subjek sampingan
yang tidak mendatangkan faedah. Tanggapan ini dikaitkan dengan mata pelajaran Sejarah
yang tidak memberikan jaminan pekerjaan dan tidak mempunyai nilai komersial
(Sivachanlingam et al. 2008). Pengajaran dan pembelajaran mata pelajaran Sejarah adalah
berbeza dengan mata pelajaran lain. Dalam pendidikan mata pelajaran Sejarah, pelajar
tidak sahaja diajar mendapatkan maklumat atau pengajaran dari peristiwa sejarah, malah
apa yang lebih penting adalah untuk membentuk pelajar yang faham makna sejarah dan
seterusnya dapat merealisasikan dalam kehidupan seharian dan merancang kehidupan
akan datang (Sivachanlingam et al. 2008).


Keberkesanan pengajaran Sejarah bergantung kepada perancangan dan kualiti guru
sejarah. Guru sejarah yang baik menunjukkan kebolehan dan keupayaan dari segi kualiti
diri, sosial dan profesional menurut Zahara Aziz (2000). Kelemahan dari segi pengajaran
masih menjadi isu utama yang berkaitan dengan pencapaian pelajar dalam peperiksaan
SPM. Corak pengajaran Sejarah di sekolah masih bersifat konvensional dan membosankan
pelajar. Berasaskan kajian Mohamad Sultan (2000) di sebuah sekolah di daerah Sabak
Bernam, menunjukkan pengajaran mata pelajaran Sejarah di sekolah berkenaan kurang
berkualiti.


Malah mengikut Hariyono (1995) guru Sejarah jarang memerhatikan sama ada maklumat
tersebut dapat membangkitkan minat atau semangat yang boleh membentuk pelajar yang
faham sejarah. Kenyataan ini telah disokong oleh Khoo Kay Kim (2008) yang menyatakan
pembelajaran mata pelajaran Sejarah lazimnya dijalankan dalam bentuk hafalan. Pelajar
difokuskan dengan menitikberatkan dari aspek mengingati tarikh, fakta-fakta serta
pergolakan dunia yang telah terjadi beribu-ribu tahun yang lampau. Ini akan menyebabkan
mereka mempunyai perspektif yang sempit tentang proses perkembangan masyarakat dan
negara, malah tidak memberi mereka peluang untuk berkomunikasi secara berkesan.


Oleh itu, ramai pelajar mendapati pelajaran Sejarah sangat menjemukan dan tidak
merangsang pelajar untuk berfikir dan berkeyakinan dalam memberi pendapat. Khoo Kay
Kim (2008). Menurut Zahara Aziz (2000) sekiranya guru mementingkan pengajaran yang
memberi latihan kepada pelajar untuk berfikir, maka apabila pelajar meninggalkan alam
persekolahan dan menjejak ke alam baharu, mereka akan berasa lebih yakin kerana
berkebolehan dan berinisiatif dalam menyelesaikan masalah dan berfikiran dengan kritis dan
kreatif. Tanggapan negatif pelajar ini boleh dilenyapkan jika guru berfikiran kreatif dan
inovatif, yang dapat melaksanakan proses pengajaran dengan berkesan berserta dapat
memberi peluang kepada pelajar untuk lebih berinteraksi sesama pelajar dan menimbulkan
keseronokan di dalam kelas.


OBJEKTIF KAJIAN

1. Mengenal pasti tahap sikap dan kemahiran berkomunikasi pelajar dalam mata pelajaran
   Sejarah antara pelajar yang menggunakan Pembelajaran Koperatif model STAD dengan
   pelajar dalam kumpulan kawalan.
2. Mengenal pasti perbezaan sikap dan kemahiran berkomunikasi pelajar dalam mata
   pelajaran Sejarah antara pelajar yang menggunakan Pembelajaran Koperatif model
   STAD dengan pelajar dalam kumpulan kawalan.
METODOLOGI

Fokus utama kajian ini adalah untuk menentukan kesan pengajaran menggunakan kaedah
Pembelajaran Koperatif model STAD atas sikap pelajar dan kemahiran berkomunikasi
pelajar dalam mata pelajaran Sejarah. Dalam kajian ini pengkaji menggunakan
Pembelajaran Koperatif model Student Team Achievement Division (STAD). Pembelajaran
Koperatif model STAD menggunakan pendekatan pembelajaran berpusatkan pelajar dan
pelajar belajar dalam kumpulan yang berstruktur. Pelajar-pelajar ditugaskan untuk bekerja
dalam satu kumpulan kecil yang terdiri daripada 4 hingga 5 orang pelajar, terdiri daripada
lelaki dan perempuan, pelbagai bangsa dan pelbagai pencapaian akademik. Setelah guru
menyampaikan bahan pelajaran, para pelajar akan berbincang dan bekerjasama dalam
kumpulan masing-masing serta memastikan semua anggota kumpulan akan menguasai
pelajaran itu. Setelah menjalani sesuatu aktiviti setiap anggota kumpulan akan menduduki
ujian secara individu. Markah yang diperoleh oleh setiap ahli kumpulan dicampur untuk
memperoleh markah kumpulan. Kumpulan yang terbaik akan diberikan ganjaran seperti
hadiah yang akan diberikan kepada setiap ahli kumpulan. Oleh itu untuk mendapat markah
yang baik, setiap ahli kumpulan mesti membantu ahli-ahli kumpulannya.


HIPOTESIS KAJIAN

Ho 1: Tidak terdapat perbezaan min yang signifikan untuk sikap pelajar terhadap mata
      pelajaran Sejarah antara pelajar yang menggunakan Pembelajaran Koperatif model
      STAD dengan pelajar dalam kumpulan kawalan.
Ho 2:Tidak terdapat perbezaan min yang signifikan untuk kemahiran berkomunikasi pelajar
      dalam mata pelajaran Sejarah antara pelajar yang menggunakan Pembelajaran
      Koperatif model STAD dengan pelajar dalam kumpulan kawalan.

REKA BENTUK KAJIAN


Reka bentuk kajian ini ialah menggunakan kaedah kuasi-eksperimen dengan reka bentuk
ujian prapasca kumpulan-kumpulan tidak serupa (Pre Test-Post Test, Non-equivalent
Control Group Design). Reka bentuk ini dipilih kerana kajian ini menggunakan kelas-kelas
yang sedia ada, iaitu subjek kajian bagi Kumpulan Eksperimen dan Kawalan tidak boleh
dipilih secara rawak kerana terikat dengan peraturan yang telah ditetapkan oleh pihak
sekolah (Chua 2006; Lim 2007; Wierma 2000; Johnson & Christensen 2000). Dalam reka
bentuk ini, pengkaji menggunakan pasangan kumpulan responden yang mempunyai ciri-ciri
yang hampir sama iaitu responden dari Kumpulan Eksperimen dan Kumpulan Kawalan.


Selain daripada itu, kaedah kualitatif yang menggunakan temu bual dan pemerhatian juga
digunakan sebagai sokongan kepada hasil kajian yang diperoleh daripada analisis
kuantitatif. Malah mengikut Marohaini (2001) penggunaan teknik temu bual juga
membolehkan penyelidik mengumpul pendapat, pemikiran dan pandangan dalam bentuk
pernyataan langsung daripada peserta kajian sendiri. Kajian kualitatif dijalankan untuk
mendapatkan kefahaman yang mendalam terhadap sesuatu perkara yang ingin dikaji
kerana banyak perkara tidak dapat dijelaskan hanya merujuk kepada data numerika dalam
penyelidikan kuantitatif sahaja (Marohaini 2001, Chua 2006). Selain itu, kajian kualitatif juga
dijalankan untuk mendapat maklumat terperinci berkaitan sesuatu perkara yang dikaji (Chua
2006).


     Rajah 3.1: Reka Bentuk Ujian Pra dan Pasca Kumpulan Rawatan dan Kawalan
                          Ujian Pra           Kaedah              Ujian Pasca
Kumpulan rawatan              A1                 X1                   A2
                           -----------------------------------------------
Kumpulan kawalan              A3                 X2                   A4


Dalam reka bentuk ini, A1 dan A3 adalah merupakan pelaksanaan ujian pra. A2 dan A4
adalah pelaksanaan ujian pasca. Manakala X1 dan X2 adalah kaedah pembelajaran yang
diberikan ke atas Kumpulan Eksperimen dan Kawalan. Ujian pra dijalankan untuk melihat
kesetaraan antara kumpulan, kerana kedua-dua kumpulan pelajar tidak dipilih secara rawak
dan juga bertujuan untuk digunakan sebagai pengawalan secara statistik. Ujian pasca akan
dijalankan setelah kedua-dua kumpulan selesai mengikuti kaedah pengajaran iaitu bagi
Kumpulan Rawatan, pelajar akan didedahkan dengan Pembelajaran Koperatif model STAD
dan Kumpulan Kawalan menggunakan kaedah Pembelajaran Konvensional. Kedua-dua
kumpulan menerima bahan pengajaran yang sama dan jumlah masa pengajaran juga sama.


SAMPEL KAJIAN


Sampel kajian adalah seramai 158 orang, Kumpulan Rawatan adalah seramai 78 orang
pelajar manakala Kumpulan Kawalan seramai 80 orang. Daripada 158 orang pelajar
tersebut, untuk Kumpulan Kawalan seramai 30 orang (18.99%) adalah pelajar Melayu, 25
orang (15.82%) pelajar Cina dan 25 orang (15.82%) adalah pelajar India. Manakala untuk
Kumpulan Rawatan seramai 30 orang (18.99%) adalah pelajar Melayu, 25 orang (15.82%)
pelajar Cina dan 23 orang (14.56%) ialah pelajar India.


DAPATAN KAJIAN


Salah satu andaian untuk kaedah kajian Kuasi Eksperimen ialah kumpulan-kumpulan yang
terlibat dalam kajian adalah setara atau homogen pada peringkat awal kajian. Untuk
memastikan andaian ini dipatuhi analisis statistik inferensi bagi ujian pra dilakukan. Pada
ujian pra andaian adalah tidak terdapat perbezaan min yang signifikan antara kumpulan-
kumpulan yang terlibat dalam kajian. Bagi menguji kehomogenan antara Kumpulan Kawalan
dan Rawatan, Ujian-T digunakan.

Keputusan Ujian-T ke atas kedua-dua pemboleh-pemboleh ubah bersandar kajian
menunjukkan tiada perbezaan min yang signifikan antara Kumpulan Kawalan dan Rawatan
bagi ujian pra untuk pemboleh ubah sikap pelajar terhadap mata pelajaran Sejarah t(156) = -
0.25, p = 0.80. Tiada perbezaan min yang signifikan antara Kumpulan Kawalan dan
Rawatan bagi ujian pra untuk pemboleh ubah kemahiran berkomunikasi dalam mata
pelajaran Sejarah t(156) = 0.11, p = 0.91.


  Jadual 1: Min, Sisihan Piawai dan Tahap bagi Pemboleh-pemboleh ubah Kajian Untuk
                         Kumpulan Kawalan dan Rawatan Bagi Ujian Pasca
                                                            Sisihan
 Pemboleh ubah Bersandar              Kumpulan      Min               Tahap
                                                            Piawai

 Sikap Terhadap     Mata    pelajaran Kawalan         3.62     1.42         Sederhana
 Sejarah
                                      Rawatan         3.93     1.20         Sederhana

 Kemahiran Berkomunikasi      Dalam Kawalan           3.77     1.26         Sederhana
 Mata pelajaran Sejarah
                                      Rawatan         4.03     1.16         Tinggi


Jadual 1 memaparkan secara keseluruhan tahap bagi pemboleh-pemboleh ubah kajian
untuk Kumpulan Kawalan dan Rawatan bagi ujian pasca, secara keseluruhannya dapatlah
disimpulkan, kemahiran berkomunikasi dalam mata pelajaran Sejarah bagi Kumpulan
Rawatan berada di tahap tinggi manakala bagi pemboleh ubah sikap terhadap mata
pelajaran Sejarah berada pada tahap sederhana. Manakala bagi Kumpulan Kawalan pula,
sikap terhadap mata pelajaran Sejarah dan kemahiran berkomunikasi pelajar dalam mata
pelajaran Sejarah berada pada tahap sederhana.


                      Jadual 2: Keputusan Ujian-T Bagi Ujian Pasca
Pemboleh ubah      df      t       P      Keputusan             Hipotesis    Rumusan
Bersandar
Sikap Terhadap     132.59   -2.40   0.02 Terdapat perbezaan       Ho 1       Hipotesis
Mata pelajaran                           min yang signifikan                 ditolak
Sejarah
Kemahiran          156.00   -2.47   0.02 Terdapat perbezaan       Ho 2       Hipotesis
Berkomunikasi                            min yang signifikan                 ditolak


Jadual 2 menunjukkan keputusan Ujian-T ke atas pemboleh-pemboleh ubah bersandar
sikap pelajar dan kemahiran berkomunikasi dalam mata pelajaran Sejarah untuk Kumpulan
Kawalan dan Rawatan bagi ujian pasca. Terdapat perbezaan min yang signifikan antara
kedua-dua kumpulan bagi ujian pasca untuk sikap pelajar terhadap mata pelajaran Sejarah
t(133) = -2.40, p = 0.02, dengan ini Ho 1 ditolak. Terdapat perbezaan min yang signifikan
antara kedua-dua kumpulan bagi ujian pasca untuk kemahiran berkomunikasi dalam mata
pelajaran Sejarah t(156) = -2.47, p = 0.02, dengan ini Ho 2 ditolak
Jadual 3: Nilai Min Pemboleh ubah Bersandar Kajian dan Saiz Kesan bagi Ujian Pasca
                                     Kawalan (N =80)     Eksperimen (N=78) Saiz
                                                                             Kesan
 Pemboleh ubah Bersandar            Min        Sisihan Min     Sisihan
                                               Piawai          Piawai        Cohen's d

 Sikap Terhadap Mata pelajaran      39.83      10.93    43.28 6.79           0.38
 Sejarah

 Kemahiran Berkomunikasi            33.90      6.59     36.31 5.69           0.40
 Dalam Mata pelajaran Sejarah



Jadual 3 menunjukkan nilai saiz kesan mengikut kaedah Cohen (Cohen’s d) dilaporkan bagi
setiap pemboleh ubah (Cohen 1988). Menurut Wolf (1986) secara umumnya nilai Cohen’s d
yang lebih besar daripada 0.25 boleh menunjukkan kesan rawatan yang signifikan. Nilai
Cohen’s d bagi pemboleh ubah sikap pelajar terhadap mata pelajaran Sejarah adalah 0.38
dan bagi pemboleh ubah kemahiran berkomunikasi dalam mata pelajaran Sejarah adalah
0.40. Kedua-dua nilai Cohen’s d adalah lebih besar daripada 0.25 ini menunjukkan bahawa
kesan Pembelajaran Koperatif model STAD adalah signifikan.


PERBINCANGAN DAN IMPLIKASI KAJIAN


i)    Kesan Pembelajaran Koperatif Model STAD Terhadap Sikap pelajar


Pembelajaran Koperatif model STAD telah memberi satu dimensi baru kepada pelajar dalam
mempelajari bahan-bahan Sejarah dalam persekitaran yang menyeronokkan, diberi
kebebasan untuk meluahkan idea dan kreativiti melalui aktiviti yang pelbagai sekali gus
mengukuhkan pemahaman mereka tentang bahan pelajaran. Pembelajaran melalui kaedah
ini jelas menggembirakan pelajar, meningkatkan keyakinan mereka dan membolehkan
kurikulum Sejarah dikembangkan secara lebih praktikal. Inilah kesan ketara yang dapat
dilihat dan diperhatikan terhadap keseluruhan gerak kerja pelajar sepanjang proses P&P
Sejarah dilaksanakan.


Dapatan kajian ini menunjukkan terdapat perbezaan min yang signifikan bagi aspek sikap
pelajar terhadap mata pelajaran Sejarah antara Kumpulan Eksperimen dan Kawalan. Ini
bermakna bahawa Pembelajaran Koperatif model STAD berjaya mengubah sikap pelajar
terhadap mata pelajaran Sejarah menjadi lebih positif walaupun nilainya masih berada pada
tahap yang sederhana. Perubahan sikap ini terjadi kerana pelajar telah diberi peluang
secara terbuka untuk bersama-sama aktif dalam perbincangan kumpulan serta
menggunakan pelbagai keupayaan deria lain yang selama ini kurang digunakan.


Keyakinan diri pelajar semakin meningkat terutamanya ketika mengemukakan soalan dan
pendapat tentang isu-isu sejarah negara. Motivasi untuk belajar juga semakin baik kerana
Pembelajaran Koperatif model STAD lebih mementingkan pergantungan positif antara rakan
dalam kumpulan, pelajar yang lemah telah dibantu oleh pelajar yang lebih berpengetahuan.
Penggunaan Pembelajaran Koperatif model STAD yang berorientasikan pelajar ini, telah
menarik minat pelajar untuk belajar Sejarah. Tanggapan bahawa mata pelajaran Sejarah
membosankan dapat diatasi.


Kajian ini juga menjadi bahan literatur berkaitan penggunaan kaedah Pembelajaran
Koperatif yang dilaksanakan di Malaysia. Pelajar menunjukkan sikap yang lebih positif
terhadap pembelajaran mereka, natijah daripada penggunaan model STAD (Effandi &
Zanaton 2007; Mazlan 2002; Suhaida et al. 2004). Kajian luar negara juga mengesahkan
bahawa pembelajaran melalui kerjasama kumpulan dan aktiviti dapat meningkatkan sikap
positif pelajar terhadap pembelajaran, bersosial dan menjadikan pelajar berfikiran kritikal
yang dinamik (Slavin 2001, Zahara dan Md. Anowar 2011).


Dapatan temu bual dengan pelajar juga mendapati mereka rasa lebih seronok, lebih aktif
dan bersemangat ketika belajar Sejarah. Sedangkan sebelum ini mereka bosan dan
mengantuk kerana guru mengajar secara sehala dan tidak melibatkan mereka secara aktif.
Data pemerhatian pula menunjukkan terdapatnya perubahan sikap yang positif dalam diri
pelajar, mereka saling tolong-menolong dan bersama-sama menyiapkan tugasan yang
diberikan dalam suasana yang seronok, berfokus serta tidak terlalu menekan pelajar.


ii) Kesan Pembelajaran Koperatif Model STAD Terhadap Kemahiran Berkomunikasi
    Pelajar


Setelah berada dalam Kumpulan Eksperimen yang menggunakan kaedah Pembelajaran
Koperatif model STAD, pelajar-pelajar didapati menunjukkan peningkatan dari segi
kemahiran berkomunikasi sama ada dengan guru, rakan belajar dan cara berbincang
menggunakan bahan pelajaran. Pelajar didapati lebih berkeyakinan memberikan idea dan
pendapat, disokong oleh persekitaran yang memberi ruang dan peluang untuk mereka
berbincang secara sistematik.

Pelajar-pelajar dari Kumpulan Eksperimen menyatakan mendapat pengalaman yang
menarik sewaktu bekerjasama dalam kumpulan terutamanya semasa berbincang serta
bertukar-tukar pendapat ketika menyiapkan tugasan secara berkumpulan. Pelajar juga
mengakui wujudnya sikap saling bergantung atau bersandar secara positif dalam kalangan
pelajar dalam sesuatu kumpulan bagi mencapai matlamat. Hal ini ada dinyatakan dalam
kajian yang dilakukan oleh Mohd Fadzli dan Normah (2011). Pelajar yang lebih pandai akan
menolong rakan kumpulannya untuk memahami tugasan atau topik yang diberi.
Sebagaimana yang diutarakan oleh Diggins (2004) iaitu pelajar mesti menjadi pendengar
yang baik, berfikir sebelum bercakap, menerima pandangan orang lain, berkeupayaan
menerangkan dengan jelas, berterus terang dan sabar dengan kerenah rakan.


Tugasan berkumpulan seperti mencipta sajak, membuat kad kemerdekaan atau merancang
pembentangan membolehkan pelajar berbincang sesama rakan. Aktiviti ini membantu
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5. jilid 4 bil1 jun 2012

  • 1. ESTIMATION AND COMPUTATION ABILITIES OF MRSM STUDENTS ON ITEMS INVOLVING WHOLE NUMBERS Noraini Noordin Universiti Teknologi Mara, Perlis noraininoordin@perlis.uitm.edu.my Fadzilah Abdol Razak Universiti Teknologi Mara, Perlis fadzilah.ar@perak.uitm.edu.my Nooraini Ali Universiti Teknologi Mara, Perlis noorainiali@perlis.uitm.edu.my Abstract It is a well established fact that estimation and number sense are closely related. Number sense is the ability to understand and use the meaning of numbers in communicating, processing and interpreting information. However, students are found to demonstrate little understanding of numerical situations in which they solve number problems and this has been the concern of mathematics educators. This lack of number sense is usually brought about by not understanding the mathematical exercises they learned in schools. Students can normally manipulate and follow symbolic rules better than at making sense of these numerical practices. Estimation allows the students to find an approximate answer before carrying out the calculation, thus helps to determine whether an answer is reasonable or not. This paper discusses the relationship between the estimation and computation skills of Form One students at Maktab Rendah Sains Mara (MRSM) in Malaysia on items involving Whole Numbers. Keywords: Estimation; Number Sense; Numerical Situations
  • 2. INTRODUCTION In any estimation exercise, a student selects simple numbers to operate on mentally to produce an approximate answer (Reys, 1984; Segovia & Castro, 2009). This definitive characteristic of an estimation exercise indicates the close relationship between estimation and mental computation. However, mental computation is not an inborn or inherent trait. Experiences and practice are required before one is able to develop strategies that are more sophisticated than traditional written methods (McIntosh, 2002; Asplin, Frid & Sparrow, 2006). This development can be experienced in many ways and need not necessarily be in the form of a test (Heirdsfield, 2002). Ahmad Zanzali and Ghazali (2002) stated that out of five strands of number sense (understanding the meaning of size and numbers, understanding the use of equivalent forms and representations of numbers, understanding the meaning and effect of operations, understanding the use of equivalent expressions and computing and counting strategies), students demonstrated having difficulties in all strands except the last two strands of number sense. It was found that although Year One to Year Three students were not formerly exposed to addition and subtraction mental calculation strategies, they were able to demonstrate intuitive mental computation strategies to solve addition and subtraction problems varying from an inefficient strategy of counting on their fingers to more sophisticated and simpler strategies such as using doubles, bridging through ten, separation and wholistic strategy (Ghazali, Alias, Anuar Ariffin & Ayub, 2010). These studies indicated the need to understand how students think when they solve mathematics problem. In another study, Ghazali, Abdul Rahman, Ismail, Idros and Salleh (2003) identified three types of strategies employed by Year One to Year Three students: i) Emergent strategies to refer to immature strategies of doing mathematics problems ii) Beginning strategies to refer to methods that exhibit some indication of thinking and employment of strategies of solving the problem that gives the correct answer but with no expert-like strategies iii) Competent strategies to refer to expert-like method of doing the mathematics. These categories were used to formulate a matrix that will be able to define different levels of strategies employed by students as well as classify the levels of the students.
  • 3. Students undergo six years of learning Mathematics at primary schools in Malaysia. The section “points to note” in the Integrated Curriculum for Primary School specifies that mental computation is to be emphasized in Primary School Mathematics at Year One and Year Two (Mathematics Year 1, 2002; Mathematics Year 2, 2003). However, mental computation is not formally taught in schools. As for estimation and approximation, students are exposed to these vocabularies at Year Three under the topic Numbers. By the end of Year Three, students will be able to estimate quantities of objects up to 1000 beginning with smaller values to higher values and round whole numbers less than 10000 to the nearest ten. Students are also taught to ensure the reasonableness of any estimates made. They are also exposed to estimates in topics like Mass and Volume of Liquid (Mathematics Year 3, 2003). At Year Five, estimation can be found in some other learning areas such as Whole Numbers, Decimals, Integers, Basic Measurements, Perimeter and Area, and Solid Geometry (Mathematics Year 5, 2006). Estimation is a significant topic in school mathematics. It is a process rather than content knowledge in the mathematics curriculum, and it applies to several strands (Bana & Dolma, 2006). According to the National Research Council (2001), being able to do quick and accurate mental computations and estimations has two advantages: i) Students are able to check the reasonableness of an answer ii) Students are able to better appreciate the knowledge of place value, mathematical operations and general number sense. However, studies found that a great number of students have encountered difficulties doing simple mental calculation or estimating answers to a problem, causing them to form a significant barrier to using mathematics in their everyday life (Case & Sowder, 1990; Star, Lee, Chang & Glasser, 2007). This paper will discuss the results of a study carried out to assess the estimation and computation abilities of Form One students. The study focused on four major areas in the curriculum, namely, Whole Numbers, Decimals, Money and Fractions. This paper will only focus on the results obtained with respect to only one area, namely, Whole Numbers. METHODOLOGY Selected samples were from MRSMs in the North Zone of Malaysia, namely MRSM Beseri in Perlis, MRSM Kubang Pasu in Kedah and MRSM Gerik and MRSM Pengkalan Hulu in Perak. Data were collected in the first semester of 2010 at the respective colleges. A three-phase procedure was carried out on these samples of
  • 4. students, beginning with a short test on estimation that had a time limit of 30 seconds per item to minimize any precise calculations. Students were also not permitted to write anything on the test paper, other than their responses. This was followed by a short test on computation with a slightly longer time limit, namely three minutes for each item. Students were allowed to use any method/s of their choice, but calculators were not permitted in the computation test. After the test sessions, a selection of three male and three female students were interviewed using the Probing Interview and the interview sessions were audio-taped. The instruments used had 15 similar stemmed items which were constructed based on the topics in the curriculum for Mathematics Year Three to Year Six covering four areas: Whole Numbers (5 items – 33.33%), Fractions (4 items – 26.67%), Decimals (4 items – 26.67%), and Money (2 items – 13.33%). The multiple-choice format was chosen for the Estimation Test to safeguard against students doing precise calculations (Bana and Dolma, 2006). Rasch Measurement Model was used to analyze the responses to both tests. Table 1 summarizes statistics of measures of reliability and correlation for both tests: TABLE 1: Summary Statistics of Measures of Reliability and Correlation TYPE OF TEST ITEMS Computation Test Estimation Test Item Reliability 0.98 0.98 Person Reliability 0.44 0.64 Item Raw Score-To-Measure Correlation -0.96 -0.94 Person Raw Score-To-Measure Correlation 0.97 0.98 The person and item reliability indices were rated using the rating scale instrument quality criteria. It reported the same index of 0.98 (> 0.94) for item reliability of both tests, thus the instrument measured an excellent item reliability rating. Since item reliability was not dependent on the length of a test, the recorded indices implied that both tests had a wide difficulty range, both tests were administered on a large sample and inferences were expected to be consistent. In addition, item ordering had a very high probability of being replicated if these same items were given to a different group of students (Bond & Fox, 2007). High reliability values also implied that the number of ranges in the scale that can be distinguished with confidence across samples also increased. Studies indicated that measures with reliabilities of 0.67 will tend to vary within two groups that can be separated with 95% confidence, measures of reliabilities of 0.80 will vary within three groups; of 0.90, four groups; of 0.94, five groups; of 0.96, six groups; of 0.97, seven groups, and so on (Fisher Jr., Elbaum & Coulter, 2010). However, the person reliability indices reported low values of 0.44 and 0.64 on the Computation Test and
  • 5. the Estimation Test, respectively. Since person reliability does not depend on sample ability variance, this paper can confidently say that this low value may imply that there was not much difference between the students’ abilities. It was also not possible to discriminate the samples into different levels, thus, this sample did not demonstrate a hierarchy of ability (Bond & Fox, 2007). In addition, a very high positive person raw score-to-measure correlation and very low negative item raw score-to-item correlation implied a low proportion of very high and very low scores (Winsteps, 2011). These values also confirmed the earlier finding that there was no distinct ability difference between the selected students from these colleges. RESULTS How students think cannot be observed directly, but can be evaluated from the work that they produced. These evaluations can help identify their level of conceptual understanding or highlight misconceptions (Wong, Evans & Anderson, 2006). This paper will focus its discussion on only five items on Whole Numbers, namely items 4, 5, 7, 8 and 11. Table 2 summarizes the objectives of these items: TABLE 2: Distribution of Items according to Topics and Objectives TOPIC ITEM OBJECTIVES 4 Develop number sense up to 1000000 5 Develop number sense up to 1000000 WHOLE 7 Develop number sense up to 1000000 NUMBERS Understand and use the vocabulary of estimation and 8 approximation 11 Multiply any two numbers with the highest product of 100000 Item maps of the responses to both tests were built to determine the hierarchy of difficulty among these items according to the type of test. The item maps found item 7 to be the easiest Whole Number item on both tests. The items ordered from easiest to most difficult were items 7, 5, 4, 8, and 11 for the Estimation Test, and items 7, 11, 5, 8 and 4 for the Computation Test. The maps also found items 5 and 8 on the Computation Test to lie on the same ability level.
  • 6. DISCUSSION Table 3 displays items and percentage measures for items on Whole Numbers: TABLE 3: Item and Percentage Measures for Items on Whole Numbers Estimation Test Computation Test Item No. Item Percentage Item Measure Percentage Measure Measure Measure 4 294 76 156 41 5 338 88 304 79 7 381 99 352 91 8 260 68 299 78 11 238 62 333 86 As can be seen, students were more able to handle items 4, 5 and 7 in the Estimation Test than on the Computation Test. From among these three items, students found item 7 to be the easiest and item 4 to be the most difficult. In particular, item 4 measured the largest range in percentage measure between both tests. The small range in percentage measure for item 7 suggested that students had no problem finding the place value for a digit in a number up to 1000000 in both tests. The level of performance shown on item 5 indicated that they have achieved the first strand in number sense; they were able to understand and use the meaning and size of numbers. However, they were not able to utilize their mastery of the ability achieved in item 5, on item 4; item 4 presented a situation that required a higher thinking capability from the students to enable them to manipulate the knowledge of the size of numbers. These three items involved the recognition of place values under different circumstances. Students first recognized the place of a digit of a number at Year One for numbers up to 20, at Year Two for numbers up to 1000, and the number of digits increased as they progressed through primary school, thus they should be able to determine what value a digit represented in any number (Mathematics Year 2, 2003). More than 90% of the students were found able to associate the digit “6” in the given number for item 7 to 6000. This paper wishes to emphasize that better student performances in the Estimation Test can be accounted for by the presence of four solution alternatives A, B, C and D provided in these items, as shown in Table 4.
  • 7. TABLE 4: Items 4, 5 and 7 in the Computation and Estimation Tests Item Computation Test Estimation Test 4 Find the missing numbers in the Find the missing numbers in the sequence given sequence given below: below: 917 158, _____, _____, 887 158 917 158, ____, ____, 887 158 A 927 158, 937 158 B 927 158, 907 158 C 907 158, 897 158 D 897 158, 892 158 5 Round up the following numbers to Which of the following numbers when rounded the nearest ten thousand. off to the nearest thousand becomes 580 000? 579 324 A 579 324 C 580 516 580 516 B 579 562 D 581 105 579 562 581 105 7 The value of the digit 6 in the The value of the digit 6 in the number number 856 943 is 856 943 is A 60 C 6 000 B 600 D 60 000 The students demonstrated having more problems rounding up numbers to the nearest ten thousand in item 5 of the Computation Test than rounding up to the nearest thousand in item 5 of the Estimation Test. It was perhaps much easier in the Estimation Test because the solution alternatives given in the test may have provided the students with better chances of determining if the thousands in the number was equal or greater than 5, or smaller than 5 to enable rounding off to the nearest 10000 (Mathematics Year 5, 2006). Since the third digit in the number 579562 was “5”, an increment of one was added to the fourth digit “9”, thus the solution alternative 579562 qualified to be rounded off to the nearest thousand as 580000. In terms of frequency of students failing item 5 of the Estimation Test, 581805 ranked the highest followed by 579324 and 580516. However, these answers did not suggest any particular rule used by the students in the estimation process. Similarly, item 5 of the Computation Test showed that the fourth digit exceeded 5 in the first and the third numbers, thus all the given numbers should round off to 580000. In order to better understand the mistakes that may have been performed by students in recognizing and applying the place value of digits in a number, this paper will take a look at the wrong answers given by students for item 5 of the Computation Test, as displayed in Table 5.
  • 8. TABLE 5: Wrong Answers for Item 5 of the Computation Test NUMBER WRONG ANSWERS 579 324 579 000, 578 000, 590 000, 600 000, 579 320, 58 000 580 516 581 000, 680 516, 580 500, 580 520, 600 000, 58 000 579 562 581 000, 579 560, 600 000, 58 000 581 105 581 000, 590 000, 581 110, 590 000, 600 000, 58 000 To be more precise, this paper will take a look at how students rounded off 579324 to the nearest ten thousand. Analysis of answers to this item revealed that the most prominent wrong answer given was 579000. This could only mean that students associated the place value for the third digit to 10000 instead of 1000. The wrong answer 600000 could be attributed to students wrongly associating the fifth digit to the place value of 10000 instead of 100000. Further research has to be done to investigate the flaws behind the incorrect answers like 570000 and 579320. Was it possible for students to have overlooked the process of determining if the selected digit was smaller or greater than 5 thus coming up with the incorrect answer of 570000? Could it be that the students did not understand the need to identify the digit with the correct place value, hence giving the answer 579320? In item 4, the students had more difficulty finding the missing numbers in a sequence of numbers up to 1000000 in the Computation Test than the Estimation Test. The item in the Estimation Test was much easier because students could see that there was a common difference of 10000 between the numbers in the series by just comparing the solution alternatives given to the blanks in the sequence of numbers in the item. By looking at the construct of item 4 in Table 3, almost 90% of students were able to eliminate solution alternatives A) 927158, 937158 and B) 927158, 907158 as answers for this particular item because these alternatives did not fit the decreasing pattern of the given sequence. The 294 students who passed this item chose the solution alternative C) 907158, 897158 over D) 897158, 892158 as the answer because both these numbers exhibited a common difference of 10000 between them and also from the first and fourth number in the sequence. However, this pattern was definitely not obvious to some students, causing them to opt for a different solution than C) and almost 11% of them did not attempt to answer this item. Unlike the Estimation Test, students who attempted this item in the Computation Test had to come up with their own counting and computing strategies for this item. However, it is important to take note that there were some students who passed this item in the Estimation Test but failed in the Computation Test. Contrasting items 4, 5 and 7, the students were found to demonstrate less ability on items 8 and 11 on the Estimation Test than on the Computation Test. Item 8 required students to determine the best estimate of the total number of sweets that Aishah bought given that she bought 7 packets with an average value of 106 to 120 sweets per packet. Both tests provided four solution alternatives for the students to choose from in this item. The construct of item 8 was almost similar for both tests. The Computation Test required an answer to the question “Which of the following
  • 9. values would be the best estimate of the total number of sweets that she bought?” while the Estimation Test wanted students to “Estimate the total number of sweets that she bought.” Contrary to the paper’s earlier perception that performances in both tests should be almost the same for this item, analysis of answers to this item noted a 10% difference in percentage measure between both tests as displayed in Table 3. Thus, students were better at finding the correct counting and computing strategies; hence demonstrating they were less competent and had lower number sense at estimation than computation. The paper wishes to point out that the nature of the construct in the Computation Test may have had some influence on how students should think. Unlike item 8, the construct of item 11 was the same for both tests. Surprisingly, Table 3 indicates that there was a 24% difference in percentage measure between performances on both tests. In tackling item 11 in the Computation Test, students had to find all the products for 750×45, 833×25, 961×40 and 1025×27, then round them up before deciding which among these products lie between 30000 and 35000. These computations took time to finish. However, analysis of answers indicates that this was easier for the students to do than to eliminate the products 833×25 and 1025×27 because they were smaller than 30000, and 961×40 because it was larger than 35000 in the Estimation Test before deciding that 750×45 would be the most appropriate answer. This paper wishes to emphasize that the performance on this item may be taken as a cue that students were not equipped with the knowledge on how to estimate product of numbers, thus causing 38% of the students to fail this item in the Estimation Test. Students may not understand the mathematical exercises they learned in schools, and may have approached mathematics as a set of rules to memorize. Thus this explains the lack of number sense shown by the students for this item. IMPLICATIONS OF THE STUDY In this study, Rasch Measurement Model was used to build item maps that generated a preference item schedule for items on estimation and computation which would help suggest significant differences in the estimation and computation abilities of students. Item measures helped to identify problematic items in both tests. In particular, this study was also able to list some issues on estimation and computation abilities of students with respect to numbers. LIMITATIONS OF THE STUDY Firstly, samples were selected Form One students of only four MRSMs in the North Zone of Malaysia. Data were collected in the first semester of schooling in 2010. Two instruments, a Computation Test and an Estimation Test were developed by the researchers. Both tests had 15 similar stemmed items based on four topics in the
  • 10. curriculum for Mathematics Year Three to Year Six, namely, Whole Numbers, Fractions, Decimals, and Money. Secondly, the tests were conducted in classrooms or halls provided by the college, thus there was no control on the space between the students when they sat for the tests. Thirdly, the Estimation Test was given first, with a time limit of 30 seconds per item to minimize any precise calculations. To further enhance the estimation aspect of the test, students were not permitted to write anything on the test paper, other than their responses and the items was structured using the multiple-choice format to safeguard against students doing precise calculations (Bana & Dolma, 2006). Fourthly, the Computation Test was given after a short break, with a three-minute time limit for each item to enable analysis of computation abilities. In addition, students were instructed that the computations could be done using any method/s of their choice, but calculators were not permitted. Lastly, three male and three female students were selected for an interview right after completing the test sessions in rooms allocated by the colleges. There was no possibility of barring off sound from the interview sessions. The interview sessions were audio-taped. CONCLUSIONS Table 6 displays the distribution of scores on both tests. As can be seen, students performed better on the Computation Test than on the Estimation Test. However, the percentage difference in the performance distribution was not large. TABLE 6: Distribution of Scores on Both Tests Computation Test Estimation Test SCORES Number of Number of % students % students Students Students Above Mean 208 54.03 202 52.47 Score Below Mean 177 45.97 183 47.53 Score 385 100 385 100 Rasch Measurement Model was used to analyze the responses to both tests. Summary statistics of the responses concluded that the students performed better on the Computation Test with a mean of 11.4 as compared to a mean of 10.3 on the Estimation Test. Both tests indicated the same maximum score (15) and minimum score (3). Interestingly, there were however four more students with a maximum score on the Estimation Test than there were on the Computation Test.
  • 11. i) Relationship between Computation and Estimation Abilities Estimation helps students to not only approximate answers before carrying out the calculations but it also helps them to determine whether an answer is reasonable or not, hence developing number sense in the students (Segovia & Castro, 2009). It requires mental computation, thinking and making sense of the computation and does not rely on rules or mechanical procedures. However, students are usually more successful on written computations than on number sense (Bana & Dolma, 2006). Therefore, if the scores on the Estimation Test can be taken as the benchmark for the development of number sense in students, then this paper posits that only 52.47% of the students have developed number sense in thinking. Analysis of the responses found that students were better at computation than estimation in ten out of 15 items, including items 8 and 11 under the topic of Whole Numbers. Table 6 indicates that there was a small range of difference between the students’ abilities. Thus, further investigation of these scores has to be done in order to assess and understand the strong relationship between computation and estimation abilities of these students. There is also a need to compare the items on both tests that involved learning areas other than Whole Numbers in order to identify problematic items. There is also a need to look into those items that have students performing better on the Estimation Test than the Computation Test. ii) Problematic Items on the Computation Test If a percentage measure of 60% can be taken as benchmark for identifying items that students had little ability to handle, then there were more items on the Estimation Test that need to be given extra focus by the educators than the Computation Test. Items 2, 6, and 14 under the topic Fractions and 15 under the topic Money were identified as problematic on the Estimation Test. On the other hand, only items 4 and 6 were found to be problematic on the Computation Test. In particular, there were no items under Whole Numbers identified as problematic to the students in the Estimation Test. On the contrary, item 4 on Whole Numbers with a percentage measure of 41% fell into this category for the Computation Test. This paper tends to believe that students were not exposed to methods of estimation that can enable them to develop the number sense needed in the finding of possible strategies to tackle this item. Analysis of answers to this item indicated that they were not only unable to see the pattern in the sequence of numbers given in this item; they were also not able to make sense of the end numbers 917158 and 887158.
  • 12. iii) Items Students Performed Better on Estimation Test than Computation Test The students were found to perform better on the Estimation Test in only five out of 15 items, which included items 4, 5 and 7 under the topic on Whole Numbers. Items 4, 5 and 7 involved the identification of place values under different circumstances. Item 7 was a very straight forward problem. Item 5 involved a bigger set of numbers than item 7. Item 4 was the most difficult since it involved a higher hierarchy of thinking strategies of finding missing items. High percentage measures for item 7 in both tests indicated that students had no problem finding the place value for a digit in a number up to 1000000 in both tests, which meant that they have developed the first strand in number sense by being able to understand and use the meaning and size of numbers. Their understanding of the effect of rounding up and rounding down to the nearest 10000 made it easier for them to find the number that would be nearest to 580000 in item 5, indicating they had also developed the first strand of number sense in this item. The multiple choices provided a clear identification of the common difference between the numbers, thus, they were better at finding counting and computing strategies for this item in the Estimation Test than they were in the Computation Test. Mental computation can be characterized by it ability to produce exact answers. When mental computation is used in an estimation procedure, simple numbers are selected and operated on mentally to bring about approximate answers, emphasizing the close relationship between estimation and mental computation; hence it is very important to teach students to do mental computation at school (Reys, 1984; Segovia & Castro, 2009). In particular, the students’ proficiency to compute in the other 10 items would be a great advantage for them in their estimation procedures. However, teaching approaches must be improved in order to upgrade students’ achievements since percentages below 85% were recorded for some of these items. Emphasis on computational skills may produce high computational scores; however, the extent to which these processes transfer to students’ understanding is still unknown (Ghazali et al, 2003). The samples used in this study were selected for admission into the MRSM schooling system, thus, higher expectations were expected in their achievements. However, there was no distinct difference between 54.03% passes in the Computation Test and 52.47% passes in the Estimation Test. In addition, the study has established that students were better at computation than estimation. Furthermore, students who can do estimation should be able to approximate answers before doing any computation and to determine the reasonableness of an answer (Segovia & Castro, 2009). Therefore, if scores on the Estimation Test can benchmark the development of number sense in students, then only 52.47% of the students have developed number sense in thinking and the highly developed number sense was observed in item 7 of the Estimation Test with 99% passes. Since item 7 dealt with the recognition of place values for numbers up to 1000000, these meant that these students have understood and were able to use the meaning and size of numbers.
  • 13. The findings of this study have shown that it is important for mathematics educators to pay attention to the development of number sense in the teaching of mathematics in schools. Item 4 was identified as one of the items students performed better at estimation than computation, but it recorded percentage passes of only 76%. That means that 24% of the students had problems with higher order thinking in problem solving, thus it was impossible for them to come up with the correct strategies to find missing numbers in the sequence 917158, _________, ___________, 887158. Lack of number sense can be felt more in item 15 with only 52% passes in the Estimation test. This paper wishes to point out that failure to succeed at item 15 may have taken place because analysis of answers given suggests the possibility that students may have misread the question. However, if it were not due to misreading, then attention should be given to help students with mixed operations on numbers in solving mathematics problem in real life. What might be the best approach to teach mixed operations? To conclude, this study has opened our eyes to some details in the learning of Whole Numbers that should be given more focus in order to increase number sense in thinking and to develop estimation capabilities. It is hoped that this study has contributed ideas to mathematics educators on improving the approaches in teaching these items.
  • 14. REFERENCES Ahmad Zanzali, N. A. and Ghazali, M. (2002). Assessment of School Childrens’ Number Sense. Retrieved from math.unipa.it/~grim/ENoor8.PDF Asplin, P., Frid, S., Sparrow, L. (2006). Game Playing to Develop Mental Computation: a case study. Merga Conference Proceedings. Bana, J. and Dolma, P. (2006). The Relationship between Estimation and Computation Abilities of Year 7 Students. Merga27 Conference Proceedings. Bond, T. and Fox, C. M. (2007). Applying the Rasch Model: Fundamental Measurement in the Human Sciences. 2nd Edition. Lawrence Erlbaum Associates. Inc. Case, R., & Sowder, J. T. (1990). The development of computational estimation: A Neo- Piagetian analysis. In Star et al. (2007). Investigating Student Thinking about Estimation: What Makes a Good Estimate? Retrieved from sitemason.vanderbilt.edu/files/e7pCrS/BRJ Vitae8_08.pdf Fisher Jr., W.P., Elbaum, B. & Coulter, A. (2010). Reliability, Precision, and Measurement in the context of Data from Ability Tests, Surveys, and Assessments. Journal of Physics: Conference Series 238 (2010) 012036. doi:10.1088/1742- 6596/238/1/012036. Ghazali, M., Abdul Rahman, S., Ismail, Z., Idros, S. N., and Salleh, F. (2003). Development of a framework to assess primary students’ number sense in Malaysia. The Mathematics Education into the 21st Century Project Proceedings of the International Conference: The Decidable and the Undecidable in Mathematics Education, Brno, Czech Republic. Ghazali, M., Alias, R., Anuar Ariffin, N. A. and Ayob, A. (2010). Identification of Students’ Intuitive Mental Computational Strategies for 1, 2 and 3 Digits Addition and Subtraction: Pedagogical and Curricular Implications. Journal of Science and Mathematics Education in Southeast Asia 2010, 33(1), 17-38. Heirdsfield, A. (2002). Mental methods moving along. In Asplin, P., Frid, S., Sparrow, L. Merga26 Conference Proceedings. Mathematics Year 1. (2002). Integrated Curriculum for Primary School. Curriculum Development Center. Ministry of Education Malaysia. Mathematics Year 2. (2003). Integrated Curriculum for Primary School. Curriculum Development Center. Ministry of Education Malaysia. Mathematics Year 3. (2003). Integrated Curriculum for Primary School. Curriculum Development Center. Ministry of Education Malaysia.
  • 15. Mathematics Year 5. (2006). Integrated Curriculum for Primary School. Curriculum Development Center. Ministry of Education Malaysia. McIntosh, A. (2002). Common errors in mental computation of students in grades 3 - 10. In Asplin, Frid, and Sparrow, Merga 26 conference Proceedings.. National Research Council. (2001). Adding it up: Helping children learn mathematics. In J. Watson & K. Beswick (Eds), Students’ Conceptual Understanding of Equivalent Fractions. (Proceedings of the 30th annual conference of the Mathematics Education Research Group of Australasia © MERGA Inc.) Reys, R. (1984). Mental computation and estimation: Past, present and future. In Segovia, I. & Castro, E. Electronic Journal of Research in Educational Psychology. Segovia, I. & Castro, E. (2009). Computational and Measurement Estimation: Curriculum Foundations and Research carried out at the University of Granada, Mathematics Didactics Department. Electronic Journal of Research in Educational Psychology. 17, 7 (1) 2009, pp. 499-536. Star, J. R., Lee, K., Chang, K. and Glasser, H. (2007). Investigating Student Thinking about Estimation: What Makes a Good Estimate? Paper presented at the 2007 annual meeting of the American Educational Research Association, Chicago, IL, at the Mathematics Cognition, Design, and Learning paper session. Retrieved from sitemason.vanderbilt.edu/files/e7pCrS/BRJ Vitae8_08.pdf Winsteps Help for Rasch analysis. (2011). Retrieved from 99.236.93.8/winman/index.htm?disfile.htm Wong, M., Evans, D. and Anderson, J. (December 2006). Developing a Diagnostic Assessment Instrument for Identifying Students’ Understanding of Fraction Equivalence. The University of Sydney. ACSPRI Conference. Sydney, Australia.
  • 16. FACTORS AFFECTING ORGANIZATIONAL COMMITMENT AMONG LECTURERS IN HIGHER EDUCATIONAL INSTITUTION IN MALAYSIA Munirah Salim Kolej Profesional MARA Bandar Melaka munirahsalim@yahoo.com Halimahton Kamarudin Kolej Profesional MARA Bandar Melaka halimahton@yahoo.com.my Mumtaz Begam Abdul Kadir Kolej Profesional MARA Bandar Melaka mumtazabdulkadir@yahoo.com Abstract A study was conducted to determine MARA Professional Colleges lecturers’ perception on organizational commitment. The study builds on social exchange theory and organizational model to identify the factors influencing the organizational commitment of these lecturers. The study analyzes whether or not there is a significant relationship between job satisfaction, job involvement, perceived organizational support and organizational commitment among lecturers in MARA Professional Colleges. Data were collected via questionnaires from 132 lecturers of three different MARA Professional Colleges. The study utilizes correlation and regression statistics to analyze the data. The findings of the survey show there is a significant relationship between job satisfaction (r=0.307), job involvement (r=0.536) and perceived organizational support (r=0.489). Job involvement contributed the most which is 28.8%, followed by perceived organizational support 23.9% and job satisfaction contributed 9.4% towards organizational commitment among MARA Professional College lectures. The study focuses on MARA Professional Colleges and concentrates only on the organizational commitment among academicians. The results suggest an improvement of social change by increasing job involvement, perceived organizational support and job satisfaction is an efficient way of obtaining highly committed human resource. The results of the study have valuable implications for policy makers in MARA Higher Education Division, college administrators and educators. Keywords: Organizational Commitment, Job Satisfaction, Job Involvement, Perceived Organizational Support
  • 17. INTRODUCTION Committed human resources are organization’s greatest assets. In order to ensure excellent and experienced academic staff always attached with the educational institutions. Committed employee should receive superior attention. Moreover, when committed lecturer quits, the college will be burden with high cost and implications for the education system. Committed and quality lecturer will take with them their teaching skills and experience. Meyer and Allen (1993) have recognized that organizational commitment as a leading factor impacting the level of achievement in many organizations. A lot of studies have been conducted on the relationship of organizational commitment either towards job satisfaction, job involvement or perceived organizational support only. However, only few have been carried out on the collaboration of these three factors towards the organizational commitment. Besides, there is very little research done to identify factors that impact organizational commitment among academics (Chang & Choi, 2007; Chen et al., 2007; Freund, 2005; Obeng & Ugboro, 2003). LITERATURE REVIEW Organizational commitment is as “a strong belief in and acceptance of the organization’s goals and values; a willingness to exert considerable effort on behalf of the organization; and a strong desire to maintain membership in the organization” (Mowday, R.T., Steers, R.M., & Porter, L.W. (1979). The concept of organizational commitment has been conceptualized from various perspectives. In this current study, the concept of organizational commitment will be discussed from the behavioral approach and psychological approach. From the behavioral approach, organizational commitment has been studied from the output of rewards/ contribution exchange processes between employers and employees (Morris & Sherman, 1981). On the other hand, the psychological approach looks at organizational commitment from the view of the attachment or identification of employees with the organization at which they work. The model of Meyer and Allen (1997) used in this current study proposed a three-component model of organizational commitment according to the nature of the bond that exists between an employee and employer as below: 1. Affective commitment is employee’s emotional attachment to, identification with and involvement in the organization (Meyer et.al., 1993; Shore and Tetrick, 1991; Romzek, 1990) 2. Continuance commitment that is based on the costs that the employee links with leaving the organization or on a perceived lack of alternative employment opportunities.(Buitendach and De Witte, 2005;Reichers, 1985; Murray, Gregoire, & Downey,1991)
  • 18. 3. Normative commitment that involves the employee’s feelings of obligation to stay with the organization.(Meyer & Allen, 1991; Wiener and Gechman, 1977; Roussenau, 1995) Job satisfaction is one of the most regularly measured organizational variables and frequently referred to as an employee’s global attitudinal or affective response to their job. Makanjee et al. (2006) explained that job satisfaction was basically the way individuals thought and felt about their multifaceted work experience. Loui (1995) examined the relationship between job satisfaction and organizational commitment among 109 workers and reported that there are positive relationship between organizational commitment and job satisfaction. Another study by Coleman & Cooper (1997) explained that job satisfaction was positively related to both affective and normative commitment. A study by Rajendran and Raduan (2005) also showed the same result that is job satisfaction has a positive influence on affective and normative commitment Mathieu and Zajac (1990) define job involvement as a belief descriptive of an employee’s relationship with the present job. Joiner and Bakalis (2006) suggested that job involvement describes how interested, enmeshed, and engrossed the worker is in the goals, culture, and tasks of a given organization. A study by Uygur and Kilic (2009) involving employees working in the central Organization of the Ministry of Health revealed that there is a positive correlation between organizational commitment and job involvements. In organization researchers, the social exchange theory (Blau, 1964), and the concept of perceived organizational support (POS) have been applied to explain the psychological process underlying the employee attitudes and behaviors (Settoon, Bennet & Liden , 1996; Wayne et al.,2002). Exchanges between an employee and employing organization are called POS. Review of POS literature uses social exchange theory interpretation of organizational commitment to explain how an employee’s commitment to an organization is influenced by the organization’s commitment to employee (Jackson et al, 2004). Many researchers have investigated the effects of POS on important work outcomes such as affective commitment and turnover intention (Eisenberger et al., 1986; Eisenberger et al., 1990; Setton et al., 1996; Wayne et.al., 1997). PROBLEM STATEMENT Educational institution is considered as a service industry playing key role in developing smart, well educated with first class mentality human capital required in vision 2020. Therefore, the main player is academicians who are responsible to produce future human capital needed by the nation. As per Atan (2007), academic staffs that are committed to improve teaching and learning methods, strengthening research and innovation are the main factor in order to turn Malaysia into leading education hub.
  • 19. Majlis Amanah Rakyat (MARA) through Bahagian Pendidikan Tinggi (BPT) has taken many steps to strengthen its education sector in order to support Malaysia into a leading education hub. Since, committed human resources are organization’s greatest assets, therefore identifying factors that help to foster organizational commitment among MARA lecturers is important. Moreover, when committed lecturer quits, MARA will be burden with high cost and implications for the education system. Committed and quality lecturer will take with them their teaching skills and experiences. Due to this, there is a desire to conduct a study focussing on factors that will influence organizational commitment among lecturers in MARA Professional Colleges. This study will investigate whether or not job satisfaction, job involvement and perceived organizational influence organizational commitment among MARA lecturers. PURPOSE OF THE STUDY The purpose of this study is to examine the relationship between job satisfaction, job involvement, and perceived organizational support towards organizational commitment among academicians. It is hoped that the findings of the study will provide empirical evidences in the aspects of factor impacting organizational commitment among academics and fulfil the research gap due to lack of studies conducted among academicians on organizational commitment. At the same time, the findings from this research will be useful to policy makers in MARA Higher Education Division and college administrator in order to maximize the capacity and capability of its lecturers by increasing their level of commitment. RESEARCH QUESTIONS The current study is thus conducted to address the following research questions: 1. Does job satisfaction contribute towards organizational commitment (Affective, continuance and normative) 2. Does job involvement contribute towards organizational commitment (Affective, continuance and normative) 3. Does perceived organizational support contribute towards organizational commitment (Affective, continuance and normative) METHODOLOGY This study was carried out through a survey method using questionnaires as the main instrument. The sample consists of respondents among lecturers from three MARA Professional Colleges.
  • 20. The conceptual framework for this current study is suggested in Figure 1. This framework was imitative from earlier theories on antecedents and consequences of organizational commitment such as social exchange theory (Blau, 1964) and model of organisational commitment by Meyer & Allen (1997). The concept of exchange says that individual becomes attached to the organization in return for gains provided by the organization. This conceptual framework explains that organizational commitment among academics is influenced by job satisfaction, job involvement and perceived organizational support .The dependent variable in this research is organizational commitment. Organizational commitment can be defined through the strength of employee’s identification with, and involvement, in a particular organization. The independent variables are job satisfaction, job involvement, and perceived organizational support. JOB SATISFACTION ORGANIZATIONAL COMMITMENT AFFECTIVE JOB INVOLVEMENT CONTINUANCE NORMATIVE PERCEIVED ORGANIZATIONAL SUPPORT Figure 1: Research Conceptual Framework The questionnaires consist of five parts to measure the studied elements, where the independent variables are job satisfaction (Spector, 1997), job involvement (Kanugo, 1982) and perceived organizational support (Eisenberger et al., 1986). The dependent variable was organizational commitment with three subscales that are affective, continuance and normative commitment. The method used to measure job satisfaction in this current study is Job Satisfaction Survey (JSS) (Spector, 1997). No modification was made on the current questionnaires. The survey uses a faceted approach to the measurement of satisfaction in terms of specific identifiable characteristics related to the job (Luthans, 1998). It measures nine aspects of an employee’s satisfaction: Pay, Promotion, Supervision, Fringe Benefits, Contingent Rewards (performance based rewards), Operating Procedures (required rules and procedures), Coworkers, Nature of Work, and Communication (Spector, 1997). The JSS consist of 36 items, and there are 4 items for each facet.
  • 21. To measure the job involvement, 10 items from the Job Involvement Questionnaire (JIQ) developed by Kanugo (1982) is used. However, modification was made by the current researcher due to a reliability test. Therefore, in the current study only 9 items were used. Perceived organizational support is measured using Survey of Perceived Organizational Support adapted from Eisenberger et al., (1986). Modifications were made by the researchers in terms of rewording the construct in order to fit with a particular sample. The shorter version which consists of 8 items was used in the current study. Organizational commitment survey developed by Meyer and Allen (1997) was used. Modifications were also done by the researchers in terms of the construct in order to fit with a particular sample. It identifies 24 items that can be broken into 3 subscales based on the definition of organizational commitment that is affective commitment, continuance commitment and normative commitment. A likert scale format with 7 choices per item is used ranging from "strongly disagree" to "strongly agree”. A pilot study was carried out to revise the questionnaires and for item analysis. The validity and reliability of the questionnaires were measured. The internal consistencies of scale were assessed through computing Cronbach’s Alpha. The components of factor affecting organizational commitment show the reliability value ranging from 0.6 to 0.9. Implication from these values indicates that all of the items used for each component in the questionnaire have a high and consistent reliability values. FINDINGS i) The relationship between job satisfaction, job involvement, perceived organizational support and organizational commitment (Affective, continuance and normative). Correlations were calculated to determine to what extent job satisfaction, job involvement and perceived organizational support correlated with organizational commitment. As can be seen in Table 1, significant positive correlations (p < .05) were formed for all three variables. Correlations ranged from 0.307 for job satisfaction, 0.489 for perceived organizational support to 0.536 for job involvement. Table 1: Analysis of Pearson Correlation-Zero Order Job Job Perceived Satisfaction Involvement Organizational Support Organizational 0.307 0.536 0.489 Commitment (132) (132) (132) P=0.00 P=0.00 P=0.00 Job Satisfaction 1.000 0.150 0.512 (0) (132) (132) P=0.00 P=0.087 P=0.00
  • 22. Job Involvement 0.150 1.000 0.422 (132) (0) (132) P=0.087 P=0.00 P=0.00 Perceived 0.512 0.422 1.000 Organizational Support (132) (132) (0) P=0.00 P=0.00 P= *p<0.05 The correlation coefficient value gained from this analysis shows a solid relationship between the variables (Davies in Baharom, 2004). This results show that there is a relationship between job satisfaction, job involvement and perceived organizational support towards organizational commitment among MARA Professional Colleges lecturers. ii) Contribution of job satisfaction, job involvement, perceived organizational support towards organizational commitment (Affective, continuance and normative) The result from the correlation as shown in Table 1 fulfils the required conditions for regression analysis. The correlation analysis shows that the studied dependent variable does not have a high correlation. Tabachnik and Fidell (1996) in Pallant (2001) stated that regression analysis can only be done if the correlation value between studied enabler is < 0.7. Thus, the regression analysis can be carried out. Linear regression analysis was used to determine the contribution of the independent variable which is job satisfaction, job involvement and perceived organizational support towards organizational commitment among lecturers in MARA Professional College as stated in hypothesis below: H1: There is significant contribution from job satisfaction towards organizational commitment (affective, continuance and normative commitment). H2: There is significant contribution from job involvement towards organizational commitment (affective, continuance and normative commitment). H3: There is significant contribution from perceived organizational support towards organizational commitment (affective, continuance and normative commitment). Table 2 and 3 show the results of linear regression analysis for the influence of job satisfaction towards organizational commitment. The linear regression analysis shows that the independent enabler which is job satisfaction is the indicator with correlation (β=0.346, t=3.679 and p=0.000) (p<0.05) and the value of R² (R²=0.094) contributes 9.4% towards organizational commitment among MARA Professional College lecturers. Thus H1 will be accepted.
  • 23. Table 2: Analysis of Linear Regression between Job Satisfactions towards Organizational Commitment Independent β Beta t Sig.-t R² Contribution Variable (β) (%) Job 0.346 0.307 3.679 0.000 0.094 9.4 Satisfaction Constant 2.926 7.035 0.000 R 0.307a R squared 0.094 Adjusted R squared 0.087 Standard Error 0.671 Table 3: Analysis of Variance Sum of Source Squares df Mean Square F Sig. Regression 6.098 1 6.098 13.533 .000a Residual 58.573 130 .451 Total 64.670 131 The contribution of job satisfaction towards organizational commitment among MARA Professional College lecturers forms the linear regression as below: Y= 2.926 + 0.346X1 + 0.671 Y= Organizational Commitment X1= Job Satisfaction Constant 2.926 Standard Error 0.416 The result of linear regression analysis for the influence of job involvement towards organizational commitment is shown in Tables 4 and 5. The linear regression analysis shows that the independent enabler which is job involvement is the indicator with correlation (β=0.419, t=7.246 and p=0.000) (p<0.05) and the value of R² (R²=0.288) contributes 28.8% towards organizational commitment among MARA Professional College lecturers. Thus H2 will be accepted. Table 4: Analysis of Linear Regression between Job Involvements towards Organizational Commitment Independent β Beta t Sig.-t R² Contribution Variable (β) (%) Job 0.419 0.536 7.246 0.000 0.288 28.8 Involvement Constant 2.604 10.066 0.000 R 0.536a R squared 0.288
  • 24. Adjusted R squared 0.282 Standard Error 0.595 Table 5: Analysis of Variance Sum of Source Squares df Mean Square F Sig. Regression 18.607 1 18.607 52.512 .000a Residual 46.064 130 .354 Total 64.670 131 The contribution of job involvement towards organizational commitment among MARA Professional College lecturers forms the linear regression as below: Y= 2.604 + 0.419X1 + 0.595 Y= Organizational Commitment X1= Job Involvement Constant 2.604 Standard Error 0.259 The regression linear analysis in Tables 6 and 7 show that the independent enabler which is perceived organizational support is the indicator which has the correlation of (β=0.332, t=6.386 and p=0.000) (p<0.05) and the value of R² (R²=0.239) contributes 23.9% towards organizational commitment among MARA Professional College lecturers. Thus H3 will be accepted. Table 6: Analysis of Linear Regression between Perceived Organizational Supports towards Organizational Commitment Independent β Beta t Sig.-t R² Contribution Variable (β) (%) Perceived 0.332 0.489 6.386 0.000 0.239 23.9 Organizational Support Constant 3.080 14.012 0.000 R 0.489a R squared 0.239 Adjusted R squared 0.233 Standard Error 0.615
  • 25. Table 7: Analysis of Variance Sum of Source Squares df Mean Square F Sig. Regression 15.444 1 15.444 40.786 .000a Residual 49.226 130 .379 Total 64.670 131 The contribution of perceived organizational support towards organizational commitment among MARA Professional College lecturers forms the linear regression as below: Y= 3.080 + 0.332X1 + 0.615 Y= Organizational Commitment X1= Perceived Organizational Support Constant 3.080 Standard Error 0.220 From the linear regression analysis can be concluded that job involvement contributed the most which is 28.8%, followed by perceived organizational support 23.9% and job satisfaction contributed 9.4% towards organizational commitment among lecturers in MARA Professional Colleges. DISCUSSION & PRACTICAL IMPLICATIONS Social exchange theory is the driving force that primarily influences employee organizational commitment specifically; job satisfaction, job involvement and perceived organizational support were identified as key drivers of organizational commitment. In the current study, job involvement was found to have a strong positively linked with organizational commitment. Job involvement also was identified as a major contributor to organizational commitment among lecturers in MARA Professional Colleges. Research by Janis (1982) and Loui (1995) also support these findings. Literature review regarding job involvement provided evidence of job involvement as significant predictor of organizational commitment (Kanugo, 1982; Hafer &Martin, 2006; Wegge et al., 2007; Uygur & Kilic, 2009). Since job involvement is a strong predictor of organizational commitment, Higher Educational Division and college administrator must take action to increase job involvement of the lecturers. The multidimensional model of job involvement by Yoshimura (1996), suggests that the individual variable which affect the job involvement can be divided into individual personality and organizational variables. Individual personality such as locus of control, growth needs, working values, way of being socialized, career stage and successful job experience whereas for organizational variables are like participation in decision making, job type and human resource management (Yoshimura,1996). Therefore, people who are very involved in their job will not feel the need to leave the organization. Thus, by increasing
  • 26. the degree of employees’ self-esteem will enrich job involvement and may lead to higher commitment. Job satisfaction is said to have direct impact on organizational commitment even though it is not a strong predictor. It reflects that when the level of job satisfaction increases, the level of organizational commitment also increases slightly. Therefore, this factor should be increased to improve an employee’s commitment to an organization. Findings from the current study in relation to facets of job satisfaction revealed that most of the lecturers are satisfied with the nature of work and least satisfied with operating condition and promotion. Results from the current study is consistent with the study conducted by Clay-Warner et al.,(2005) on organizational justice and job satisfaction. Procedural justice and the level of fairness in the methods by which rewards were distributed among employees by the organization directly impacted an employee’s level of satisfaction. Therefore, it is recommended that the institution’s rules, policies and procedures should be fair and equitable According to McFarlin and Sweeney (1992), the fairness of an institution’s procedures defines the institution’s capacity to treat its employees fairly. Thus, if employees see the procedures as fair, they are likely to view the organization positively, which in turn would motivate them to remain committed to their respective institutions. Therefore, higher authorities in MARA Higher Education Division should make an intensive effort to improve procedures and reward distributions at MARA Professional Colleges. Since most of the lecturers are satisfied with the nature of work, the current jobs should be enriched so as to make them more interesting, challenging, and motivating. Furthermore, most research indicated that the presence of certain core job dimensions such as autonomy (Dunham et al., 1994), job challenge (Meyer et al., 1997), variety (Steers, 1977) and positive feedback (Hutchison & Garstka, 1996) direct to greater commitment. As a result, it is recommended that MARA Higher Education Division should give more autonomy to teachers such as giving them more freedom to choose text books, determine the teaching methodology, set grading and evaluation criteria for their courses and also be given some discretion in scheduling their classes. Besides autonomy, current jobs can be enriched by adding variety to their work like giving a right balance between teaching and research. Presently, conducting research in their respective areas of specialization is not a requirement for lecturers in MARA Professional Colleges. If there is a right blend of teaching and research, the lecturers will not only have a greater variety of work to do but will also get a chance to upgrade their skills and abilities. The present study shows a moderately significant relationship between perceived organizational support and organizational commitment. In line with the current studies, Tek (2009) found evidence that perceived organizational support has a direct influence on organizational commitment based on research amongst 134 academicians in four private universities in Malaysia. Several studies have provided evidence that perceived organizational support plays a critical role in enhancing organizational commitment (Eisenberger et al., 1986; Mottaz, 1988; Vancouver et al., 1994). As perceived organizational support is related to organizational commitment, organizations should find ways to promote higher perceived organizational support employees. Hence, the organizations should always recognize the academician’s contributions and care for their well being in order to achieve
  • 27. the organization’s mission so that the academicians can deliver high quality teaching and support Malaysia into a leading education hub. Job satisfaction, job involvement and perceived organizational support have been identified as significant factors that influence organizational commitment among academicians. Director of each MARA Professional Colleges may use this useful information as an opportunity to create committed team of lecturers. This is because lecturers are part of an influential force that plays a key role in the success of students which at the end shows the success of the institution. CONCLUSION From the above discussion, it is clear that fostering commitment among faculty members has important implications for educational institutions. Therefore, highly committed lecturers would make a positive contribution to their respective institutions and may lead to increase the effectiveness of the educational institutions. Thus, institutions which seek to retain their lecturers by building strong organizational commitment are in a better position to reap the benefits of a more dedicated, motivated, and reliable teaching staff. In total, this study contributes to the limited body of knowledge underlying the formation of organizational commitment among academicians through the perspectives of social exchange theory. Besides, it justifies the importance of creating organizational commitment among academicians in order to turn Malaysia into a leading educational hub.
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  • 32. KESAN MODEL STAD TERHADAP SIKAP DAN KEMAHIRAN BERKOMUNIKASI PELAJAR DALAM MATA PELAJARAN SEJARAH Azwani bin Ismail Bahagian Sumber Manusia MARA azwaniha@yahoo.com Prof. Madya Dr .Datin Zahara Aziz Universiti Kebangsaan Malaysia Dr. Sharifah Nor Puteh Universiti Kebangsaan Malaysia Prof. Madya Dato’ Abdul Razaq Ahmad Universiti Kebangsaan Malaysia Abstrak Kajian ini bertujuan untuk mengkaji keberkesanan Pembelajaran Koperatif model Student Team Achievement Division (STAD) terhadap sikap dan kemahiran berkomunikasi pelajar terhadap mata pelajaran Sejarah. Reka bentuk kajian ini ialah kuasi-eksperimen dengan reka bentuk ujian pra- pasca kumpulan-kumpulan tidak serupa, (Pre Test-Post Test, Non- equivalent Control Group Design). Sampel kajian ialah pelajar-pelajar Tingkatan 2 daripada sebuah sekolah di Selangor iaitu seramai 158 orang. Bagi Kumpulan Rawatan adalah seramai 78 orang pelajar manakala Kumpulan Kawalan seramai 80 orang. Kajian ini menggunakan pendekatan kuantitatif dan disokong oleh data kualitatif. Dua kaedah digunakan dalam pemilihan sampel iaitu pensampelan bertujuan (purposive sampling) bagi memilih sekolah dan pensampelan rawak mudah (simple random sampling) bagi memilih kelas untuk membentuk kumpulan. Alat kajian yang digunakan adalah soal selidik pelajar (ujian pra-pasca), pemerhatian dan temu bual atas pelajar. Kajian ini dijalankan selama 14 minggu. Dapatan kajian menunjukkan terdapat perbezaan min yang signifikan antara kumpulan bagi ujian pasca bagi sikap pelajar terhadap mata pelajaran Sejarah t(133) = - 2.40, p = 0.02. Terdapat perbezaan min yang signifikan antara kumpulan bagi ujian pasca bagi kemahiran berkomunikasi pelajar dalam mata pelajaran Sejarah t(156) = -2.47, p = 0.02. Hasil kajian ini telah menjawab persoalan kajian bahawa kaedah Pembelajaran Koperatif model STAD berkesan menerapkan sikap yang positif dan kemahiran berkomunikasi yang berkesan dalam mata pelajaran Sejarah. Berdasarkan analisis temu bual dengan pelajar dari pelbagai bangsa, jelas menunjukkan para pelajar menunjukkan perkembangan yang positif setelah menggunakan model STAD. Kata kunci: pembelajaran koperatif model STAD, kaedah kuasi- eksperimen, sikap, kemahiran berkomunikasi.
  • 33. PENDAHULUAN Sejarah ialah mata pelajaran teras dalam Kurikulum Bersepadu Sekolah Menengah (KBSM) yang wajib dipelajari oleh semua pelajar secara berterusan selama lima tahun. Penyemakan kurikulum Sejarah Kurikulum Bersepadu Sekolah Menengah (KBSM) (2000) bertujuan memantapkan Akta Pendidikan 1996, memenuhi semangat Falsafah Pendidikan Kebangsaan (FPK) dan menyediakan warganegara Malaysia untuk menghadapi cabaran pendidikan pada abad ke-21. Proses pengajaran dan pembelajaran (P&P) Sejarah seharusnya menjadi sesuatu yang hidup dan boleh menarik minat pelajar. menurut Anuar Ahmad, Siti Haishah Abd Rahman & Nur Atiqah T. Abdullah. (2009). Dua prinsip utama yang ditekankan dalam model STAD adalah persandaran positif dan tanggungjawab individu. Idea utama di sebalik penggunaan model STAD adalah untuk memberi motivasi kepada pelajar supaya memberi galakan dan bantuan kepada rakan- rakannya (Effandi 2005). Slavin (2000) menjelaskan bahawa terdapat dua komponen penting dalam semua kaedah pembelajaran koperatif iaitu struktur insentif koperatif (pelajar diberi ganjaran berdasarkan pencapaian kumpulan) dan struktur tugasan koperatif (pelajar menyelesaikan tugasan secara berkumpulan). Slavin (2006) juga menyatakan kaedah pengajaran yang berpusatkan pelajar yang menarik akan menyebabkan pengajaran dan pembelajaran dalam kelas akan lebih menyeronokkan, malah mengikut Carr (2007) pelajar hendaklah didedahkan dengan pembelajaran yang berbentuk kumpulan kerana ini akan membantu pelajar untuk belajar membuat keputusan sendiri. Pembelajaran yang efektif ini akan melahirkan pelajar yang celik sejarah, bersikap positif, mempertingkatkan kemahiran berkomunikasi sesama rakan, daya pemikiran dan seterusnya boleh mengambil iktibar daripada pengalaman sejarah. PERNYATAAN MASALAH Kebanyakan pelajar mempunyai tanggapan awal bahawa mata pelajaran Sejarah ialah mata pelajaran yang membosankan. Tanggapan awal ini akan menyebabkan pelajar kurang tumpuan dan kurang bermotivasi untuk mempelajari Sejarah. Menurut Abdul Razak dan Ali (2000) dan Anuar Ahmad, Siti Haishah Abd Rahman & Nur Atiqah T. Abdullah. (2009), mata pelajaran Sejarah kurang diminati pelajar dan membosankan. Kajian oleh Abdul Razak dan Abdullah (2000) terhadap 240 pelajar di daerah Petaling Jaya dan Kuala Selangor mendapati pelajar-pelajar menganggap mata pelajaran Sejarah sebagai subjek sampingan yang tidak mendatangkan faedah. Tanggapan ini dikaitkan dengan mata pelajaran Sejarah yang tidak memberikan jaminan pekerjaan dan tidak mempunyai nilai komersial (Sivachanlingam et al. 2008). Pengajaran dan pembelajaran mata pelajaran Sejarah adalah berbeza dengan mata pelajaran lain. Dalam pendidikan mata pelajaran Sejarah, pelajar tidak sahaja diajar mendapatkan maklumat atau pengajaran dari peristiwa sejarah, malah apa yang lebih penting adalah untuk membentuk pelajar yang faham makna sejarah dan
  • 34. seterusnya dapat merealisasikan dalam kehidupan seharian dan merancang kehidupan akan datang (Sivachanlingam et al. 2008). Keberkesanan pengajaran Sejarah bergantung kepada perancangan dan kualiti guru sejarah. Guru sejarah yang baik menunjukkan kebolehan dan keupayaan dari segi kualiti diri, sosial dan profesional menurut Zahara Aziz (2000). Kelemahan dari segi pengajaran masih menjadi isu utama yang berkaitan dengan pencapaian pelajar dalam peperiksaan SPM. Corak pengajaran Sejarah di sekolah masih bersifat konvensional dan membosankan pelajar. Berasaskan kajian Mohamad Sultan (2000) di sebuah sekolah di daerah Sabak Bernam, menunjukkan pengajaran mata pelajaran Sejarah di sekolah berkenaan kurang berkualiti. Malah mengikut Hariyono (1995) guru Sejarah jarang memerhatikan sama ada maklumat tersebut dapat membangkitkan minat atau semangat yang boleh membentuk pelajar yang faham sejarah. Kenyataan ini telah disokong oleh Khoo Kay Kim (2008) yang menyatakan pembelajaran mata pelajaran Sejarah lazimnya dijalankan dalam bentuk hafalan. Pelajar difokuskan dengan menitikberatkan dari aspek mengingati tarikh, fakta-fakta serta pergolakan dunia yang telah terjadi beribu-ribu tahun yang lampau. Ini akan menyebabkan mereka mempunyai perspektif yang sempit tentang proses perkembangan masyarakat dan negara, malah tidak memberi mereka peluang untuk berkomunikasi secara berkesan. Oleh itu, ramai pelajar mendapati pelajaran Sejarah sangat menjemukan dan tidak merangsang pelajar untuk berfikir dan berkeyakinan dalam memberi pendapat. Khoo Kay Kim (2008). Menurut Zahara Aziz (2000) sekiranya guru mementingkan pengajaran yang memberi latihan kepada pelajar untuk berfikir, maka apabila pelajar meninggalkan alam persekolahan dan menjejak ke alam baharu, mereka akan berasa lebih yakin kerana berkebolehan dan berinisiatif dalam menyelesaikan masalah dan berfikiran dengan kritis dan kreatif. Tanggapan negatif pelajar ini boleh dilenyapkan jika guru berfikiran kreatif dan inovatif, yang dapat melaksanakan proses pengajaran dengan berkesan berserta dapat memberi peluang kepada pelajar untuk lebih berinteraksi sesama pelajar dan menimbulkan keseronokan di dalam kelas. OBJEKTIF KAJIAN 1. Mengenal pasti tahap sikap dan kemahiran berkomunikasi pelajar dalam mata pelajaran Sejarah antara pelajar yang menggunakan Pembelajaran Koperatif model STAD dengan pelajar dalam kumpulan kawalan. 2. Mengenal pasti perbezaan sikap dan kemahiran berkomunikasi pelajar dalam mata pelajaran Sejarah antara pelajar yang menggunakan Pembelajaran Koperatif model STAD dengan pelajar dalam kumpulan kawalan.
  • 35. METODOLOGI Fokus utama kajian ini adalah untuk menentukan kesan pengajaran menggunakan kaedah Pembelajaran Koperatif model STAD atas sikap pelajar dan kemahiran berkomunikasi pelajar dalam mata pelajaran Sejarah. Dalam kajian ini pengkaji menggunakan Pembelajaran Koperatif model Student Team Achievement Division (STAD). Pembelajaran Koperatif model STAD menggunakan pendekatan pembelajaran berpusatkan pelajar dan pelajar belajar dalam kumpulan yang berstruktur. Pelajar-pelajar ditugaskan untuk bekerja dalam satu kumpulan kecil yang terdiri daripada 4 hingga 5 orang pelajar, terdiri daripada lelaki dan perempuan, pelbagai bangsa dan pelbagai pencapaian akademik. Setelah guru menyampaikan bahan pelajaran, para pelajar akan berbincang dan bekerjasama dalam kumpulan masing-masing serta memastikan semua anggota kumpulan akan menguasai pelajaran itu. Setelah menjalani sesuatu aktiviti setiap anggota kumpulan akan menduduki ujian secara individu. Markah yang diperoleh oleh setiap ahli kumpulan dicampur untuk memperoleh markah kumpulan. Kumpulan yang terbaik akan diberikan ganjaran seperti hadiah yang akan diberikan kepada setiap ahli kumpulan. Oleh itu untuk mendapat markah yang baik, setiap ahli kumpulan mesti membantu ahli-ahli kumpulannya. HIPOTESIS KAJIAN Ho 1: Tidak terdapat perbezaan min yang signifikan untuk sikap pelajar terhadap mata pelajaran Sejarah antara pelajar yang menggunakan Pembelajaran Koperatif model STAD dengan pelajar dalam kumpulan kawalan. Ho 2:Tidak terdapat perbezaan min yang signifikan untuk kemahiran berkomunikasi pelajar dalam mata pelajaran Sejarah antara pelajar yang menggunakan Pembelajaran Koperatif model STAD dengan pelajar dalam kumpulan kawalan. REKA BENTUK KAJIAN Reka bentuk kajian ini ialah menggunakan kaedah kuasi-eksperimen dengan reka bentuk ujian prapasca kumpulan-kumpulan tidak serupa (Pre Test-Post Test, Non-equivalent Control Group Design). Reka bentuk ini dipilih kerana kajian ini menggunakan kelas-kelas yang sedia ada, iaitu subjek kajian bagi Kumpulan Eksperimen dan Kawalan tidak boleh dipilih secara rawak kerana terikat dengan peraturan yang telah ditetapkan oleh pihak sekolah (Chua 2006; Lim 2007; Wierma 2000; Johnson & Christensen 2000). Dalam reka bentuk ini, pengkaji menggunakan pasangan kumpulan responden yang mempunyai ciri-ciri yang hampir sama iaitu responden dari Kumpulan Eksperimen dan Kumpulan Kawalan. Selain daripada itu, kaedah kualitatif yang menggunakan temu bual dan pemerhatian juga digunakan sebagai sokongan kepada hasil kajian yang diperoleh daripada analisis kuantitatif. Malah mengikut Marohaini (2001) penggunaan teknik temu bual juga membolehkan penyelidik mengumpul pendapat, pemikiran dan pandangan dalam bentuk pernyataan langsung daripada peserta kajian sendiri. Kajian kualitatif dijalankan untuk mendapatkan kefahaman yang mendalam terhadap sesuatu perkara yang ingin dikaji kerana banyak perkara tidak dapat dijelaskan hanya merujuk kepada data numerika dalam
  • 36. penyelidikan kuantitatif sahaja (Marohaini 2001, Chua 2006). Selain itu, kajian kualitatif juga dijalankan untuk mendapat maklumat terperinci berkaitan sesuatu perkara yang dikaji (Chua 2006). Rajah 3.1: Reka Bentuk Ujian Pra dan Pasca Kumpulan Rawatan dan Kawalan Ujian Pra Kaedah Ujian Pasca Kumpulan rawatan A1 X1 A2 ----------------------------------------------- Kumpulan kawalan A3 X2 A4 Dalam reka bentuk ini, A1 dan A3 adalah merupakan pelaksanaan ujian pra. A2 dan A4 adalah pelaksanaan ujian pasca. Manakala X1 dan X2 adalah kaedah pembelajaran yang diberikan ke atas Kumpulan Eksperimen dan Kawalan. Ujian pra dijalankan untuk melihat kesetaraan antara kumpulan, kerana kedua-dua kumpulan pelajar tidak dipilih secara rawak dan juga bertujuan untuk digunakan sebagai pengawalan secara statistik. Ujian pasca akan dijalankan setelah kedua-dua kumpulan selesai mengikuti kaedah pengajaran iaitu bagi Kumpulan Rawatan, pelajar akan didedahkan dengan Pembelajaran Koperatif model STAD dan Kumpulan Kawalan menggunakan kaedah Pembelajaran Konvensional. Kedua-dua kumpulan menerima bahan pengajaran yang sama dan jumlah masa pengajaran juga sama. SAMPEL KAJIAN Sampel kajian adalah seramai 158 orang, Kumpulan Rawatan adalah seramai 78 orang pelajar manakala Kumpulan Kawalan seramai 80 orang. Daripada 158 orang pelajar tersebut, untuk Kumpulan Kawalan seramai 30 orang (18.99%) adalah pelajar Melayu, 25 orang (15.82%) pelajar Cina dan 25 orang (15.82%) adalah pelajar India. Manakala untuk Kumpulan Rawatan seramai 30 orang (18.99%) adalah pelajar Melayu, 25 orang (15.82%) pelajar Cina dan 23 orang (14.56%) ialah pelajar India. DAPATAN KAJIAN Salah satu andaian untuk kaedah kajian Kuasi Eksperimen ialah kumpulan-kumpulan yang terlibat dalam kajian adalah setara atau homogen pada peringkat awal kajian. Untuk memastikan andaian ini dipatuhi analisis statistik inferensi bagi ujian pra dilakukan. Pada ujian pra andaian adalah tidak terdapat perbezaan min yang signifikan antara kumpulan- kumpulan yang terlibat dalam kajian. Bagi menguji kehomogenan antara Kumpulan Kawalan dan Rawatan, Ujian-T digunakan. Keputusan Ujian-T ke atas kedua-dua pemboleh-pemboleh ubah bersandar kajian menunjukkan tiada perbezaan min yang signifikan antara Kumpulan Kawalan dan Rawatan bagi ujian pra untuk pemboleh ubah sikap pelajar terhadap mata pelajaran Sejarah t(156) = - 0.25, p = 0.80. Tiada perbezaan min yang signifikan antara Kumpulan Kawalan dan
  • 37. Rawatan bagi ujian pra untuk pemboleh ubah kemahiran berkomunikasi dalam mata pelajaran Sejarah t(156) = 0.11, p = 0.91. Jadual 1: Min, Sisihan Piawai dan Tahap bagi Pemboleh-pemboleh ubah Kajian Untuk Kumpulan Kawalan dan Rawatan Bagi Ujian Pasca Sisihan Pemboleh ubah Bersandar Kumpulan Min Tahap Piawai Sikap Terhadap Mata pelajaran Kawalan 3.62 1.42 Sederhana Sejarah Rawatan 3.93 1.20 Sederhana Kemahiran Berkomunikasi Dalam Kawalan 3.77 1.26 Sederhana Mata pelajaran Sejarah Rawatan 4.03 1.16 Tinggi Jadual 1 memaparkan secara keseluruhan tahap bagi pemboleh-pemboleh ubah kajian untuk Kumpulan Kawalan dan Rawatan bagi ujian pasca, secara keseluruhannya dapatlah disimpulkan, kemahiran berkomunikasi dalam mata pelajaran Sejarah bagi Kumpulan Rawatan berada di tahap tinggi manakala bagi pemboleh ubah sikap terhadap mata pelajaran Sejarah berada pada tahap sederhana. Manakala bagi Kumpulan Kawalan pula, sikap terhadap mata pelajaran Sejarah dan kemahiran berkomunikasi pelajar dalam mata pelajaran Sejarah berada pada tahap sederhana. Jadual 2: Keputusan Ujian-T Bagi Ujian Pasca Pemboleh ubah df t P Keputusan Hipotesis Rumusan Bersandar Sikap Terhadap 132.59 -2.40 0.02 Terdapat perbezaan Ho 1 Hipotesis Mata pelajaran min yang signifikan ditolak Sejarah Kemahiran 156.00 -2.47 0.02 Terdapat perbezaan Ho 2 Hipotesis Berkomunikasi min yang signifikan ditolak Jadual 2 menunjukkan keputusan Ujian-T ke atas pemboleh-pemboleh ubah bersandar sikap pelajar dan kemahiran berkomunikasi dalam mata pelajaran Sejarah untuk Kumpulan Kawalan dan Rawatan bagi ujian pasca. Terdapat perbezaan min yang signifikan antara kedua-dua kumpulan bagi ujian pasca untuk sikap pelajar terhadap mata pelajaran Sejarah t(133) = -2.40, p = 0.02, dengan ini Ho 1 ditolak. Terdapat perbezaan min yang signifikan antara kedua-dua kumpulan bagi ujian pasca untuk kemahiran berkomunikasi dalam mata pelajaran Sejarah t(156) = -2.47, p = 0.02, dengan ini Ho 2 ditolak
  • 38. Jadual 3: Nilai Min Pemboleh ubah Bersandar Kajian dan Saiz Kesan bagi Ujian Pasca Kawalan (N =80) Eksperimen (N=78) Saiz Kesan Pemboleh ubah Bersandar Min Sisihan Min Sisihan Piawai Piawai Cohen's d Sikap Terhadap Mata pelajaran 39.83 10.93 43.28 6.79 0.38 Sejarah Kemahiran Berkomunikasi 33.90 6.59 36.31 5.69 0.40 Dalam Mata pelajaran Sejarah Jadual 3 menunjukkan nilai saiz kesan mengikut kaedah Cohen (Cohen’s d) dilaporkan bagi setiap pemboleh ubah (Cohen 1988). Menurut Wolf (1986) secara umumnya nilai Cohen’s d yang lebih besar daripada 0.25 boleh menunjukkan kesan rawatan yang signifikan. Nilai Cohen’s d bagi pemboleh ubah sikap pelajar terhadap mata pelajaran Sejarah adalah 0.38 dan bagi pemboleh ubah kemahiran berkomunikasi dalam mata pelajaran Sejarah adalah 0.40. Kedua-dua nilai Cohen’s d adalah lebih besar daripada 0.25 ini menunjukkan bahawa kesan Pembelajaran Koperatif model STAD adalah signifikan. PERBINCANGAN DAN IMPLIKASI KAJIAN i) Kesan Pembelajaran Koperatif Model STAD Terhadap Sikap pelajar Pembelajaran Koperatif model STAD telah memberi satu dimensi baru kepada pelajar dalam mempelajari bahan-bahan Sejarah dalam persekitaran yang menyeronokkan, diberi kebebasan untuk meluahkan idea dan kreativiti melalui aktiviti yang pelbagai sekali gus mengukuhkan pemahaman mereka tentang bahan pelajaran. Pembelajaran melalui kaedah ini jelas menggembirakan pelajar, meningkatkan keyakinan mereka dan membolehkan kurikulum Sejarah dikembangkan secara lebih praktikal. Inilah kesan ketara yang dapat dilihat dan diperhatikan terhadap keseluruhan gerak kerja pelajar sepanjang proses P&P Sejarah dilaksanakan. Dapatan kajian ini menunjukkan terdapat perbezaan min yang signifikan bagi aspek sikap pelajar terhadap mata pelajaran Sejarah antara Kumpulan Eksperimen dan Kawalan. Ini bermakna bahawa Pembelajaran Koperatif model STAD berjaya mengubah sikap pelajar terhadap mata pelajaran Sejarah menjadi lebih positif walaupun nilainya masih berada pada tahap yang sederhana. Perubahan sikap ini terjadi kerana pelajar telah diberi peluang secara terbuka untuk bersama-sama aktif dalam perbincangan kumpulan serta menggunakan pelbagai keupayaan deria lain yang selama ini kurang digunakan. Keyakinan diri pelajar semakin meningkat terutamanya ketika mengemukakan soalan dan pendapat tentang isu-isu sejarah negara. Motivasi untuk belajar juga semakin baik kerana
  • 39. Pembelajaran Koperatif model STAD lebih mementingkan pergantungan positif antara rakan dalam kumpulan, pelajar yang lemah telah dibantu oleh pelajar yang lebih berpengetahuan. Penggunaan Pembelajaran Koperatif model STAD yang berorientasikan pelajar ini, telah menarik minat pelajar untuk belajar Sejarah. Tanggapan bahawa mata pelajaran Sejarah membosankan dapat diatasi. Kajian ini juga menjadi bahan literatur berkaitan penggunaan kaedah Pembelajaran Koperatif yang dilaksanakan di Malaysia. Pelajar menunjukkan sikap yang lebih positif terhadap pembelajaran mereka, natijah daripada penggunaan model STAD (Effandi & Zanaton 2007; Mazlan 2002; Suhaida et al. 2004). Kajian luar negara juga mengesahkan bahawa pembelajaran melalui kerjasama kumpulan dan aktiviti dapat meningkatkan sikap positif pelajar terhadap pembelajaran, bersosial dan menjadikan pelajar berfikiran kritikal yang dinamik (Slavin 2001, Zahara dan Md. Anowar 2011). Dapatan temu bual dengan pelajar juga mendapati mereka rasa lebih seronok, lebih aktif dan bersemangat ketika belajar Sejarah. Sedangkan sebelum ini mereka bosan dan mengantuk kerana guru mengajar secara sehala dan tidak melibatkan mereka secara aktif. Data pemerhatian pula menunjukkan terdapatnya perubahan sikap yang positif dalam diri pelajar, mereka saling tolong-menolong dan bersama-sama menyiapkan tugasan yang diberikan dalam suasana yang seronok, berfokus serta tidak terlalu menekan pelajar. ii) Kesan Pembelajaran Koperatif Model STAD Terhadap Kemahiran Berkomunikasi Pelajar Setelah berada dalam Kumpulan Eksperimen yang menggunakan kaedah Pembelajaran Koperatif model STAD, pelajar-pelajar didapati menunjukkan peningkatan dari segi kemahiran berkomunikasi sama ada dengan guru, rakan belajar dan cara berbincang menggunakan bahan pelajaran. Pelajar didapati lebih berkeyakinan memberikan idea dan pendapat, disokong oleh persekitaran yang memberi ruang dan peluang untuk mereka berbincang secara sistematik. Pelajar-pelajar dari Kumpulan Eksperimen menyatakan mendapat pengalaman yang menarik sewaktu bekerjasama dalam kumpulan terutamanya semasa berbincang serta bertukar-tukar pendapat ketika menyiapkan tugasan secara berkumpulan. Pelajar juga mengakui wujudnya sikap saling bergantung atau bersandar secara positif dalam kalangan pelajar dalam sesuatu kumpulan bagi mencapai matlamat. Hal ini ada dinyatakan dalam kajian yang dilakukan oleh Mohd Fadzli dan Normah (2011). Pelajar yang lebih pandai akan menolong rakan kumpulannya untuk memahami tugasan atau topik yang diberi. Sebagaimana yang diutarakan oleh Diggins (2004) iaitu pelajar mesti menjadi pendengar yang baik, berfikir sebelum bercakap, menerima pandangan orang lain, berkeupayaan menerangkan dengan jelas, berterus terang dan sabar dengan kerenah rakan. Tugasan berkumpulan seperti mencipta sajak, membuat kad kemerdekaan atau merancang pembentangan membolehkan pelajar berbincang sesama rakan. Aktiviti ini membantu