ENHANCING STUDENT’S AKHLAQ BEHAVIOUR THROUGH … - Adibah... · Proceeding of the International...

Proceeding of the International Conference on Social Science Research, ICSSR 2013 (e-ISBN 978-967-11768-1-8). 4-5 June 2013, Penang, MALAYSIA. Organized by WorldConferences.net 502

ENHANCING STUDENT’S AKHLAQ BEHAVIOUR THROUGH HOLISTIC ASSESSMENT

Adibah Abdul Latif, Mohamed Najib b Abdul Ghafar , Wilfredo Herrera Libunao, Norfadila Mohd Amin, & Crystal Joan Peter

Faculty of Education Universiti Teknologi Malaysia

[email protected], [email protected], [email protected], [email protected], [email protected]

ABSTRACT

In Malaysia, public examination is the only mode of measuring students’ achievement to date. But in line with the on-going national educational system transformation, a new assessment method will be introduced to gauge the competence of students by taking into account all domains: cognitive; psychomotor; and, affective. This study was carried out to investigate student akhlaq learning in higher education through holistic assessment. The instrument was developed using the Rasch model measurement to analyze the construct validity, reliability, rating scale and dimensionality. Thirty students participated as samples and each of them was assessed by two of their peers using the instrument developed by the researcher. Two tests were administered, before and after the akhlaq learning assessment. Results showed that all item scores of the second test have had better logit, indicating that the students’ akhlaq behaviour has improved considerably. The results of the second test was found to be significantly better than the first test results further demonstrating significant improvement on students’ akhlaq behaviour. Several implications on the akhlaq assessment were drawn from the study that could be used to improve future assessment processes. Similar research should be done on educational assessment of other domains.

Field of Research: Akhlaq Assessment, Holistic Assessment, Rasch Model

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1.0 Introduction

Education plays an important role in developing the capacity of human capital with strong identity, competent, generous personality, knowledgeable and highly skilled. Moreover, education can add value to individuals i.e., enhancing intellectual value and enriching cultural capital among others. There is a growing demand for education to produce individuals that are able to think critically and creatively, solve problems effectively, able to create and launch new technologies, strong and able to cope with the changes in the global environment (Yahaya Ibrahim, 2010; Azhar & Zawawi, 2009 and Ibrahim Mamat, 2008). Thus, to achieve those objectives, the national education should pursue holistic and integrated approach in developing a balanced individual.

The Malaysia Vision 2020 outlined nine challenges, one of which is the development of human capital that is in-line with society needs and that will contribute to the country’s development efforts. The school institution, with the support from the society and student’s family, will play a crucial role in meeting this challenge. In the process, educational institutions should be able to infuse positive social


and moral values to their students (Azizi Yahya, 2009; Hamedah Wok Awang, 2009 and Ahmad Sarji, 2003).

The goal of the National Philosophy of Education (NPE) is to produce individuals who are excellent in intellectual ability, physical strength, emotional balance and spiritual purity. Excellence means that a person is in possession of knowledge and skills, as well as moral standards, adhere to the religious values they believe and physically healthy (Curriculum Development Centre, 2001). Akhlaq is a very important value that can give students the strength to deal with the competition and challenges in the future.

Akhlaq benefits have been outlined in the second core of the Education Development Master Plan (PIPP) (2006). The National Education Curriculum Structure and National Assessment System, in order to make education more meaningful, introduced a strategy to reform the exam-oriented evaluation into a more holistic assessment system (Bahagian Perancangan Dasar dan Penyelidikan Dasar Pendidikan, 2006; Habsah & Aminuddin, 2009 and Ismail Awang, 2009).

Akhlaq decay can be reduced through a comprehensive approach by manipulating every aspect of educational system including the evaluation and assessment process. Through a holistic education system, higher akhlaq can be achieved and it might be useful in reducing social problems in the future (Norshaipah, 2002; Abdul Zubire, 2007 and Tan, 1996). Unfortunately, akhlaq is a difficult aspect to measure and will requirement well-design instrument and assessment guideline.

Assessment should be made as part of the teaching and learning process. Akhlaq assessment can improve students' ability to focus on the good values and hopefully will lead to reduced social problems. The effectiveness of a system cannot be ensured without a good instrument. Education transformation by the MOE and MOHE therefore, should also pursue the construction of akhlaq measuring instruments that can help to assess the lessons learned from akhlaq aspect.

2.0 Students’ Akhlaq Assessment Instrument

The instruments for akhlaq assessment were developed following a series of steps. First, five experts from Akhlaq’s field were interviewed to gain constructs related to akhlaq assessment. Then, the qualitative data were analyzed and some identified aspects were listed. Finally, the researcher came out with three main constructs namely; a) behavior; b) oral communication and c) personality. There were two other main constructs; (i) worship; and (ii) faith. However, they were not included in this study because these two constructs have a big and obvious difference across religions. Thus, after having a discussion with the experts, those two constructs were not included in this instrument.


Figure 2.1 shows the findings from the interview:

Figure 2.1 : Results of construct development from the experts.

Item construction were based on the literature review and two focal sources namely, a) Holy Quran, and b) Ihya’ Ulumuddin book by Imam al Ghazali. In addition, a few sources were also referred to in order to make sure that there is no important information being left out. A few resources were compared by Meta Data analysis to ensure all the sub constructs measured are significant in akhlaq development.

Table 2.1 shows the results of the Meta Data analysis. The Students’ Akhlaq Assessment instrument consists of 2 parts. The first part is student’s demographic characteristics, which consists of student’s; i) name; ii) gender; iii) course; and iv) religion. The second part is akhlaq assessment, which includes; i) behaviour; ii) oral communication and iii) personality constructs. The resulting instrument has 67 items.

Interview Topic (Students’ Akhlaq assessment in Higher Education)

Is students’ Moral assessment important to be implemented

and can be used for all students?

Very important and can be implemented regardless of religions

and races

What are the crucial aspects to be assessed?

Oral communication, behavior, personality, worship and faith

Oral Communication Personality Behavior

Soft spoken,

greetings, wisdom,

polite words, not

talking bad about

others, tell the truth

Neat, proper dress,

clean, fulfill the

students’ attire

criteria, not wearing

attire / accessories for

different gender

Trust, fair, helpful,

respect to lecturer

and friends, well

mannered, humble,

kind hearted and

ihsan


Table 2.1: Meta Data analysis for sub constructs development.

References Oral Communication Behavior Personality

Expression Message Trust Ihsan Patience Humble Social Attire Hygiene

Al-Qur’an √ √ √ √ √ √ √ √ √

Imam al Ghazali (2006)

√ √ √ √ √ √ √ √ √

Syeikh uthaimin (1996)

√ √ √ √ √ √

Al-Tusi (1964)

√ √ √ √ √ √ √ √ √

Ibn Masykawaih (1961)

√ √ √ √ √ √ √ √ √

Haron Din (2007)

√ √ √ √ √ √ √

Percentage 100

100

100

100

100

100

71

57

57

The instrument used four point Likert Scale to minimise “noise” in score data validity (Kelly & Kenneth, 2006; Linacre, 2005; Spector, 1992; Wright & Masters, 1982 and Fleiss, 1971). There is no ‘neutral’ option because the respondents were allowed to leave the answer blank if they are not sure with their answer. The scale refers to 1-Never, 2 -Sometimes, 3 -Frequent and 4- always. The Scale Calibration Analysis was done during the pilot test phase.

3.0 Methodology

This study made use of the pre and post-test research design. Respondents for this research include 30 students as self-assessors; 15 students were from science stream while another 15 students were from non-science stream, and 60 students as peer assessors. All students were from one Public Higher Education in Malaysia. The evaluation processes were done in sequential steps. First, students did the self-assessments and then after that, two other students assessed them. The students who act as peer assessors did not reveal their identity to the students that they assessed.


Table 3.1 shows the distribution of the research participants in this study.

Table 3.1: Research participants

Self Assessment Peer Assessment

University Stream Gender Religion

One of Public Higher Education in Malaysia

Science Non Science

Male Female Muslim Non Muslim

15 15 7 8 10 5 60

Total 30 students 60 students

During the first implementation of students’ Akhlaq Assessment, the lecturer administered the instrument (pre-test) at the beginning of the semester. The assessment process was explained to the students and their friends at the onset. It was an on-going process and their friends were observing them throughout the semester. The post test was administered at the end of the semester or three months thereafter. Lecturers and parents were not involved as assessors due to low reliability and usability of results.

4. Data Analysis

The data were analysed using combination of Item Response Theory 1 Parameter (also known as Rasch Model Analysis) and Classical Test Theory. Before analysing the findings of comparison between pre-test and post test score, the validity and reliability of instrument, the rating scale analysis and the dimensionality of the instrument were tested. The software for Rasch Model analysis was Winstep while for Classical Test Theory; SPSS software version 19 was used.


Table 4.1 shows the data analysis employed to adequately answer the research questions and objectives.

Table 4.1: Statistical analysis used in the study

Objective Analysis

To analyse the content and construct validity of instrument

Fleiss Kappa analysis, item polarity and Principle Component Analysis

To analyse the item and person reliability Item and Person Reliability

To measure the understanding of agreement towards the rating scale

Rating Scale Analysis

To compare students score for pre-test and post test

Item Map

To analyse significant differences between pre-test and post test

t-test

To analyse significant differences of akhlaq score across gender, stream and religion

T-test and One Way ANOVA

5.0 Findings

5.1 Content and Construct Validity of Instrument

After the instrument was developed, two content experts and one expert from psychometrics’ field

verified it. Each item was checked and rated as 0-“Withdraw the Item”, 1- “Retain the item with some

modification” and 2-“Retain the item”. All scores were then analysed by construct using Fleiss Kappa

analysis.

Table 5.1 shows the k value for all constructs. The very high value indicates that all the experts had very

close agreement to say the content validity of this instrument is very high (Fleiss, J. L., 1971).

Table 5.1: Fleiss Kappa Analysis for Inter rater

Construct k value

Oral communication .91

Behaviour .94

Personality .92

For analysing construct validity, item polarity and dimensionality analyses were conducted. Table 5.2

shows that all values of Point Measure (PTMEA) correlation are positive. This indicates that all the items

generally measure all the constructs. Results of the dimensionality analyses (Table 5.3) show that the

value of raw variance as explained by measure is more than 40% and the value of unexplained variance

in the first contrast is less than 15%. This shows that there is no sub dimension that exists under the

akhlaq dimension.


Table 5.2: Analysis of Polarity Item

Numb sub PTMEA CORR Total Item construct Min Item Max Item 1. E 0.43 23 0.74 6 6 2. M 0.40 8 0.82 10 13 3. A 0.29 21 0.74 29 6 4. I 0.62 11 0.76 5 3 5. S 0.61 12 0.84 3 4 6. R 0.69 13 0.83 16 6 7. H 0.23 41 0.79 34 19 8. P 0.29 9 0.90 7 7 9. K 0.54 12 0.67 5 3 Total 67

*E : Ekspressi Pertuturan M: Mesej Pertuturan A: Amanah I: Ihsan S: Sabar R: Rendah Hati H : Hubungan Sosial P : Pemakaian K: Kebersihan

Table 5.3: Principle Component Analysis

Total raw variance in observations = 232.5 100.0%

100.0%

Raw variance explained by measures = 98.5 42.4%

42.7%

Raw variance explained by persons = 32.4 13.9%

14.1%

Raw Variance explained by items = 66.1 28.4%

28.7%

Raw unexplained variance (total) = 134.0 57.6% 100.0%

57.3%

Unexplned variance in 1st contrast = 15.5 6.7% 11.6%

Unexplned variance in 2nd contrast = 13.1 5.6% 9.8%

Unexplned variance in 3rd contrast = 10.6 4.6% 7.9%

Unexplned variance in 4th contrast = 8.3 3.6% 6.2%

Unexplned variance in 5th contrast = 7.9 3.4% 5.9%


5.2 Item and Person Reliability

Table 5.4 and 5.5 shows the reliability of item and person

Table 5.4: Item Reliability

----------------------------------------------------------------------

---------

| TOTAL MODEL INFIT

OUTFIT |

| SCORE COUNT MEASURE ERROR MNSQ ZSTD MNSQ

ZSTD |

|---------------------------------------------------------------------

--------|

| MEAN 85.7 29.3 .00 .29 1.03 .0 1.03

.0 |

| S.D. 15.9 3.3 1.01 .05 .44 1.4 .42

1.4 |

| MAX. 114.0 30.0 2.36 .54 3.25 4.3 3.22

4.2 |

| MIN. 30.0 10.0 -2.66 .26 .41 -2.8 .43

-2.7 |

|---------------------------------------------------------------------

--------|

| REAL RMSE .32 TRUE SD .95 SEPARATION 2.96 ITEM

RELIABILITY .90 |

|MODEL RMSE .29 TRUE SD .96 SEPARATION 3.28 ITEM

RELIABILITY .92 |

| S.E. OF ITEM MEAN = .09

|

----------------------------------------------------------------------

---------

Table 5.4 presents the item reliability using Rasch Model Analysis. Results of the analysis show that the value of reliability is 0.90 and close to suggested value of 0.92 in the Model, indicating homogeneity of results (Linacre, 2005; Bond & Fox, 2007 and Azrilah & Saidfudin, 2008). Results also show that the item separation is also more than 2 although it involved only 30 students, further indicating that the items

can discriminate the level of student’s capability.

Table 5.5: Person Reliability

----------------------------------------------------------------------

---------

| TOTAL MODEL INFIT

OUTFIT |

| SCORE COUNT MEASURE ERROR MNSQ ZSTD MNSQ

ZSTD |

|---------------------------------------------------------------------

--------|


| MEAN 383.0 130.9 .93 .13 1.02 -.1 1.02

-.1 |

| S.D. 47.6 1.0 .83 .01 .27 2.3 .27

2.3 |

| MAX. 467.0 132.0 2.66 .17 1.56 4.2 1.59

4.4 |

| MIN. 260.0 130.0 -1.08 .13 .49 -5.6 .49

-5.5 |

|---------------------------------------------------------------------

--------|

| REAL RMSE .14 TRUE SD .82 SEPARATION 5.73 PERSON

RELIABILITY .97 |

|MODEL RMSE .13 TRUE SD .82 SEPARATION 6.11 PERSON

RELIABILITY .97 |

| S.E. OF PERSON MEAN = .15

|

----------------------------------------------------------------------

--------

Table 5.5 shows person reliability for this study. Results indicate that value of person validity is .97, perfectly same as value suggested by the Model. Item separation is also more than 2 and fulfils the requirement in person separation (Bateman, et al., 2009; Linacre, 2005; Bond & Fox, 2007; Azrilah & Saidfudin, 2008 and Rasch, 1980).

5.3 Scale Calibration

Rasch analysis is very useful to verify scale calibration by calculating the zero setting calibration. This analysis can determine the probability how responses scatter unevenly between the stated scales (Norlide, 2007; Alagumalai et,al., 2005; Azrilah Aziz, 2010 dan Perkins et,al., 2002). Table 5.6 and Figure 5.1 presents the results of the scale calibration analysis for this instrument.

Table 5.6: Summary of Category Structure

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--

|CATEGORY OBSERVED|OBSVD SAMPLE|INFIT

OUTFIT||STRUCTURE|CATEGORY|

|LABEL SCORE COUNT %|AVRGE EXPECT| MNSQ MNSQ||CALIBRATN|

MEASURE|

|-------------------+------------+------------++---------+-------

-|

| 1 1 231 6| -.71 -.84| 1.16 1.22|| NONE |( -

3.02)| 1

| 2 2 933 24| .05 .02| 1.01 1.04|| -1.80 | -1.00

| 2

| 3 3 1663 42| .87 .96| 1.01 .96|| -.09 | .96

| 3


| 4 4 1101 28| 2.11 2.03| .91 .94|| 1.90 |(

3.09)| 4

|-------------------+------------+------------++---------+-------

-|

|MISSING 92 2| 1.03 | || |

|

-----------------------------------------------------------------

--

CATEGORY PROBABILITIES: MODES - Structure measures at

intersections

P -+------+------+------+------+------+------+------+------

+-

R 1.0 +

+

O |

|

B |11

4|

A | 111 444

|

B .8 + 11 44

+

I | 1 44

|

L | 11 4

|

I | 1 44

|

T .6 + 11 33 4

+

Y | 1 2222 333 3333 4

|

.5 + 1 222 222 33 3344

+

O | 2* 2*3 433

|

F .4 + 2 11 3 22 4 3

+

| 22 1 3 2 44 33

|

R | 22 1 33 22 4 33

|

E | 22 113 2 4 33

|

S .2 + 22 331 ** 33

+

P | 222 33 11 44 22 333

|


O |22 333 111 444 222

3|

N | 33333 4444*1111 22222

|

S .0 +**********44444444444444

1111111111111***********+

E -+------+------+------+------+------+------+------+------

+-

-4 -3 -2 -1 0 1 2 3 4

PERSON [MINUS] ITEM MEASURE

Figure 5.1: Structure measure at scale calibration intersection

Table 5.6 and Figure 5.1 show that structure measures towards scale calibration and structure measure at intersections. Table 4.7 shows that most frequent answer given by respondents was Scale 3 , followed by Scale 4 and Scale 2 with f values of 163 (42%), 1101 (28%) and 933 (24%), respectively. The least scale chosen by respondents was Scale 1 (f=231, 6%). The pattern of responses started from logit -.71 and increase in one way to +2.11 logit. This indicates that the pattern of responses is normal.

In this study, the differences between Scale 1 and 2 was 1.8, while differences between Scale 2 and 3 was 1.71 and the differences between Scale 3 and 4 was 1.99. This confirmed that the usage of Scale 1, 2, 3 and 4 could be discriminated by respondents. According to Bond & Fox (2007), the value to keep one scale is when the value is more than 1.4 and less than 5.

5.4 Pre and Post Score

Figure 2 and 3 show students’ score for pre-test and post-test.

ITEM - MAP - PERSON

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2 +T

|

X | Fadzil sumay

T|

|

X |S Afina arifah faris

fatin

1 XXXX + Ridzwan

XX S| Faisal Isma

X | wendy

XXXXXXXXX | Eliyana jay lim

shimin

XXXXXXXXX |M faizul hairu phua

sheila

XXXXXXXX | Azam

0 XXXXXX M+ nasrul

XXXXXX | Azhar intan yong


XXXXXX |T maya

XXXXXX |

X |

XXX S|

-1 X +

XX |

X |

X |

T|

X |

-2 X +

X |

|

|

|

|

-3 +

<frequ>|<less>

Figure 3: Student Post Test Score

From Figure 2 and 3, students’ score for pre-test and post-test can be compared. Figures show that for pre-test score the highest logit achieved by student is near to Logit 2, while for post-test the highest Logit attained by students is Logit 4. The improvement in Logit value shows that students improve their abilities in doing good or better level in their akhlaq. If we go for each student, we can detect that all students perform the better Logit in their post-test rather than pre-test.

Table 5.7 shows that there was a significant difference between Pre-Test and Post-Test (p<.001). The post-test shows better result compared to pre-test.

Table 5.7: t test for pre and post test score

Test Mean t df Sig

Pre 1.69 13.046

29

.000 Post 2.70

5.5 Score comparison among demographical factors.

The score of akhlaq achievement was compared among demographical factors (gender, stream and race).


Table 5.8, 5.9 and 5.10 show the analysis for t-test and one way ANOVA.

Table 5.8: t-test across gender

Construct Mean Value t df Sig

Male Female

Oral communication .567 .827 -.561 28 .579

Behavior 1.090 .913 .520 28 .607

Personality 1.393 1.921 -.821 28 .418

Overall .931 .914 .053 28 .958

Table 5.8 shows the results of the t-test analysis across gender for each construct and overall. From the table we can conclude that there was no significant difference between gender (p>.05) for each constructs and also akhlaq score in general.

Table 5.9: Analysis of One Way ANOVA for Races factor

Construct Sum of Squares F Df Sig

Within Group Between Group

Oral communication 4.44 42.10 1.425 27 .258

Behavior 2.02 22.38 1.217 27 .312

Personality 10.64 77.72 1.848 27 .177

Overall 2.38 19.252 1.667 27 .208

Table 5.9 shows analysis of ANOVA for students’ race. From the table we can say that there was no significant difference among races (p>.05) for each constructs and also akhlaq score in general.

Table 5.10: t test analysis for students’ stream

Construct Mean Value t df Sig

Science Non Science

Oral communication .818 .59 .486 28 .631

Behavior .587 1.404 -2.687 28 .012

Personality 1.08 2.27 -1.946 28 .062

Overall .679 1.166 -1.580 28 0.125

Table 5.10 shows t test analysis for students’ stream score. From the table we can summarize that there was no significant difference between their educational stream (p>.05) for each constructs and also akhlaq score in general.


6. Conclusion and Recommendations

From the findings we can conclude that a valid instrument is needed for assessing students’ akhlaq. Based on the theory of personality Imam al Ghazali, theory of constructivism and theory of moral development by Kohlberg, students’ behaviour can be developed by social factor. In this study, student’s akhlaq assessment is the treatment to make behavioural changes. Students will respond to the system of assessment and learn about good akhlaq and moral and eventually will change from bad to a good and acceptable behaviour based on norm of society.

The recommendations derived from the conclusions and implications of this study are: (i) To involve international students and make comparison between score; (ii) The results of the akhlaq assessment should be added to students’ grading system. This way, holistic assessment encompassing cognitive, affective and psychomotor domains can be developed; and (iii) Lecturer’s involvement in the assessment should be ensured as they can be a good evaluator and indirectly they will become a good role model in performing good akhlaq.

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