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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
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 503
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.
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 504
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
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 505
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.
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 506
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.
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 507
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.
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 508
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%
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 509
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 |
|---------------------------------------------------------------------
--------|
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 510
| 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
-----------------------------------------------------------------
--
|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
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 511
| 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
|
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 512
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
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 513
XXXXXX | kiren zety
X |S Farha
XXX | shikin
X S|
-1 X +
| ailin
|T Firdaus
T|
XX |
|
-2 XX + maya
|
|
|
|
X |
-3 +
<frequ>|<less> Figure 2: Student Pre Test Score
ITEM - MAP - PERSON
<rare>|<more>
4 + sumay
|T
| Fadzil
|
| wendy
|
3 + Eliyana
| Afina fatin
|S intan
|
| phua
| faris hairu
2 + arifah iwan
| faisal
XX T|M jay
X | isma
X | Azhar nasrul lim
sheila shimin yong 1
X |
1 XXX + faizul
XXXX S| Azam shikin zety
XX |S farha kiren
XXXXX | ailin
XXXXX |
XXXXXXXXXX |
0 XXXXXXX M+ daus
XX |
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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).
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 515
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.
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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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