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FACULTY OF ALLIED HEALTH SCIENCES DEPARTMENT OF NUTRITION AND DIETETICS SESSION 2010/2011 FACULTY OF ALLIED HEALTH SCIENCES DEPARTMENT OF NUTRITION AND DIETETICS SESSION 2010/2011 STUDY OF THE EFFECT OF THE HOURS SPENT IN EXTRACURRICULAR ACTIVITIES ON STUDENT’S ACADEMIC PERFORMANCE (CGPA) AMONG 2010/2011 FIRST YEAR FACULTY OF ALLIED HEALTH SCIENCES, UNIVERSITI KEBANGSAAN MALAYSIA, KUALA LUMPUR CAMPUS KUALA LUMPUR.

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No.NameMatric No. 1.HOR POOI EEA130182 2.NURUL ATIQAH BINTI ABD AZIZA127367 3.SIAH PEK JIAA130238 4.HASME ANIM BINTI AHMAD BASRIA127021 5.YAP PUI TENGA130356 6.NURWAHIDAYU BINTI ABD WAHABA126764 7.CHIA BING SHINA130341 8.GOH SU SANGA130279 9.SA`IDAH NAFISA ZAIRA BINTI AHMAD NAZLIA127376 10.LEE YING HUIA130128 11.ROOPINI A/P PADMANABHANA126997 12.AFIRA BINTI ZULKIFLIA127179 13.NURFATINA BINTI MAT DINA127304 14.MUHAMMAD HAZIQ BIN SHARIFFA126978 15.NG CHEE SENA130232 16.TAN SAU PEIA130408

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INTRODUCTION/ RESEARCH JUSTIFICATION To determine the effects of joining extracurricular activities, which include KTSN residential college activities, faculty activities and non beneficial organisations towards student’s academic performance (CGPA). Our respondents are made up of first year undergraduates of Faculty of Allied Health Sciences (FSK), UKM session 2010/2011. With this, we can know either involvement of university undergraduates in extracurricular activities can affect academic performance or not, and to identify other factors that might affect study performance among students.

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GENERAL OBJECTIVE To study of the effect of the hours spent in extracurricular activities on student’s academic performance (CGPA) among first year undergraduates Faculty Of Allied Health Sciences, Universiti Kebangsaan Malaysia, Campus Kuala Lumpur session 2010/2011.

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SPECIFIC OBJECTIVES 1. To identify types of extracurricular activities which the students get involved. 2. To compare hours spent on extracurricular activities between genders among 1st year FSK, UKM KL campus students. 3. To determine the significance between sleeping hours and hours spent on extracurricular activities among 1 st year FSK, UKM KL campus students. 4. To determine the significance between study hours and hours spent on extracurricular activities among 1 st year FSK, UKM KL campus students.

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SPECIFIC OBJECTIVES 5. To determine the significance between stress/distraction and hours spent on extracurricular activities among 1 st year FSK, UKM KL campus students. 6. To identify the preferences of student to participate in extracurricular activities on weekdays, weekend or both among 1 st year FSK, UKM KL campus students. 7. To compare the effect of number of sleeping hours, study hours and stress/distraction to academic performance among 1 st year FSK, UKM KL campus students.

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Research Design Observational Studies, Cross Sectional Studies Sampling Method Systematic Random Sampling Sample size= 290 subjects Target Population= All first year undergraduates of University Kebangsaan Malaysia, Kuala Lumpur Campus for 2010/2011 session.

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Material and Research Method Pilot Study and Questionnaire (13 Questions) Research AnalysisPearson’ correlation ANOVA Simple regression Multiple regression

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Variable *Dependent *Independent CGPA Individual factors, demographic factors, hours spent in extracurricular activities. Inclusion Criteria All first year undergraduates of FSKB, UKM session 2010/2011 Exclusion Criteria First year undergraduates from Forensic Science Program, FSKB, UKM session 2010/2011

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RESULTS AND DISCUSSION

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Table 3 Demographic Factors of Students VariableTotal Number of Respondent, N Percentage (%) Gender *Male *Female 219 31 140 18.13% (31) 81.87% (140) Race *Malay *Chinese *Indian *Other 219 114 50 6 1 66.67%(114) 29.24% (50) 3.51% (6) 0.58% (1)

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VariableTotal no. of Respondents Percentage (%) Course Biomedical Science Optometry Physiotherapy Nutrition Dietetics Diagnostic Imaging & Radiotherapy Environmental Health Speech Science Occupational Therapy Audiology 35 23 10 23 19 12 16 12 9 12 20.47 13.45 5.85 13.45 11.11 7.02 9.36 7.02 5.26 7.02

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Table 4 Cumulative Grade Point Average (CGPA) of Students Variable Total Number of Respondents (N) MeanMinMax CGPA1692.751.704.00 # The mean of the CGPA obtained among respondents = 2.75

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Table 5 Types of Activities Joined by Students VariableMeanMinimumMaximum KTSN Activities University/ Faculty Activities Non-beneficial organisation Others 3.72± 2.66 1.43±1.08 0.46±1.02 0.18±0.52 0.00 19.00 4.00 8.00 3.00

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VariableMeanMedianMode Minimu m Maximu m No of hours spent in extracurricular activities per day 2.7 ± 1.42.52012 No of hours spent in extracurricular activities per week 16.6 ± 16.6 11.256184 Table 6 Number of Hours Spent in Extracurricular Activities Per Day and Per Week

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VariableMeanMedianModeMinimumMaximum No of hours spent in extracurricular activities per day 2.8 ± 1.42.82012 No of hours spent in extracurricullar activities per week 9.7 ± 10.0 76184 Table 7 Number of Hours Spent in Extracurricular Activities per Day and per Week by Female Respondents

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VariableMeanMedianMode Minimu mMaximum No of hours spent in extracurricula r activities per day 2.8 ± 1.42.82012 No of hours spent in extracurricull ar activities per week 9.7 ± 10.076184 Table 8 Number of Hours Spent in Extracurricular Activities per Day and per Week by Male Respondents

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VariableN = 141Percentage (%) Weekday 2618.4 Weekend 2215.6 Both 9366 Table 9 Preferable Day of Joining Extracurricular Activities by Respondents There are only 141 respondents answer this questions as some of them do not answer the question. Missing data is not within the 10% drop-off in the calculation of sample size. The result considered as not reliable.

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Kolmogorov-Smirnov Test A type of analytical method of testing normality of distribution for large sample size. More sensitive than coefficient of variance. More objective than histogram and plots. In an analysis, if p>0.05, null hypothesis is not rejected.

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Hours spent in extracurricular activities StatisticdfSignificant 10.119150.200 20.091420.200 2.50.28250.200 30.089390.200 40.147150.200 50.22850.200 60.33730.200 Table 10 Test of Normality using Kolmogorov Smirnov Test Since p>0.05, null hypothesis is not rejected.

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Table 11 Test of Normality using Kolmogorov Smirnov Test Hours spent in extracurricular activities per week StatisticdfSignificant CGPA1.17890.200 2.197120.200 3.13290.200 4.232100.135 5.31570.035 6.112230.200 7.18780.200

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Hours spent in extracurricular activities per week StatisticdfSignificant CGPA8.27060.196 10.141140.200 15.24370.200 21.15390.200 From the analysis, p>0.05, null hypothesis is accepted. Therefore, all the data distributed normally.

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Table 12 Test of Normality using Kolmogorov-Smirnov Test Numbers of hours spent in sleepingSignificant 40.155 60.200 6.50.200 80.054 100.125 From the analysis, p>0.05, null hypothesis is not rejected. Hence, the data is distributed normally.

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Table 13 Test of Normality using Kolmogorov-Smirnov Test. Numbers of hours spent in studying 0.51.01.52.0 2.33.04.05.0 Sig.0.2 0.072 Since p>0.05, null hypothesis is not rejected.

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PEARSON’S CORRELATION Pearson’s correlation is a parametric test to measure the strength of the linear association between two variables.

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Table 14 Correlation Coefficient of Factors that Affect CGPA Correlation coefficiant, r p Number of hours spent in extracurricular activities per day -0.0610.493 Number of hours spent in extracurricular activities per week 0.1190.151 Number of sleeping hours 0.1750.024 Number of study hours -0.1230.115

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By using Pearson’s correlation: There is a significant relationship between number of hours spent on sleeping and CGPA. With the positive correlation between the number of hours spent on sleeping and CGPA, this indicates that spending more time on sleeping will lead to high CGPA. However, this correlation is classified as weak with the correlation coefficient, r =.175. The correlation between number of hours spent on sleeping and CGPA is classified as weak with the correlation coefficient, r =.175.

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PRIOR TO STUDY 1. Variables associated with shorter sleeping hours, such as anxiety and psychological maladjustment, have consistently been shown to be negatively associated with educational performance (Covington & Omelich, 1987; Hill & Wigfield, 1984)

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2. There is no significant relationship between number of hours spent on extracurricular activities per day or per week and CGPA, with the p >.05. This finding shows that joining extracurricular activities or not, does not influence students’ CGPA.

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A study conducted by the U. S. Department of Education revealed that “students who participate in co-curricular activities are three times more likely to have a grade point average of 3.0 or better than students who do not participate in co-curricular activities” (Stephens & Schaben, 2002, para. 4). Another study that been conducted by the National Educational Longitudinal Study, found that “participation in some activities improves achievement, while participation in others diminishes achievement” (Broh, 2002, para. 1). Since the results for relationship between amounts of time spend in extracurricular and CGPA is very contradicting, hence its effect is still being debated.

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3. For demographic factor, there is no significant association between amounts of time spent in extracurricular activities and CGPA for aspect of race, but has significant effect for gender’s aspect. Male students spend more time in extracurricular activities than female student in a week.

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Normally, girls spend more time outside the home in organized activities, taking lessons, doing academic activities, engaging in outdoor play and socializing, whereas boys spend more time outside the home in unorganized activities and team sports (McHale et al., 2001). Previous research from Liu, O.L., Rijmen, F., MacCann, C., & Roberts, R., in 2009 also reveals that boys spend significantly more time on non- academic activities such as computer gaming, television, sports and the Internet. This certainly support our findings that male student spent more time in extracurricular activities than female student.

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4. Number of hours spent on studying has no significant relationship with CGPA, where p >.05. This finding implies that students who spend more time on studying might not have a high CGPA.

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Data collected from the survey conducted in Harvard University and Kalamazoo College (2004) also shows that amount of study hours correlate with GPA, although the correlation is weak where value r is 0.199225. This might due to the respondents were not being honest with their study’s hours.

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5. The amount spent in sleeping hours was positively correlated with CGPA. spending more time in sleeping will obtain a higher CGPA.

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The variables associated with shorter sleeping hours, such as anxiety and psychological maladjustment, have consistently been shown to be negatively associated with educational performance (Covington & Omelich, 1987; Hill & Wigfield, 1984). The experience of anxiety, psychological maladjustment, and neuroticism tend to adversely affect the educational experience by decreasing individuals' attention and concentration and increasing task performance errors (Woolfolk, 1993).

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Stress is negatively correlated with CGPA Although an optimal level of stress can enhance learning ability (Kaplan & Sadock, 2000), too much stress can cause physical and mental health problems (Niemi& Vainiomaki, 1999), reduce students’ self esteem (Linn & Zeppa, 1984; Silver & Glicken, 1990) Increased anxiety from the test reduces the capacity available for performing the task, the result is that performance breaks down and the result becomes self-confirming (Fisher, 1994).

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Coefficients a ModelBBetaSig. Constant2.6230.000 No. of study hours -0.033-0.1100.158 No. of sleeping0.0480.0580.042 Stress-0.059-0.0730.352 Multiple Regression Equation: Y = AX+B+C GCPA = 2.623+ (-0.033* no. of study hour) + (0.048*no. of sleeping hour) + (-0.059*stress) = 2.579 R 2 = 4.7%. F (3.160) = 2.604.

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largest influence on CGPA is no. of sleeping (0.158) negatively correlated no. of study hours and stress (-0.011, -0.073) Discussion: ** shows that the presence of stress will had an adverse effect on academic performance. Learning and memory can be affected by stress. Although an optimal level of stress can enhance learning ability (Kaplan & Sadock, 2000)

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CONCLUSION Highest reasons for students to join extracurricular activities is for merit (N=140, 37%) compared to other reasons like self interest (N=100, 27%), being forced to join (N=84, 22%), influence by peer group (N=46, 12%) and for other reasons (N=7, 2%). Students that involve in extracurricular activities mostly are females (81.87%), and Malays (66.67%). Activities that join by students, mostly is KTSN activities with mean of 3.72±2.66.

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On average, students join 4 KTSN college activities, 2 university or faculty activities, 1 non-beneficial organization and 1 other activity. Parameter of the academic performance, CGPA, the result showed mean CGPA of 2.75±0.39. The amounts of time spending on extracurricular by students daily and weekly showed the mean hours of 2.78±1.40 hours and 16.6±1.66 hours respectively. Female students spent more times in joining extracurricular activities daily with mean of 2.8±1.4 hours while male students spent only 2.5±1.3 hours per day.

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However, female students spent less time (9.7±10.0 hours) than male students (10.5±10.1 hours) in extracurricular Most of the students preferably like joining activities for both weekends and weekdays (N=93, 66%) rather than only joining activities during weekdays (N=26, 18.4%), or only in weekends (N=22, 15.6%).

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There is a significant positive relationship between number of hours spend on sleeping and CGPA but the correlation is considered as weak, with the correlation coefficient, r =.175. There is no significant relationship between number of hours spent on studying with CGPA, where p >.05.

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From regression analysis between number of hours spent on sleeping and CGPA, it comes out with the regression equation of CGPA= 2.435 + (0.052* Number of hours spent on sleeping) Since t value for number of hours spent on sleeping is (t= 2.274, p<0.05), regression for sleeping hours and CGPA is significant.

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Equation For Multiple Linear Regressions: GCPA = 2.623+ (-0.033* no. of study hour) + (0.048*no. of sleeping hour) + (-0.59*stress) largest influence on CGPA is number of hours spent in sleeping while number of hours spent on studying and stress are negatively correlated.

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Overally, there is no significant relationship between these amounts of thime spend in extracurricular activities and CGPA.

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REFERENCES Broh, B. A. (2002, January). Linking extracurricular programming to academic achievement: Who benefits and why? [Electronic version]. Sociology of Education, 75, 69-96. Stephens, L. J., & Schaben, L. A. (2002, March). The effect of interscholastic sports participation on academic achievement of middle level school activities [Electronic version]. National Association of Secondary School Principals Bulletin, 86, 34-42. Pascarella, E.T., & Terenzini, P. T. (1991). How college affects students. San Francisco: JosseyBass. Conclusion. (2007). Student spending at Kalamazoo College and Harvard University. Retrieved: March 6, 2011 from www.kzoo.edu/pfolio/archive/example/weigandt/Concl usion.htm

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REFERENCES Covington, M., & Omelich, C. L. (1987). "I knew I could before the exam": A test of the anxiety-blockage hypothesis. Journal of Educational Psychology, 79, 393- 400. Hill, K. T., & Wigfieid, A. (1984). Test anxiety: A major educational problem and what can be done about it. Elementary School Journal, 85, 105-126. Woolfolk, A. E. (1993). Educational psychology (5th ed.). Boston, MA: Allyn and Bacon. Niemi, P.M. & Vainiomaki, P.T. (1999). Stress and academic performance. Journal of Medical Education. 59, 7-12. Clark, E.J. & Rieker, P.P. (1986). Stress and academic performance: A study among prescience students. Students Affair Journal Online, Journal of Health and Social Behaviour. 24, 4, 385-396.

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SUGGESTIONS FOR FUTURE RESEARCH State clearly in the questionnaire that the subject should give the exact time and not time range. Put only one unit of time instead of two for the answer in the questionnaire. Highlight the vital keywords in questionnaire to avoid misunderstanding by the respondents. Recruit more respondents to be in the survey so that the data obtained can have higher tendency of forming normally distributed data

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For more accurate results for studying relationship between sleeping hours and CGPA, bigger sample size used: to increase r-value Besides that, can also test on their alertness rather than sleeping hours only, as there are research showed that there are relationship between sleeping hours, alertness and CGPA. Take into consideration of factors which may affect academic performances

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Thank You

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