An Analysis of Students Academic Performance: A Case
Study of Sarhad University, Peshawar, Pakistan
Rabia Shah, Assistant
Professor, Department of Business administration,
Sarhad University of Science & IT, Peshawar,
Pakistan.
Email: rabia.ba@suit.edu.pk
WaheedurRahman, Assistant
Professor, Department of Business Administration, Sarhad University of Science &
IT, Peshawar, Pakistan
Email: waheedrehman.ba@suit.edu.pk
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Gohar Abbas, Assistant
Professor, Department of Business administration,
Sarhad University of Science & IT, Peshawar,
Pakistan
Email: abbas.ba@suit.edu.pk
Abstract
The researcher has tried to investigate the factors affecting academic
performance of graduate students in this article. In the study academic
performance (student’s grades/marks) is taken as a dependent variable and the
gender, age, Attendance, schooling, Household Income, residential area, medium
of schooling; daily study hours and accommodation as independent variables. 100
students were selected though simple random sampling for data collection and
the data was collected through structured questionnaire from the different departments
of Sarhad University of Peshawar. For analysis, linear regression analysis,
correlation analysis, and descriptive analysis are used. It was extracted from
the findings that attendance, Household income and daily study hours
significantly contribute to the academic performance of graduate students.
Key Words: Academic performance, attendance, household income, age, daily study
hours
Introduction
Students’ performance
remains at top priority for academicians. Students performance is meant for
making a difference locally, regionally, nationally and globally. Educators, trainers, and researchers have
long been interested in exploring variables contributing effectively for
improving quality of performance of learners. Student’s performance is affected
by internal and external variables. The researcher after studying several
studies on the relevant field of research identified that there are many factors
that contribute towards student’s academic performance. Such as students’
effort, previous schooling is among the important factor that can affect their
performance (Siegfried & Fels, 1979). Another analysis showed some other
factors affecting student academic performance in 81 an introductory
biochemistry course at the University of the West Indies Benjamin, 1994),
parents’ education, family income (Devadoss & Foltz, 1996), self
motivation, age of student, learning preferences (Aripin, Mahmood, Rohaizad,
Yeop, & Anuar, 2008), class attendance (Romer, 1993), and entry
qualifications as the affecting factors.
Researchers conducted detailed studies about these factors
contributing to student performance at different study levels. Durden and Ellis
(2002) are of the opinion that student’s previous educational results are also
among the important factors of student’s future success. Graetz (1995)
suggested “A student educational success is contingent heavily on social status
of student’s parents/guardians in the society. Minnesota (2007) observed that
higher education performance depends upon the academic performance of graduate
students. Considine and Zappala (2002) noticed that parent’s income or social
status positively affects the student test score in examination).
Karshan (2005) concluded that students whose parents are
educated score higher on standardized tests than those whose parents were not
educated. Fantuzzo and Tighe (2000) claim that educated parents can better
communicate with their children regarding the school work, activities and
information being taught at school. Educated Parents can better assist their
children in their work and participate at school. Tsinidou, Gerogiannis and Fitsilis (2010)
claim that “education services are often not tangible and are difficult to
measure because they result in the form of transformation of knowledge, life
skills and behavior modification of learners”.
The relationship between gender and academic achievement of the
students has been discussed for decades Elite, (2005). Chambers and Schreiber,
(2004) view that a gap between the achievement of boys and girls has been
found, with girls showing better performance than boys in certain instances.
Mccoy, (2005) is of the view that gender, ethnicity and father occupation are
significant contributor to students’ achievement. Peng and Hall (1995) had the
same view about the students performance. Jeynes (2002) found that “social and
economical status of students is generally determined by combining parent’s
qualification, occupation and income standard”.
Although in many cases students who come from sound
socioeconomic background perform better because they have all the facilities
required for better study environment such as stated by Pedrosa et.al (2006) in
their study on social and educational background argue that students who come
from higher socioeconomic status sometimes fail to perform well in their
studies due to extra comfort provided to them where as students from poor
socioeconomic and educational background mostly perform better than those
coming from higher socioeconomic and educational area.
It was observed that that employment negatively
affects students’ academic achievement stated that an increase in the amount of
hours worked was the most important variable. In a study, more hours worked
decreased the probability of being an “A grade” student Pritchard, (1996).
According to Furr and Elling (2000), 29% of the students working 3039 hours
per week and 39% of those students working full time indicated that work had an
inverse impact on their academic progress. Whereas highquality, parttime jobs
that seemed to extend careerrelated skills may contribute to improved levels
of “career maturity,” and such type of jobs are assumed to be more flexible and
work with students’ schedules (Healy, O'Shea, & Crook, 1985).
While exploring the impact of absenteeism on students
performance many researchers (Devadoss & Foltz, 1996; Durden & Ellis,
1995; Romer, 1993; Park & Kerr, 1990; Schmidt, 1983), provide a consensus
that students who miss classes perform poorly compared to those who attend
classes.
This research let the researcher to make certain
assumptions about different factors contributing towards student’s academic
performance those are stated below:
H1 There is an impact of gender on
students’ performance.
H2 There is an impact of the type of
school (i.e. Government /Private) on students’ performance.
H3
There is an impact of the area of
residence (i.e. Urban /Rural) on students’ performance.
H4 There is an impact of mode of
instruction in school (i.e. English /Urdu) on students’ performance.
H5 There is an impact of accommodation
facility (i.e. Hostelries/Day Scholar) on students’ performance.
H6 There is an impact of students’
attendance on the students’ performance.
H7 There is an impact of financial
constraints on the students’ performance.
Research Methodology
The study aimed at identifying student’s performance
by considering different factors such as the dependent variable( graduate
student academic performance which can be studies by identifying their scores
or grades and gender, age, attendance,
schooling, father/guardian social economic status, residential area, medium of
schooling, study hour and accommodation as an independent variables. Linear regression
analysis was used to assess the impact of all these independent variables on
the dependent variable. The sample of 100 graduate students was selected for
the study purpose from the Sarhad University of Science and Information
Technology Peshawar.
Simple random sampling technique was employed in the
selection of sample from the targeted population. The questionnaires were
distributed to the students personally so that the true responses could be
obtained. Close ended questionnaires were used for data collection. Data from
Questionnaires was compiled, sorted, edited, classified and coded into the
coding sheet of SPSS 20.0 (version).
The researcher has used regression analysis for
conducting analysis. Correlation was also applied to check the positive or
negative relationship between the significant variables. For testing the
hypothesis that the academic performance of graduate students of Sarhad
University was tested using built in ttest function in SPSS.
Discussion and Result
The table 1 is the summaries the fitted or expected
linear regression model by the method of least square. We use the SPSS in
determining the results. The summary given below explains the academic
performance based upon gender, age, attendance, schooling, father/guardian social
economic status, financial constraints, part time job and residential area,
medium of schooling, tuition, study hour and accommodation as independent
variables.
Table 1 Regression
Analysis of Dependent and Independent Variables
Model 
R 
R Square 
Adjusted R Square 
Std. Error of the Estimate 
1 
.855^{a} 
0.731 
0.644 
0.65306 
Model 
Unstandardized Coefficients 
Standardized Coefficients 
T 
Sig. 
95.0% Confidence Interval for B 



B 
Std. Error 
Beta 
Lower Bound 
Upper Bound 


(Intercept) 
1.414 
1.422 

0.994 
0.327 
1.477 
4.304 


Average
attendance of the student 
0.034 
0.007 
0.54 
4.506 
0 
0.018 
0.049 


Age
of the student 
0.11 
0.053 
0.241 
2.08 
0.045 
0.217 
0.003 


Gender
of the student 
0.165 
0.395 
0.043 
0.42 
0.678 
0.968 
0.637 


To
which area student belong 
0.264 
0.218 
0.122 
1.21 
0.235 
0.707 
0.18 


Where
do you live? 
0.012 
0.25 
0.005 
0.046 
0.963 
0.497 
0.52 


Medium
of instruction at school 
0.125 
0.224 
0.057 
0.559 
0.58 
0.331 
0.581 


in
which college have you studied? 
0.129 
0.292 
0.045 
0.44 
0.661 
0.722 
0.464 

Your
household income 
0.0605 
0.166 
0.025 
0.202 
0.002 
0.303 
0.37 


Financial
Constraints 
0.207 
0.259 
0.088 
0.798 
0.431 
0.32 
0.733 


Daily
study hours 
0.259 
0.102 
0.325 
2.555 
0.015 
0.053 
0.466 


Findings of the above analysis comprises
of the following points: Adjusted R^{2}= 64%; R^{2} shows that
64% variations in academic performance
is due to the
gender, age, attendance, schooling, father/guardian social
economic status, residential area, medium of schooling, part time job,
financial constraints , study hour and accommodation. The coefficients of
Attendance show that test score will increase by .034 units if he remained
regular throughout the program and shows higher percentage of attendance. Coefficient of attendance is also
significant at 5% level of significance. The coefficients of Age
shows that a unit increases
in Age, decreases in academic performance by 0.110,
holding other factors as constant. Age is also significant at 5% level of significance.
It was observed that if gender is female
then it will decrease the academic performance by 0.165 units. Whereas the
significance level at 5% shows it insignificant for the study. While studying
about the impact of the coefficients of Urban (Residential Area) the researcher
came to know that if we increase a unit in urban graduates this will cause of
decrease in academic performance by 0.264, keeping other factors as constant.
Whereas the significance level at 5% shows it to be an insignificant variable
for the study.
While identifying about the Government
(Medium of Schooling) it was analyzed that a unit increase in Government
(Medium of Schooling) graduates gives an increase in academic performance by
0.129, keeping other factors as constant. But the significance level at 5%
shows it to be an insignificant variable for the study. In order to judge the
impact of accommodation whether graduate is Hostelries or Day Scholar the
researcher identified that if one unit of day scholar is increased it shows the
increase in academic performance by 0.012, keeping other factors as constant.
Whereas the significance level at 5% shows it to be an insignificant variable
for the study.
As stated above researcher also searched
about the impact of mode of instruction whether it is English or Urdu and it
was observed after analyzing the data that a unit increase in English Medium
(Medium of Schooling) shows the increase in academic performance by 0.125,
keeping other factors as constant. Although the significance level at 5% shows
it to be an insignificant variable for the study. While searching about the
Schooling background (Govt/Private) the researcher analyzed that a unit
increases in Govt. School (Background of Schooling) cause of decrease in
academic performance by 0.129, keeping other factors constant. Whereas the
significance level at 5% shows it to be an insignificant variable for the
study. While studying about the impact of Income on student’s performance it
was observed that if we increase one unit of Income it will increase the
academic performance by 0.06, keeping other factors as constant. Whereas the
significance level at 5% shows it to be a significant variable for the study.
In order to check whether financial constraints have any impact on students
performance or not the researcher came to know after analyzing the data that if
one unit of financial constraints is
increased it will increase the academic performance by 0.207, keeping other
factors as constant. Whereas the significance level at 5% shows it to be an
insignificant variable for the study.
While searching about the impact of daily
study hours on students’ performance the results show that one unit increase in
daily study hour’s increases the academic performance by 0.259, keeping other
factors as constant. Whereas the significance level at 5% shows it to be a
significant variable for the study.
Table 2
Correlation Analysis of the Significant
Independent Variables

Average attendance of the student 
Age of the student 
Your household income 
Daily study hours 

Marks /CGPA of the student 
Pearson Correlation 
.773^{**} 
0.216 
.447^{**} 
.614^{**} 
The regression analysis explained the
variables that cause variation in academic performance of the students. Hence the significant independent variables
were selected and further relationship was identified in table 2, which showed
that test score and attendance are positively correlated this implies that
students who are more regular show higher scores. The next one is age which
shows negative correlation with the scores. Then the household income which
also showed a positive relationship although not very strong but still has a
relationship with the obtained scores of the students. This relationship
clarifies that the parents having high household income affect positively the
performance of the students. Another important factor is study time which after
attendance shows strong relationship with the students’ academic performance.
The overall Correlation results show that attendance and daily study hours i.e.
77 % and 61 have strong relationship with the students’ performance.
Table 3 Students’
Performance and Gender


Levene's Test for Equality of Variances 
ttest for Equality of Means 



F 
Sig. 
T 
Df 
Sig. 
Mean Diff 
Std. E. Diff 


Marks
/ CGPA of
the student 
Equal variances assumed 
4.82 
0.03 
0.19 
98 
0.854 
0.107 
0.579 


Equal
variances not assumed 


0.35 
65.6 
0.737 
0.107 
0.306 


In above table the two tailed value (pvalue) is greater than
5%, so
we can
not
reject
the null hypothesis and conclude at statistically the performance
of graduate student do
not vary with
gender.
Table 4 Students’
Performance and Medium of Instruction


Levene's Test for Equality of Variances 
ttest for Equality of Means 



F 
Sig. 
T 
Df 
Sig. 
Mean Diff 
Std. E. Diff 

Marks /CGPA of the students 
Equal variances assumed 
0.005 
0.943 
0.44 
98 
0.66 
0.144 
0.326 

Equal
variances not assumed 


0.44 
43.58 
0.66 
0.143 
0.326 

In table 4 the two tailed value (pvalue) is less than 5%,
so we
reject the null hypothesis
and conclude at statistically the performance of graduate student vary with medium of instructions. That
means if students are taught in English language or any other language effects
the students performance , it might be because when students from the start are
taught in international language do not have understanding problems in later
stages if same language is used.
Table 5 Students’
Performance and Residential Area


Levene's Test for Equality of Variances 
ttest for Equality of Means 



F 
Sig. 
T 
Df 
Sig. 
Mean Diff 
Std. E. Diff 

Marks
/CGPA of
the students 
Equal variances assumed 
3.41 
.068 
2.76 
98 
.005 
3.41 
1.235 

Equal
variances not assumed 


3.15 
71.20 
.002 
3.40 
1.082 

In above table the two tailed value (pvalue) is greater than 5%,
so we can not reject the
null hypothesis and identify that
the performance of graduate student does not vary with residential area. In
residential area urban and rural areas were taken, so it obvious that living
areas have no significant impact on students performance.
Table 6 Student Performance and
Schooling


Levene's Test for Equality of Variances 
ttest for Equality of Means 



F 
Sig. 
T 
Df 
Sig. 
Mean Diff 
Std. E. Diff 

Obtained
Score 
Equal variances assumed 
3.52 
.064 
2.36 
98 
.024 
3.043 
1.290 

Equal
variances not assumed 


2.79 
63 
.006 
3.042 
1.089 

In above table the two tailed value (pvalue) is less than 5%,
so we
reject
the null hypothesis and
conclude
at statistically the performance of graduate student vary with schooling perspectives
as
if they belong to private
or government schools. Hence it is observed that schooling whether it is Private school or Government
schools it definitely put effect on student’s performance.
Table 7 Students Academic Performance
and Accommodation


Levene's Test for Equality of Variances 
ttest for Equality of Means 



F 
Sig. 
T 
Df 
Sig. 
Mean Diff 
Std. E. Diff 

Obtained
Score 
Equal variances assumed 
.19 
.667 
1.4 
98 
.162 
.46 
.321 

Equal
variances not assumed 


1.9 
42 
.163 
.46 
.321 

In above table the two tailed value (pvalue) is greater than 5%, so we can not reject the
null hypothesis and identify that the performance of graduate students does not
vary with where they live. Those who live at their own homes don’t show greater
differences from those staying at hostels.
Table 8 Students
Academic Performance and Financial Constraints


Levene's Test for Equality of Variances 
ttest for Equality of Means 



F 
Sig. 
T 
Df 
Sig. 
Mean Diff 
Std. E. Diff 

Obtained
Score 
Equal variances assumed 
4.6 
.038 
.92 
98 
.365 
.32 
.352 

Equal
variances not assumed 


1.01 
31.3 
.323 
.32 
.320 

In above table the two tailed value (pvalue) is greater than 5%, so
we can not reject the
null
hypothesis and
observe that the students
having financial constrains perform
some time same results means it does not affect the performance of graduate
student.
5. Conclusion
To identify the student’s
performance different factors were considered in the study such as the academic
performance of the students (Grades/ CGPS) and gender, age, attendance,
schooling, father/guardian social economic status, residential area, medium of
schooling, study hour, accommodation, part time job and financial constraints.
Linear regression analysis was used to assess the impact of all these
independent variables on the dependent variable. The results showed that the
model explained 64 % impact of the students performance with the above studied
variables, out of which four (i.e. Attendance , study hours, household income
and age) were significant. It was observed that attendance was highly and
positively correlated to the students performance which shows that students who
are more regular in attending lectures obtain greater performance along with
daily study hours and parental income, whereas it is inversely related to the
age of the students. While testing the
hypothesis the researcher identified that gender, residential area,
accommodation and financial constraints have no impact on student’s performance
whereas medium of instruction and schooling background have and impact on
student’s academic performance.
References
Aripin, R.,
Mahmood, Z., Rohaizad, R., Yeop, U., & Anuar, M. (2003). Students’ learning
styles and academic performance. 22^{nd} Annual SAS Malaysia Forum,
15th July 2008, Kuala Lumpur Convention Center, Kuala Lumpur, Malaysia.
Chambers, E.
A., & Schreiber, J. B. (2004). Girls’ academic achievement: Varying
associations of extracurricular activities.
Gender & Education, 16(3), 327346.
Considine, G.
& Zappala, G. (2002). Influence of social and economic disadvantage in the
academic performance of school students
in Australia. Journal of Sociology, 38,
129148.
Crosnoe, R.,
Johnson, M. K., & Elder, G. H. (2004). School size and the Interpersonal
side of education: An examination of race/ethnicity And organizational context.
Social Science Quarterly, 85(5),
12591280.
Devadoss, S.,
& Foltz, J. (1996). Evaluation of factors influencing students attendance
and performance. American Journal of
Agricultural Economics, 78(3), 499507.
Durden, G.
C., & Ellis, L. V. (1995). The effects of attendance on student learning in
Principles of Economics. American
Economic Review, 85(2), 343–346.
Eitle, T. M.
(2005). Do gender and race matter? Explaining the relationship between sports
participation and achievements. Sociological
Spectrum, 25(2), 177195.
Fantuzzo, J.,
& Tighe, E. (2000). A family involvement questionnaire. Journal of Educational Psychology, 92(2),
367376.
Furr, S. R.,
& Elling, T. W. (2000). The influence of work on college students’
development. NASPA Journal, 37, 2,
454470.
Graetz, B.
(1995). Socioeconomic status in education research and policy in John Ainley
et al., SocioEconomic Status and School
Education DEET/ACER Canberra.
Healy, C.C.,
O'Shea, D., & Crook, R. H. (1985). Relation of career attitudes to age and
programs during college. Journal of
Counseling Psychology, 32, 239244.
Jeynes,
William H. (2002). Examining the effects of parental absence on the academic
achievement of adolescents: The challenge of controlling for family income. Journal of Family and Economic Issues 23(2).
Krashen, S.
(2005). The hard work hypothesis: Is doing your homework enough to overcome the
effects of poverty? Multicultural
Education, 12(4), 1619.
Mann, M.
(1985). Macmilan Student’s Encyclopedia
of Sociology. England: Anchor Brendon Ltd.
McCoy, L. P.
(2005). Effect of demographic and personal variables on Achievement in eighth
grade algebra. Journal of Educational
Research, 98(3), 131135.
Park, K. H.,
& Kerr, P. M. (1990). Determinants of academic performance: A multinomial
logit approach. Journal of Economic
Education, 21(2), 101–111.
Romer, D.
(1993). Do students go to class? Should they? Journal of Economic Perspectives, 7(3), 167– 174.
Schmidt, R.
(1983). Who maximizes what? A study in student time allocation. American Economic Review, 73(2), 23–28.
Siegfried,
J., & Fels, R. (1979). Research on teaching college economics: A survey. Journal of Economic Literature, 17(3),
923 – 939.
Trusty, J.
(2000). High educational expectations and low achievement: Stability of
educational goals across adolescence.
Journal of Educational Research, 93, 356366.
Tsinidou, M.,
Gerogiannis, V., & Fitsilis, P. (2010). Evaluation of the factors that
determine quality in higher education: An empirical study. Quality Assurance in Education, 18(3), 227244.
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