subject: Determinants Of Poor Academic Performance [print this page] Determinants Of Poor Academic Performance
ABSTRACT
The study empirically examines the causes of poor academic performance of the students in the native area, Ward 6, enrolled at Gokomere High School, Matova Secondary School, St Stanslous Secondary School and Chidzikwe Secondary School using Ordinary Least Squares approach for a sample of 200 native students. The study seeks to address the achievement of one of the Millenium Development Goals by effectively addressing the hindering factors underpinning the native children's academic performance. Human development is an instrument of economic growth and hence has to be promoted. The determinants of academic performance have been found to include the walking distance to school, sex of child, education status of parent/guardian, nutrition levels, late entrance and repetition at school and language spoken at home. The study failed to prove that late entrance and repetition at school indicate poor academic performance.
INTRODUCTION
The development of any nation or community depends largely on the quality of education of such a nation. It is generally believed that the basis for any true development must commence with the development of human resources (Akanle, 2007). Hence formal education remains the vehicle for social-economic development and social mobilization in any society.
Given the importance of education to development, why then it is not taken seriously as indicated by low pass rates. What then mainly determines academic performance in the specific case of Ward 6 secondary students? Well, in factual context, many ideas come to our mind if we think why some students perform better than others: is it because they study more? Do they have a higher capacity to learn? Does the personal background, way of life and environment of the student favor his/her performance?
Most programs undertaken to improve educational efficiency in developing countries focus on changing the educational system itself (Harbison and Hanushek, 1993). Policy planners generally recommend revising the curriculum, increasing the number of schools, and distributing educational materials more widely and equitably. Zimbabwe, in particular, has given priority in the last decades to building new schools and equipping urban schools with computers.
As this standard course of action is not based on empirical data, it overlooks the role of family and personal factors in shaping the academic trajectory of school children. Gender and nutritional status of the child and educational level of the parents have also been shown to influence school performance (Harbison and Hanushek 1993; Lockheed and Verspoor 1992), as have preschool cognitive abilities, a finding from a study of school children in rural Guatemala (Gorman and Pollitt 1993). Of particular importance is that some of these non-educational influences may also be changed through reasonable governmental policies.
It has been generally noticed that native students in Ward 6 perform far poorly than their counterparts who come to learn as borders. This is supported by a very small percentage of native students who obtain five ordinary level passes including Maths, English and Science and those who proceed to Advanced level each year. Also from the percentage proceeding to A' level another few will make their way to the university. Many students after failing just add to the unemployed in the district and hence low contribution to development. Crime rates are now reported as highly increasing as school leavers try to survive themselves. It is in the interest of this study to explore the determinants of such performance and ways of improving the performance.
The performance of the native students is summarized in the table perented below, showing the percentage of those who obtain 5 O' levels with Maths, English and Science.
Percentage pass rate of native students with 5 O' levels, Including Maths, English and Science
Year/School Gokomere St Stanslous Chidzikwe Matova
2000 6 3 2 -
2001 10 5 4 -
2002 7 4 4 -
2003 5 65 3
2004 5 6 3 2
2005 7 7 3 2
20065 5 2 3
20075 4 4 4
20087 4 4 3
Source: Respective Schools Annual Statistics
From the table above, the annual percentage pass remains very low for the entire period, with those learning at Gokomere performing better than other schools. However it is indicated that the majority of the native students do not pass Ordinary level and hence perform poorly. Hence this study seeks to find explanation to such performance and ways of improving academic performance.
This study tested the proposition that family (e.g., parental education) and personal (e.g., nutritional history) factors, demographic factors (e.g., walking distance to school), in combination with social characteristics (e.g., age, sex and English proficiency), contribute to the academic progress of school children.
We also hypothesized that the language spoken at home would affect school success. Most families in the rural areas of Ward 6 speak only Shona at home, and children often do not speak English, the language of instruction, prior to enrolling in school. This language predictor was also evident in Santa Maria de Jesus in the Guatemalan altiplano (Watkins and Pollitt 1996), where primary school children who spoke Catchiquel at home performed more poorly than those whose families spoke Spanish.
The study will be of significance as it adds to literature on the determinants of academic performance of Zimbabwean rural areas students. The study will also help in developing development policies in the community and the nation at large. It will help on crime and crisis management.
The paper is organised into five main parts. In the next section, we will review the literature that has previously analysed the role of different factors in student's academic performance. In third section, we will provide a description of the data that we used. Then, we will present our econometric model. After this, we will describe and analyse the results and finally in last section, we will offer our conclusions.
REVIEW OF THEORETICAL AND EMPIRICAL LITERATURE
Numerous studies have analysed the factors behind the academic performance of students. Identifying the variables that influence the achievement of young individuals at school, high school or university is of great importance for two different communities. It is an essential tool for the public authorities in charge of the definition of optimal and efficient education policies. On the other hand, this kind of analysis can help the parents, students and educational institutions to improve the quality of their career options. Also, some authors have suggested that there is a relationship between the performance of students during their studies and their future earnings.
Stricker and Rock (1995) conducted an analysis by assessing the impact of the examinees' initial characteristics (gender, ethnicity, parental education, geographic region and age), college-related characteristics and college-related performance variables in the performance on the Graduate Record Examinations (GRE) General Test. They found that the students' initial characteristics have a modest impact on the GRE results and among them parental education is the most significant. On the contrary, the college-related characteristics (major, institutional quality and research university) seem to have a more important role in explaining the difference in GRE scores among students.
Sakho (2003) carried out a study of the determinants of academic performance of HEC-lausanne graduates using a tobit model. He analyses econometrically the relationship between different variables and the average grade obtained during the licence studies by 156 students. The findings suggest that a large number of different factors related with the personal and family background, with the work and study discipline and with the type of degree interact together in order to explain the variation of HEC students' performance.
Akanle (2007) studied Socio-Economic Factors Influencing Students Academic Performance in Nigeria using some explanation from a local survey. The major instrument used in collecting data for the study was the self-developed instrument tagged social-economic and academic performance rating scale of the students. The data collected were analysed using t-test at (0.05 alpha level). The time frame of the study covers the period of 2004 to 2007. A total of one hundred and twenty (120) copies of questionnaire were administered to respondents. The study revealed that insufficient parental income, family type and lack of funding by governments are factors influencing students' academic performance. Based on these findings, certain recommendations were made towards improving student academic performance. Prominent of these include proper funding of education by government, sensitization of parents towards their children education and the support of NGOs to eradicate poverty.
Using the concepts of financial capital, human capital, and social capital, Chow (2000) attempted to disentangle the major factors which affected the academic performance of 368 recent Hong Kong immigrant students attending 26 different public high schools in Toronto. Results of the ordinary-least square regression analysis used indicated that presence of father in Canada, higher self-rated socio-economic status, immigration to Canada being politically motivated, and higher level of English proficiency were significantly and positively related to academic performance.
Jing-Lin (2009) studied the determinants of international students' academic performance comparing between Chinese and other international students using a multipleregression analysis. The results suggest that the perceivedimportance of learning success to family, English writing ability,and social communication with their compatriots are significantpredictors for all international students. As the predominantgroup, Chinese students display some distinctive characteristics.A less active learning strategy was observed among Chinese studentsrelative to others, but no evidence was found that this negativelyaffects their academic achievement.
A retrospective study was conducted by Amosun, Balogun and Alawale (1996) to determine the best predictors of academic and clinical performance in the physiotherapy education programme in the University of Ibadan, Nigeria. Reviewing the records of 94 students enrolled in the programme between 1983 and 1987, multiple and stepwise regression analyses revealed that pre-admission requirements were not significantly related to academic and clinical performance. When all the predictor variables were included in the multiple and stepwise regression analyses, the variance accounted for by the predictor variables was dismally low: 33.8% and 21.3% for academic achievement and clinical performance, respectively. It was concluded that the pre-admission requirements were not viable predictors of academic and clinical performance in the programme.
In conclusion, with respect to the determinants of academic performance, there are several studies based on the ordinary least squares (OLS) estimation. Spector and Mazzeo (1980) produced the first study that applied a qualitative model to determine academic performance. However, their ordered probit analysis concentrated on the probability of getting a letter grade of A versus the probability of not getting an A. Because there are more than two categories in a grading system, the study fails to give enough evidence. The following section reveals the methodology to be applied in the study.
METHODOLOGY
The study instead of using multinomial logit or probit model will employ the Ordinary Least Squares (OLS) procedure in determining the determinants of academic performance. The OLS methodology is deemed appropriate because of the nature of the dependant variable used in the study, Academic performance is measured by the average mark obtained by the student in English, Mathematics and Science, the mark is in percentages. The mutinomial logit and probit models have not been used because they restrict the dependant variable from taking values that widely differs among the respondents. Because of the disparity in performance of students, the author opts for OLS econometric model. The empirical model will be specified as follows;
PERF = f(AGE, SEX, DIST, LANG, PARENT, NUTR)
Where; AGE- the age of student at Form One, SEX- represents gender of student, DIST- walking distance to school, LANGUAGE- English proficiency at home, PARENT- education level of parents/guardians and NUTR- evaluation of nutrition standards received by student at their homes.
Justification For The Choice of Variables
The model uses Academic Performance (PERF) as the dependent variable. It is measured as a percentage average mark for a student in three main subjects which are English, Mathematics and Science. The subjects have been of choice because they form the bases for the future of the individual in any development career he/she pursues to undertake and hence it is a must' to pass them. The measurement used to the dependent variables allows us to analyse the distribution of performance across the students and the level of motivation needed to improve the academic performance.
Sex variable (SEX) has been included in the model because there is a belief that male students perform better than their female counterparts especially under unfavourable conditions. Also male students get encouragement from their families to improve academic performance than females ecause they are taken as the future of the respective families. The SEX variable is a dummy which takes the value one if male and zero otherwise (if female).
Walking distance to school (DIST) is also considered as a factor that explains academic performance. It is measured in kilometers the student has to walk to school. It is hypothesized that the longer the distance a student has to walk to school the less he performs at school. This is because by the time the student reaches school, he/she is tired and this will reduce hi/her academic performance. The effective time of study will be reduced and hence we expect a negative sign for this variable.
Education status of parents or guardians (PARENT) is also an important variable. It is expected that if parents are more educated then they usually motivate their students to do likewise and usually more than and hence those students with better educated parents are better performers at school. The variable is measured as a dummy, taking values of zero if parent has no qualification, one if completed O' level, two if completed tertiary education. A positive sign is expected.
Age (AGE) of students when they attain Form One level, is also considered as a variable to explain academic performance. It is hypothesized that students who are late to undertake primary education or are repeaters perform poorly as far as academic performance is considered. Form One has been the basis because from there onwards repeating cases of students is very low until completion at O' level. A negative sign is expected for this variable.
Nutrition (NUTR) has also been deemed appropriate to be in the model. This is measured by the average quality of food which the students take at their respective homes. The practice of balanced diet is taken into account, this enables to determine the adequacy of energy to the student to partake education. The variable takes values two if above normal, one if its average and zero if its below expected. A positive value is expected.
Language spoken at home (LANG) also is included in the model. It is expected that those students who speak English at their homes are good academic performers. English is the centre of all other subjects and hence its practice brings more efficiency in understanding other subjects. A positive sign is expected.
Sources of Data
The data used in the study is based on questionnaires and thus the response of students interviewed. For the dependant variable academic performance the information is taken from the students reports for the previous two terms, with the help of authority from respective school heads.
The methodology discussed in this section is going to be applied in the next section to determine the determinants of poor academic performance of the Ward 6, native students. A conclusion will be drawn based on the regression results to be undertaken; significance of coefficients in the regression will be of great importance.
ESTIMATION AND INTERPRETATION OF RESULTS
The study in order to answer its objective and research questions used the Eviews Econometric software to process the data obtained from the survey. Eviews is used to run an OLS model to obtain how the chosen variable explains the academic performance variable.
Summary Statistics for Quantitative Variables
Variable PERF DIST AGE
Mean 38.78500 1.384000 13.44000
Maximum 74.000003.400000 17.00000
Minimum 10.00000 0.300000 12.00000
Std. Dev. 16.05170 0.867877 1.205682
Observations 200 200 200
From the table above Average performance of the 200 students considered is 38.8 percent and is far below the pass mark of 50 percent. This shows that there is poor academic performance among the Ward 6 students. A maximum value of 74 percent and a lowest value of 10 percent have been recorded; this indicates disparity among the students as supported by a standard deviation of 16.05 which is very high comparing with other variables. The mean walking distance to school is 1.38 kilometers with a maximum distance of 3.4 km and lowest of 0.3km. This shows that some students are taking long distance to school daily. However the disparity is relatively low though there is positive skewness. On average students are 13.4 years old when they attend secondary, with some having as far as 17 years. This means that the students go to school lately.
Summary Statistics for Qualitative Variables
Variable SEX LANG NUTRI PARENT
Skewness 0.000000 0.675521 -0.100473 0.497833
Kurtosis 1.000000 1.456328 1.739990 2.150888
Jarque-Bera 33.33333 35.0686313.56670 14.26953
Observations 200 200 200 200
For the sex (SEX) variable, out of 200 students half are males and another half females and thus a kurtosis of 1 and skewness 0. For English proficiency, more students do not use it as their language at home, (68 used English and the majority Shona). Nutrition variable shows negative skewness towards poor diet, (48 students were found to be underfed, 84 average diet and 68 on good diet). Most of the parents/guardians are not highly educated, they have at least attained O' level (56 have not completed O" level, 80 completed O' level, 32 completed A' level and 28 have completed universities).
Correlation Matrix: Showing strength and direction of variable relationships
AGE -0.361977 -0.099779 0.144110 -0.438116 -0.313666 -0.185898 1.000000
The correlation matrix shows the relationship between variables and its strength. It helps in identifying multicollinearity among explanatory variables. From the table above there is no evidence of multicollinearity and hence all the variables can be incorporated in the regression equation. The highest correlation is 0.642 and is found between distance variable and parental education and it explains a negative relationship.
Regression Results from Ordinary Least Squares Methodology
Dependent Variable: PERF
Method: Least Squares
Date: 08/18/09 Time: 13:47
Sample(adjusted): 1 200
Included observations: 200 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
AGE 2.203039 0.169332 13.01017 0.0000*
DIST -5.281934 0.895429 -5.898775 0.0000*
LANG 12.90136 1.592217 8.102765 0.0000*
NUTRI 2.0420060.967165 2.111332 0.0360**
PARENT 4.884809 0.774843 6.304254 0.0000*
SEX 7.5530801.222123 6.180295 0.0000*
C 58.93119 7.041579 8.369031 0.0000*
R-squared 0.743556Mean dependent var 38.78500
Adjusted R-squared 0.736947 S.D. dependent var 16.05170
S.E. of regression 8.232707 Akaike info criterion 7.083648
Sum squared resid 13148.83 Schwarz criterion 7.182597
Log likelihood -702.3648 F-statistic 112.5003
Durbin-Watson stat 1.819499 Prob(F-statistic) 0.000000
From the regressions above the coefficients and standard errors are efficient since there is no serious autocorrelation as indicated by the DW-statistic of 1.819499. There is no evidence of multicollinearity as indicated earlier by the correlation matrix. The presence of heteroskedasticity has not been found in the data. Hence we can proceed to comment on the model regression results.
Discussion of Results
The OLS model specification used in the study is correctly specified as indicated by the significance of the F-test with a value of 112.5003 and a p-value of 0.0000, implying significance at all levels. The result shows that at least one of the explanatory variables explains academic performance. According to the adjuster R-squared of 0.736947 obtained in the regression, about 74 percent variation in students' academic performance is explained by the included explanatory variables. These indicators give us confidence to derive policy conclusion from our results.
The age variable (AGE) is significant at 1 percent but with a positive sign. The coefficient value recorded is 2.203 and a p-value of 0.0000, showing that it is a major variable. It implies that the older students perform better than those who go to school at an early age. In other dimension it also shows that those students who have an opportunity to repeat some grades perform better at secondary level. Therefore late entrance and repetition improves academic performance. This is in line with the findings of Rumberger (1995) who found that late entrance and repetition do not exerts negative effects on academic performance. Rumberger sited the lack of statistical power to detect an effect as an explanation to the finding.
The sex variable (SEX) has a positive coefficient of 7.553 and a p-value of 0.0000. It has taken the expected sign according to revealed literature. Male students academically perform better than female students as already hypothesized. Economically male students perform 7.55 percent greater than female students, implying that they have a better chance of passing.
Education status of parents/guardians (PARENT) has been found to explain academic performance. It has a positive significant value of 4.885. This supports the null hypothesis that educated parents/guardians motivate their children to study harder and have better results.
Language variable (LANG) is also significant at 1 percent level with a coefficient value of 12.5. It is one of the major variables with the expected sign. It implies that those students who speak English at their homes perform about 12.5 percent more than their counterparts. Hence the use of English is significant in explaining academic performance.
Walking distance (DIST) to school variable is significant at 1 percent with a negative sign. It shows that the greater the distance a student walks to school the poor he/she academically performs. The variable records a coefficient value of -5.28, meaning that increasing a distance a student should walk by 1 percent leads to his/her academic performance to decline by 5.28 percent.
The Nutrition variable (NUTR) has been found significant at 5 percent level. The variable although significant has proved to be minor as compared to other explanatory variables. It has a correct sign and has recorded a value of 2.042 with a p-value of 0.036. A student who gets a balanced diet performs better than the one who feeds on poor diet whilst going to school. Nutrition is important to the improvement of academic performance.
From the regression results factors that have been found to explain academic performance include distance travelled to school, age of student, sex, language spoken at home, education status of parents/guardians, and nutrition levels.
CONCLUSION AND POLICY RECOMMENDATIONS
The OLS model used in the study proves beyond doubt that the determinants of academic performance for Ward 6 students are distance travelled to school, age of student, sex, language spoken at home, education status of parents/guardians, and nutrition levels.
The first conclusion that may be drawn from this study is that family background and nutritional history of the student are as distinct factors that shape educational progress as we envisioned initially. We found that the four schools in Ward 6, have poor academic performers as indicated by the average mark that was below a pass mark of 50 percent. This indicates that something should be done to improve the performance of the students. Our data suggests that learning distance is an important factor in academic school performance as it increases underperformance. In addition to that the study found that education of parents, nutrition and speaking English at home improves academic performance. The study also finds that there is difference in the performance of male and female students, with male students performing better. Surprisingly the study indicated that late entrance and repetition did not undermine academic performance rather it improves performance.
Based on the above, the following recommendations are hereby proffered. Firstly, government should increase allocation of funds to provide for more amenities to facilitate learning in the schools. Secondly, parents should be sensitized on the need to make education of their children balanced across gender; this involves promoting and recognizing importance of educating girls, by adequately providing for their school materials. Thirdly, both parents and students should be informed about practicing the use of English at home and school, as it helps in attaining good results. Fourthly, parents should be informed to motivate their students to work hard in schools although they may have failed themselves and students should not try to follow the footsteps of uneducated parents/guardians rather have to aim higher. From nutrition dimension, families should e educated to exercise balanced diet for their children as this helps in improving their performance. Also local and international Non-Government organizations (NGOs) and other stakeholders in education should be sensitized to weld support for the funding of secondary school projects in Counseling as things helps in making availability of important information to both students and parents. Finally, concerning late entrance and repetition, parents should however be recommended to have their children be to school at the right age for the timing development of our nation and its communities.
In conclusion, the study results can be helpful to students themselves for attaining good future, the government and community as improving human capital ensures economic development, interested parties who deal with social improvement for the attaining Millennium Development Goals, especially illiteracy. By utilizing the study findings policies can be formulated and hence implemented timely to improve academic performance of school children in rural areas.
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