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The effect of social factors on students' academic performance in Nigerian tertiary institutions.

Introduction

College life can be stressful, although it is undoubtedly one of the most memorable experiences in one's life. It represents a critical developmental period for both late adolescents and young adults (Chickering, 1969). Social factors such as romantic relationships, organizations and clubs, and sports activities have been found to have effects on students' academic performance. These social factors affect academic performance in terms of time demanded and the psychological state they may cause. A student may be influenced to be involved in any of the stated variables. The question is how one strikes a balance between the stressful academic attainment and social activities.

Environment

Environment comprises factors that play a role in academic performance. The environment may be physical or socio-physical. All factors have a direct or indirect relationship with students' performance.

Romantic Relationships

The daily routine of university life brings new sleeping and eating habits, increased workload, and new responsibilities. University students are prone to stress due to the transitional nature of university life (Wright, 1967). They must adjust to being away from home, perhaps for the first time, and maintain a balance between high level of academic success and a new social environment. These daily stressors do not cause anxiety by themselves. Stress results from interactions between stressor and the individual's perception and reaction to them (Romano, 1992). The amount of stress experienced may be influenced by the individual's ability to effectively cope with stressful events or situations (Zurilla and Sheedy, 1991). A romantic relationship may ease environmental stress (Berger, 1997). Paul and White (1990) observe that being in an intimate relationship involves trust, sensitivity, and responsiveness, being able to make a commitment, striving for equity and mutuality. For a student, it also means working to achieve academic balance. However, Zimmer and Ginerbec (2001) find dating has a positive effect on the emotional health of adolescents.

Quatman, et. al., (2001) study dating status, academic performance, and motivation in high schools in the US state of California, showing that students who dated more frequently had a lower academic performance. The study supported a significant relationship between dating status and academic achievement, which can cause serious problems among university students (Prisbell,1986). While having an intimate relationship may have benefits for emotional health, that being overly involved in dating is associated with a more negative effect on the psychosocial function and health of students (Baumeister,1995).

Clubs and Organizations

Research conducted by Kerssen-Griep, Hess, and Tree. (2003) on learning motivation and interaction in school shows that student perception of instructional behaviour sustains their involvement in classroom. Jackson, Weiss, Lundquist, and Hooper (2003) examine the degree to which cognitive motivation predicts academic performance. They point out that increased school activity may assist motivation. Paul and White (1990) examined extracurricular activity participation and academic achievement in a senior high school setting. They found that extracurricular activities and academic performance were highly correlated. They supported the hypothesis stated by Mynell (2004) more involvement in school activities means a better grade point average.

Student Cults

Student cults may have a pronounced effect on the academic performances in institutions of higher education. A cult is an association like every other, with hierarchy, ranks, a governing body, and a head or leader, but it is secretive in its activities. Its members may be students who seek initiation, with others who are influenced or even coerced into becoming members. A member of a student cult is expected to place members' interest over any others'. Students cannot strike a balance between the cult and academic performance. Members may be usually enticed with benefits, including:

* Payment of school fees

* Protection from aggression

* Popularity and admiration

* Good grades while in school

Unfortunately, most of these promised privileges will never come their way, and students are been left alone to cope with demands such as:

* Lecture times and meeting with members

* Studying times and working on other members' assignments

* Initiation ceremonies, etc.

Research Problem

This study is asks the following questions:

* What is the effect of romantic relationships on the academic performance of university students?

* What is the effect of involvement in clubs or organizations on the academic performance of university students?

* What is the effect of membership in student cults on the academic performance of university students?

* What is the effect of excessive sporting activities on the academic performance of university students?

Significance and Objectives of the Study

Academic performance is continuously falling as student populations are increasing. This paper looks at social variables and their effect on academic performance. The study may be significant to parents who expect not just excellent performance but also responsible men and women outside school. It may also interest undergraduates and prospective students who may wish to pursue excellence in their chosen academic career.

Research Hypotheses

Ho: There is no significant relationship between dating and students' academic performance.

Ho: There is no significant relationship between membership in student cults and students' academic performance.

Ho: There is no significant relationship between membership in clubs and organizations and students' academic performance.

Ho: There is no significant relationship between excessive sporting and students' academic performance

Ho: There is no significant relationship between dating, student cults, clubs and organizations, excessive sporting, and student's academic performance

Research Design

The survey involves sampling technique using the mid-point squares approach to randomly selecting students from departmental graduates lists.

Population and Study Sample

1500 graduates were sampled from the departments of the Federal Polytechnic, Auchi, Nigeria graduate lists in the Exams and Records Office between 1999/2000 to 2007/2008 academic sessions using three digit serial numbering system with the concept of mid-point approach. A stratified sample of 120 was created (Umar & Shaib, 2008).

Methodology

The research uses 5-point Likert scale for grading system describes as X and Y defines the variables of interest.
Performance       Distinction    Upper          Lower
                                 credit         credit

CGPA              3.50-4.00      3.00-3.49      2.50-2.99
Likert scale      5              4              3

Performance       Pass           Fail

CGPA              2.00-2.49      1.50-1.99
Likert scale      2              1


The data was analyzed using SPSS version 12.0.
Data Presentation and Analysis

Clubs/Organizations

X       Y

5       3
4       15
3       54
2       37
1       11

Romantic Relationships

X       Y

5       2
4       14
3       26
2       42
1       36

Student Cults

X       Y

5       0
4       13
3       33
2       38
1       36

Excessive Sporting

X       Y

5       3
4       15
3       48
2       27
1       19


Analysis with Model Results
Analysis 1. Variables Entered/Removed (b)

Model     Variables Entered        Variables Removed   Method

1         Cluborganisation(a)                     .    Enter

(a) All requested variables entered.

(b) Dependent Variable: academic peformance

Model Summary

Model        R            R Square     Adjusted     Std. Error
                                       R Square     of the
                                                    Estimate

1            .286(a)      .082         -.224        1.749

(a) Predictors: (Constant), club/organisation

ANOVA(b)

Model                     Sum of     df         Mean
                          Squares               Square

1          Regression     .820       1          .820
           Residual       9.180      3          3.060
           Total          10.000     4

Model                     F          Sig.

1          Regression     .268       .640(a)
           Residual
           Total

(a) Predictors: (Constant), club/organisation

(b) Dependent Variable: academicpeformance

Coefficients(a)

Model                          Unstandardized
                               Coefficients

                               B              Std. Error

1          (Constant)          3.518          1.270
           Club/organisation   -.022          .042

Model                          Standardized   t         Sig.
                               Coefficients

                               Beta

1          (Constant)          -.286          2.770     .070
           Club/organisation                  -.518     .640

(a) Dependent Variable: academicpeformance


Model:

Academic performance = 3.518-0.022 club/organization.

Step I: Ho: The is no significant relationship between club/organization and academic performance

Step II: Test--statistic

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]

Step III: F cal = Ms Regression = 0.82 = 0.268

Ms Residual 3.060

Step IV: Decision variable

i. If, accept Ho.

If, do not accept Ho.

Step V: Comparison

Fcal= 0.268, [F.sub.tab] = 10.128

Step VI: Conclusion

We accept Ho and conclude that parameter of estimate between clubs/organizations and academic performance is not significant.

Step VII: Interpretation of model

There is a negative relationship between clubs/organizations and academic performance that further implies that a unit change or increase in cluborganizational involvement of students brings about 2.2% percent decrease in academic performance.
Analysis 2. Variables Entered/Removed (b)

Model       Variables         Variables         Method
            Entered           Removed

1           student cults     .                 Enter

(a) All requested variables entered.

(b) Dependent Variable: academicpeformance

Model Summary

Model      R          R Square     Adjusted       Std. Error of
                                   R Square       the Estimate

1          .917(a)    .842         .789           .727

(a) Predictors: (Constant), student cults

ANOVA (b)

Model                  Sum of      df    Mean      F         Sig.
                       Squares           Square

1        Regression    8.416       1     8.416     15.938    .028 (a)
         Residual      1.584       3     .528
         Total         10.000      4

(a) Predictors: (Constant), student cults

(b) Dependent Variable: academicpeformance

Coefficients (a)

Model 1         Unstandardized
                Coefficients

                B               Std. Error

(Constant)      5.082           .615
student cults   -.087           .022

Model 1         Standardized    t          Sig.
                Coefficients

                Beta

(Constant)      -.917           8.270      .004
student cults                   -3.992     .028

(a) Dependent Variable: student cults


Model

Academic performance = 5.082-0.087 student cults

Step I: Ho: There is no significant relationship between student cults and academic performance.

Step II: Test--statistic

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]

Step III: F cal = Ms regression = 8.416 = 15.938

Ms residual 0.528

Step IV: Decision Rule

If, accept Ho

If, do not reject Ho

Step V: Comparison

Fcal= 15.938, [F.sub.tab] = 10.128

Step VI: Conclusion

Since [F.sub.cal] > [F.sub.tab] ; we therefore accept H1, and therefore conclude that there is significant relationship between student cults and student academic performance. This implies that a unit increase in student cults activities of student result in 8.7% decrease in academic performance.

Analysis 3.
Variables Entered/Removed (b)

Model    Variables Entered            Variables    Method
                                      Removed

1        romantic relationship (a)    .            Enter

(a) All requested variables entered.

(b) Dependent Variable: academicpeformance

Model Summary

Model     R           R Square    Adjusted     Std. Error of
                                  R Square     the Estimate

1         .934 (a)    .873        .830         .651

(a) Predictors: (Constant), romantic relationship

ANOVA (b)

Model                  Sum of     df    Mean       F         Sig.
                       Squares          Square

1        Regression    8.727      1     8.727      20.571    .020 (a)
         Residual      1.273      3     .424
         Total         10.000     4

(a) Predictors: (Constant), romantic relationship

(b) Dependent Variable: academicpeformance

Coefficients (a)

Model 1                   Unstandardized Coefficients

                          B               Std. Error

(Constant)                5.182           .562
romantic relationship     -.091           .020

Model 1                   Standardized    t         Sig.
                          Coefficients

                          Beta

(Constant)                -.934           9.214     .003
romantic relationship                     -4.536    .020

(a) Dependent Variable: academicpeformance


Model

Academic performance = 5.182 = 0.091 Romantic relationship

Step I: Ho: These is no significance relationship between romantic relationship and academic performance

Step II: Test--Statistic

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]

Step III: F cal = Ms Regression = 8.727 = 20.571

Msresidual 0.424

Step IV: Decision Rule

If, accept Ho

If, do not accept Ho

Step V:Comparison

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]

Step VI: Conclusion

Since [F.sub.cal] > [F.sub.tab] ; we accept H1 and conclude that the parameter of estimate between romantic relationships and academic performance is significant.

Step VII: Interpretation of model

There is a negative relationship between romantic relationships and academic performance, meaning a unit increase in romantic relationships among student about 9.16 percent decrease in the academic performance.
Analysis 4

Variables Entered/Removed (b)

Model    Variables Entered        Variables    Method
                                  Removed

1        excessivesporting (a)    .            Enter

(a) All requested variables entered.

(b) Dependent Variable: academicpeformance

Model Summary

Model    R            R Square    Adjusted     Std. Error of
                                  R Square     the Estimate

1        .566 (a)     .320        .093         1.506

(a) Predictors: (Constant), excessivesporting

ANOVA (b)

Model                  Sum of       df           Mean
                       Squares                   Square

1        Regression    3.200        1            3.200
         Residual      6.800        3            2.267
         Total         10.000       4

Model                  F            Sig.

1        Regression    1.412        .320 (a)
         Residual
         Total

(a) Predictors: (Constant), excessivesporting

(b) Dependent Variable: academicpeformance

Coefficients (a)

Model 1               Unstandardized Coefficients

                      B               Std. Error

(Constant)            4.600           1.506
excessive sporting    -.067           .056

Model 1               Standardized    t              Sig.
                      Coefficients

                      Beta

(Constant)            -.566           3.055          .055
excessive sporting                    -1.188         .320

(a) Dependent Variable: academic peformance


Model

Academic performance = 4.6-0.067 excessive sporting

Step I: Ho: these is no significant--relationship between Excessive sporting and academic performance

Step II: Test statistic

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]

Step III: F cal = Ms regression = 3.20 = 1.412

Ms residual 2.267

Step IV: Decision Rule

If, accept Ho

If, reject Ho

Step V: Comparison

[F.sub.cal] = 1.412, [F.sub.tab] = 10.128

Step VI: Conclusion

Since [F.sub.cal] < [F.sub.tab] ; we therefore accept Ho and conclude that there is no significant relationship between excessive sporting activities and academic performance.

Step VII: Interpretation

There is a negative relationship between excessive sporting activities and student academic performance. Hence, a unit increase in excessive sporting activities results in 6.7% decrease in the level of academic performance of students.

Summary of Hypotheses, Results, and Conclusions
Hypothesis Result F, Calculated and Conclusion

No. s    Hypothesis                         F-             F-tabulate
                                            computed       at 0.05
                                                           with 1,3
                                                           d.f

1.       Ho: These is no significant        15.94          10.128
         relationship between student
         cults and academic performance

2.       Ho: These is no significant        0.268          10.128
         relationship between club /
         organization and academic
         performance

3.       Ho: These is no significant        20.57          10.128
         relationship between romantic
         relationship and academic
         performance

4.       Ho: These is no significant        1.42           10.128
         relationship excessive sporting
         and academic performance

No. s    Hypothesis                         Comparison     Conclusion

1.       Ho: These is no significant        15.94 >        Do not
         relationship between student       10.128         reject H1
         cults and academic performance

2.       Ho: These is no significant        0.268 <        Accept Ho
         relationship between club /        10.128
         organization and academic
         performance

3.       Ho: These is no significant        20.57 >        Do not
         relationship between romantic      10.128         reject H1
         relationship and academic
         performance

4.       Ho: These is no significant        1.42 <         Accept Ho
         relationship excessive sporting    10.128
         and academic performance


Findings

The regression model shows that excessive sporting activity and involvement in clubs and organizations by students does not have a significant effect on academic performance, while membership in student cults and romantic relationships does have a significant effect.

Conclusion

Academic performance is an excellent measure of the transfer of knowledge in modern society. Some variables of interaction can be studied. This research finds that student cults are an academic impediment and perhaps an outright evil. Romantic relationships having the highest impact, and may be a psychological barrier to an effective learning process. Excessive sporting activities and involvement in clubs and organizations may pose a threat, but an insignificant one.

Recommendations

(1) There should be an enlightenment campaign on the evil perpetuated on our knowledge-based environment by student cults, in order to empathetically disabuse the young people and learners from getting involved in these illicit and unwholesome associations, which greatly affects the survival of academics in society.

(2) Efforts should be made to advise young people of the negative role romantic relationships may play in academic performance and the adverse consequences.

(3) Sporting should be seen as an enriching leisure activity, and not an agent of antisocial behaviour among students resulting in enmity and distraction.

(4) Regulatory bodies should be charged with the responsibility of setting standards and checking excess on the part of students.

(5) Further studies are expected to verify the effect of the combined variables on the level of academic performance among students.

Reference

Baumeister, R.F., & Leary, M.R. (1995). The need to belong: Desire for interpersonal attachments as a fundamental human motivation. Psychological Bulletin 117 : 497-529.

Berger , J. B. ( 1997 ). Students ' sense of community in residence halls , social integration , and first year persistence . Journal of College Student Development 38 : 441-452.

Chickering , A.W. ( 1969 ). Education and identity. San Francisco : Jossey-Bass

D'zurrilla, T.J., & Sheedy, C.F. (1991). Relation between social ability and subsequent level of psychological stress in college students. Journal of Personality and Social Psychology 61 : 841-846.

Kerssen-Griep, J., Hess, J., & Trees, A. (2003). Sustaining the desire to learn: Dimensions of perceived instructional facework related to student involvement and motivation to learn. Western Journal of Communication 67: 357-381.

Jackson, T., Weiss, K. E., Lundquist, J. J., & Hooper, D. (2003). The impact of hope, procrastination, and social activity on academic performance of midwestern college student. Education, 124 (2): 310-320.

Martin, M. L. (2004). Involvement in College Clubs and Organizations and Its Relationship to Academic Performance. National Undergraduate Research Clearinghouse 7 . Available: http://www.webclearinghouse.net/volume/7/MARTIN-Involvemen.php

Paul, E.L., & White, K.M. (1990). The development of intimate relationships in late adolescence. Adolescence 24 : 375-400.

Prisbell, M. (1986). The relationship between assertiveness and dating behaviour amongcollege students. Communication Research Reports 60 : 659-664.

Quatman, T., Sampson, K., Robinson, C., & Watson, C. M. (2001). Academic, motivational, and emotional correlates of adolescent dating. Genetic, Social, and General Psychology Monographs 127 (2): 211-234.

Umar, S.S., & Shaib, I.O. (2007). Design and analysis of experiments: Concept, theory, and application . Edo, Nigeria: Smitel.

Umar, S.S & Shaib, I.O. (2008). Research methods and statistics: Concepts and applications. Auchi, Nigeria: Smitel.

Wright, J.J. (1967). Reported personal stress sources and adjustment of entering freshmen. Journal of Counseling Psychology. Vol 14 (4): 371-373

Zimmer, G. (2001). Diverse aspects of adolescent dating association with psycho- social. functioning from early to middle adolescence: Journal of Adolescence 24: 313-336.

S.S. Umar

I.O. Shaib

D.N. Aituisi

Department of Statistics

N.A. Yakubu

Department of Computer Science

O. Bada

Department Of Statistics

Federal Polytechnic

Auchi, Nigeria
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Author:Umar, S.S.; Shaib, I.O.; Aituisi, .N.; Yakubu, N.A.; Bada, O.
Publication:Library Philosophy and Practice
Article Type:Report
Geographic Code:6NIGR
Date:Mar 1, 2010
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