Factors influencing academic success or failure of first-year and senior university students: do education students and lecturers perceive things differently?

South African universities are changing in several very important ways; their entry standards are changing, their programmes are focusing more specifically on the outcomes that learners are required to achieve, and their student populations are becoming more diverse. These changes are occurring in a climate of increased accountability. It is, therefore, important for universities to be concerned about the standards of their academic programmes and about the success rates of students. Together, these factors have produced a range of opinions about what needs to happen in universities if the diverse range of students is to be successful in outcomes-based programmes that maintain high standards. Some educators argue that entry standards are the most important determinants of success at university; others maintain that non-academic factors must also be considered. There is considerable evidence that the views and expectations about success held by lecturers and stud ents are not always consistent. This article presents the results of a recent empirical investigation at the University of Pretoria that attempted to identify the post-enrolment factors that lecturers and students perceived as having important influences on students' success in their university studies. The study investigated the different expectations of first-year students, senior students and lecturers and identified numerous important similarities and inconsistencies. Most notably, there was a high and significant correlation between the rankings the three groups (lecturers, first-year students and senior students) gave to 52 factors linked to successful university study. There was also a high and significant correlation between the rankings of lecturers and senior students on 55 factors suggestive of unsuccessful university study. However, the perceptions of first-year students were not strongly correlated with either lectures or senior students. This suggests that First-year students may have unrealistic expectations about the non-academic factors that could reduce their chances of successful study. The results of the research could be used in three ways. University administrators could provide more supportive learning environments to enhance the chances that students will be successful and lecturers could also use the information to enhance the influences of positive factors on student learning. The influence of negative factors could also be minimised accordingly. Finally students could also be assisted and supported to approach university studies in a way that will increase their chances of success. South African Journal of Education Vol.23(4) 2003: 254-263

[1]  J. Villiers,et al.  The Effect of a Bridging Year on the Graduation Success of Educationally Disadvantaged Commerce Students. , 1998 .

[2]  E. Minium.  Statistical reasoning in psychology and education , 1970 .

[3]  RolandR . Roy,et al.  The role of prior academic performance and nonacademic attributes in the prediction of the success of high-risk college students. , 1991 .

[4]  I. Goduka.  Challenges to Traditionally White Universities: Affirming Diversity in the Curriculum. , 1996 .

[5]  J. B. Vancouver,et al.  A graphic approach for presenting expectancy of success based on two predictors , 1992 .

[6]  B. Weiner,et al.  A theory of motivation for some classroom experiences. , 1979, Journal of educational psychology.

[7]  Joanne Gainen,et al.  Barriers to Success in Quantitative Gatekeeper Courses. , 1995 .

[8]  L. K. Miller,et al.  12 Teaching Methods To Enhance Student Learning. What Research Says to the Teacher. , 1991 .

[9]  William G. Spady,et al.  Dropouts from higher education: An interdisciplinary review and synthesis , 1970 .

[10]  R. Killen.  OUTCOMES-BASED EDUCATION: PRINCIPLES AND POSSIBILITIES , 2000 .

[11]  A. E. Bartz.  Basic Statistical Concepts , 1976 .

[12]  Jill Johnes.  Determinants of student wastage in higher education , 1990 .

[13]  Vincent Tinto.  Dropout from Higher Education: A Theoretical Synthesis of Recent Research , 1975 .

[14]  Lawrence D. Graham,et al.  Predicting Academic Success of Students in a Master of Business Administration Program , 1991 .

[15]  John Cotton.  Basic statistical concepts in education and the behavioral sciences. , 1976 .

[16]  T. Dunne,et al.  Individual study orchestrations and their association with learning outcome , 1990 .

[17]  W. Holtzman.  Fundamental statistics in psychology and education. , 1951 .

[18]  N. M. Downie,et al.  Basic Statistical Methods , 1966 .

[19]  W. Mischel.  Toward a cognitive social learning reconceptualization of personality. , 1973, Psychological review.

[20]  Personality Correlates and Personal Investment of College Students Who Persist and Achieve. , 1990 .

[21]  S. Siegel,et al.  Nonparametric Statistics for the Behavioral Sciences , 2022, The SAGE Encyclopedia of Research Design.

[22]  W. Spady.  Outcome-based education : critical issues and answers , 1995 .

[23]  A. Minnaert,et al.  SUCCESS AND PROGRESS IN HIGHER-EDUCATION: A STRUCTURAL MODEL OF STUDYING , 1992 .

[24]  Vincent Tinto.  Principles of Effective Retention. , 1987 .

[25]  Claire D. Schmelzer,et al.  Using the Critical Incident Technique to Determine Reasons for Success and Failure of University Students. , 1987 .

[26]  S. Keef.  Pass Rates in the First Year of University Study: The Effect of Gender and Faculty , 1992 .

[27]  L. C. Jacobs,et al.  Predicting College Success: The Utility of High School Achievement Averages Based on Only "Academic" Course. , 1989 .

[28]  J. P. Guilford,et al.  Fundamental statistics in psychology and education , 1943 .

[29]  D. C. Howell.  Fundamental Statistics for the Behavioral Sciences , 1985 .

[30]  Kirsten McKenzie,et al.  Who Succeeds at University? Factors predicting academic performance in first year Australian university students , 2001 .

[31]  R. Killen,et al.  Differences between Students' and Lecturers' Perceptions of Factors Influencing Students' Academic Success at University , 1994 .

[32]  M. Riggs,et al.  Predictors of Student Success in a Teacher Education Program: What is Valid, What is Not , 1991 .

[33]  Brand Aa,et al.  Diversity in South African dental schools. , 1996 .

[34]  B. Weiner.  An attributional theory of motivation and emotion , 1986 .

[35]  U. Chikte,et al.  Diversity in South African dental schools. , 1996, The Journal of the Dental Association of South Africa = Die Tydskrif van die Tandheelkundige Vereniging van Suid-Afrika.

[36]  D. Watkins.  Student Perceptions of Factors Influencing Tertiary Learning , 1984 .

[37]  Nathaniel J. Bray,et al.  Faculty Teaching Skills and Their Influence on the College Student Departure Process , 2000 .