Students’ Enrollments in Urban and Regional Planning Programs and Crossroad to Career in Planning in Nigerian Universities

Abstract

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Chinese

This study investigated students’ enrollments in Urban and Regional Planning (URP) programs in Nigerian universities. It also explored factors that influenced decisions about URP education. A total of 550 students from nine universities selected across the country participated in the survey. The research revealed that only 46 percent of students applied to study URP. It identified skills acquisition, interest, and career specialization as key factors that influenced students’ choices. Ignorance was identified as a major restraint for the choice of URP. The dominant factor that differentiated between students who chose URP and those that did not was the time of awareness.

Keywords

career choices career decisions career determinants Urban and Regional Planning

Introduction

For the past two decades, Urban and Regional Planning (URP) education in Sub-Saharan Africa has been a major theme of debate among planning scholars (see, for example, Diaw, Nnkya, and Watson 2002; Odendaal 2012; Watson and Odendaal 2012). This rekindled interest may be predicated on the need to train planners in alternative planning approaches, more suited to the peculiarities of cities and urban development in Africa (Parnell, Pieterse, & Watson 2009; Silva 2012). Unfortunately, previous planning education reforms such as the one initiated by the Association of African Planning Schools in 2008 (Watson and Odendaal 2012, 99) rarely considered the enrollment processes leading to the planning schools in the continent. Nevertheless, enrollments of the right candidates into planning schools are essential for training the envisioned urban planners.

In Nigeria, as elsewhere in Africa, much of the expectations and capacities to train the new-generation planners rest on the universities and other tertiary institutions. The official entrance examination to high institutions in the country is the Unified Tertiary Matriculation Examination (UTME). The examination is conducted by the Joint Admissions and Matriculation Board (JAMB), Nigeria. Besides, each tertiary institution conducts a post-UTME screening exercise to finally select candidates that merit provisional admission.

Applicants seeking admission into the universities often find themselves at career crossroads, where they have to make choices from a range of courses available, including URP. Many studies have been carried out across the world on students’ enrollments into different disciplines like accounting, management, nursing, among others (see Ahmed 2015; McKenna, Brooks, and Vanderheide 2017; Rababah 2016). However, only a few scholars (such as Adeleye 2008; Al-Hasan, Shaka, and Olowojoba 2013; Morenikeji and Shaibu 2006; Todes and Harrison 2004) have focused on students’ enrollments into planning schools. Although these previous studies are instructive, there is still a paucity of information on factors that influence the decision to enroll in planning programs. This study sought to fill this gap in knowledge.

The study aimed at exploring students’ enrollments in Nigerian planning schools. Specific objectives of the study were to (1) determine the proportion of candidates that chose URP as their preferred course in the UTME, (2) identify factors that influenced students’ choice of URP as a course of study, (3) determine whether time and sources of awareness of the discipline varied significantly across the country, and (4) ascertain whether personal characteristics and background (i.e., gender, secondary school subjects, and time of awareness of URP) can be used to discriminate choosing URP as a first choice course.

Specifically, the study sought to ascertain the extent to which such variables as career advancement prospects, personal interests, opportunity to apply knowledge and skills, career specialization opportunities, employment opportunities, job security, career flexibility, financial reasons, gender, and training demand, among others, influenced the choice of URP among students. It also sought to ascertain whether the time of awareness and sources of information about URP varied significantly across the six geopolitical zones¹ in Nigeria.

The next section presents an exploration of factors that can influence the career choices of students across different disciplines and contexts. A description of the scope and methods of the study follows thereafter. The section following this presents the research results and findings. The final section attempts to link findings made with existing writings and thoughts on career choices.

Determinants of Career Choice

Generally, the factors influencing career choices can either be intrinsic or extrinsic or a mixture of both (Marinas et al., 2016; Nyamwange 2016). It is, however, possible to identify specific factors that affect career choice of an individual. Several studies showed that the desires and expectations of parents greatly swayed adolescents’ aspirations (see Etiubon, Ugwu, and Ado 2018; Fouad et al., 2016; Ulrich, Frey, and Ruppert 2018). In some situations, the teachers and friends they made in their high schools influenced young individuals’ career choices (Falaye and Adams 2008; Natalie 2006).

A role model is another vital factor that has influenced career decision-making of young people as demonstrated by the works of Brown and Trevino (2014); Edwards and Quinter (2011). Some individuals selected professions which they perceived to command high prestige, others followed the opportunities their educational choices presented to them, a few persons were guided by their interest (Ahmed, Sharif, and Ahmad 2017; Fatoki 2014; Nyamwange 2016), irrespective of the potential gains, while other persons chose the careers that gave high income (Hewitt 2010).

Korir and Wafula (2012) examined the influence of personal issues, environmental factors, and opportunities in career decisions among students of Hospitality Management at Moi University, Kenya. They discovered that the majority of the students were influenced by opportunity and environmental factors. Ignorance about utility and career prospects had also been identified as reasons for low enrollments in some disciplines (Baloch and Shah 2014; Issa and Nwalo 2008; Jones and Larke 2005).

In Nigeria, Morenikeji and Shaibu (2006) found that only 35.8 percent of the students surveyed purposely chose URP as their life career, 4.7 percent were swayed by their parents; while as much as 59.4 percent enrolled into the course against their wishes. The study further showed that irrespective of how students got into the planning program, 75 percent of them were optimistic about bright prospects in planning as a future profession. Similarly, the research carried out by Al-Hasan et al. (2013) in Nigeria revealed that only 23 percent of the students purposely chose URP as their preferred course of study leading to a life career, whereas 77 percent of the students got into the planning program by chance. According to the study, students who were willing to join public planning organizations or seek a higher degree in planning were 6.5 and 15.8 percent, respectively, whereas 77.7 percent of the students hoped to venture into business or seek employment in other sectors after graduation. From the foregoing, it is obvious that the major reasons that influenced young individuals’ decisions about URP when they applied for university admission need further investigations.

Method of the Study

The study adopted a quantitative technique, using data obtained from a cross-sectional survey. It used a structured questionnaire to elicit information from students enrolled in the undergraduate program of planning schools across Nigeria. It also sought the views of Heads of Department and eighteen lecturers (drawn from the sampled schools) on students’ enrollment trends.

At the time of the survey, seventeen universities spread across the six geopolitical zones in the country offered both undergraduate and postgraduate degrees in URP, while one (University of Ibadan) offered only postgraduate degree. The study used stratified random sampling technique to select nine universities² offering planning, and which had been in existence for at least five years (normal duration for completing the first-degree program in URP in Nigeria) as case studies.

The total population of students in the nine selected universities was 1,849. Out of this, the study selected 550 (29.75%) across the schools to serve as a sample. The researchers personally administered the survey instrument to students in two universities—Ahmadu Bello University, Zaria and the University of Nigeria, Nsukka. For the rest universities, copies of the questionnaire were administered through seven lecturers, who volunteered to serve as field officers in their respective institutions. In line with prescribed instructions, the field officers explained the content of the questionnaire to students to ensure proper completion. The survey yielded 392 (71.27%) valid copies of the questionnaire.

The study used the severity index (SI) method to rate the factors that influenced students’ decisions in choosing URP (to achieve objective 2). SI, as put forward by Al-Hammad and Assaf (1996), is as follows:

SI = \sum_{i = o}^{4} a_{i} x_{i} / 4 \sum_{i = 0}^{4} x_{i} (100 %)

where $a_{i}$ = index of a class; constant expressing the weight given to the class; $x_{i}$ = frequency of response; i = 0, 1, 2, 3, 4 and explained as follows: where $x_{i}$ , $x_{0}$ , $x_{1}$ , $x_{2}$ , $x_{3}$ are the frequencies of a response corresponding to: $a_{0} = 0$ , $a_{1} = 1$ , $a_{2} = 2$ , $a_{3} = 3$ , $a_{4} = 4$ , respectively.

The rating classification is given as follows:

$a_{0}$ = Strongly Disagree (SD) 0.00 ≤ SI < 12.5

$a_{1}$ = Disagree (D) 12.5 ≤ SI < 37.5

$a_{2}$ = Neutral (N) 37.5 ≤ SI < 62.5

$a_{3}$ = Agree (A) 62.5 ≤ SI < 87.5

$a_{4}$ =Strongly Agree (SA) 87.5 ≤ SI < 100.00

The study used Statistical Package for Social Sciences (SPSS) to analyze the raw data. Specifically, it used the chi-square (χ²) analysis and the discriminant analysis methods to verify objectives 3 and 4, respectively.

Results and Findings

Students’ Choice of URP in UTME

The analysis revealed that only 46 percent of the sampled students purposely chose URP as their preferred course of study, whereas 54 percent did not. The latter group got into the program through remedial admission measures. Planning schools often made up for the shortfalls through “course shopping”—relying on admission committees of the respective universities to redirect candidates who were rejected in other programs to URP. Heads of Departments of the nine sampled planning schools and eighteen lecturers randomly interviewed affirmed these remedial measures. Thus, the resulting population of planning students in Nigerian universities comprised individuals with low interest and technical ability, which are essential for the course. This trend does not augur well for the growth of the planning profession in the country.

Determinants of URP as a Career

SI analysis revealed the predominant factors that influenced the decision of all sampled students who chose URP as their preferred course. The factors with their respective SIs include an opportunity to apply skill and knowledge (78.48%), personal interest in URP (76.98%), ability to choose career specialization (76.88%), and the opportunity for advancement (76.42%). The most influencing factors, however, differed along the gender divide. For female students, the principal factors and their corresponding SIs were the ability to choose career specialization (80.11%), opportunity to apply skill and knowledge (77.91%), and the opportunity for advancement (76.63%). The main influencing factors for males were personal interest (79.49%), opportunity to apply skills and knowledge (79.04%), and the opportunity for advancement (76.2%).

For students that did not choose URP as a first choice, the most important factor that restrained them was the lack of awareness of the course. This finding validates the assertion of Gati, Krausz, and Osipow (1996) that dearth of information on career alternatives is one of the issues that limit individuals’ choices. Further analysis showed that 63.8 percent of the students became aware of URP after high school, as against 36.2 percent that had prior knowledge about it.

Duration and Sources of Course Awareness

The chi-square result suggests that there was no significant difference in time of awareness of URP across the zones with a χ² value of 4.77, df (15), p < .05. In other words, the lack of knowledge about URP was a nationwide problem and might be a contributory factor for the students not choosing it as a first choice course in UTME.

The major sources of information about URP were during admission on campus (24%), from parents (21.9%), from UTME brochure (21.4%), and peers/friends (17%). The study used chi-square (χ²) to test whether there was a significant difference in the sources of information about URP across the six zones. The result indicated that there was a significant difference in the sources of information across the six zones, χ² = (44.233), df (35), p > .05. The late awareness of URP notwithstanding, a good proportion of the students (74.5%) hoped to practice the profession after graduation. This finding is in agreement with that made by Morenikeji and Shaibu (2006) but contradicts that of Al-Hasan et al. (2013).

Personal Characteristics, Subject Background, Awareness, and Career Decision

Covariance matrices of discriminant analysis in Table 1 suggest that there is a positive relationship between gender, secondary school subjects, and the decision to choose URP or not. There is, however, a negative relationship between the time of awareness of URP and choosing or not choosing the course (see Table 1).

Table 1.

Covariance Matrices.

Group variable belongs to	Student chose URP	Student did not choose URP
Gender
Student chose URP	0.190	0.042
Student did not choose URP	0.042	0.243
Secondary
Student chose URP	0.873	0.050
Student did not choose URP	0.050	0.919
Awareness
Student chose URP	0.378	−0.009
Student did not choose URP	−0.009	0.291

Note: Gender (Male = 0, Female = 1); Subject Background (Science = 0, Arts = 1, Social Science = 2); Time of Awareness (Primary School = 0, Secondary School = 1, After Secondary School = 2). URP = Urban and Regional Planning.

The analysis yielded an eigenvalue of 1.750 and variance of 99.8 which indicates that the first variate (student chose URP) accounted for 99.8 percent of the variance and the second variate (student did not choose URP) represented only 2 percent. The analysis also had a canonical correlation value of .798 suggesting that there is a strong relationship between choice of URP and the variables. Moreover, the resulting significant Wilks’ lambda and chi-square values, respectively, of .362 and 586.32 and p < .01 show that only the first variate (choice of URP) is significant (see Table 2). The structure matrix suggests that those that chose URP are slightly more important in differentiating the three groups (.792 is greater than .654; see Table 3). The score for gender and secondary school subjects is negative, while that for the time of awareness of URP is positive, signifying that those that chose URP discriminated awareness from the other two groups (notably, gender, because the difference between centroid is greater for these two groups). Not choosing URP that is non-significant seems to discriminate secondary school subjects from the other two groups but not significantly (see Table 4).

Table 2.

Wilks’ Lambda.

Test of function(s)	Wilks’ lambda	Chi-square	df	Significance
1 through 2	.362	586.321	4	.000
2	.996	2.120	1	.145

Table 3.

Structure Matrix.

	Function
	1	2
Student did not choose URP	.792^a	−.610
Students chose URP	.654	.756^a

Note: URP = Urban and Regional Planning.

Largest absolute correlation between each variable and any discriminant function.

Table 4.

Functions at Group Centroids.

Group variable belongs to	Function
Group variable belongs to	1	2
Gender	−1.133	−0.068
Secondary	−0.712	0.079
Awareness	1.855	−0.011

Note: Unstandardized canonical discriminant functions evaluated at group means.

The analysis suggests that the group separation can be explained in terms of one underlying dimension—students’ choice of URP (comprising those that chose URP and those that did not). We can conclude that gender, secondary school subjects, and time of awareness influenced the decision on the choice of URP. From Table 4, we can infer that the most influential factor for choosing the course is the time of awareness.

Discussion

The outcomes of this study have some relationships with existing writings and thoughts on career choices. For instance, low enrollment in the undergraduate planning program was earlier observed by Todes and Harrison (2004) in South Africa. They noted that the enrollment trends were reflections of changing circumstances at the global and local scales. The study showed that young individuals tended to shift to other disciplines they considered to be more focused and marketable.

The predominant factors found to influence the career choices of individuals in this study include an opportunity to apply knowledge and skills, personal interests, ability to choose career specialization, and opportunity for advancement. The finding on “knowledge and skills” confirms earlier work by Amoor and Aliyu (2014) and also underpins the theory of Mitchell and Krumboltz as cited in Amoor and Aliyu (2014, 185). The technical disposition of URP might be a possible explanation for the influence of this factor.

Although an individual’s interest ranked second in this study, it featured more prominently in other studies (Ahmed et al., 2017; Edwards and Quinter 2011; Fatoki 2014; Nyamwange 2016). Previously too, Etiubon, Ugwu, and Ado (2018) had identified “subject area specialization” as a sine qua non for career choices, which is in agreement with one of the findings of this study. Opportunity for career advancement as a predictor of career choice also corroborates the work of Edwards and Quinter (2011). The findings, however, differ from the outcomes of some previous works (like Shumba and Naong 2012; Ulrich, Frey and Ruppert 2018).

Finally, this study revealed that lack of awareness restrained some students from choosing URP when they applied for university admission. Some researches like Baloch and Shah (2014) and Jones and Larke (2005) attested to this, as they showed a positive correlation between information availability and career decision-making. This implies that ignorance is capable of depriving individuals of promising career opportunities. Coupled with the lack of awareness is the issue of poor perception of the planning system and planners by the public (Agbola 2005; Morenikeji and Shaibu 2006). The haphazard developments that characterize Nigerian cities, which largely stem from weak planning systems or unwholesome practices, do not portray planning as an attractive profession (Agbola 2005).

In conclusion, this study showed that a lesser proportion of the students purposely enrolled in URP, whereas majority of the students got into the program by chance. It also revealed that opportunity to supply skills and knowledge, personal interests, and ability to select career specialization were key factors that motivated students that purposely chose URP as a course. On the contrary, lack of awareness was identified as a major restraint to students that did not choose the course across the nation. The analysis also suggested that time of awareness was the most influential determinant of URP career. The study further revealed that personal characteristics (such as gender, secondary school subjects) were important issues that influenced the decision to choose URP or not. The mixed results from previous studies and the present research tend to illustrate the complexities in the career decision process. To be able to generalize on URP career determinants in Africa, further researches are needed.

Footnotes

Acknowledgements

We are grateful to Dr. Victor U. Onyebueke of the University of Nigeria, Nsukka, for his critique of the manuscript. We are also thankful to the lecturers who assisted in administering copies of the questionnaire in seven of the sampled universities.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

David S. Osiyi

Uloma Jiburum

Notes

Author Biographies

David S. Osiyi is a senior lecturer in the Department of Urban and Regional Planning at The Federal Polytechnic, Nasarawa, Nigeria. His research interests include land management, housing, social service delivery, and urban management. He was a postgraduate student at the University of Nigeria, Nsukka, at the time this article was written.

Uloma Jiburum is a reader in the Department of Urban and Regional Planning at the University of Nigeria, Nsukka. Her research interests include environmental management, infrastructure planning, and regional planning.

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