Sustainability consciousness of selected university students in South Africa

Abstract

Purpose

Sustainable development as well as sustainability is desired globally. However, the knowledge and consciousness of people on issues around sustainability remains questionable. Hence, the purpose of this study is to explore the sustainability consciousness (SC) of university students in South Africa.

Design/methodology/approach

Quantitative research methodology was adopted for this study. The sample comprised 1,591 randomly selected students from four South African universities. The data was collected through an online survey. Statistical Package for the Social Sciences was used for analysis.

Findings

The findings of this study showed that there is need to consider country-specific contextual issues when considering factors capable of promoting the SC of students. Also, the incorporation of modules on sustainability has the potency of increasing the SC of students.

Originality/value

This study recommends, amongst others, the need for the revision of the curricula of universities to accommodate topical issues on sustainability that are capable of increasing the consciousness of students on the subject. In addition, pedagogical approaches that enhance sustainability knowledge and action (like green pedagogies) are required.

Citation

Uleanya, C., Ilesanmi, K.D., Yassim, K., Olumuyiwa Omotosho, A. and Kimanzi, M. (2024), "Sustainability consciousness of selected university students in South Africa", International Journal of Sustainability in Higher Education, Vol. 25 No. 9, pp. 505-521. https://doi.org/10.1108/IJSHE-01-2024-0046

Introduction

Sustainability which can be used to mean developments in relation to various spheres of human endeavours like environment, economic growth and social well-being without compromising the need(s) of future generation(s) is a major subject matter. It has attracted the attention of various scholars such as Li and Lei (2023), Ogishima et al. (2023) and Ovais (2023) as well as Berglund et al. (2020) from different regions of the world. This is in an attempt to ensure that the future is preserved for the next sets of generations. Thus, the subject cuts across various disciplines (Mutinda and Liu, 2021).

On the other hand, considering the importance of education to change in the society (Agrawal, 2022; Yuliani and Hartanto, 2017), sustainability consciousness (SC) in institutions of learning becomes paramount. Moreover, during the first, second and third revolutions, education was seen to have played a crucial role (Focacci and Perez, 2022; Penprase, 2018). In other words, education was considered pivotal in conscientising people on the practices and helping them adjust as well to the demands of the eras. Similarly, the works of Carrim (2022) as well as Oke and Fernandes (2020) show that education is a useful tool for helping people acclimatise to the demand and practices of the Fourth Industrial Revolution. By implication, it is deduced that education is paramount in conscientising people on the practices, changes and demands of different eras. Moreover, citing President Nelson Mandela, Almeida (2022) and Nagpal (2023) submit that “education is the most powerful weapon which you can use to change the world”. This implies that, to help make people change to the practices of an era, education is a useful tool. Thus, following reviews of the works of Carrim (2022) and Oke and Fernandes (2020), it can be stated that during the eras of the first, second and third industrial revolutions, education was used to conscientise people and help them adjust to the practices and demands of the eras. The same applies to the fourth industrial revolution. In the context of sustainable development as well as sustainability, education is considered as a major player (Skrefsrud, 2022; Tikly, 2019; Pauw et al., 2015) which has the potential of conscientising people to become aware of the demands and required practices. The foregoing shows the importance of education to individuals and the society in different era. Hence, to ensure SC amongst people, education is important (Purwaningsih et al., 2023). For instance, a sustainable university, one that “apart from seeking academic excellence, tries to embed human values into the fabric of people’s lives; a university that promotes and implements sustainability practices in teaching, research, community outreach, waste and energy management, and land use and planning”, (Nejati and Nejati, 2013, p. 105) is considered pivotal. Moreover, Agenda 21 (UNCED, 1992) had earlier indicated the role of education as important in promoting sustainability by propelling consciousness of all stakeholders, especially students who are future citizens and leaders of any country. This implies that by promoting and encouraging sustainable behaviour and action amongst students, the profile of sustainable university initiatives, providing solutions to sustainability issues, building trust and promoting enriching learning experiences are possible. According to Amaral et al. (2015), the inclusion and promotion of sustainability education in the university curriculum has been slower than desired especially in the non-scientific disciplines. Similarly, the work of Mondragon et al. (2023) suggests that sustainability education is limited, not integrated across programmes and/or faculties. Meanwhile, individuals need to be sensitised and involved through effective multi-disciplinary approaches that connects social, economic and environmental environments (Ditlhake, 2022; Edwards, 2019). Moreover, as a conduit and custodian of social development, universities have a responsibility to develop future leaders and, in the promotion, of sustainability awareness towards action (Žalėnienė and Pereira, 2021).

From an African perspective, Akrofi et al. (2019) hold the view that knowledge plays a pivotal role in enhancing the SC of students. In the South African context, Irlam et al. (2023) as well as Matiwaza and Boodhoo (2020) consider institutions of learning as a major outlet for ensuring SC, especially for students. Ovais (2023) shows that sustainability behaviour amongst university students from India is impacted more by sustainability attitude as compared to sustainability knowledge. Similarly, the sustainability knowledge of students is higher than their sustainability attitude and behaviour (Ovais, 2023). Also, the work of Ovais (2023) showed that in the context of India, sustainability behaviour can be driven by economic concerns. However, the study of Ovais (2023) only focused on the responses of undergraduates, leaving out postgraduates.

Meanwhile, Gericke et al. (2019) had earlier conducted a similar study using the context of students within the age range of 18–19 years studying in Sweden. According to Gericke et al. (2019), in exploring the SC of people, there is need to take into account the knowingness, attitudes, behaviour, economic, social and environmental ideology of the individuals. Thus, Gericke et al. (2019) in an attempt to establish a standardised questionnaire for measuring the SC of people considered the following: K = knowingness; A = attitudes; B = behaviour; ECO = economic; SOC = social; and ENV = environmental (p. 9). However, the authors disclosed that there is need for users of the questionnaires to take into account that the questionnaire was designed using a western Swedish context. Also, issues revolving around rural and economic development were excluded based on the notion that they are “considered to be exclusively situated in a developing country context in the UNESCO definition” (Gericke et al., 2019, p. 5). Thus, in this present study, the SC of students in selected South African universities were investigated. This was done by adapting the questionnaire designed by Gericke et al. (2019) while taking into account the context of South Africa.

This study is guided by the research question:

RQ1.

What is the sustainability consciousness of selected university students in South Africa?

Attempt was made at proffering answer to the research question while taking cognisance of the following as highlighted by Gericke et al. (2019): K = knowingness; A = attitudes; B = behaviour; ECO = economic; SOC = social; and ENV = environmental. Meanwhile, Ovais (2023) posits that sustainability attitude and knowledge do not transform into sustainability behaviour to bring about the basis for attaining sustainable development. Similarly, with regards to SC, Ovais (2023) defines it as “a person’s awareness of the environment as well as the experience or knowledge of sustainable facts and events, including thoughts, feelings, and behaviours” (P. 14). In this study, SC implies the awareness of people in relation to developments related to different spheres of human beings such as social well-being, economic growth and environment without compromising the need(s) of future generation(s).

Methodology

A quantitative research method was adopted for this study. This was based on the submission of Kumar (2019) and Creswell (2014) who support that quantitative method allows for the collection of large data which can aid generalisation of results. The study was conducted using four selected universities in South Africa. The four selected universities comprised both rural and urban as well as those that offer contact and distance education. The universities were conveniently selected. Edgar and Manz (2017) submit that convenient sampling gives researchers the opportunity to select based on their convenience. The use of convenient sampling in selecting the universities was based on the possibility of the researchers being able to access the universities easily as long as they were either urban or rural and whether they offer contact or distance learning. Also, the four selected institutions of higher learning adopted for this study were used to cater for the different categories of universities in South Africa. In this regard, rural, urban as well as open and distance learning-based universities were represented. Additionally, the researchers ensured that the selected universities were from different provinces in the nation. This allowed for representation of three provinces in the study. Meanwhile, the open and distance university selected in this study has campuses which caters for students across all the nine provinces in the nation.

Instrument and administration

A 27-item Sustainability Consciousness Questionnaire designed by Gericke et al. (2019) to measure university stakeholder’s environmental, social and economic knowingness, attitudes and behaviour was adapted. The questionnaire was adapted for this study because of the various dimensions covered by the items. For instance, the questionnaire covered dimensions of social, economic and environmental which are critical to this study; hence, it was worthwhile to adapt it though it was originally designed using a western, first world context, namely, Sweden. Also, the questionnaire was adapted in this study because the specific items of each of the dimensions were also considered useful. However, because South Africa has certain issues peculiar to its context which differs from Sweden, a new section was included. For instance, an issue such as load shedding does not apply to the Swedish context though it exists in South Africa. Also, the authors believe that rural areas in the South African context differ from Sweden. Hence, the researchers of this present study saw the need to add a second section to the Gericke et al. (2019) questionnaire to accommodate the context of South Africa. To this end, the questionnaire was designed to have three sections. Section 1 was targeted at retrieving biographic information of respondents. Section 2 was used to retrieve information on students’ SC using Gericke et al’s. (2019) shortened questionnaire. Section 3 was designed using sustainability issues in South Africa/Africa and included some open-ended questions to solicit respondent views and experiences that might have not been included in the survey instrument. A five-point Likert scale of Strongly Disagree (SD), Disagree (D), Neutral (N), Agree (A) and Strongly Agree (SA) was used in both the second and third sections.

The questionnaire was administered to the students through an online mode using survey monkey. The generated link was shared on university platforms offering all students in the four selected institutions an equal opportunity to participate. This was based on the nature of the study which cuts across all students in the selected universities. Thus, all the students in the four selected universities had equal opportunity to participate. This was in an attempt to avoid bias. To encourage student participation, lecturers were requested to also advertise the link on their learning management systems through announcements in their course modules. Suffice to state that the respondents self-selected. Meanwhile, for the purpose of the respondents being self-selected, the researchers took extra measures to avoid bias. Hence, large sample size was recruited to help in increasing the sample’s diversity and reduce the impact of outliers following the notion from the review of Kaplan et al. (2014) which indicates that large sample size is representative of the population.

Data analysis

This study used a binomial logistic regression estimation technique to examine the SC of selected students in the majority world. Binomial logistic regression is used to predict the probability of the dependent variable (SC) which is dichotomous and dependent variables which can either be dichotomous or continuous. The mathematical representation of binomial logistic regression is given in equation (1):

$$P\left(Y\right)=\frac{e^{{\beta }_0+{\beta }_1{X}_1+{\beta }_2{X}_2+\dots +{\beta }_k{X}_k}}{1+e^{{\beta }_0+{\beta }_1{X}_1+{\beta }_2{X}_2+\dots +{\beta }_k{X}_k}}$$

where

P = is the probability of Y occurring;

e = is the natural log base;

β_0 = is the intercept;

β_1-β_k = regression coefficient; and

X_1-X_k = independent/predictor variables.

This study used a modified version of Gericke et al. (2019) theoretical model of SC. The model consists of main variables which include SOC, ECO and ENV dimensions of SC. These three variables have three sub-categories, each of which includes sustainability knowingness (k), sustainability attitude (a) and sustainability behaviour (b). The models explored the impact of the three dimensions (social, economic and environmental) on the students’ SC. This is represented mathematically as follows:

(1)

SC is sustainability consciousness, Soc is the social dimension, Eco is the economic dimension, Env is the environmental dimension, CS_i represents the country-specific items, X_i represents other control variables and k, a and b represent all the items under each dimension including the country-specific items (Table 1). The baseline model includes the items as adapted from the study of Gericke et al. (2019), while in Model 2, the authors included the country-specific factors. For Models 3–6, the authors included variables which measure different interventions by the university stakeholders to see the possible effect on the level of SC amongst university students. The question “Have you heard of Sustainable Development?” (SC) was used as the dependent variable, while the list of questions for the independent variable consists of 26 items which are categorised as one of the environments, economic and social dimensions. The authors also control for country-specific items. This study drew a total of 1,591 respondents from four universities across South Africa who participated in the survey. It must be noted that the analysis was divided into three sections which include the environment, economic and social dimensions. Amongst these factors are issues bordering around social, economic and environmental matters in the context of the nation. For instance, the survey attempted to retrieve information on access to electricity, engagement in topical environmental sustainability promoting issues, access to internet and information on water sustainability, amongst others which are contemporary challenges facing the nation. For each subsection, six models were estimated.

Table 1 presents the definition of variables as used in this study.

The demographic information of respondents is presented in Tables 24 which show the distribution of respondents according to age, gender, status or level of qualification of the respondents.

The results as presented in Table 2 indicate age bracket of respondents.

Table 3 presents the gender of respondents.

Table 4 presents the study level of the students. It must be stated that fourth year was included because while most of the undergraduate degrees in South Africa are three years, education degree is a four-year programme. Thus, the inclusion of fourth year was to cater for such students.

Ethical consideration

In this study, issues of ethics were taken into account. Hence, details of all four selected universities were withheld. Similarly, the details of the respondents were left anonymous. Also, following the submissions of Creswell (2014) and Saunders et al. (2009), the respondents were made to know that their participation was voluntary and they had the right to withdraw at any time. Confidentiality and anonymity were also ensured.

Findings and discussion

The findings of this study are presented using the three identified dimensions, namely: social, economic and environmental.

Social dimensions

This finding of the study presents six estimated models for the social dimension. The based model (Model 1) examined the influence of social dimension of sustainability factors on the students’ level of consciousness in South Africa. Models 2–6 accounted for the country-specific effects and other moderating variables which included their level of awareness. For instance, respondents were asked the question whether they have heard of sustainable development? Knowledge intervention question such as whether they have had module(s) with core focus on sustainable development was asked. Also, project intervention question like students having had any university project(s) with core focus on sustainable development was asked. Similarly, question on extra-curricular intervention was asked. Thus, respondents were asked whether they have had any extra-curricular activity(s) with core focus on sustainable development. These were very important for us to identify specific factors that contribute significantly to the level of SC amongst the selected university students. Table 5 presents the analysis of data collected for social dimension items.

The logit coefficients are in log-odds units and cannot be interpreted as regular Ordinary Least Squares regression (OLS) coefficients. To interpret the coefficients, the odd ratios were estimated and discussed. The Prob > Chi² is used to test whether all the coefficients in the model are different than zero. The decision rule is if Prob > Chi² < 0.05, then the authors can conclude that the models have some relevant explanatory power. In this case, the likelihood ratio chi-square of 40.302, 109.83, 382.133, 180.644, 165.86 and 412.059 for Models 1–6, respectively, and Prob > Chi² for the six models are less than 0.05. It is, therefore, concluded that the models have some relevant explanatory power. Looking at the Pseudo R² for the six models estimated which ranges between 0.018 and 0.209, the authors can say that there are other social dimensional factors that affect students’ SC which have not been accounted for in the model. However, it must be noted that this is quite different from the R² of the OLS regression which is used to measure the proportion of variance in the dependent variable. Specifically, Model 1 was estimated to test the proposition of Gericke et al. (2019). This was based on the fact that the questionnaire of Gericke et al. (2019) cannot be relied upon wholly without considering other country-specific factors that influence the SC of people. The result as presented in Table 5 indicates that only knowledge factor 2 and attitude factor 1 of the social dimension significantly influenced the students’ SC. It is also clear that these two factors (knowledge factor 2 and attitude factor 1) are significant across the six models at either the 1% or 5% significance level. This finding corroborates the work of Mohammadi et al. (2023), who consider sustainability knowledge and attitude as being significant.

However, in Models 2–6 (Table 5), which accounts for the moderating effects of country-specific factors and other possible interventions, the result indicates that country-specific factors identified as soccs3, soccs4 and soccs5 significantly influence students’ level of SC. This is because the p-values for soccs3, soccs4 and soccs5 are less than 0.01, 0.05 and 0.01, respectively, except for Model 5 where soccs4 was significant at 10% level of significance. With respect to soccs3 and soccs4 in Model 2, the odds of the SC (strongly agree and agree) compared to the other categories are 1.529 and 1.133 higher for students respectively given that all of the other variables in the model are held constant. This implies that the likelihood of the students being more sustainability conscious is higher when they have adequate skills to promote sustainability practices. Meanwhile, the students have internet connectivity to perform duties related to sustainability. Furthermore, when the authors controlled for different possible interventions (Models 3, 5 and 6), it was revealed that in addition to soccs3, soccs4 and soccs5 which were significant across Models 2–6, the results indicate that soccs1 does statistically influence the SC of students. For example, in Model 3, the authors controlled for the introduction of a module on sustainability and examined its impact on the level of SC of students.

Our findings indicate that educating students by incorporating sustainability related module have significant influence on the SC of students in the selected South African universities. Specifically, the result indicates that the odds of the SC of students who have undertaken a module related to sustainability are 0.083 higher compared to the other categories given that all the other variables in the model are held constant. This finding is in line with the views of Skrefsrud (2022), Tikly (2019) and Pauw et al. (2015), who opined that education plays a major role in conscientising people to become aware of the demands and required practices. In Models 4 and 5, the moderating effects of university project and extra-curricular activity related to sustainability on students’ level of SC were presented. Our findings revealed that the odds of the SC of students who have taken part in a university project or extracurricular activity related to sustainability are 0.104 and 0.093 higher when compared to those who have not. This is based on all other variables in the model being held constant.

Furthermore, Model 6 tested for the joint moderating effects of the introduction of a module, a university project and extra-curricular activity related to sustainability on their level of SC, respectively. The result as presented in Table 5 indicates that all the three variables are significant at 1% and 5% significance level. This implies that the likelihood of the students being more sustainability conscious is higher when they are educated on sustainability practices either through a module or a university project or an extracurricular activity. This is dependent on all the three moderating variables being included in the model.

Economic dimensions

In the case of economic dimensions, the likelihood ratio chi-square of 66.268, 98.876, 380.981, 172.204, 155.651 and 413,882 for Models 1–6, respectively, and Prob > Chi² for the six models are less than 0.05. It is, therefore, concluded that the models have some relevant explanatory power. Moreover, the pseudo R² for the six estimated models ranged between 0.03 and 0.21.

This implies that there are other economic dimensional factors that students’ SC which have not been accounted for in the model. The result as presented in Table 6 indicates that majorly, only knowledge factor 1 and attitude factor 6 of the economic dimension significantly influence the students’ SC. It is also clear that these two factors (knowledge factor 1 and attitude factor 6) are significant across the six models at the 1% significance level. However, in Models 2–6 (Table 6), when other moderating variables were introduced, some other factors were found to significantly influence the SC of students. Table 6 presents the analysis of data collected for items on economic dimension.

Specifically, when the country-specific factors were introduced in Model 2 and the different possible interventions (Models 3, 5 and 6), the result indicates that country-specific factors such as ecocs1 and ecocs3 significantly influence students’ level of SC. This is because the p-values for ecocs1 and ecocs3 are less than 0.01. With respect to ecocs1 and ecocs3 in Model 2, the odds of the SC (strongly agree and agree) compared to the other categories are 1.322 and 0.834 higher for students, respectively. This is, however, on the condition that all of the other variables in the model are held constant. This implies that the likelihood of the students being more sustainability conscious is higher when they are exposed to topical subjects on the development of innovation skills and have access to resources to perform sustainability practices. Moreover, innovation skills are the cornerstones of sustainable economic growth. It must also be noted that knowledge factor 2 and attitude factor 4 significantly influence the students’ level of SC. This is in addition to the knowledge factor 1 and attitude factor 3 being significant across the six models. This finding indicates that poverty reduction and the responsible actions of companies towards their employees, customers and suppliers can significantly influence the level of SC of people.

Furthermore, in Model 3, the authors controlled the introduction of a module on sustainability and examined its impact on the level of SC of students. Our findings indicate that educating students by incorporating sustainability-related module has significant influence on the SC of students. This finding coincides with the works of scholars such as Lafuente-Lechuga et al. (2024), García-Planas (2018) and Sammalisto, Sundström and Holm (2015), who support the need for the inclusion of courses capable of enhancing and increasing the SC of students.

Specifically, the result indicates that the odds of the SC of students who have undertaken a module related to sustainability are 0.082 higher when compared to the other categories given that all the other variables in the model are held constant. This is similar to the findings under the social dimension. The inverse of the odds ratio equals 12.196. This implies that there is a 12.196 times higher chance that a student will not be sustainability conscious when there are no modules related to sustainability development being undertaken by the students.

Environmental dimensions

In the case of environmental dimension, the likelihood ratio chi-square of 100.148, 103.124, 376.962, 179.059, 156.877 and 409.653 for Models 1–6, respectively, and Prob > Chi² for the six models are less than 0.05. The authors can, therefore, conclude that the models have some relevant explanatory power. Furthermore, the pseudo R² for the six estimated models ranged between 0.046 and 0.208. The findings are similar to the other dimensions, as the result indicates that there are other environmental dimensional factors that students’ SC which have not been accounted for in the model. Table 7 presents the analysis of data collected for items on environmental dimension.

The result presented in Table 7 indicates that in Model 1, students’ SC are significantly influenced by knowledge factor 1, 3, attitude factor 4, 6 and behavioural factor 7 of the environmental dimension. This is because their p-values are less than 0.01, 0.10, 0.01, 0.10 and 0.05. With respect to knowledge factor 1, 3, attitude factor 4, 6 and behavioural factor in Model 1, the odds of the SC (strongly agree and agree) compared to the other categories are 1.488, 0.867, 1.243, 1.184 and 0.862 higher for students. This is given that all of the other variables in the model are held constant. The result indicates that preserving biological diversity and educating people on how to protect themselves against natural disasters can significantly influence their SC. This implies that knowledge is important in raising SC. Furthermore, the result revealed that attitude and behaviour that focus on proper use of natural resources, taking measures against problems that impact climate change and changing personal lifestyle like throwing away less food or not wasting materials significantly influence the level of SC.

However, unlike the social and economic dimensions, in Models 2–6 (Table 7), when other moderating variables were introduced, there was not much improvement in the models. This implies that while some items of knowledge, attitude and behavioural factors of the environmental dimension influence significantly the SC of students, others do not.

Precisely, when the country-specific factors were introduced in Model 2 and the different possible interventions (Models 3, 4, 5 and 6), the result indicates that only country-specific factors such as envcs5 significantly influence students’ level of SC across the models except Model 3. This is because the p-values for envsc5 is less than 0.01 in Models 2 and 6 and 0.10 in Models 4 and 5, respectively. This implies that engaging in topical issues promoting environmental sustainability influence students’ level of consciousness. For example, in Model 2, the odds of the SC (strongly agree and agree) compared to the other categories is 1.231 higher for students. This is subject to all other variables in the model being held constant. In this regard, the inverse of the odds ratio equals 0.812. By implication, there is a 0.812 times higher chance of students not being sustainability conscious when they do not engage in topical issues that promote environmental sustainability.

Furthermore, in Models 3–6, our findings indicate that educating students by incorporating sustainability related module, university project and extra-curricular activity related to sustainability development have significant influence on their environmental SC. Specifically, the result indicates that the odds of the SC of students who have undertaken a module related to sustainability, involved in a university project and extra-curricular activity are 0.084, 0.099 and 0.10 higher when compared to the other categories. This is given that all the other variables in the model are held constant. This finding of the study corroborates the works of Lafuente-Lechuga et al. (2024) and Mohammadi et al. (2023), who support the need for the curricula to be designed in a manner that topical and relevant sustainability issues are incorporated. Lafuente-Lechuga et al. (2024) add that the need for training targeted at promoting sustainability is paramount.

Conclusion and recommendations

When relating to the subject of sustainability, there is need to take country-specific contextual issues into consideration. In other words, matters of sustainability are not to be addressed using the common cliché – “one size fits all”. Also, it is noteworthy that student SC is significantly influenced by economic. This is because poor socio-economic experiences and the need to survive offer poor students less options and resources for sustainability consideration. This is, however, with the exception of the recycling practice. This is attributed to the notion that re-use, re-sale and re-purpose are all part of cost-saving measures amongst poorer students. Thus, the motivation for re-use tilts more towards lack or unaffordability of new items than to sustainability. Nevertheless, students unintentionally recycling items regardless of the reason are contributing positively to sustainability. Therefore, linking sustainability solutions to the economy and poverty reduction is of particular interest to South African students in the selected universities. Hence, it should be supported. Additionally, in terms of knowledge and attitude factors of the social dimension, students tend to be sustainability conscious. Moreover, environmental knowledge and attitude factors significantly influence students’ SC than behavioural factors. Meanwhile, students’ non-engagement in sustainability topical issues, as well as the non-inclusion of sustainability-related modules in the curricula, limits SC.

In brief, students’ SC tends to be high based on knowledge and attitude, but in practice, action is limited. Sequel to the findings of the study, the following recommendations are made:

• The curricula of South African higher institutions of learning and by extension, the majority world should be designed to accommodate and promote SC by including topical subjects targeted at promoting SC. This is envisaged to aid the education system of the nation to be more explicit in how it could address the perceived shortfall in the understanding of sustainability.

• Regular and periodic orientation programmes aimed at ensuring SC should be organised for university students. This can be done at the level of faculty and/or department as well as university wide as part of extra-curricular activities.

Limitation and suggestion for further study

The data used for this study was collected from only four participating universities in South Africa. Hence, findings may not be generalizable to institutions with different settings and features. It is, therefore, suggested that similar study be conducted using two or more countries or regions in the majority world. Also, additional variables where possible and available can be investigated in the different highlighted dimensions. Additionally, how education could be more explicit in how South Africa and other nations with similar features could address the perceived shortfall in understanding of sustainability is suggested for further study.

Table 1.

Definition of variables

Category	Dependent variable
SC	Sustainability consciousness
	Independent variables
	Social dimension
Sock1	Social dimension (Knowledge 1)
Sock2	Social dimension (Knowledge 2)
Sock3	Social dimension (Knowledge 3)
Soca4	Social dimension (Attitude 1)
Soca5	Social dimension (Attitude 2)
Soca6	Social dimension (Attitude 3)
Socb7	Social dimension (Behaviour 1)
Soccs1	Social dimension (Country-specific item 1)
Soccs2	Social dimension (Country-specific item 2)
Soccs3	Social dimension (Country-specific item 3)
Soccs4	Social dimension (Country-specific item 4)
Soccs5	Social dimension (Country-specific item 5)
	Economic dimension
Ecok1	Social dimension (Knowledge 1)
Ecok2	Social dimension (Knowledge 2)
Ecok3	Social dimension (Knowledge 3)
Ecoa4	Social dimension (Attitude 1)
Ecoa5	Social dimension (Attitude 2)
Ecoa6	Social dimension (Attitude 3)
Ecob7	Social dimension (Behaviour 1)
Ecocs1	Social dimension (Country-specific item 1)
Ecocs2	Social dimension (Country-specific item 2)
Ecocs3	Social dimension (Country-specific item 3)
Ecocs4	Social dimension (Country-specific item 4)
Ecocs5	Social dimension (Country-specific item 5)
	environmental dimension
Envk1	Social dimension (Knowledge 1)
Envk2	Social dimension (Knowledge 2)
Envk3	Social dimension (Knowledge 3)
Enva4	Social dimension (Attitude 1)
Enva5	Social dimension (Attitude 2)
Enva6	Social dimension (Attitude 3)
Envb7	Social dimension (Behaviour 1)
Envcs1	Social dimension (Country-specific item 1)
Envcs2	Social dimension (Country-specific item 2)
Envcs3	Social dimension (Country-specific item 3)
Envcs4	Social dimension (Country-specific item 4)
Envcs5	Social dimension (Country-specific item 5)
	Other control variables
Module	Have you had any module(s) with a core focus on sustainable development?
Project	Have you had any university project(s) with the core focus being on sustainable development?
Extra-cur	Have you had any extra-curricular activity(s) with the core focus being on sustainable development?

Source: Authors’ own creation

Table 2.

Age of respondents

Category	Frequency	%	Cumulative %
20 years or younger	232	14.6	14.6
21–24 years	341	21.4	36.0
25–30 years	381	23.9	60.0
31 years or older	637	40.0	100.0
Total	1,591	100.0

Source: Authors’ own creation

Table 3.

Gender of respondents

Category	Frequency	%	Cumulative %
Male	556	34.9	34.9
Female	1,014	63.7	98.7
Non-binary	9	0.6	99.2
Prefer not to state	12	0.8	100.0
Total	1,591	100.0

Source: Authors’ own creation

Table 4.

Status/level of students

Level	Frequency	%	Cumulative %
First year undergraduate	727	45.7	45.7
Second–fourth year undergraduate	550	34.6	80.3
Honours/BTech honours student	115	7.2	87.5
Masters/MTech student	63	4.0	91.5
PhD student	36	2.3	93.8
Other (please specify)	99	6.3	100.0
Total	1,591	100.0

Source: Authors’ own creation

Table 5.

Binary logic regression analysis (social dimension)

Category	(1)	(2)	(3)	(4)	(5)	(6)
	SC	SC	SC	SC	SC	SC
Sock1	1.000 (0.066)	0.976 (0.07)	1.068 (0.088)	0.989 (0.074)	0.943 (0.069)	1.029 (0.087)
Sock2	1.312*** (0.103)	1.345*** (0.115)	1.247** (0.117)	1.31*** (0.114)	1.346*** (0.117)	1.244** (0.118)
Sock3	0.89 (0.076)	0.89 (0.083)	0.885 (0.091)	0.908 (0.087)	0.914 (0.087)	0.919 (0.096)
Soca4	1.199*** (0.075)	1.194*** (0.08)	1.2** (0.089)	1.218*** (0.084)	1.18** (0.08)	1.197** (0.09)
Soca5	1.009 (0.081)	1.009 (0.086)	0.989 (0.093)	1.016 (0.089)	1.032 (0.09)	1.007 (0.095)
Soca6	1.054 (0.101)	0.973 (0.101)	0.979 (0.111)	0.971 (0.104)	0.972 (0.103)	0.98 (0.112)
Socb7	1.063 (0.059)	1.018 (0.062)	0.979 (0.066)	1.013 (0.063)	1.000 (0.062)	0.972 (0.066)
Soccs1		0.883 (0.067)	0.864* (0.071)	0.899 (0.07)	0.877* (0.068)	0.856* (0.072)
Soccs2		0.946 (0.058)	0.923 (0.062)	0.924 (0.058)	0.933 (0.058)	0.92 (0.063)
Soccs3		1.529*** (0.103)	1.392*** (0.103)	1.446*** (0.099)	1.499*** (0.103)	1.367*** (0.102)
Soccs4		1.133** (0.071)	1.182** (0.083)	1.133* (0.073)	1.14** (0.073)	1.18** (0.083)
Soccs5		0.838*** (0.043)	0.812*** (0.046)	0.831*** (0.044)	0.846*** (0.044)	0.823*** (0.048)
Module			0.083 (0.015)			0.103*** (0.019)
Project				0.104*** (0.036)		0.414** (0.157)
Extra-cur					0.096*** (0.039)	0.193*** (0.085)
Constant	0.214*** (0.078)	0.132*** (0.057)	20.404*** (11.827)	11.93*** (9.63)	15.241*** (13.971)	2023.342*** (2436.014)
Observations	1,583	1,583	1,583	1,583	1,583	1,583
Pseudo R2	0.018	0.055	0.194 382.133	0.091	0.084	0.209 412.059
LR chi2(6)	40.302	109.830	0.0000	180.644	165.860	0.0000
Prob > chi2	0.0000	0.0000		0.0000	0.0000

Notes:

Standard errors are in parentheses; ***p < 0.01, **p < 0.05 and *p < 0.1

Source: Authors’ own creation

Table 6.

Binary logic regression analysis (economic dimension)

Category	(1)	(2)	(3)	(4)	(5)	(6)
	SC	SC	SC	SC	SC	SC
ecok1	1.247*** (0.099)	1.319*** (0.115)	1.332*** (0.129)	1.32*** (0.118)	1.319*** (0.117)	1.338*** (0.131)
ecok2	1.149 (0.109)	1.184* (0.121)	1.179 (0.133)	1.204* (0.125)	1.193* (0.123)	1.179 (0.135)
ecok3	1.037 (0.092)	1.008 (0.097)	0.907 (0.096)	0.984 (0.096)	1.003 (0.098)	0.922 (0.099)
ecoa4	0.883 (0.08)	0.805** (0.082)	0.84 (0.095)	0.825* (0.086)	0.82* (0.085)	0.863 (0.098)
ecoa5	1.001 (0.069)	1.019 (0.076)	1.029 (0.085)	1.054 (0.081)	1.024 (0.078)	1.025 (0.086)
ecoa6	1.29*** (0.086)	1.273*** (0.089)	1.306*** (0.103)	1.226*** (0.088)	1.243*** (0.089)	1.274*** (0.102)
ecob7	0.936 (0.061)	0.903 (0.064)	0.918 (0.071)	0.903 (0.065)	0.891 (0.064)	0.911 (0.071)
ecocs1		1.322*** (0.083)	1.158** (0.081)	1.266*** (0.082)	1.274*** (0.082)	1.13* (0.08)
ecocs2		1.018 (0.071)	1.064 (0.081)	1.002 (0.071)	1.004 (0.071)	1.039 (0.08)
ecocs3		0.834*** (0.051)	0.808*** (0.054)	0.838*** (0.053)	0.821*** (0.052)	0.801*** (0.055)
ecocs4		1.000 (0.06)	0.985 (0.065)	0.99 (0.061)	0.992 (0.061)	0.996 (0.067)
ecocs5		1.08 (0.066)	1.08 (0.073)	1.076 (0.068)	1.099 (0.069)	1.088 (0.075)
Module			0.082*** (0.015)			0.10*** (0.018)
Project				0.103*** (0.035)		0.388** (0.149)
Extra-cur					0.097*** (0.039)	0.191*** (0.083)
Constant	0.123*** (0.048)	0.111*** (0.048)	15.615*** (9.179)	10.686*** (8.68)	13.506*** (12.477)	1894.938*** (2294.041)
Observations	1,583	1,583	1,583	1,583	1,583	1,583
Pseudo R2	0.030	0.050	0.193	0.087	0.079	0.210
LR chi2(6)	66.268	98.876	380.981	172.204	155.651	413.882
Prob > chi2	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000

Notes:

Standard errors are in parentheses; ***p < 0.01, **p < 0.05 and *p < 0.1

Source: Authors’ own creation

Table 7.

Binary logic regression analysis (environmental dimension)

Category	(1)	(2)	(3)	(4)	(5)	(6)
	SC	SC	SC	SC	SC	SC
envk1	1.488*** (0.113)	1.379*** (0.109)	1.301*** (0.114)	1.399*** (0.114)	1.338 (0.107)	1.277 (0.113)
envk2	1.048 (0.052)	1.04 (0.055)	0.996 (0.058)	1.016 (0.055)	1.034 (0.055)	0.985 (0.058)
envk3	0.867* (0.065)	0.867* (0.069)	0.908 (0.079)	0.87* (0.071)	0.864 (0.07)	0.916 (0.081)
enva4	1.243*** (0.074)	1.268*** (0.08)	1.285*** (0.091)	1.253*** (0.081)	1.25 (0.08)	1.265 (0.09)
enva5	1.008 (0.084)	1.001 (0.088)	1.072 (0.107)	1.031 (0.093)	1.048 (0.094)	1.121 (0.114)
enva6	1.184* (0.104)	1.17* (0.11)	1.118 (0.115)	1.18* (0.114)	1.172 (0.112)	1.126 (0.118)
envb7	0.862** (0.064)	0.884 (0.069)	0.875 (0.074)	0.876* (0.069)	0.888 (0.071)	0.872 (0.075)
envb8	1.1 (0.071)	1.031 (0.072)	1.042 (0.079)	1.017 (0.072)	1.025 (0.072)	1.035 (0.08)
envb9	0.934 (0.052)	0.898* (0.055)	0.919 (0.062)	0.913 (0.057)	0.91 (0.057)	0.942 (0.064)
envcs1		1.059 (0.077)	1.031 (0.083)	1.042 (0.078)	1.042 (0.076)	1.033 (0.084)
envcs2		0.975 (0.075)	0.975 (0.083)	0.946 (0.074)	0.989 (0.077)	0.976 (0.084)
envcs3		1.019 (0.081)	1.004 (0.088)	1.054 (0.086)	1.034 (0.084)	1.01 (0.09)
envcs4		1.024 (0.052)	1.02 (0.058)	1.039 (0.055)	1.023 (0.053)	1.022 (0.059)
envcs5		1.231*** (0.094)	1.138 (0.096)	1.154* (0.091)	1.158 (0.09)	1.084 (0.093)
Module			0.084*** (0.015)			0.104 (0.019)
Project				0.099*** (0.034)		0.357 (0.135)
Extra-cur					0.10 (0.041)	0.211 (0.091)
Constant	0.098*** (0.036)	0.072*** (0.029)	8.998*** (4.873)	7.322** (5.777)	7.516** (16.739)	966.805*** (1134.988)
Observations	1,583	1,583	1,583	1,583	1,583	1,583
Pseudo R2	0.046	0.052	0.191	0.091	0.079	0.208
LR chi2(6)	100.148	103.124	376.962	179.059	156.877	409.653
Prob > chi2	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000

Notes:

Standard errors are in parentheses; ***p < 0.01, **p < 0.05 and *p < 0.1

Source: Authors’ own creation