Exploring the link between generations and environmental literacy among peruvian individuals aged 11 years and older, currently enrolled in school or having graduated

Environmental education (EE), as per SDG 4.7, is “a process that allows individuals to explore environmental issues, engage in problem-solving, and take action to improve the environment.” By instilling vital knowledge, skills, values, and attitudes, it empowers individuals to be “change agents for sustainable development.”

 

Unfortunately, EE — crucial to reducing human-driven environmental impacts—is lacking in society. As UNESCO (2023) warned, “only half of the national curricula in the world have a reference to climate change,” something concerning considering that environmental issues, such as this one, are affecting everyone worldwide. Therefore, if no awareness is created about these escalating problems, there might not be a future ahead.

 

Part of the problem also lies in the lack of class time, support, and teachers with adequate backgrounds on the subject (Ham & Sewing, 1988). Thus, as Nijhuis (2011) states, it cannot keep up with the rate of environmental deterioration and the effects of human activity on the environment. Moreover, even where EE is taught, it often fails to impact students' attitudes, as they are not living its impacts just yet.

 

Specifically in Peru, a large portion of its environmental issues are consequences of the population's lack of awareness in this matter. However, insufficient studies exist to determine the national EE level. Conducting such research could guide the development of a more effective EE system, which, in turn, would play a crucial role in increasing the level of EE in the most polluted country in the American continent and the 12th most polluted country globally, as reported by Numbeo (2023). This would not only foster awareness among citizens about their environmental impact but also enhance their eco-friendly practices. Additionally, it could help preserve the 5th most biodiverse country in the world (Butler, 2016), where studies show that because of global warming, it is already too warm for some species to survive.

 

Hence, it is of utmost importance to analyze the relationship between EE levels and generations to assess the effectiveness of its implementation in Peru over time. This will be valuable as all the analyzed generation groups have experienced the evolving EE standards in Peru, leading to variations in how it has been taught and its impact on each generation. Thus, this investigation will allow an identification of the generations in most need of EE.

To what extent is there a correlation between generations and the environmental literacy (in terms of knowledge, attitudes, and practices) of a group of Peruvian individuals aged 11 years and above, currently in school or having already graduated?

It is hypothesized that the younger the generation, the higher the level of environmental education. This is due to the rising global environmental concerns which have driven the implementation of new EE programs.

• Google Forms
• Google Sheets
• Computer

• A computer was used to create a Google Form, a platform compatible with various devices and capable of handling unlimited responses.
• A question regarding age and 14 multiple-answer questions based on previous EE questionnaires were created in Spanish, the primary language of Peruvians, to ensure all respondents could understand.
• These questions were divided into four sections, each to collect information about the level of EE in different aspects -
  • Age
  • Knowledge

• Questions were teacher-validated and pilot-tested.
• The survey was sent via WhatsApp and email, as this was a quick and effective method to gather a minimum of 30 respondents per generation group while sending it only to individuals who adhered to the control variables.
• Google Sheets was used to process the data.
• To facilitate data interpretation and mitigate sample size disparities, percentages were utilized for clearer visualization of responses.

The survey included confidential disclosure and informed consent in the introduction to comply with Peru’s Data Protection Law. Participation was voluntary, and participants were informed that their responses would be used purely for an investigation and would not be published publicly. The survey also maintained anonymity by not requesting names or emails.

The first five questions were grouped into Figure 27, Figure 15 and 16 were averaged and grouped into Figure 5, and the four practices evaluated in Figure 18 and 22 were also averaged and grouped into Figures 7 and 8. All other questions were evaluated individually, and Figure 12 was excluded due to lack of relevance to the research question.

 

Moreover, statistical tests were evaluated with the conventional 0.05 significance level, where the following conclusions could be reached -

Specifically, a Kruskal-Wallis Test for the Likert Scale questions was carried out using an online test calculator. The other remaining questions, qualitative in nature, were evaluated with the Chi - Square Test of Independence, also using an online test calculator.

Regarding environmental knowledge, Figure 27 shows that “Baby Boomers + Silent Generation” had the highest values while “Generation Z” scored the lowest (27.89%). The Chi - Square Test (Figure 28) was highly significant, showing a positive trend where the older the generation, the greater the knowledge.

Figure 29 displayed equal medians but varying modes where "Millenials + Generation X" and "Baby Boomers + Silent Generation" showed the highest concern, while "Generation Z" had the lowest one. The Kruska – Wallis Test (Figure 30) was highly significant, reinforcing the relationship where the older the generation, the greater the concern regarding environmental issues.

Regarding the level of agreement about the direct impact of environmental issues on respondents, Figure 31 shows that each group’s modes, in order from youngest to oldest, were “3”, “4,” and “5,” respectively. This suggests that older generations tend to perceive these environmental issues as having a more significant impact on them. The Kruskal–Wallis Test (Table 5) was highly significant, confirming this relationship.

Figure 33 shows a vast difference between each generation’s willingness to change their practices to reduce their environmental impact. The medians and modes for the oldest groups were the maximum, while the youngest group had “3” as its mode and median. The Kruskal – Wallis Test (Figure 34) confirmed a relationship, where older generations are more willing to change their practices to reduce their environmental impact.

Regarding the frequency of recycling and reusing habits, Figure 35 shows higher frequencies for the two oldest groups while a lower one for the youngest. Nevertheless, the Kruskal–Wallis Test (Figure 36) was not significant, disregarding the existence of a relationship.

Regarding participation in environmental improvement events, a negative trend can be visualized in Figure 37, as the younger the generation, the higher the participation in these events. However, the Chi-Square Test (Figure 38) was not significant.

Figure 39 shows no clear link between generations and water conservation habits, except for mode differences. The two younger groups had the highest mode, while the oldest group had one of "4." However, the lack of this relationship was also supported by the Kruskal–Wallis Test (Figure 40), which was not significant.

Regarding the frequency of the habits to reduce electricity consumption (Figure 41), despite all modes having the highest frequency, the median only showed a frequency of 5” for the two oldest groups, while one of “4” for “Generation Z.” The Kruskal–Wallis Test (Figure 42) was significant, supporting a relationship.

It can be concluded that the older the respondents' generation, the more environmental knowledge, and attitudes. However, the relationship between environmental practices and generations is statistically unclear. This suggests a moderate to strong relationship, indicating that the older an individual in generation, the higher the level of EE.

This study’s findings have shown that younger Peruvian generations mostly lack adequate EE levels—especially in terms of knowledge and attitudes. Moreover, this conclusion is supported by previous investigations in other countries (Jones et al., 2020) but also challenged (EY and JA Worldwide, 2023), which is why further research, such as triangulation, should be carried out to fully confirm this complex relationship.

 

The reason behind this generational trend can be a consequence of the historical context in which these older Peruvian generations have been present. They have witnessed the evolution of deforestation in the Amazon rainforest, the growing impacts of the mining industry, and increasingly destructive weather patterns due to the ENSO phenomenon.

 

Still, this study has also shown that Peruvians overall do not have high EE levels compared to other countries such as Argentina, Singapore, and Finland. One possible explanation for this can be drawn from the demographic transition model (DTM). This suggests that, as countries develop in the DTM stage, the level of EE increases. This is a result of improved access to education, economic development, and shifts in societal priorities, all of which are associated with a country's progress through the DTM. Thus, Peru (DTM Stage 3) could be in a transition stage to reach EE levels such as those in Finland (DTM Stage 4), the country with the highest EE worldwide.

The method's strengths were that it ensured that all respondents were educated nationally, thus obtaining a more precise overview of the country’s EE level. Moreover, the questionnaire was completely anonymous, so bias and social desirability were somewhat avoided. Additionally, using multiple-choice questions allowed for more effective data processing and analysis of trends, as responses could be quantified, unlike open-ended ones.

 

However, the weaknesses included varying sample sizes among generations. Thus, they had to be grouped into three generation categories to make sure there were at least 30 respondents for each. This made the results less exact, but it was necessary to ensure that statistical tests worked appropriately. To avoid this, more data could have been collected, aiming for similar sample sizes for each generation. Furthermore, other independent variables that may also affect EE levels, such as gender and culture, were not considered since they may affect the statistical analyses. However, to avoid this, in further investigations, these other variables should be investigated separately to compare the relationships of each of these factors.

 

Limitations included central tendency bias, as some individuals may have refrained from using the extreme responses of the Likert scales (1 and 5). Furthermore, while 216 respondents can offer a reasonable insight into the trends within each generational group, it remains impossible to draw fully accurate conclusions when a sample is used to represent an entire population. This problem could have been minimized, but not eliminated, by sending this questionnaire to even more people. Additionally, despite being anonymous, a certain degree of social desirability always exists, as individuals tend to choose more positive answers to make themselves feel better.

• Focus groups could be carried out to determine the level of EE more precisely, as open-ended questions could be asked in smaller groups to better understand the differences between each generation.
• Observations, where specific individuals would be monitored, could also be performed in public spaces or workplaces to see the different generational behaviors.

Locally, an anthropocentric application with an ecocentric viewpoint can be applied. This approach could mirror the efforts of DEEKSHA in India, where individuals with higher EE levels, like ESS students, engage in activities to raise awareness among people of all ages who lack this type of education. Thus, environmentally educated people can contribute back to their community with their experience and expertise.

 

This project would have the strength that many students would be eager to participate, especially IB students, as this could be used for CAS or their resumes. Therefore, positive feedback would happen as people would increasingly get higher EE levels as projects such as this one continue.

 

Nevertheless, volunteers could be underqualified, meaning some false information might spread. Moreover, the lack of funding for the project might jeopardize the continuity of the solution. Also, if only one tutor teaches one student, the education would not be fully effective as EE is based on a community level.

 

The solution's limitations include the time for an effect or benefit to be observed. Also, because the activities might be done virtually for convenience, it may not be entirely effective because virtual education has proven to yield a worse performance in students.

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