Sustainable development (SD) is an approach that aims to meet the needs of the present generation without compromising the ability of future generations to meet their own needs. Education for sustainable development (ESD) is a key component in achieving this goal, as it equips young people with the knowledge, skills, and values needed to make sustainable decisions. This study investigated how preschool teachers in Saudi Arabia understood (SD) and the state of (ESD) practices. A survey was used to collect data from 230 Saudi preschool teachers. The findings revealed that 90% of teachers lacked awareness regarding SD. The overall evaluation of ESD practices among participants indicated a weak subpar status, with an average score of 2.49 out of 4. Notably, in ascending order, the following three dimensions had weak mean scores: the content aspect (2.38) had the lowest score, followed by the practice aspect (2.54) and the competencies aspect (2.58). Meanwhile, the values aspect (2.63) had an average outcome. Analysing the mean scores of ESD practices based on teachers’ qualifications and school types revealed significant differences, although no variations were observed based on experience. The primary obstacle to ESD implementation in pre-schools was the lack of awareness regarding SD/ESD. The study underscores the significance of expanding teacher training to promote ESD effectively in pre-school settings. The results highlight the need for professional development opportunities to improve ESD implementation in classrooms, educate Saudi preschool teachers about SD, and create instructional materials that align with the principles of ESD.

In this paper, we explore the static and dynamic effects of oil rent on competitiveness in Saudi Arabia’s economy during the period 1970–2022. In addition, we examined the short-run, strong and long-run relationships between exports and industry, inflation, energy use (oil rents) and agriculture using the Autoregressive Distributed Lag (ARDL) approach developed. The analysis showed that government spending will contribute to enhancing the competitive environment with a difference of one year. Moreover, the industry will contribute to increasing competitiveness for a positive relationship in the long term. The results stated that there is an insignificant relationship between competitiveness, inflation, and oil rents. The analysis also shows that inflation has a negative impact with statistical significance in the short term. In addition, the error correction model (ECM) coefficient is negative and has statistical significance at 0.76 at a 1% significant level, which indicates the existence of an error correction mechanism and thus the existence of a long-term relationship between the variables.

The Consumer Price Index (CPI) is a vital gauge of economic performance, reflecting fluctuations in the costs of goods, services, and other commodities essential to consumers. It is a cornerstone measure used to evaluate inflationary trends within an economy. In Saudi Arabia, forecasting the Consumer Price Index (CPI) relies on analyzing CPI data from 2013 to 2020, structured as an annual time series. Through rigorous analysis, the SARMA (0,1,0) (12,0,12) model emerges as the most suitable approach for estimating this dataset. Notably, this model stands out for its ability to accurately capture seasonal variations and autocorrelation patterns inherent in the CPI data. An advantageous feature of the chosen SARMA model is its self-sufficiency, eliminating the need for supplementary models to address outliers or disruptions in the data. Moreover, the residuals produced by the model adhere closely to the fundamental assumptions of least squares principles, underscoring the precision of the estimation process. The fitted SARMA model demonstrates stability, exhibiting minimal deviations from expected trends. This stability enhances its utility in estimating the average prices of goods and services, thus providing valuable insights for policymakers and stakeholders. Utilizing the SARMA (0,1,0) (12,0,12) model enables the projection of future values of the Consumer Price Index (CPI) in Saudi Arabia for the period from June 2020 to June 2021. The model forecasts a consistent upward trajectory in monthly CPI values, reflecting ongoing economic inflationary pressures. In summary, the findings underscore the efficacy of the SARMA model in predicting CPI trends in Saudi Arabia. This model is a valuable tool for policymakers, enabling informed decision-making in response to evolving economic dynamics and facilitating effective policies to address inflationary challenges.