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This study aims to quantify and analyse the dynamics of land use and land cover (LULC) changes over three decades in the rapidly urbanizing city of Abha, Saudi Arabia, and to assess urban growth using Morphological Spatial Pattern Analysis (MSPA).

Using the Support Vector Machine (SVM) classification in Google Earth Engine, changes in land use in Abha between 1990 and 2020 are accurately assessed. This method leverages cloud computing to enhance the efficiency and accuracy of big data analysis. Additionally, MSPA was employed in Google Colab to analyse urban growth patterns.

The study demonstrates significant expansion of urban areas in Abha, growing from 62.46 km² in 1990 to 271.45 km² in 2020, while aquatic habitats decreased from 1.36 km² to 0.52 km². MSPA revealed a notable increase in urban core areas from 41.66 km² in 2001 to 194.97 km² in 2021, showcasing the nuanced dynamics of urban sprawl and densification.

The novelty of this study lies in its integrated approach, combining LULC and MSPA analyses within a cloud computing framework to capture the dynamics of city and environment. The insights from this study are poised to influence policy and planning decisions, particularly in fostering sustainable urban environments that accommodate growth while preserving natural habitats. This approach is crucial for devising strategies that can adapt to and mitigate the environmental impacts of urban expansion.

The purpose of this study is to investigate the state of undergraduate business statistics education in the Middle East and North Africa (MENA) and assess its alignment with the best practices in equipping business graduates with the knowledge and skills demanded by the labor market.

A survey of 108 instructors from 80 business schools in 17 MENA countries was conducted to gauge information on the delivery of business statistics courses. The survey results were benchmarked to a proposed framework for best practices in business statistics education.

The gap analysis identified deficiencies in the delivery of business statistics education in the region as compared to international best practices. This study revealed a need to revise statistics education as part of a comprehensive reform of business education with the aim to meet international quality standards in business education.

The study relied on the self-reported responses of business statistics instructors in MENA. One hundred eight questionnaires were completed, corresponding to a response rate of 40 per cent. Moreover, the study did not measure the effectiveness of teaching and learning in business statistics courses.

Recommendations from the study are intended to guide business statistics instructors in improving the quality of business statistics education through adopting more effective ways to enhance student learning experience and graduate employability.

This study is the first of its kind to investigate and assess the business statistics education in the MENA region.