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Soil quality is in decline in many parts of the world, in part due to the intensification of agricultural practices. Whilst economic instruments and regulations can help incentivise uptake of more sustainable soil management practices, they rarely motivate long-term behavior change when used alone. There has been increasing attention towards the complex social factors that affect uptake of sustainable soil management practices. To understand why some communities try these practices whilst others do not, we undertook a narrative review to understand how social capital influences adoption in developed nations. We found that the four components of social capital – trust, norms, connectedness and power – can all influence the decision of farmers to change their soil management. Specifically, information flows more effectively across trusted, diverse networks where social norms exist to encourage innovation. Uptake is more limited in homogenous, close-knit farming communities that do not have many links with non-farmers and where there is a strong social norm to adhere to the status quo. Power can enhance or inhibit uptake depending on its characteristics. Future research, policy and practice should consider whether a lack of social capital could hinder uptake of new practices and, if so, which aspects of social capital could be developed to increase adoption of sustainable soil management practices. Enabling diverse, collaborative groups (including farmers, advisers and government officials) to work constructively together could help build social capital, where they can co-define, -develop and -enact measures to sustainably manage soils.

This paper is one of the first studies to examine specificities, including limits of mindfulness at work in an African organisational context, whilst dealing with the ongoing COVID-19 pandemic. It specifically addresses the role of organisational and managerial support systems in restoring employee wellbeing, social connectedness and attachment to their organisations, in order to overcome the exclusion caused by the ongoing pandemic.

The study uses a qualitative research methodology that includes interviews as the main data source. The sample comprises of 20 entrepreneurs (organisational leaders) from Ghana and Nigeria.

The authors found that COVID-19-induced worries restricted the practice of mindfulness, and this was prevalent at the peak of the pandemic, particularly due to very tough economic conditions caused by reduction in salaries, and intensified by pre-existing general economic and social insecurities, and institutional voids in Africa. This aspect further resulted in lack of engagement and lack of commitment, which affected overall team performance and restricted employees’ mindfulness at work. Hence, quietness by employees even though can be linked to mindfulness was linked to larger psychological stress that they were facing. The authors also found leaders/manager’s emotional intelligence, social skills and organisational support systems to be helpful in such circumstances. However, their effectiveness varied among the cases.

This paper is one of the first studies to establish a link between the COVID-19 pandemic and mindfulness limitations. Moreover, it is a pioneering study specifically highlighting the damaging impact of COVID-19-induced concerns on leader–member exchange (LMX) and team–member exchange (TMX) relationships, particularly in the African context. It further brings in a unique discussion on the mitigating mechanisms of such COVID-19-induced concerns in organisations and highlights the roles of manager’s/leader’s emotional intelligence, social skills and supportive intervention patterns. Finally, the authors offer an in-depth assessment of the effectiveness of organisational interventions and supportive relational systems in restoring social connectedness following a social exclusion caused by COVID-19-induced worries.

The retention and success of engineering undergraduates are increasing concern for higher-education institutions. The study of success determinants are initial steps in any remedial initiative targeted to enhance student success and prevent any immature withdrawals. This study provides a comprehensive approach toward the prediction of student academic performance through the lens of the knowledge, attitudes and behavioral skills (KAB) model. The purpose of this paper is to aim to improve the modeling accuracy of students’ performance by introducing two methodologies based on variable selection and dimensionality reduction.

The performance of the proposed methodologies was evaluated using a real data set of ten critical-to-success factors on both attitude and skill-related behaviors of 320 first-year students. The study used two models. In the first model, exploratory factor analysis is used. The second model uses regression model selection. Ridge regression is used as a second step in each model. The efficiency of each model is discussed in the Results section of this paper.

The two methods were powerful in providing small mean-squared errors and hence, in improving the prediction of student performance. The results show that the quality of both methods is sensitive to the size of the reduced model and to the magnitude of the penalization parameter.

First, the survey could have been conducted in two parts; students needed more time than expected to complete it. Second, if the study is to be carried out for second-year students, grades of general engineering courses can be included in the model for better estimation of students’ grade point averages. Third, the study only applies to first-year and second-year students because factors covered are those that are essential for students’ survival through the first few years of study.

The study proposes that vulnerable students could be identified as early as possible in the academic year. These students could be encouraged to engage more in their learning process. Carrying out such measurement at the beginning of the college year can provide professional and college administration with valuable insight on students perception of their own skills and attitudes toward engineering.

This study employs the KAB model as a comprehensive approach to the study of success predictors. The implementation of two new methodologies to improve the prediction accuracy of student success.