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In this case study, we offer an analysis of feedback from a student experience survey completed by Black undergraduate students who received proactive, targeted coaching and mentoring support during 2021–2022. All the students were studying at a large higher education institution in the United Kingdom which offers a broad range of degree courses by distance learning.

This paper reports on the intervention delivered and analyses the student experience of being offered, and receiving, proactive coaching and mentoring. It is based on the responses of 102 students who engaged with the experience survey after having self-selected to receive the intervention. What follows is an analysis of their experiences using a qualitative in vivo approach based on word frequency in students’ free-text comments.

The findings presented are that, in this intervention, students who self-select to receive coaching and mentoring support experience tangible (self-reported) behaviour changes with potentially longer term benefits for their studies. These include improved self-confidence and self-efficacy, increased proactive help-seeking behaviour, greater recognition of strengths and achievement and personal growth and self-awareness.

In presenting this case study, we aim to contribute to the growing corpus of practitioner case studies and research papers that show the benefits of coaching and mentoring in higher education and – more specifically – why coaching and mentoring can be a worthwhile targeted intervention for students from underrepresented backgrounds. This lends support to the growing consensus that students with positive, proactive help-seeking behaviours perform better than students not able to access support (Byrne et al., 2014). We conclude the case study with some practical implications for providers looking to provide targeted support to students.

The purpose of this study is to explore the incorporation of the sustainable development goals (SDGs) at the National University of Moreno (Universidad Nacional de Moreno, UNM, in Spanish), focusing on teaching and research activities, encountering difficulties from primary and secondary information sources, to integrate the SDGs, and contribute with actions for their incorporation into teaching and learning processes and research, in a newly established university.

To describe the implementation of the SDGs, an empirical study was conducted using a mixed methodology for data collection. Data collected from the survey were combined with information from the UNM project database for the period 2017–2022. Non-parametric methods were used to analyse both sets of data.

This study provides an initial overview of SDG implementation at UNM, allowing the identification of constraints and challenges to scale up contributions to the SDGs at UNM, as well as the generation of relevant action lines in the interaction with university's authorities.

Conducting studies through questionnaires has limitations, similar to other cases analysed. To increase the validity of the data, prior consultations were carried out. In addition, the database of research projects was used to identify the application of the SDGs in research. However, an approximation of the current situation could be obtained.

Particular importance was given to the challenges encountered during the data analysis phase in relation to capacity building needs. This enabled a set of actions to be defined to bring the SDGs closer to the UNM.

Although the paper used methodologies already proposed by other authors, such as survey collection, its value lies in demonstrating the possibility of using them to analyse whether the SDGs are integrated into teaching and research activities in a recently founded university, where the SDGs are integrated into its principles. The analysis also complements the survey results with information from project databases, which has not yet been analysed in the literature. Based on the results, activities are designed so that the SDGs could begin to guide teaching and research activities.

The domains of Industry 4.0 and Smart Farming encompass the application of digitization, automation, and data-driven decision-making principles to revolutionize conventional sectors. The intersection of these two fields has numerous opportunities for industry, society, science, technology and research. Relatively, this intersection is new, and still, many grey areas need to be identified. This research is a step toward identifying research areas and current trends.

The present study examines prevailing research patterns and prospective research prospects within Industry 4.0 and Smart Farming. This is accomplished by utilizing the Latent Dirichlet Allocation (LDA) methodology applied to the data procured from the Scopus database.

By examining the available literature extensively, the researchers have successfully discovered and developed three separate research questions. The questions mentioned above were afterward examined with great attention to detail after using LDA on the dataset. The paper highlights a notable finding on the lack of existing scholarly research in the examined combined field. The existing database consists of a restricted collection of 51 scholarly papers. Nevertheless, the forthcoming terrain harbors immense possibilities for exploration and offers a plethora of prospects for additional investigation and cerebral evaluation.

This study examines the Industrial Revolution's and Smart Farming's practical effects, focusing on Industry 4.0 research. The proposed method could help agricultural practitioners implement Industry 4.0 technology. It could additionally counsel technology developers on innovation and ease technology transfer. Research on regulatory frameworks, incentive programs and resource conservation may help policymakers and government agencies.

The paper proposes that the incorporation of Industry 4.0 technology into agricultural operations can enhance efficiency, production and sustainability. Furthermore, it highlights the significance of creating user-friendly solutions specifically tailored for farmers and companies. The study indicates that the implementation of supportive legislative frameworks, incentive programmes and resource conservation methods might encourage the adoption of smart agricultural technologies, resulting in the adoption of more sustainable practices.

This study examines the Industrial Revolution's and Smart Farming's practical effects, focusing on Industry 4.0 research. The proposed method could help agricultural practitioners implement Industry 4.0 technology. It could additionally counsel technology developers on innovation and ease technology transfer. Research on regulatory frameworks, incentive programs and resource conservation may help policymakers and government agencies.

Based on a thorough examination of existing literature, it has been established that there is a lack of research specifically focusing on the convergence of Industry 4.0 and Smart Farming. However, notable progress has been achieved in the field of seclusion. To date, the provided dataset has not been subjected to analysis using the LDA technique by any researcher.