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This chapter presents an exploration of the ways in which humanitarian non-government organisations (NGOs) and communities affected by the 2014 floods in Solomon Islands interpreted and responded to the disaster, identifying factors that assisted and constrained stakeholders in disaster response and recovery. The research investigates the extent to which communities were consulted and participated in NGO responses, and the factors which informed community–NGO relationships. A qualitative case study approach was used, employing interviews, focus groups and document analysis, guided by a reflexive discourse analysis and narrative inquiry approach, which places the focus of the study on the experiences of participants. Communities played very limited roles in NGO responses, especially non-dominant or marginalised sectors of society, such as youth, women and people with disabilities. Failure to respond appropriately to the differentiated needs of affected populations can exacerbate their risk of experiencing secondary disaster. The authors argue that there is a need to improve the inclusiveness of responses to disaster, engaging women, youth and people with disabilities in decision making in order to respond more appropriately to their needs.

Marrakech is today the most important tourist destination in Morocco. Marrakech, however, is not only a key reference point for mass international tourism, but also the preferred choice for those hunting for an “authentic” experience in this North African country. The “Red City” is indeed often presented in literature and advertising alike as a place out of modern time where the real “soul” of Morocco can be found and unveiled (Minca, 2006). This chapter investigates how this “soul” was established—and is now, in Marrakech, constantly reenacted—through layers of colonial and postcolonial interactions between Europe and Morocco.

Introduction: Numerous decision-making situations are faced in education where Artificial Intelligence may be prevalent as a decision-making support tool to capture streams of learners’ behaviours.

Purpose: The purpose of the present study is to understand the role of AI in student performance assessment and explore the future role of AI in educational performance assessment.

Scope: The study tries to understand the adaptability of AI in the education sector for supporting the educator in automating assessment. It supports the educator to concentrate on core teaching-learning activities.

Objectives: To understand the AI adaption for educational assessment, the positives and negatives of confidential data collections, and challenges for implementation from the view of various stakeholders.

Methodology: The study is conceptual, and information has been collected from sources comprised of expert interactions, research publications, survey and Industry reports.

Findings: The use of AI in student performance assessment has helped in early predictions for the activities to be adopted by educators. Results of AI evaluations give the data that may be combined and understood to create visuals.

Research Implications: AI-based analytics helps in fast decision-making and adapting the teaching curriculum’s fast-changing industry needs. Students’ abilities, such as participation and resilience, and qualities, such as confidence and drive, may be appraised using AI assessment systems.

Theoretical Implication: Artificial intelligence-based evaluation gives instructors, students, and parents a continuous opinion on how students learn, the help they require, and their progress towards their learning objectives.