The role of environment on women's perception about their STEM studies: observations from a Global South country.

The growing global demand for STEM professionals is not being met by the supply of new graduates, a supply that is characterised by a significant lag in the percentage of women pursuing STEM studies. Interestingly enough, the percentage of female applicants entering STEM majors has been increasing yet only a minority of them pursue, or complete, engineering programs. Several studies for the developed world have identified several environmental factors responsible for this phenomenon. The scarcity of engineering professionals is a handicapping factor for development, even for the most advanced countries of the Global South. The objective of this exploratory study is to examine whether the environmental factors identified in the international literature are sufficient to explain the asymmetry in selecting an engineering or a natural sciences career among female undergraduates in an exemplary Global South country, Kazakhstan. To this purpose, a multifaceted survey was conducted among the female students pursuing STEM majors in the premier Kazakhstani university in the academic year 2021-2022. This study utilized a Likert Scale questionnaire, ordinal logistic regression, and factor analysis to explore factors affecting female students. Data reliability was confirmed through Confirmatory Factor Analysis (CFA). The factor and regression analysis of the results obtained demonstrates that there is no discernible difference between the observations in the literature and the situation in Kazakhstan.

An intelligent methodology for the use of multi-criteria decision analysis in impact assessment: the case of real-world offshore construction.

Impact assessment of large-scale projects involves a plethora of technical, economic, social, and environmental factors that must be assessed along with the expectations of the stakeholders of each project. While impact assessment is required for a development project to receive regulatory approval to proceed, it is also an invaluable tool during the design phase of complex projects, providing for informed decision-making. Molding multiple perspectives of diverse stakeholders into a single collective choice is a key challenge in the process. Multi-Criteria Decision Analysis (MCDA) is the methodology used to rank a finite number of decision options based on a finite set of evaluation criteria. Different MCDA techniques, however, may lead to different decisions when applied to the same problem while different sets of criteria and weights may rank choices differently even when the same method is applied. This is a cause of concern, and even acrimony, amongst the stakeholders, often leading to protracted periods of negotiation and delaying project launching. The objective of this paper is to present an intelligent system to ameliorate the effects of the inherent subjectivity in MCDA techniques and to develop a consensus amongst the stakeholders in a data-driven setting. A case study from the field of offshore construction is used as a running example. This case study, informed by real-world experience in the field, demonstrates succinctly the issues involved and illustrates clearly the proposed intelligent methodology and its merits.