Wildfires pose significant environmental threats in Australia, impacting ecosystems, human lives, and property. This review article provides a comprehensive analysis of various empirical and dynamic wildfire simulators alongside machine learning (ML) techniques employed for wildfire prediction in Australia. The study examines the effectiveness of…

Learning style recognition is an indispensable part of achieving personalized learning in online learning systems. The traditional inventory method for learning style identification faces the limitations such as subject and static characteristics. Therefore, an automatic and reliable learning style recognition mechanism is designed in this…

The quality assurance and evaluation of primary schools requires early risk detection. This is a daunting task, not only because risks are typically rare and their origins complex, but also because governing institutions have limited resources and capacity and desire efficiency and proportionality. Many countries, including most Organisation for…

International survey researchers are increasingly turning to a geospatial sampling approach known as gridded population sampling for finer resolution and a more updated sampling frame than conventional census-based sampling. To date, there have been no direct comparisons of accuracy between survey results derived from the two methods. This…

Today, with the extension of learning management systems (LMSs) and the diversity of learners' needs for online learning, instructors have to be assisted to adapt their syllabus to meet learners' needs. Therefore, it is necessary to tailor course instruction to meet individual needs and determine how well they serve the learners using these online…

Sub-Saharan Africa exhibits higher fertility and lower education than other world regions. Economic and demographic theory posit that these phenomena are linked, with slow fertility decline connected to slow education growth among both adults and children. Using microdata from 33 African countries, this paper documents the co-evolution of adult…

Selecting courses in an open-curriculum education program is a difficult task for students and academic advisors. Course recommendation systems nowadays can be used to reduce the complexity of this task. To control the recommendation error, we argue that course recommendations need to be provided together with "statistical" confidence.…

In the last decade education has experienced a shift from privatization to commercialization. This paper argues that the commercialization of education has evolved more recently as a result of artificially intelligent corporate players, enabling forms of insights sales called 'Dark Advertising'. It unpacks how Dark Advertising are profiting from…

The large rates of students' failure is a very frequent problem in undergraduate courses, being even more evident in exact sciences. Pointing out the reasons of such problem is a paramount research topic, though not an easy task. An alternative is to use Educational Data Mining techniques (EDM), which enables one to convert data from educational…

Misrepresentation and mischief in the research process can impact on ethical conduct, the validity of findings and deliberately change the outcome. This short report presents a scenario about deliberate interference in adoption research by one organisation seeking accreditation to deliver adoption services. Unbeknown to the researchers, fake…

Recent negotiations of 'data' in schools place focus on student assessment and NAPLAN. However, with the rise in artificial intelligence (AI) underpinning educational technology, there is a need to shift focus towards the value of teachers' digital data. By doing so, the broader debate surrounding the implications of these technologies and rights…

It is not possible to predict how we might re-exist/resist while most of our bodies fail to be hospitable to the virus. For now, what seems possible, and potent, is to make strange the solutions we have been putting into practice, while sharing the world and our bodies with this enemy / companion species. This article focuses on some solutions…

Agent-based models combine data and theory during both development and use of the model. As models have become increasingly data driven, it is easy to start thinking of agent-based modelling as an empirical method, akin to statistical modelling, and reduce the role of theory. We argue that both types of information are important where the past is…

This article proposes an approach based on experiments to teach optimization technique (OT) courses in the Systems Engineering curricula at undergraduate level. Artificial intelligence techniques in terms of nature-inspired optimization algorithms and neural networks are inserted in the lecture and laboratory parts of the syllabus. The experiments…

This contribution addresses the challenges brought on by the pandemic and argues that a forced acceleration in online teaching and assessment practices can become a sustainable model for the post-COVID-19 world. Technology is a great asset that provides learning opportunities for the whole community and the education sector should seek to adopt an…