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Artificial Intelligence And Big Data Technologies To Close The Achievement Gap.
We observe achievement gaps even in rich western countries, such as the UK, which in principle have the resources as well as the social and technical infrastructure to provide a better deal for all learners. The reasons for such gaps are complex and include the social and material poverty of some learners with their resulting other deficits, as well as failure by government to allocate sufficient resources to remedy the situation. On the supply side of the equation, a single teacher or university lecturer, even helped by a classroom assistant or tutorial assistant, cannot give each learner the kind of one-to-one attention that would really help to boost both their motivation and their attainment in ways that might mitigate the achievement gap.
In this chapter Benedict du Boulay, Alexandra Poulovassilis, Wayne Holmes, and Manolis Mavrikis argue that we now have the technologies to assist both educators and learners, most commonly in science, technology, engineering and mathematics subjects (STEM), at least some of the time. We present case studies from the fields of Artificial Intelligence in Education (AIED) and Big Data. We look at how they can be used to provide personalised support for students and demonstrate that they are not designed to replace the teacher. In addition, we also describe tools for teachers to increase their awareness and, ultimately, free up time for them to provide nuanced, individualised support even in large cohorts
Grounding semantics in robots for Visual Question Answering
In this thesis I describe an operational implementation of an object detection and description system that incorporates in an end-to-end Visual Question Answering system and evaluated it on two visual question answering datasets for compositional language and elementary visual reasoning
Fuzzy Decision-Support System for Safeguarding Tangible and Intangible Cultural Heritage
In the current world economic situation, the maintenance of built heritage has been limited
due to a lack of funds and accurate tools for proper management and implementation of these actions.
However, in specific local areas, the maintenance and conservation of historical and cultural heritage
have become an investment opportunity. In this sense, in this study, a new tool is proposed, for the
estimation of the functional service life of heritage buildings in a local region (city of Seville, South
Spain). This tool is developed in Art-Risk research project and consists of a free software to evaluate
decisions in regional policies, planning and management of tangible and intangible cultural heritage,
considering physical, environmental, economic and social resources. This tool provides a ranking of
priority of intervention among case studies belonging to a particular urban context. This information
is particularly relevant for the stakeholders responsible for the management of maintenance plans in
built heritage
Using a cognitive architecture to examine what develops
Different theories of development propose alternative mechanisms by which development occurs. Cognitive architectures can be used to examine the influence of each proposed mechanism of development while keeping all other mechanisms constant. An ACT-R computational model that matched adult behavior in solving a 21-block pyramid puzzle was created. The model was modified in three ways that corresponded to mechanisms of development proposed by developmental theories. The results showed that all the modifications (two of capacity and one of strategy choice) could approximate the behavior of 7-year-old children on the task. The strategy-choice modification provided the closest match on the two central measures of task behavior (time taken per layer, r = .99, and construction attempts per layer, r = .73). Modifying cognitive architectures is a fruitful way to compare and test potential developmental mechanisms, and can therefore help in specifying “what develops.
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