A review of Websites and Mobile Applications for People with Autism Spectrum Disorders: Towards Shared Guidelines

Many studies show the effective positive impact of using computer technologies to support the lives of users with autism spectrum disorders (ASD), for simplifying interaction with other people, for organising daily activities, for improving relation with family and friends. Despite that, only a restricted part of the current websites is accessible for people with ASD. In this paper, we discuss a set of guidelines that should be followed by designers while developing websites or mobile applications for users with ASD. We review many of the existing websites and applications in order to check which comply with all, or parts of these guidelines. We finally highlight current common limitations and address new challenging research directions. \ua9 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017

Internalising symptoms and working memory as predictors of mathematical attainment trajectories across the primary-secondary education transition

The transition from primary to secondary education is a critical period in early adolescence which is related to increased anxiety and stress, increased prevalence of mental health issues, and decreased maths performance, suggesting it is an important period to investigate maths attainment. Previous research has focused on anxiety and working memory as predictors of maths, without investigating any long-term effects around the education transition. This study examined working memory and internalizing symptoms as predictors of children's maths attainment trajectories (age 7–16) across the transition to secondary education using secondary longitudinal analysis of the Avon Longitudinal Study of Parents and Children (ALSPAC). This study found statistically significant, but very weak evidence for the effect of internalizing symptoms and working memory on maths attainment. Greater parental education was the strongest predictor, suggesting that children of parents with a degree (compared with those with a CSE) gain the equivalent of almost a year's schooling in maths. However, due to methodological limitations, the effects of working memory and internalizing symptoms on attainment cannot be fully understood with the current study. Additional research is needed to further uncover this relationship, using more time-appropriate measures

Psychophysiology in games

Psychophysiology is the study of the relationship between psychology and its physiological manifestations. That relationship is of particular importance for both game design and ultimately gameplaying. Players’ psychophysiology offers a gateway towards a better understanding of playing behavior and experience. That knowledge can, in turn, be beneficial for the player as it allows designers to make better games for them; either explicitly by altering the game during play or implicitly during the game design process. This chapter argues for the importance of physiology for the investigation of player affect in games, reviews the current state of the art in sensor technology and outlines the key phases for the application of psychophysiology in games.The work is supported, in part, by the EU-funded FP7 ICT iLearnRWproject (project no: 318803).peer-reviewe

A Reflection on Economic Uncertainty and Fertility in Europe: The Narrative Framework

none5openVignoli, Daniele; Guetto, Raffaele; Bazzani, Giacomo; Pirani, Elena; Minello, AlessandraVignoli, Daniele; Guetto, Raffaele; Bazzani, Giacomo; Pirani, Elena; Minello, Alessandr

What Was I Thinking? Using Multi-Voxel Pattern Analysis to Identify Shared Neural Representations Between External and Internal Speech

The phenomenological experience of hearing one’s own voice inside one’s head – inner speech – is a fundamental yet mysterious aspect of cognition. Compared to speech perception and production, relatively little is known about the neural representations that underlie inner speech. This is partly due to its “hidden” nature; functional neuroimaging offers one way to observe the neural substrates of inner speech. In particular, multi-voxel pattern analysis (MVPA) is well suited to investigate its representational nature using functional magnetic resonance imaging (fMRI) data. In this dissertation, I use MVPA and fMRI to investigate the extent to which auditory and motor representations of speech are co-opted during inner speech. In Chapter 2, I establish that MVPA can be used to identify phonological features (voicing, place of articulation, and manner of articulation) during speech perception. In Chapter 3, this work is extended to include silent speech production (“speech miming”). Together, these data show that phonological features are represented throughout the bilateral auditory cortices during perception and that certain phonological features are robustly represented in the speech-motor system during miming. In Chapter 4, I use a technique known as multivariate cross-decoding to demonstrate that inner speech recapitulates neural patterns of activation observed during miming in both the auditory and motor cortices. In Chapter 5, the concept of inner speech is extended to include a verbal working memory (WM) task and MVPA is used to track the neural time-course of auditory and motor representations. The results from Chapter 4 are replicated and it is further shown that neural patterns associated with speech perception can also be reactivated during verbal WM. The neural representations shared between perception and inner speech are active early in the WM task, while the representations shared between miming and inner speech remain active throughout the WM task. This work suggests that MVPA can detect the underlying representations associated with inner speech and that multiple types of representations interact to support the task at hand. Further, it demonstrates that the patterns of activation present in the auditory and motor systems during miming provide a reliable model from which to predict inner speech.Ph.D

Student privacy and educational data mining: perspectives from industry

While the field of educational data mining (EDM) has generated many innovations for improving educational software and student learning, the mining of student data has recently come under a great deal of scrutiny. Many stakeholder groups, including public officials, media outlets, and parents, have voiced concern over the privacy of student data and their efforts have garnered national attention. The momentum behind and scrutiny of student privacy has made it increasingly difficult for EDM applications to transition from academia to industry. Based on experience as academic researchers transitioning into industry, we present three primary areas of concern related to student privacy in practice: policy, corporate social responsibility, and public opinion. Our discussion will describe the key challenges faced within these categories, strategies for overcoming them, and ways in which the academic EDM community can support the adoption of innovative technologies in large-scale production