Kaska Porayska-Pomsta

Training Attentional Control in Infancy

Summary Several recent studies have reported that cognitive training in adults does not lead to generalized performance improvements [1, 2], whereas many studies with younger participants (children 4 years and older) have reported distal transfer [3, 4]. This is consistent with convergent evidence [5–8] for greater neural and behavioral plasticity earlier in development. We used gaze-contingent paradigms to train 11-month-old infants on a battery of attentional control tasks. Relative to an active control group, and following only a relatively short training period, posttraining assessments revealed improvements in cognitive control and sustained attention, reduced saccadic reaction times, and reduced latencies to disengage visual attention. Trend changes were also observed in spontaneous looking behavior during free play, but no change was found in working memory. The amount of training correlated with the degree of improvement on some measures. These findings are to our knowledge the first demonstration of distal transfer following attentional control training in infancy. Given the longitudinal relationships identified between early attentional control and learning in academic settings [9, 10], and the causal role that impaired control of attention may play in disrupting learning in several disorders [11–14], the current results open a number of avenues for future work.

The uses of cognitive training technologies in the treatment of autism spectrum disorders

In this review, we focus on research that has used technology to provide cognitive training – i.e. to improve performance on some measurable aspect of behaviour – in individuals with autism spectrum disorders. We review technology-enhanced interventions that target three different cognitive domains: (a) emotion and face recognition, (b) language and literacy, and (c) social skills. The interventions reviewed allow for interaction through different modes, including point-and-click and eye-gaze contingent software, and are delivered through diverse implementations, including virtual reality and robotics. In each case, we examine the evidence of the degree of post-training improvement observed following the intervention, including evidence of transfer to altered behaviour in ecologically valid contexts. We conclude that a number of technological interventions have found that observed improvements within the computerised training paradigm fail to generalise to altered behaviour in more naturalistic settings, which may result from problems that people with autism spectrum disorders experience in generalising and extrapolating knowledge. However, we also point to several promising findings in this area. We discuss possible directions for future work.

The TARDIS Framework: Intelligent Virtual Agents for Social Coaching in Job Interviews

The TARDIS project aims to build a scenario-based serious-game simulation platform for NEETs and job-inclusion associations that supports social training and coaching in the context of job interviews. This paper presents the general architecture of the TARDIS job interview simulator, and the serious game paradigm that we are developing.

Social communication between virtual characters and children with autism

Children with ASD have difficulty with social communication, particularly joint attention. Interaction in a virtual environment (VE) may be a means for both understanding these difficulties and addressing them. It is first necessary to discover how this population interacts with virtual characters, and whether they can follow joint attention cues in a VE. This paper describes a study in which 32 children with ASD used the ECHOES VE to assist a virtual character in selecting objects by following the characters gaze and/or pointing. Both accuracy and reaction time data suggest that children were able to successfully complete the task, and qualitative data further suggests that most children perceived the character as an intentional being with relevant, mutually directed behaviour.

A Job Interview Simulation: Social Cue-Based Interaction with a Virtual Character

This paper presents an approach that makes use of a virtual character and social signal processing techniques to create an immersive job interview simulation environment. In this environment, the virtual character plays the role of a recruiter which reacts and adapts to the users behavior thanks to a component for the automatic recognition of social cues (conscious or unconscious behavioral patterns). The social cues pertinent to job interviews have been identified using a knowledge elicitation study with real job seekers. Finally, we present two user studies to investigate the feasibility of the proposed approach as well as the impact of such a system on users.

Supporting children's social communication skills through interactive narratives with virtual characters

The development of social communication skills in children relies on multimodal aspects of communication such as gaze, facial expression, and gesture. We introduce a multimodal learning environment for social skills which uses computer vision to estimate the childrens gaze direction, processes gestures from a large multi-touch screen, estimates in real time the affective state of the users, and generates interactive narratives with embodied virtual characters. We also describe how the structure underlying this system is currently being extended into a general framework for the development of interactive multimodal systems.

Building an Intelligent, Authorable Serious Game for Autistic Children and Their Carers

This paper introduces the SHARE-IT project, which leverages serious games paradigm to motivate and engage children with autism diagnosis in interactive activities, based on the state-of-the-art autism intervention practices. The aim of SHARE-IT is to formulate, in partnership with schools, parents and industry, the requirements for a robust, intelligent and authorable environment for supporting children in exploring, practicing and acquiring social interaction skills. SHARE-IT focuses on two key challenges: (i) developing robust system architecture and implementation, able to support both continuing development of a serious game for children with autism and its real world use; and (ii) selecting appropriate technologies and techniques to allow for (a) multi-device and operating system deployment, (b) the development of an intelligent serious game for supporting social interaction while (c) allowing the flexibility for the environment to be authored by lay persons. SHARE-ITs architecture is presented and several considerations of importance to enabling the engineering of an intelligent and authorable serious game are discussed. Examples of technologies developed to date are given throughout and a discussion of future challenges offered.

Building autonomous social partners for autistic children

We present the design and implementation of an autonomous virtual agent that acts as a credible social partner for children with Autism Spectrum Conditions and supports them in acquiring social communication skills. The agents design is based on principles of best autism practice and input from users. Initial experimental results on the efficacy of the agent show encouraging tendencies for a number of children.

Workshop on Social and Emotional Intelligence in Learning Environments

It has been long recognised in education that teaching and learning is a highly social and emotional activity. Students’ cognitive progress depends on their psychological predispositions such as their interest, confidence, sense of progress and achievement as well as on social interactions with their teachers and peers who provide them (or not) with both cognitive and emotional support. Until recently the ability to recognise students’ socio-affective needs constituted exclusively the realm of human tutors’ social competence. However, in recent years and with the development of more sophisticated computer-aided learning environments, the need for those environments to take into account the student’s affective states and traits and to place them within the context of the social activity of learning has become an important issue in the domain of building intelligent and effective learning environments. More recently, the notion of emotional intelligence has attracted increasing attention as one of tutors’ pre-requisites for improving students’ learning.

Affect in one-to-one tutoring

It is well known that human tutors take into account both the students knowledge and understanding of what is being taught, in addition to considering the emotional and motivational state of the student. However, there are many gaps in our understanding of the relationship between cognition and affect in tutoring. We have some insight into how human tutors infer students cognitive and affective states, and current research has attempted to apply this knowledge to the inference of such states by computer tutors. There is ongoing research on how human tutors use their knowledge of students states in their decisions and actions, and how we might use such research to inform the design of computer tutors.