Development of An Arabic Conversational Intelligent Tutoring System for Education of Children with ASD

This paper presents a novel Arabic Conversational Intelligent Tutoring System (CITS) that adapts the learning styles VAK for autistic children to enhance their learning. The proposed CITS architecture uses a combination of Arabic Pattern Matching and Arabic Short Text Similarity to extract the responses from the resources. The new Arabic CITS, known as LANA, is aimed at children with autism (10 to 16 years old) who have reached a basic competency with the mechanics of Arabic writing. This paper describes the architecture of LANA and its components. The experimental methodology is explained in order to conduct a pilot study in future

Assistente virtual para facilitar o autocuidado de pessoas mais velhas com diabetes tipo 2

Trabalho de projecto de mestrado, Engenharia Informática (Interação e Conhecimento) Universidade de Lisboa, Faculdade de Ciências, 2018Neste projeto apresenta-se uma solução tecnológica para o autocuidado de idosos com diabetes tipo 2, na qual se encontra incluído um avatar com representação antropomórfica e dotado de inteligência artificial, que desempenha a função de assistente virtual. O objetivo é preencher uma lacuna existente na falta de acompanhamento entre consultas médicas presenciais da diabetes, respondendo às necessidades diárias do doente: i) motivando-o à prática de exercício físico com planos adaptados às suas limitações; ii) aconselhar nas suas escolhas alimentares e no planeamento de refeições; e iii) relembrar a toma da medicação receitada por profissionais de saúde. O assistente responde consoante a motivação do utilizador, felicitando-o por etapas já conquistadas e promovendo a continuação de um bom trabalho, propondo-lhe novos desafios. Este sistema está disponível para dispositivos tablet com o sistema operativo Android. O desenvolvimento da solução foi seguido da realização de testes com doentes do grupo alvo e profissionais de saúde em centros de saúde da área de Lisboa e na Escola Superior de Enfermagem de Lisboa (ESEL). Este trabalho recebeu o apoio financeiro da Fundação para a Ciência e a Tecnologia (FCT) através de dois financiamentos distintos, o da Unidade de I&D BioISI - Biosystems & Integrative Sciences Institute (referência UID/MULTI/04046/2013) e o do projeto VASelfCare, projeto nº 024250. Neste projeto, liderado pela ESEL, trabalha uma equipa multidisciplinar composta por investigadores da própria ESEL, da Faculdade de Farmácia da Universidade de Lisboa (FFUL), da Faculdade de Ciências da Universidade de Lisboa (FCUL) e da Escola Superior de Desporto de Rio Maior (ESDRM) do Instituto Politécnico de Santarém.This project presents a technological solution for the selfcare of elderly people with type 2 diabetes, in which an avatar with an anthropomorphic representation and artificial intelligence are incorporated. The main goal is to fill a gap in the lack of follow-up between face-to-face diabetes medical appointments, responding to the patient's daily needs by: i) motivating him/her to practice physical activity, with plans adapted to his/her limitations; ii) advising on his/her food choices and meal planning; and iii) reminding him/her to take the medication prescribed by health professionals. The assistant will respond according to the users’ motivation, congratulating him/her on the steps already taken and promoting the continuation of a ‘good job’ by proposing new challenges. This system is available for tablet devices. The development of the solution has been followed by tests with real patients of the target group and health professionals in health centers in the Lisbon area and in Escola Superior de Enfermagem de Lisboa (ESEL). This project received financial support from the Fundação para a Ciência e a Tecnologia (FCT), sponsored by two different funding, one from Unidade de I&D BioISI - Biosystems & Integrative Sciences Institute (reference UID/MULTI/04046/2013), and the other from VASelfCare project, no. 024250. It is led by ESEL, and involves a multidisciplinary team composed by researchers from ESEL, from Faculdade de Farmácia da Universidade de Lisboa (FFUL), from Faculdade de Ciências da Universidade de Lisboa (FCUL), and from Escola Superior de Desporto de Rio Maior (ESDRM) of Instituto Politécnico de Santarém

Arabic conversational agent for modern Islamic education

This thesis presents research that combines the benefits of intelligent tutoring systems (ITS), Arabic conversational agents (CA) and learning theories by constructing a novel Arabic conversational intelligent tutoring system (CITS) called Abdullah. Abdullah CITS is a software program intended to deliver a tutorial to students aged between 10 and 12 years old, that covers the essential topics in Islam using natural language. The CITS aims to mimic a human Arabic tutor by engaging the students in dialogue using Modern standard Arabic language (MSA), whilst also allowing conversation and discussion in classical Arabic language (CAL). Developing a CITS for the Arabic language faces many challenges due to the complexity of the morphological system, non-standardization of the written text, ambiguity, and lack of resources. However, the main challenge for the developed Arabic CITS is how the user utterances are recognized and responded to by the CA, as well as how the domain is scripted and maintained. This research presents a novel Arabic CA and accompanying a scripting language that use a form of pattern matching, to handle users’ conversations when the user converse in MSA. A short text similarity measure is used within Abdullah CITS to extract the responses from CAL resources such as the Quran, Hadith, and Tafsir if there are no matching patterns with the Arabic conversation agent’s scripts. Abdullah CITS is able to capture the user’s level of knowledge and adapt the tutoring session and tutoring style to suit that particular learner’s level of knowledge. This is achieved through the inclusion of several learning theories and methods such as Gagne’s learning theory, Piaget learning theory, and storytelling method. These learning theories and methods implemented within Abdullah’s CITS architecture, are applied to personalise a tutorial to an individual learner. This research presents the first Arabic CITS, which utilises established learning typically employed in a classroom environment. The system was evaluated through end user testing with the target age group in schools both in Jordan and in the UK. Empirical experimentation has produced some positive results, indicating that Abdullah CITS is gauging the individual learner’s knowledge level and adapting the tutoring session to ensure learning gain is achieved

Development of an Arabic conversational intelligent tutoring system for education of children with autism spectrum disorder

Children with Autism Spectrum Disorder (ASD) are affected in different degrees in terms of their level of intellectual ability. Some people with Asperger syndrome or high functioning autism are very intelligent academically but they still have difficulties in social and communication skills. In recent years, many of these pupils are taught within mainstream schools. However, the process of facilitating their learning and participation remains a complex and poorly understood area of education. Although many teachers in mainstream schools are firmly committed to the principles of inclusive education, they do not feel that they have the necessary training and support to provide adequately for pupils with ASD. One solution for this problem is to use a virtual tutor to supplement the education of pupils with ASD in mainstream schools. This thesis describes research to develop a Novel Arabic Conversational Intelligent Tutoring System (CITS), called LANA, for children with ASD, which delivers topics related to the science subject by engaging with the user in Arabic language. The Visual, Auditory, and Kinaesthetic (VAK) learning style model is used in LANA to adapt to the children’s learning style by personalising the tutoring session. Development of an Arabic Conversational Agent has many challenges. Part of the challenge in building such a system is the requirement to deal with the grammatical features and the morphological nature of the Arabic language. The proposed novel architecture for LANA uses both pattern matching (PM) and a new Arabic short text similarity (STS) measure to extract facts from user’s responses to match rules in scripted conversation in a particular domain (Science). In this research, two prototypes of an Arabic CITS were developed (LANA-I) and (LANA-II). LANA-I was developed and evaluated with 24 neurotypical children to evaluate the effectiveness and robustness of the system engine. LANA-II was developed to enhance LANA-I by addressing spelling mistakes and words variation with prefix and suffix. Also in LANA-II, TEACCH method was added to the user interface to adapt the tutorial environment to the autistic students learning, and the knowledge base was expanded by adding a new tutorial. An evaluation methodology and experiment were designed to evaluate the enhanced components of LANA-II architecture. The results illustrated a statistically significant impact on the effectiveness of LANA-II engine when compared to LANA-I. In addition, the results indicated a statistically significant improvement on the autistic students learning gain with adapting to their learning styles indicating that LANA-II can be adapted to autistic children’s learning styles and enhance their learning