4 research outputs found
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
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
A framework for developing a conversational agent to improve normal age- associated memory loss and increase subjective wellbeing
Research has developed a baseline conversational agent (CA)
framework that experiments suggest may improve normal ageing
memory problems and increase Subjective Wellbeing (SWB) in
participants aged 60+ with normal age-associated memory loss.
In 2008, 1.3 million people in the United Kingdom were aged 85+, this
figure is projected to reach 3.3 million by 2033 (Morse, 2010). Thus, as
the population profile changes, ageing memory impairment problems will
become acuter (Morse, 2010). The number of people worldwide with
diagnosed clinical memory problems is expected to double every 20
years to 66 million by 2030 and 115 million by 2050 (Casey et al., 2016,
Prince et al., 2013). Improving memory impairment reduces distress for
individuals and enhances wellbeing and independence (Dorin, 2007);
(Wagner et al., 2010). The quality of life in old age can be improved by
increasing SWB (George, 2010) that is concerned with how people
experience the quality of their lives and includes both emotional
reactions and cognitive judgments (George, 2010).
Experiments performed as part of the pilot study suggested evidence of
increased SWB and improved memory after use of the CA. To
support these early findings, modification to the agent and further
experimentation was undertaken. Further work enhanced the
preliminary work that was carried out and provided the opportunity to
run further, more in-depth evaluations of the CA as both a
reminiscence aid and as an improver of SWB.
This PhD study applied for and gained ethical approval (SE111219) from
the Faculty of Science & Engineering Ethics Committee, Manchester
Metropolitan University on 25 October 2012
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