(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 4, No. 3, 2013 125 | Page www.ijacsa.thesai.org Diagnosing Learning Disabilities in a Special Education by an Intelligent Agent Based System Khaled Nasser elSayed Computer Sciences Department, College of Computer and Information Systems, Umm-AlQura University Makkah AlMokaramah, Saudi Arabia Kingdom Abstract—The presented paper provides an intelligent agent based classification system for diagnosing and evaluation of learning disabilities with special education students. It provides pedagogy psychology profiles for those students and offer solution strategies with the best educational activities. It provides tools that allow class teachers to discuss psycho functions and basic skills for learning skills, then, performs psycho pedagogy evaluation by comprising a series of strategies in a semantic network knowledge base. The system’s agent performs its classification of student’s disabilities based on its past experience that it got from the exemplars that were classified by expert and acquired in its knowledge base. Keywords—Intelligent Agent; Learning Disabilities; Special Education; Semantic Network; Psych Pedagogy Evaluation; Exemplar Based Classification I. INTRODUCTION Educational software programs in science education have become increasingly complex in both concept and design. Thus, there is a paradigm shift in the role of computer from solely a transmitter of knowledge to a tool that aids in the construction of knowledge. This is due to the fact the science concepts are abstracts, as in [1]. Students in a special mental education have disabilities in their learning, especially in the basic education. They need psycho pedagogy evaluation as a strategy for analyzing problems that children may have in the teaching-learning process. This evaluation can be done manually by specialists and professionals in the special education, who are sometimes not enough in the special education schools. Class teachers, who are always, keeping track of students whose learning is not as expected. This student should be evaluated by a specialist, who diagnose the case and specifies reasons of that problem. If possible, the specialist also determines strategies that should be applied on that case to help in decreasing his LDs. In the time being, Artificial Intelligence algorithms, techniques, and applications have wide use in education and tutoring systems. One of the AI techniques is the intelligent agent, which can be used in education. An intelligent agent is an autonomous calculated entity. In the dynamic changes information environment without prior modeling, it can independently plan complex operation steps to solve practical problems, can independently discover and obtain the available resources the learners needed and then provide the corresponding services under the circumstance that the learners do not take part in [13]. Currently, the state of intelligent is focused on one-to-one learning instruction. Some examples include ACT systems [1], DEBUGGY [2], and PIXIE [11] and. specifically, the kind of learning modality used is centered on learning by being told [3]. The agent has to collect users' personal interests and give fast response according to the pre-specified demands of users. The personal agent can discover users' personal interests voluntarily without bothering the users. It is very suitable for personalized e-learning by voluntarily recommending learning materials [7]. An agent is something that perceives and acts in an environment. The agent function for an agent specifies the action taken by the agent in response to any percept sequence as in [10]. Intelligent agents are task-oriented software components that have the ability to act intelligently. They may contain more knowledge about the needs, preferences and pattern of the behaviors of a person or a process as in [8]. Intelligent agents should have the ability of adaptive reasoning. They must have the capability to access information from other sources or agents and perform actions leading to the completion of some task. Also, they must control over their internal state and behavior and work together to perform useful and complex tasks. Thus, they should be able to examine the external environment and the success of previous actions taken under similar conditions and adapt their actions as in [9]. According to the observation and implementation of unstructured interviews with specialist in the special basic education institute (in a primary school in Makkah AlMokaramah area, Saudi Kingdom), it was evident that most institutes have a few specialist staff in LDs, not providing an efficient care to all students who have special educational needs. The presented paper proposes a framework design for an Intelligent Agent Based classification System. It provides a methodology for the design and development of an intelligent agent-based system for diagnosing of learning and disabilities with children in special education. Regarding that those students spend most of their times with their classroom teacher, it is desirable that he can diagnose