Designing dietary menu planning is a complex problem-solving task. It involves several constraints and extensive common sense. Case-based reasoning (CBR) solves the complexity by storing an expert common sense in the case base. Case adaptation (CA) is important for design task using CBR since old cases are partially similar as a current one. An automatic CA mainly focused on the processing level rather than at the data level. On the other hand, semantic technology (ST) inserts the intelligence features by shifting the focus on the application code to the data. This can leverage the burden on the logical processing of adaptation engine. Ontology is a prerequisite in ST. Thus, this research proposes a computational model of design CA using an ontological approach. This paper discusses the experience we gained during the process of ontology modelling based on the OD101 method. The Malaysian food ontology was successfully developed to make the domain assumptions explicit in supporting the reasoning process of case adaptation for dietary menu planning recommendation.

This paper presents our findings of an evaluation study conducted to gauge the effectiveness of a design pattern application tool (DPACoach) in providing the needed support to novices. The tool has been designed around the actual difficulties encountered by novices when applying pattern solution to a design problem. The data indicates improvement in novices' performance after they have been given the time to interact with DPACoach. Performance is measured in terms of their ability to select the right patterns, the number of application errors and the total time spend to complete pattern application tasks.

Accessing and extracting semantic meanings from web documents is crucial for the realization of Semantic Web. While the web offers the flexibility of making information easily available, it is considerably hard to find a fruitful way to describe, classify and present this information with rich semantic content. Therefore, the semantic information content of web documents need to be specified in order to make the tangled information more accessible to search engines and other applications. In this paper we propose an approach meant to assist in constructing semantic document models using natural language analysis technique and a domain specific ontology.

Mathematics is an important subject for science and technological careers but many children still have difficulties and failures in mathematics learning. Therefore, educational design for effective learning and teaching environment is important in the prevention and remediation of mathematical learning difficulties. Since individuals differ in cognitive ability (intelligence), prior knowledge and the way they perceive and process information or learning styles, adapting instruction to these differences will facilitate learning and thus help increase learning gains especially for low and moderate achieving students. Information Technology, in the form of courseware can be used effectively to individualize instruction. We are developing a learning style inventory to identify student's learning styles and propose a multimedia tutor that can adapt instruction to learner's styles and ability level for secondary school mathematics.

Automated database design tools employ knowledge-based systems technology in order to provide intelligent support to humans during the process of database analysis and design. However, the level to which these tools can simulate the diagnostic capabilities of human designers when performing a design task remains in question. Human designers employ what might be called "knowledge of the real world" in carrying their design activities; such knowledge is employed by only a few automated database design tools. Therefore, in recent years, there have been a number of attempts to develop tools that are capable of exploiting such real-world knowledge. It has been claimed that the use of such knowledge has the potential to increase the diagnostic performance of automated database design tools. However, to date, little if any formal exploration and validation of this claim has taken place. This paper presents our activities in exploring and validating the implications for exploiting three approaches facilitating the use and exploitation of real-world knowledge in the diagnostic performance of database design tools. The results obtained have demonstrated that the improvement of certain aspects of diagnostic performance has been achieved. However, the extent to which these aspects have been attained and subsequently statistically validated varies.