Digital content management of Heet Sib Sorng custom for semantic search

This research presents the results of the alteration knowledgeable following the instruction of the digital content management by semantic technology development. The boundary of this research consists of the integration of the opportunities provided by the existing ontology and two datasets with the resources having different contents, including the datasets from the central library, physical and electronic data, and the development of semantical web approaches in ontology. In this research, research and development methodology is used and the data were acquired through literature review. This research shows that the ontology and applications evaluated are high level, and that there is an inclination for integrated systems oriented towards digital content management in the Thai custom semantic search system, which finally bring to the convergence of linked data and knowledge-based system

A Learning Model for Cultivating Self-Awareness on Human Decision-Making in an Emergency Situation

People may have knowledge to handle a certain situation; however, often they might not be able to perform their behaviour well when encountering the actual situation. There are knowledge-to-action gaps that make ones do not aware the existing knowledge and act improperly. This research aims to motivate learner to become aware of their thought by proposing 1) a learning model using “surprise” as a trigger for motivating learner to realize their thinking process; and 2) a Relax-Half-Baked Microworld and its decision-making model which are used as a simulated environment. Learners could modify parameters, anticipate expected outcomes and compare observed simulated outcomes with their expected ones. Learners would feel surprise from unexpected results in the comparison, and used it to reflect their thought and to be aware of how did they make decision

Effectiveness of E-Learning Design in Thai Public Schools

Purpose –This study examined the effectiveness of e-learning content design by considering two different subjects (mathematics and reading) and areas (metropolitan and rural). This study also investigated several variables, i.e., students’ satisfaction, motivation and experience, that influenced learning abilities. Moreover, we suggested ways of improving the effectiveness of e-learning for different kinds of students, subjects, and areas.Methodology – The participants were recruited from 263 randomly selected students in secondary school grades 9-10 (15year-olds). One hundred and thirty-eight students were from a public metropolitan school in Bangkok province, and 125 were from a public rural school in Suphanburi province. Pilot testing was conducted to confirm the reliability, validity, and internal consistency of the program and the exam questions, followed by field testing methods, which was used to identify the effectiveness of content design. Data analysis involved a quantitative research approach using a paired t-test to find the difference in scores between the pre- and post-tests. Analysis of variance (ANOVA) was used to analyse and find the relationships between improvements in scores and variables. Findings – The results indicated that the selected patterns of content and design were effective in mathematics and reading subjects and in both rural and metropolitan areas. In addition, academic achievement, accumulated grade point average (GPAX), significantly influenced improvements in reading subjects, and the intelligence indicator (IQ) had a significant effect on mathematics subjects in both areas. Furthermore, students’ satisfaction had an effect on learning abilities in most student groups.Significance – This pattern of design content may be significant for both instructors and program designers. This study provided a way of designing effective e-learning content that integrated effective indicators to identify potential students and improve their abilities. The pattern can be integrated with active learning.This blended learning model might be a new solution to solving problems with low-performing students in rural areas

Memory-inductive categorial grammar: an approach to gap resolution in analytic-language translation

This paper presents a generalized framework of syntax-based gap resolution in analytic language translation using an extended version of categorial grammar. Translating analytic languages into Indo-European languages suffers the issues of gapping, because “deletion under coordination ” and “verb serialization ” are necessary to be resolved beforehand. Rudimentary operations, i.e. antecedent memorization, gap induction, and gap resolution, were introduced to the categorial grammar to resolve gapping issues syntactically. Hereby, pronominal references can be generated for deletion under coordination, while sentence structures can be properly selected for verb serialization.