• International Journal of Contents
• /
• v.4 no.2
• /
• pp.19-23
• /
• 2008

This paper presents a novel method to construct a personalized e-Learning system based on dynamic estimations of item parameters and learners' abilities, where the learning content objects are of the same intrinsic quality or homogeneously distributed and the estimations are carried out using IRT(Item Response Theory). The system dynamically connects the test and the corresponding learning procedures. Test results are directly applied to estimate examinee's ability and are used to modify the item parameters and the difficulties of learning content objects during the learning procedure is being operated. We define the learning unit 'Node' as an amount of learning objects operated so that new parameters can be re-estimated. There are various content objects in a Node and the parameters estimated at the end of current Node are directly applied to the next Node. We offer the most appropriate learning Node for a person's ability throughout the estimation processes of IRT. As a result, this scheme improves learning efficiency in web-base e-Learning environments offering the most appropriate learning objects and items to the individual students according to their estimated abilities. This scheme can be applied to any e-Learning subject having homogeneous learning objects and unidimensional test items. In order to construct the system, we present an operation scenario using the proposed system architecture with the essential databases and agents.

• Journal of Practical Engineering Education
• /
• v.12 no.2
• /
• pp.339-351
• /
• 2020

In response to changes in Fourth Industrial Revolution in recent years, the field of education has focused on development of the human resources in the areas of artificial intelligence (AI: Artificial Intelligence) and industrial robot. Due to particular interest in these areas, the importance of developing integrated human resources equipped with artificial intelligence technology is emphasized in higher education and vocational competence development. In regards to rapid changing environment, this study created a program "Fostering personalized AI integrated human resource" and established an operational model correspond to latest personalized education trend. The established operational model was conducted twice using Delphi survey with experts in AI and innovative education in order to verify the suitability of program's basic structure, training process, and the sub-components of the operational strategy. The final training model was applied to the online vocational training platform (STEP) and a plan was proposed to establish a personalized training model to foster an AI integrated competent individual.

• Journal of Practical Engineering Education
• /
• v.11 no.1
• /
• pp.75-86
• /
• 2019

Globally, the change in higher education is gradually moving toward a trend that seeks a change in innovative higher education through the revitalization of digital-based education. Accordingly, this study designed a customized education model based on e-learning that can be used in undergraduate education and development of lifelong vocational skills. The use of online learning platforms and the expansion of education are major factors that change the overall higher education system as the form and content of curriculum changes around the world. In order to establish a customized education model using online learning platform, this study analyzed major overseas advanced education cases and selected the basic direction of customized learning as personalized learning, competency based learning, and training for talents leading the 4th Industrial Revolution. Then, FGI was conducted for undergraduate and lifelong vocational ability development experts. As a result, a customized education model using an online learning platform was derived from a degree-type model available in undergraduate education and a non-degree-type model available in the field of lifelong vocational ability development, and each operation strategy was suggested.