• Asia pacific journal of information systems
• /
• v.16 no.1
• /
• pp.1-21
• /
• 2006

e-Learning can be seen as not only one of Internet-based information technologies which can provide education services but also one of teaching-learning methods which can implement self-directed learning. Thus, for evaluation of e-Learning effectiveness, both information-technology-based learning environment and learners' abilities in self-learning and computer-using should be considered simultaneously. This study suggests a research model for evaluating the effectiveness of e-Learning, which is theoretically based on information systems success model, constructivism and self-efficacy. The model is composed of three parts: effectiveness, learning environment, and learners' self-efficacy. Effectiveness is a part of dependent variables: satisfaction and academic performance. Learning environment and learners' self-efficacy can be considered as two sets of explanation variables for effectiveness. The former consists of learning management system, learning contents, and interactions that are provided bye-Learning and the latter means learners' self-regulated efficacy and computer self-efficacy. We show validity of the model empirically by surveying the college students who have experienced e-Learning. In result, most of all hypotheses suggested in this model are accepted in low significant level.

• Journal of Information Technology Services
• /
• v.20 no.4
• /
• pp.129-140
• /
• 2021

Recently, interest in AI tutors is rising as a way to bridge the educational gap in school settings. However, research confirming the effectiveness of AI tutors is lacking. The purpose of this study is to explore how effective learner characteristics and recommended item learning activities are in predicting learner's academic performance in an adaptive online learning environment. This study proposed the hypothesis that learner characteristics (prior knowledge, midterm evaluation) and recommended item learning activities (learning time, correct answer check, incorrect answer correction, satisfaction, correct answer rate) predict academic achievement. In order to verify the hypothesis, the data of 362 learners were analyzed by collecting data from the learning management system (LMS) from the perspective of learning analytics. For data analysis, regression analysis was performed using the regsubset function provided by the leaps package of the R program. The results of analyses showed that prior knowledge, midterm evaluation, correct answer confirmation, incorrect answer correction, and satisfaction had a positive effect on academic performance, but learning time had a negative effect on academic performance. On the other hand, the percentage of correct answers did not have a significant effect on academic performance. The results of this study suggest that recommended item learning activities, which mean behavioral indicators of interaction with AI tutors, are important in the learning process stage to increase academic performance in an adaptive online learning environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.4
• /
• pp.78-96
• /
• 2023

Urban traffic information is collected by various systems such as VDS, DSRC, and radar. Recently, with the development of deep learning technology, smart intersection systems are expanding, are more widely distributed, and it is possible to collect a variety of information such as traffic volume, and vehicle type and speed. However, as a result of reviewing related literature, the performance evaluation criteria so far are rbs-based evaluation systems that do not consider the deep learning area, and only consider the percent error of 'reference value-measured value'. Therefore, a new performance evaluation method is needed. Therefore, in this study, individual error, interval error, and overall error are calculated by using a formula that considers deep learning performance indicators such as precision and recall based on data ratio and weight. As a result, error rates for measurement value 1 were 3.99 and 3.54, and rates for measurement value 2 were 5.34 and 5.07.

• Journal of Cadastre & Land InformatiX
• /
• v.46 no.2
• /
• pp.297-312
• /
• 2016

The current government strives to train those supposed to drive the national economy, and bridge the gap between qualification and industrial sites through competency-based qualification systems, not the educational background. In this regards, the government is planning to adopt the course evaluation qualification system. The course evaluation qualification system, on a basis of the NCS, is a system to qualify certain people completing the education and training fulling a specific requirement for a national technical qualification in case they meet the internally and externally assessed criteria. This can be seen as an attempt to practically link between job training and qualifications. The NCS model and learning module in the cadastral field are already utilized as the training and eduction in the specialized school and colleges. However, the current national technical qualification system is considered as a main system because the course evaluation qualification system has not been introduced yet. This study analyzed the process of the course evaluation qualification system, and conducted a survey to solicit feedback on introduction of course evaluation qualification system, Besides, the NCS evaluation model is presented in order for the introduction of course evaluation qualification system in the cadastral fields.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.694-698
• /
• 2004

In this paper, as one of these efforts for making the intelligent data mining system we propose the Associative frame of the memory according to the following three steps. First,the structured frame for performing the main brain function should be made. In this frame, the concepts of learning memory and episode memory are considered. Second,the learning mechanism for data acquisition and storing mechanism in the memory frame are provided. The obtained data are arranged and stored in the memory following the rules of the structured memory frame. Third, it is the last step of processing the inference and knowledge retrieval function using the stored knowledge in the associative memory frame. This system is applied to the area for estimating the purchasing degree from the type of customer's tastes, the pattern of commodities and the evaluation of a company.

• Genomics & Informatics
• /
• v.2 no.2
• /
• pp.99-106
• /
• 2004

In this paper we introduce PubMiner, an intelligent machine learning based text mining system for mining biological information from the literature. PubMiner employs natural language processing techniques and machine learning based data mining techniques for mining useful biological information such as protein­protein interaction from the massive literature. The system recognizes biological terms such as gene, protein, and enzymes and extracts their interactions described in the document through natural language processing. The extracted interactions are further analyzed with a set of features of each entity that were collected from the related public databases to infer more interactions from the original interactions. An inferred interaction from the interaction analysis and native interaction are provided to the user with the link of literature sources. The performance of entity and interaction extraction was tested with selected MEDLINE abstracts. The evaluation of inference proceeded using the protein interaction data of S. cerevisiae (bakers yeast) from MIPS and SGD.

• Journal of The Korean Association of Information Education
• /
• v.4 no.2
• /
• pp.232-240
• /
• 2001

The aim of this study was to develop the performance evaluation processing system in elementary schools. First of all, the researcher reviewed theoretical aspects of performance evaluation. Fuzzy was used to devise the system for learning course. The performance evaluation processing system has been applied to Practical Arts Subject in elementary schools, from which good results were obtained.

• The Transactions of the Korea Information Processing Society
• /
• v.5 no.6
• /
• pp.1583-1592
• /
• 1998

Recently, massive amount of infonnation is provided for the internet users. So users want to search information on Internet, but it is difficult to search information what you want. In this paper, we propose a personal Web-agent system using Case-based learning, Web-Guide. Web-Guide consists of two sub-system, interface-system and learning-system. Interface-system operates other web-browser nearly the same and connects user to system. And interface-system transfer datas of current page to learning-queue. Learning-system visit and evaluate the value of each page in learning-queue using evaluation-function that gave weight values occupied by analyzing tag used the character of HTML document. After all users who are known about artificial intelligence well and not made experiments by using Web-Guide, they reached their desired sites faster than before.

• Journal of Practical Engineering Education
• /
• v.16 no.3_spc
• /
• pp.309-325
• /
• 2024

The purpose of this study was to develop self-evaluation criteria for objective verification and performance analysis of LINC 3.0. To achieve this goal, evaluation indicators in the fields of human resources development and skill development and commercialization were developed and their validity was verified. We investigated previous evaluation-related studies and similar cases to construct an evaluation model and system and develop indicators. The validity of the developed evaluation indicators was secured through two round Delphi surveys. As a result of the research, LINC 3.0 evaluation indicators can be divided into the field of human resources development and skill development and commercialization. A total of 66 evaluation indicators were developed. CIPP in the field of human resources development was developed with 13 categories and 38 evaluation indicators, and CIPP in the field of skill development and commercialization was developed with 12 categories and 28 evaluation indicators. The significance of this study is that it suggests a way to increase the objective verification and validity of the university industry-academia cooperation model by developing self-evaluation indicators for the LINC 3.0 project. The evaluation indicators developed in the research need to be continuously upgraded based on field usability, and it is necessary to improve the quality and competitiveness of university education by sharing and spreading excellent affairs.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.12
• /
• pp.5531-5540
• /
• 2011

The Learning Models including the design principle about web 2.0 use in education has been recently presented. In types of web 2.0 tools, blogs are the best tool that reflected the trends of web 2.0 and these are able to share a lot of information and contents. To invent new learning methods involving web 2.0, this study aims to get the results about effectiveness of learning performance on a supplementary learning tool based on blog using learner-centric UI/UX design in higher education. As a study tool, installation-type blog that can be designed as user-centric system is applied to experimental environment. This study presents the conclusion that supplementary learning tool based on blog using learner-centric UI/UX design influences on learning achievement and learning flow through the analysis of questionnaire results of learners, learning evaluation score of learners and assignments evaluation score of learners.