• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.599-601
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• 2009

In currently being adopted as a e-leaning standard, SCORM it is difficult to provide the customized contents to a learner by changing the learner's level at runtime, and to control selective studying. So, we designed and implemented the customized contents organization engine(CCOE) in order to complement SCORM's faults in this paper. The CCOE consists of a level evaluation module, a contents re-organization module and a question item selection module. A level evaluation module evaluates the learner's level based on a question item reaction theory. And a question item selection module selects some random items by each level or by considering the learner's level which is then provided to a studying before evaluation, a section evaluation, and a quiz. And then this module transmits the selected items to the contents reorganization module for providing the quiz. A contents re-organization module selects the customized contents based on the learner's level by searching the tagged difficulty to the content, and creates the sequence with the selected items and the transmitted items from the question item selection module. If proposed in this paper CCOE is applied, the higher effectiveness of learning is expected by providing the customized learning contents based on the re-evaluated learner's level by each section.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3266-3285
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• 2023

With the popularity of online learning, intelligent tutoring systems are starting to become mainstream for assisting online question practice. Surrounded by abundant learning resources, some students struggle to select the proper questions. Personalized question recommendation is crucial for supporting students in choosing the proper questions to improve their learning performance. However, traditional question recommendation methods (i.e., collaborative filtering (CF) and cognitive diagnosis model (CDM)) cannot meet students' needs well. The CDM-based question recommendation ignores students' requirements and similarities, resulting in inaccuracies in the recommendation. Even CF examines student similarities, it disregards their knowledge proficiency and struggles when generating questions of appropriate difficulty. To solve these issues, we first design an enhanced cognitive diagnosis process that integrates students' affection into traditional CDM by employing the non-compensatory bidimensional item response model (NCB-IRM) to enhance the representation of individual personality. Subsequently, we propose an affection-enhanced personalized question recommendation (AE-PQR) method for online learning. It introduces NCB-IRM to CF, considering both individual and common characteristics of students' responses to maintain rationality and accuracy for personalized question recommendation. Experimental results show that our proposed method improves the accuracy of diagnosed student cognition and the appropriateness of recommended questions.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.4
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• pp.431-438
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• 2003

In this study, we have developed a web-based adaptive testing system using item response theory´s computerized adaptive testing to diagnose underachievers, and to check the evaluation results immediately. Adaptive testing system simple is not the fact that it presents a question to students. It calculates information of a question and presents the question to students. It controls the response of the students under extraction conditions of the next question. It extracts the question which is the most suitable it presents. In this adaptive testing system, you can extract questions according to the level of the students, and adjust the length and the level of the difficulty according to the response of the students.

• The Journal of Korean Association of Computer Education
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• v.10 no.3
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• pp.1-8
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• 2007

In this paper, we introduce a new measure called surprisal that estimates the informativeness of transactional instances and attributes in the item response dataset and improve the quality of association rules. In order to this, we set artificial dataset and eliminate noisy and uninformative data using the surprisal first, and then generate association rules between items. And we compare the association rules from the dataset after surprisal-based pruning with support-based pruning and original dataset unpruned. Experimental result that the surprisal-based pruning improves quality of association rules in question item response datasets significantly.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.11-24
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• 2022

For the questions asked for LMS-based online evaluation the professor directly set exam questions, or use the automatic question-taking method according to the level of difficulty using the question bank divided by category. Among them, it is important to manage the difficulty of questions in an objective and efficient way, above all, in the automatic question-taking method according to difficulty. Because the questions presented to the evaluators may be different. In this paper, we propose an difficulty re-adjustment algorithm that considers not only the correct rate of a problem but also the time taken to solve the problem. For this, a logistic regression classification algorithm was used of machine learning, and a reference threshold was set based on the predicted probability value of the learning model and used to readjust the difficulty of each item. As a result, it was confirmed that there were many changes in the difficulty of each item that depended only on the existing correct rate. Also, as a result of performing group evaluation using the adjustment difficulty problem, it was confirmed that the average score improved in most groups compared to the difficulty problem based on the percentage of correct answers.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.43-48
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• 2006

The educational system has been changed owing to Web, which is most actively used on internet and has the characteristics of providing suitable environments for implementing constructivism study theory. WBI(Web Based Instruction), web-mediated teaching form for students at a long distance, has the advantages of possible interact between instructors and learners, offering a great variety of learning materials, and overcome the spatiotemporal restriction. This paper focuces on the construction of learning surroundings where the learner-centered, active learning can be done by design and Implementation of web based instruct system providing a sham examination with an item pool system. The web based Self-directed Learning system for word processor qualifying exams on this paper, can be mentioned as a real item pool that the question is not setting each time by the instructors but can be reused by reference on item pool bank, designed the number of question. It helps the learner Self-directed Learning study with evaluation during the web based instruct process and immediate feedback. It also provides the chance to research some similar using keyword. To sum up, this system can amplify the efficiency of study.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.309-321
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• 2014

Recently, due to the advent of ubiquitous computing and the spread of intelligent portable device such as smart phone, iPad and PDA has been amplified, a variety of services and the amount of information has also increased fastly. It is becoming a part of our common life style that the demands for enjoying the wireless internet are increasing anytime or anyplace without any restriction of time and place. And also, the demands for e-commerce and many different items on e-commerce and interesting of associated items are increasing. Existing collaborative filtering (CF), explicit method, can not only reflect exact attributes of item, but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, using a implicit method without onerous question and answer to the users, not used user's profile for rating to reduce customers' searching effort to find out the items with high purchasability, it is necessary for us to analyse the segmentation of customer and item based on customer data and purchase history data, which is able to reflect the attributes of the item in order to improve the accuracy of recommendation. We propose the method of recommendation system using association rule and weighted preference so as to consider many different items on e-commerce and to refect the profit/weight/importance of attributed of a item. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.

• Journal of Fashion Business
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• v.23 no.3
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• pp.1-9
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• 2019

The purpose of this study was to develop questions for fashion design development, by applying 7 elements of the scamper to the fashion design elements, and to present a scamper checklist of fashion design elements, and item structures. In this study, the scope of research was limited to clothing design among various fashion products, and among various design development stages. Fashion design development focusing on design sketching, was limited to the research scope. The research method was based on an empirical study that derived scamper questions through FGI (Focus Group Interview), consisting of 5 fashion experts. Fashion design elements applied to development of scamper questions consisted of silhouettes, constructive lines, structural details, decorative details, patterns and textures of fabrics, and item structures, derived by applying these elements to the individual 7 elements of the scamper: substitute, combine, adjust, modify, put to other uses, eliminate, and reverse. Results of the study included 7 questions for substituting, 8 questions for combining, 6 questions for applying, 15 questions for modifying, 4 questions for putting to other uses, 4 questions for eliminating, and 7 questions for reversal. The scamper checklist for fashion design elements and item structures drew to 5 lists of silhouette variations, 7 lists of constructive line variations, 11 lists of structural detail variations, 10 lists of decorative detail variations, 11 lists of fabric variations, and 9 lists of structural modifications of items.

• Journal of the Korean Society of Earth Science Education
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• v.9 no.3
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• pp.255-268
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• 2016

The education should adapt learners well to any changes and have them create something for such a era. Form the point of this view. question sheet was developed for middle school students to improve their scientific creativity. For this study, 146 item questions, which was from chapter 7 about solar system movement in the 3rd grade textbook for middle school students, was developed. For 5 weeks, 142 third graders in middle school were chosen and observed. They were divided into an experimental group and a control group. The teaching model using question sheet was applied to the experimental group, while the traditional teaching model, to the control group. This study compared two groups based on scientific creativity and academic achievement. In both scientific creativity and academic achievement, the group using question sheet showed meaningful differences. This result of the analysis indicated that teaching model using question sheet stimulated student's creative thinking and helped them to achieve a goal of lesson. The teaching model using question sheet can be used as an effective way to increase students' creativity.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1319-1329
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• 2013

The purpose of this research was to develop and validate the coach-athlete relationship scale suitable to amateur golf players by applying the Rasch rating scale model. As the coach-athlete relationship scale, the Korean form of scale developed by Kim and Park (2008), which was revised based on the evidence on the basis of inspection contents, was used to conduct a survey on 217 amateur golf athletes. And the unidimensionality, which is the basic assumption of the Rasch model, was verified using the WINSTEPS program, and the appropriateness of the item category was established through the step calibration. The goodness of fit of each question was tested through the goodness-of-fit index and the differential item functioning (DIF) was estimated according to the golf career. When the goodness-of-fit index estimated for each question was 1.30 or more it was judged unfit and the significance level in the analysis was all set as.05. The results of the analysis showed that the measures variance explained by the Rasch measurement model was more (33.7%) than 20%, so the unidimensionality assumptions of the 11 questions (..hospitable posture when my coach is teaching) were satisfied. The result of analyzing the item category (7 scale) with step calibration was found to be unfit, but in the result of reanalyzing by rescoring into a 5-point scale, it was found to be fit. Particularly, in the result of estimating the goodness-of-fit using the systematized item category (5 scale), Question 10 (...my best when my coach is teaching) and Question 11 were found to be unfit, and as a result of estimating the differential functioning item according to golf career, Question 11 was found to be unevenly differentiated according to golf career. So the 5-point scale of Question 9 after eliminating the two questions which were unfit and differentiated was validated to be the coach-athlete relationship scale suitable to amateur golf athletes.