• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.316-324
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• 2005

e-Learning has been mushrooming with wide range of teaming groups from pedagogy to andragogy As e-teaming opportunities increase, many people raise question about whether e-teaming show positive teaming effects. The related research emphasized that e-learning would be a failure in terms of understanding of e-Learners and activating intuitive teaming activities from learner's long-term memory span. The e-teaming strategies based on the traditional classroom and resulted boring and ineffective teaming outcomes, should be changed to provide authentic and effective teaming results. This paper analyzed that how learners have received e-Learning for the last few years from the research and explained what could be the failing aspects in e-Learning. To be successful, e-loaming should consider the e-learner's individualized teaming style and thinking patterns. When considering of various e-Learning components, the quality of e-teaming should not be focused on any specific single factor, but develop every individual factor to be integrated into high level of quality. In conclusion, this paper suggest that it is needed new understandings of e-Loaming and e-Learner. Also the e-Learning strategies should be examined throughly whether they are on the side of learners and realized how they learn from e-Learning. Finally, we should add enormous imagination into e-loaming for next generation because new generation's teaming patterns significantly differ from their parent's generation.

• School Mathematics
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• v.10 no.2
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• pp.259-277
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• 2008

Conventional assessments only provide a single summary score that indicates the overall performance level or achievement level of a student in a single learning area. For assessments to be more effective, test should provide useful diagnostic information in addition to single overall scores. Cognitive diagnosis modeling provides useful information by estimating individual knowledge states by assessing whether an examinee has mastered specific attributes measured by the test(Embretson, 1990; DiBello, Stout, & Rousses, 1995; Tatsuoka, 1995). Attributes are skills or cognitive processes that are required to perform correctly on a particular item. By the results of this study, students, parents, and teachers would be able to see where a student stands with respect to mastering the attributes. Such information could be used to guide the learner and teacher toward areas requiring more study. By being able to assess where they stand in regard to the attributes that compose an item, students can plan a more effective learning path to be desired proficiency levels. It would be very helpful to the examinee if score reports can provide the scale scores as well as the skill profiles. While the scale scores are believed to provide students' math ability by reporting only one score point, the skill profiles can offer a skill level of strong, weak or mixed for each student for each skill.

• Journal of Engineering Education Research
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• v.18 no.2
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• pp.77-88
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• 2015

Recently, there has been an increasing interest in 'Flipped Learning,' an IT-based learner-centered teaching-learning method corresponding to meet the paradigm of the future education. For smooth Flipped Learning, there are three steps in total: a pre-class should precede; then, in the structure of classes in the classroom, in-class learning among peer learners should be done; and lastly, the operation of a post-class should be done. For successful Flipped Learning, class elements in each step should be designed with a time difference, interconnected so as to achieve a single educational objective. However, it was found that there was a limitation in that the teaching-learning model of the preceding Flipped Learning consisted of the order of analysis, design, development, implementation and evaluation as general procedures, so it would not sufficiently consider the situations of Flipped Learning only. On this background, this thesis proposes a differentiated Flipped Learning model for mastery learning in a subject of an institute of technology as a model of systematic instructional design and presents a case of a class applied to an actual subject of computer engineering.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.2
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• pp.135-139
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• 2009

We present a new ensemble learning method that employs the set of region experts, each of which learns to handle a subset of the training data. We split the training data and generate experts for different regions in the feature space. When classifying a data, we apply a weighted voting among the experts that include the data in their region. We used ten datasets to compare the performance of our new ensemble method with that of single classifiers as well as other ensemble methods such as Bagging and Adaboost. We used SMO, Naive Bayes and C4.5 as base learning algorithms. As a result, we found that the performance of our method is comparable to that of Adaboost and Bagging when the base learner is C4.5. In the remaining cases, our method outperformed the benchmark methods.

• Journal of muscle and joint health
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• v.29 no.3
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• pp.185-193
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• 2022

Purpose: This study aims to provide basic data for future nursing education by identifying the effects of flipped learning-type project-based learning on nursing college students' self-directed learning ability, self-leadership, and academic self-efficacy. Methods: It is a pre-experimental study designed before and after a single group to verify the effect of flipped learning project-based learning on nursing students' self-directed learning ability, self-leadership, and academic self-efficacy in 81 third-grade nursing students. Results: No statistically significant difference in self-efficacy (t=-0.80, p=.545) but self-directed learning ability (t=-3.85, p<.001) and self-leadership (t=-5.18, p<.001) were found to have a statistically significant difference before and after. Conclusion: Flipped learning-type project-based learning was confirmed effective in improving nursing college students' self-directed learning ability and self-leadership. Therefore, instructors will need to develop and apply teaching methods that provide learners with opportunities for pre-learning and carry out learner-centered projects to improve nursing college students' self-directed learning ability and self-leadership.

• Educational Technology International
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• v.13 no.1
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• pp.145-173
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• 2012

The purpose of this study is to develop collaboration scripts as an instructional means to facilitate argumentation in computer-supported collaborative learning, and to analyze their effects. To develop collaboration scripts for argumentation, researchers used activity theory as a conceptual framework and refined the design principles by design-based research. Using LAMS, collaboration scripts for argumentation were developed based on the ArgueGraph. To examine their effects, 72 participants were divided into two groups by internal scripts and randomly allocated to one of three external scripts. Applying mixed methods, researchers analyzed argumentation competence related to the cognitive aspect, examined self-efficacy related to the motivational aspect, and identified the factors influencing collaborative learning processes and outcomes. Researchers found that the internal script is a critical factor to determine the dimensions, degrees, and duration of improvement in argumentation competence. That is, learners with higher internal scripts improved highly in the quality of single arguments, while learners with lower internal scripts improved continuously in the quality of argumentation sequences. The effects of the external scripts varied with the internal script levels and supporting periods. Besides, collaboration scripts for argumentation had positive effects on learners' self-efficacy, and learners with higher internal scripts had better self-efficacy. The factors influencing collaborative learning processes and outcomes showed different results depending on the learning context. Therefore, when scripting learner's interaction in CSCL, researchers should design the scripts adaptable to a natural context of activities.

• Journal of Science Education
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• v.40 no.1
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• pp.17-30
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• 2016

The purpose of this study was to investigate the effects of problem solving activities of STEAM program on metacognition of middle school students. The subject was 63 middle school students. This study was designed single group pre-posttest. A single-group t-test was performed for analyzing difference between the pre-post test on metacognition. In the result of this study, there was significant difference between pretest and posttest on middle school students' metacognition. Also there was significant difference on metacognitive knowledge and metacognitive regulation. The analysis on the subelements of metacognition showed significant difference between pretest and posttest. The multiple regression analysis to investigate the relation of sub-elements of metacognition was performed in this study. The result of the analysis showed high explanatory power among metacognition subelements. This result suggests that the problem solving activities of STEAM program can have a positive effect in promoting metacognition. of the learner.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.108-114
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• 2019

In this paper, we propose an intelligent vocabulary recommendation agent that automatically provides vocabulary corresponding to game-based learners' needs and requirements in the mobile education augmented reality game environment. The proposed agent reflects the characteristics of mobile technology and augmented reality technology as much as possible. In addition, this agent includes a vocabulary reasoning module, a single game vocabulary recommendation module, a battle game vocabulary recommendation module, a learning vocabulary list Module, and a thesaurus module. As a result, game-based learners' are generally satisfied. The precision of context vocabulary reasoning and thesaurus is 4.01 and 4.11, respectively, which shows that vocabulary related to situation of game-based learner is extracted. However, In the case of satisfaction, battle game vocabulary(3.86) is relatively low compared to single game vocabulary(3.94) because it recommends vocabulary that can be used jointly among recommendation vocabulary of individual learners.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1773-1793
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• 2023

Automated machine learning, often referred to as "AutoML," is the process of automating the time-consuming and iterative procedures that are associated with the building of machine learning models. There have been significant contributions in this area across a number of different stages of accomplishing a data-mining task, including model selection, hyper-parameter optimization, and preprocessing method selection. Among them, preprocessing method selection is a relatively new and fast growing research area. The current work is focused on the recommendation of preprocessing methods, i.e., feature subset selection (FSS) algorithms. One limitation in the existing studies regarding FSS algorithm recommendation is the use of a single learner for meta-modeling, which restricts its capabilities in the metamodeling. Moreover, the meta-modeling in the existing studies is typically based on a single group of data characterization measures (DCMs). Nonetheless, there are a number of complementary DCM groups, and their combination will allow them to leverage their diversity, resulting in improved meta-modeling. This study aims to address these limitations by proposing an architecture for preprocess method selection that uses ensemble learning for meta-modeling, namely AutoFE-Sel. To evaluate the proposed method, we performed an extensive experimental evaluation involving 8 FSS algorithms, 3 groups of DCMs, and 125 datasets. Results show that the proposed method achieves better performance compared to three baseline methods. The proposed architecture can also be easily extended to other preprocessing method selections, e.g., noise-filter selection and imbalance handling method selection.

• Journal of Service Research and Studies
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• v.6 no.2
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• pp.175-184
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• 2016

The educational computer game service, due to its entertainment role, is a very attractive tool for students to raise their interests in learning. Especially mathematics, the most difficult subject for many students, is one of the typical subjects in which the educational computer game service can be efficiently applied. Most of the previous game services is for single or two learners. And learner only have to simply submit a solution for the proposed math expression in the game. In this paper a multi-player game service based on TCP/IP socket programming technique is designed and implemented to join in the game for multiple learners. In addition, we design a game rule to improve learners' number sense by letting them arrange various ways to solve the problem. Finally, using the requirements of educational game service, we evaluate the proposed game service and its usability.