• Educational Technology International
• /
• v.10 no.1
• /
• pp.1-23
• /
• 2009

Learners are often posited in a paradoxical situation where they are not fully involved in decision making processes on how to learn, in designing their tools. Cognitive artifacts in e-learning are supposed to effectively support learner-centered e-learning. The purpose of the study is to analyze cases of cognitive artifacts and to inquire those design principles for facilitating the learner-centered e-learning. Four research questions are suggested: First, it will be analyzed the characteristics of learners with respect to design of cognitive artifacts for supporting the learner-centered e-learning. Second, characteristics of four cases to design cognitive artifacts in learner-centered e-learning environment are analyzed. Third, it will be suggested the appropriate design principles of cognitive artifacts to facilitating learner-centered learning in e-learning environment. Four cases of cognitive artifacts design in learner-centered e-learning was identified as follows: Wiki software as cognitive artifacts in computer-supported collaborative learning; 'Play Around Network (PAN)' as cognitive artifact to monitor learning activities in knowledge community; Knowledge Forum System (KFS) as a cognitive artifact in knowledge building; cognitive artifacts in Courses-as-seeds applied meta-design. Five design principles are concluded as follows: Promoting externalization of cognitive artifacts to private media; Helping learners to initiate their learning processes; Encouraging learners to make connections with other learners' knowledge building and their cognitive artifacts; Promoting monitoring of participants' contributions in collaborative knowledge building; Supporting learners to design their cognitive artifacts.

• Journal of the Korea Convergence Society
• /
• v.13 no.4
• /
• pp.39-44
• /
• 2022

Mathematics franchise education companies are developing various online learning systems to provide on-off integrated education to learners. Most online learning systems deliver one-way lecture content to learners and perform quantitative problem-solving learning for learning results. However, each learner has different academic achievement competencies, and it is impossible to determine exactly where the level of understanding fell when solving a math method. and based on this, establish an online learning system to discover the weak points of learners and propose an effective learner management method. Through the developed learning method and system, it is expected to cultivate balanced problem-solving ability for learners and provide differentiated brand image and counseling service to franchise companies.

• Journal of IKEEE
• /
• v.27 no.4
• /
• pp.537-547
• /
• 2023

In many domains, lack of data inhibits adoption of advanced machine learning models. Recently, Few-Shot Learning (FSL) has been actively studied to tackle this problem. Utilizing prior knowledge obtained through observations on related domains, FSL achieved significant performance with only a few samples. In this paper, we present a survey on FSL in terms of data augmentation, embedding and metric learning, and meta-learning. In addition to interesting researches, we also introduce major benchmark datasets. FSL is widely adopted in various domains, but we focus on image analysis in this paper.

• Educational Technology International
• /
• v.10 no.2
• /
• pp.127-143
• /
• 2009

The purpose of this study was to identify the interaction patterns in distance only mode e-Learning. In order to investigate this study, messages shown in the electronic notice board were analyzed to see how interaction occurs between teacher and learner or learner and learner under the e-learning of cyber university. To analyze messages was applied according to the framework by Henri's contents analysis model. As a result of contents analysis on electronic board, the participative dimension was 399 messages. A learner put on 7~8 messages a day. The number of messages was low compared to the number of learners, but the number of inquiries was about 140. That means that each learner contacts and checks messages at least once a day. The meaning dimension was 600 units. The main interaction patterns were Interactive-social-cognitive-metacognitive. This means that e-Learning in distance only mode leads a positive attitude of learners as a self-directed learning, and needs teacher's well-structured instructional strategies for increasing interaction. In conclusion, social dimension and interactive dimension of messages support learners psychologically in the process of learning though they directly guide learning under the circumstances of e-learning lacking face-to-face element. It can be interpreted that the teacher's role is significantly important in order to attract learners' positive participation and cognitive and meta-cognitive dimension of messages and activities

• International Journal of Advanced Culture Technology
• /
• v.12 no.3
• /
• pp.449-465
• /
• 2024

This study conducted a systematic literature review using online databases to investigate the effective feedback types that enhance the learning experiences of online students. Feedback is a critical component for learner success. With the expansion of online education, the importance of feedback has become more evident due to the reduced interaction between instructors and learners. Instructors must provide high-quality feedback that motivates learners and supports their educational goals. This involves using automated tools appropriate for the environment and effective feedback strategies to deliver personalized feedback. The literature was gathered through an extensive search process, adhering to predetermined inclusion and exclusion criteria, and included a risk assessment of selected studies, drawing from sources such as Google Scholar, Elsevier, and other Scopus-indexed journals. The review adhered to the guidelines set forth by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Specific keywords related to the study's focus, including "Online learning," "Improving learning," "Learner performance," "Feedback type," and "Feedback," guided the database searches. The protocol for selecting systematic reviews on learning enhancement involved screening articles published from 2013 to 2021 based on their titles and abstracts according to established criteria. Analyzing and studying data on learning patterns in non-face-to-face educational environments can improve learners' needs and educational effectiveness. Selecting the right types of feedback, taking into account the learners' levels and educational objectives, is crucial for providing effective feedback. A variety of feedback types are essential for the continuous improvement of learners' learning.

• The Journal of the Korea Contents Association
• /
• v.10 no.1
• /
• pp.486-497
• /
• 2010

The purpose of this study is to investigate the research trends and the present conditions of real digital texts on "Visual Transformation." For the purpose of this study adopted two different methods: meta analysis and case study. The research trends on visual transformation of digital text were investigated through analyzing the total of 167 literature by means of synthetic meta analysis. Relevant literature was categorized into three types of research: functional, dynamic, and interactional transformation. The type of literature and research methods in each literature were analyzed. The present conditions of real digital texts on visual transformation were investigated by means of case study. The well designed 12 e-learning contents selected and analyzed in terms of the analysis framework which was drawn by the research trends. The results suggested problems as follows in designing e-learning contents. Firstly, there were some cases that did not follow the basic design principles related to typography. Secondly, the content was just provided in each learning steps without consideration of design to enhance text comprehension in many cases. Thirdly, web technology adequately was not applied to design e-learning contents.

• Journal of Gifted/Talented Education
• /
• v.19 no.3
• /
• pp.457-476
• /
• 2009

The research aimed to investigate characteristics of middle school students in a biology class as science gifted education in terms of self-regulated learning abilities, personality traits and learning preferences. The twenty subject in the study responded to questionnaires of a self-regulated learning ability instrument, a personality trait tool, and a learning preference survey in March, 2009. It was found that the research subjects showed higher levels of cognitive strategies, meta-cognition, and motivation than those students in a previous study(Jung et. al., 2004), while environment was opposite. The level of cognitive strategies was significantly correlated with meta-cognition(r=.610, p=.004) and motivation (r=.538, p=.014) and meta-cognition with environment(r=.717, p=.000). Those students who showed highest levels of self-regulated learning ability displayed various personality traits. One male student with the highest level of self-regulated learning ability showed a personality of hardworking, tender-minded, and conscientious traits and wanted to be a medical doctor. The female student with the second highest level of self-regulated learning ability presented a personality as creative, abstract and divergent thinker and she showed a strong aspiration to be a world-famous biologist with breakthrough contribution. The five students with highest levels of self-regulated learning ability showed a common preference in science learning: they dislike memory-oriented and theory-centered lecture with note-taking from teacher's writings on chalkboard; they prefer science learning with inquiry-oriented laboratory work, discussion among students as well as teachers. However, reasons to prefer discussion were diverse as one student wants to listen other students' opinions while the other student want to present his opinion to other students. The most favorable science teachers appeared to be who ask questions frequently, increase student interests, behave friendly with students, and is a active person. In conclusion, science teaching for the gifted should employ individualized teaching strategies appropriate for individual personality and preferred learning styles as well as meeting with individual interests in science themes.

• The Journal of Bigdata
• /
• v.4 no.1
• /
• pp.99-118
• /
• 2019

This study used network analysis and clustering techniques to analyze studies on social media participation. As a result of the main path analysis, 37 major studies were extracted and divided into two networks: community-related networks and new media-related. Network analysis and clustering result in four clusters. This study has the academic significance of using academic data to grasp research trends at a macro level and using network analysis and machine learning as a methodology.

• Geomechanics and Engineering
• /
• v.39 no.1
• /
• pp.27-41
• /
• 2024

Accurately estimating the performance of tunnel boring machines (TBMs) is crucial for mitigating the substantial financial risks and complexities associated with tunnel construction. Machine learning (ML) techniques have emerged as powerful tools for predicting non-linear time series data. In this research, six advanced meta-heuristic optimization algorithms based on long short-term memory (LSTM) networks were developed to predict TBM penetration rate (TBM-PR). The study utilized 1125 datasets, partitioned into 20% for testing, 70% for training, and 10% for validation, incorporating six key input parameters influencing TBM-PR. The performances of these LSTM-based models were rigorously compared using a suite of statistical evaluation metrics. The results underscored the profound impact of optimization algorithms on prediction accuracy. Among the models tested, the LSTM optimized by the particle swarm optimization (PSO) algorithm emerged as the most robust predictor of TBM-PR. Sensitivity analysis further revealed that the orientation of discontinuities, specifically the alpha angle (α), exerted the greatest influence on the model's predictions. This research is significant in that it addresses critical concerns of TBM manufacturers and operators, offering a reliable predictive tool adaptable to varying geological conditions.

• Journal of Fisheries and Marine Sciences Education
• /
• v.27 no.2
• /
• pp.430-440
• /
• 2015

The purpose of this study was to analyze student's metacognition interaction based on a robot lesson. For this research as an analytical metacognition interaction tool was utilized. The results of this study revealed that, first, elementary school students had more metacognition interaction in middle learning levels but middle school students had more in the low learning level. Second, in the low learning level, middle school students revised the initiated goal strategy of the robot lesson. Third, in all learning levels, students showed much diagnosis and assesment metacognition interaction in the robot lesson. According to this study's results, the robot lesson has a positive effect in facilitating diagnosis meta cognition for processing of task performance. These results could provide effective cues and information on how to improve the robot lesson.