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

• Korean Journal of Child Studies
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• v.36 no.6
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• pp.1-21
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• 2015

This study was aimed at examining the paths through which family socioeconomic status as indicated by family income and parental education influenced preschool-aged children's socioemotional and cognitive development through the mediating role of parental warmth and the home learning environment. The study made use of data from 1,080 families who participated in the 5th wave of the Panel Study on Korean Children, when their children were approximately 4 years of age. Structural equation modeling analysis revealed that the models, including both parental warmth and the home learning environment did not fit the data well. The effects of warmth on social competence and cognitive development were not statistically significant. The modified models, using the home learning environment as a mediator between family SES and child's developmental outcomes showed that higher level of family income and parental education predicted a more cognitively stimulating home environment, which in turn, predicted a child's greater levels of social competence and positive cognitive development. The social competence of preschool-aged children again significantly predicted their cognitive development. The mediating effects of the home learning environment were statistically supported.

• Journal of The Korean Association For Science Education
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• v.19 no.2
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• pp.315-328
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• 1999

The purpose of this study was to investigate the effects of psychological learning environment generated by science teachers upon students' affective perceptions and cognitive learning. The subjects of the study were consist of 2.693 students from secondary school. The students' perception were examined by the tools of PLEIS(Psychological Learning Environment Instrument by Science teacher). SAMS(Science Anxiety Measurement Scale). HARS(High schools' s Attitude Related Science). and ALWSS(Attitude toward Laboratory Work Scale in Secondary school). and cognitive learning outcomes assessed to TIPS II (Test of Integrated Process Skills II ) and science test score. The results of this study suggest that positive psychological learning environment by science teacher should be offered to students for the improvement of science achievement. and learning environment will be used as an instrument of self assessment for improving science teaching strategy. Understanding of relationship among psychological learning environment, affective perception and cognitive learning will be helpful to the design of science teaching and learning process.

• Educational Technology International
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• v.15 no.2
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• pp.143-170
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• 2014

As it was argued that students' cognitive engagement can be, at least in part, modified by individual or learning environmental factors, prior studies have attempted to identify the factors explaining the variability of students' cognitive engagement. This literature review has shown that students' cognitive engagement can be altered by various elements in the learning environment design such as factors related students' perceptions of teaching quality, characteristics of tasks and learning activities, teachers' behaviors during instruction, classroom goal structures, the integration of student oriented learning, action learning, problem-based learning, and constructivist learning, and academic disciplines. Based on the review, this study suggests that more studies are required to focus on understandings how the integration of instructional design principles into courses and the levels of student cognitive engagement in these courses are related. Also, an investigation of direct and indirect effect of learning environments taking into account students' personal factors would provide a more accurate picture of the relationship between learning environmental factors and students' cognitive engagement.

• Journal of The Korean Association For Science Education
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• v.12 no.2
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• pp.19-29
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• 1992

In this study, five learning models were compared and discussed in terms of their learning procedures and learning strateies. After a brief introduction of each model, the author discussed the differences and similarities among the five learning models. As a result, Kwon's procedual learning (Kwon, 1989) seemed to encompass almost all the learning models proposed by the other four author. All the models emphasized the importance of cognitive conflict. However, I. K.Kim(1991), Park(1992) and Y.M.Kim(1991) seemed to be concentrated their attention on the cognitive conflict between concepts ; while Hashweh and Kwon emphasized cognitive conflict between cognitive structure and environment. The study also suggested more study on the empirical evidence of the three kinds of the cognitive conflicts proposed by Kwon(1989) and on the development of learning strategies to induce and overcome the cognitive conflicts.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.3
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• pp.1-9
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• 2022

In this study we conducted a research regarding the effect on learning immersion and perception of the learning environment by learning presence of students in the Department of aeronautical science and flight operation in the context of non-face-to-face lectures caused by COVID-19. The relationship between learning presence (cognitive presence, emotional presence, and social presence) and learning commitment showed a high correlation. The learning immersion was also found to increase when cognitive presence, emotional presence, and social presence increased in multiple regression analysis to find out the effects of cognitive presence, emotional presence, and social presence, which are sub-factors of learning presence. The advantage of non-face-to-face classes was to be the ease of learning, and the disadvantage of non-face-to-face classes was the most difficulty of the learning process in the content analysis of the non-face-to-face class environment.

• Journal of The Korean Association of Information Education
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• v.23 no.6
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• pp.639-653
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• 2019

The purpose of this study is to design an instructional framework and cognitive learning environment for AI education based on computational thinking in order to ground the theoretical rationale for AI education. Based on the literature review, the learning model is proposed to select the algorithms and problem-solving models through the abstraction process at the stage of data collection and discovery. Meanwhile, the instructional model of AI education through computational thinking is suggested to enhance the problem-solving ability using the AI by performing the processes of problem-solving and prediction based on the stages of automating and evaluating the selected algorithms. By analyzing the research related to the cognitive learning environment for AI education, the instructional framework was composed mainly of abstraction which is the core thinking process of computational thinking through the transition from the stage of the agency to modeling. The instructional framework of AI education and the process of constructing the cognitive learning environment presented in this study are characterized in that they are based on computational thinking, and those are expected to be the basis of further research for the instructional design of AI education.

• The Journal of Korean Association of Computer Education
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• v.10 no.6
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• pp.79-89
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• 2007

The advent of e-Learning paradigm requires a various type of e-Learning models and systems which are appropriate to support effective teaching-learning process. Accordingly, the teaching-learning system using the Internet and the intelligent tutoring system(ITS) in e-Learning environment has attracted a fair amount of critical attention. However there is a wide gap between infrastructure of a present educational site and the u-learning environment. Therefore, in this paper, an ITS teaching-learning model is proposed and system is developed for a school environment, which is based on a learner's cognitive structure and applies a concept of u-Learning, and then is verified for validity. X-Neuronet, the developed system, offers a method of representing a learner's cognitive structure so as to apply the method for the efficient individualized learning.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.223-228
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• 2021

As a consequence of sudden outbreak of COVID-19 pandemic worldwide, educational institutes around the globe are forced to switch from traditional learning systems to e-learning systems. This has led to a variety of technology-driven pedagogies in e-teaching as well as e-learning. In order to take the best advantage, an appropriate understanding of the cognitive capability is of prime importance. This paper presents an intelligent cognitive maturity recognition system for confidence-based e-learning. We gather the data from actual test environment by involving a number of students and academicians to act as experts. Then a Genetic Programming based simulation and modeling is applied to generate a generalized classifier in the form of a mathematical expression. The simulation is derived towards an optimal space by carefully designed fitness function and assigning a range to each of the class labels. Experimental results validate that the proposed method yields comparative and superior results which makes it feasible to be used in real world scenarios.

• Knowledge Management Research
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• v.11 no.1
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• pp.115-128
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• 2010

The dramatic increase in e-Learning enrollments in higher education is likely to continue. These e-Learning environments have made learning much more convenient by stretching the spatial and temporal barriers. Their effectiveness, however, remains to be examined. In this research, the author explore the importance of personalization, interactivity and the important role of contents organizing in online education environment. Furthermore, the authors divide e-learning outcome into psychomotor, cognitive, and affective outcome. Indeed, e-Learning for psychomotor outcome has been viewed as impossible. The authors discuss the implications of the findings for theory and practice.