• Educational Technology International
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• v.14 no.2
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• pp.189-213
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• 2013

The study was conducted to find out the interaction between learning styles, and types of task on satisfaction and achievement in Chinese learning on Facebook. 44 students from D University in Seoul, Korea finished the questionnaires. To measure the participants' learning styles and satisfaction, the learning style instrument and satisfaction instrument were used. The data received were analyzed to find out the interaction between learning styles, and types of task on satisfaction and achievement. Through the analysis, the study suggests that, in the SNS environment for learning, instructors should focus on more on types of tasks than learning styles. Learning styles are important, however, for new pedagogy for one new learning environment, types of task are definitely more important than learning styles. Depending on the study results, the instructors should pay more attention to types of task, and they should also use different strategies to facilitate the contents of tasks to improve achievement and satisfaction in an SNS environment.

• Journal of Families and Better Life
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• v.26 no.3
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• pp.53-64
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• 2008

This study was to investigate the learning motive types and degree of psychological well-being of middle-aged married women attending the Korea National Open University and to examine the difference in their psychological well-being according to the types of learning motives. For these purposes, a survey was conducted to 263 middle-aged married women from 36 to 60 at the Korea National Open University. The findings were as follows: First, learning motive types of middle-aged women could be classified into 3 types; a non-oriented type, an activity and goal-oriented type and a multi-oriented type. A multi-oriented types were the most popular among those. Second, the overall level of self-respect was above the median, but the life satisfaction level was below the median. Third, there was difference in their self-respect level according to the learning motive types. That is, students who had a multi-oriented learning motive were higher self-respect level than those who had an activity and goal-oriented learning motive. Therefore, lifelong education is very significance in these days when average life span is prolonged.

• The Mathematical Education
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• v.45 no.4 s.115
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• pp.493-505
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• 2006

This research studied learning model for the purpose of renovation of mathematics teaching methods. Especially, this research classified the types of cooperative learning, the theoretical background for cooperative learning, the need of cooperative learning in school mathematics, and the differences between cooperative learning and traditional small group learning, This research also suggested special features of cooperative learning and various types of cooperative learning models. The main types of cooperative learning which this research supported are TAI(Team-Assisted Individualization, JIGSAW cooperative learning, JIGSAW II cooperative learning, JIGSAW III cooperative learning, STAD(Student Team-Achievement division) cooperative learning, and TGT(Teams-Games-Tournament).

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.28-37
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• 2020

We conducted a comprehensive review on the previous research on r-Learning. By reviewing 843 previous studies about r-Learning published from 2004 to 2015, this study investigated 1) the trend of research on r-Learning over time, 2) the characteristics of targeted students in r-Learning, 3) the educational activities implemented for r-Learning, and 4) the types of educational robots used for r-Learning. The study found that the research on r-Learning has rapidly and steadily increased and the types of educational activities and educational robots has been diversified. Relying on the findings of this review, this study suggests 1) ensuring growth in both the quality and the quantity of research on r-Learning, 2) broadening the target student population of r-Learning beyond the age-limited boundaries, 3) enhancing educational activities of r-Learning, and 4) recognizing the necessity for systematic and clear concepts of types of educational robots.

• Educational Technology International
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• v.16 no.2
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• pp.183-200
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• 2015

This study investigated the effect of learning achievements and cognitive load according to different types of presenting learning materials and epistemological beliefs (EB). Learning achievements in this study were composed by retention and transfer of ill-structured problem. A total of 80 college students participated in the study. Prior to the learning, students were guided to fill out a questionnaire regarding epistemological beliefs and a prior knowledge test. The students of each group studied with a different type of reading material: full text (FT), full text including key questions (KeyFT) and full text including a concept map (CmFT). After a session of study was finished, they were asked to complete the posttest: retention and transfer. The results showed that there was a significant difference in transfer achievements. CmFT outperformed higher scores than the other types. There was no significant difference in retention among the groups. It is strongly believed that the types of presenting learning materials may have affected the understanding of ill-structured problem solving skills. Students with sophisticated EB showed higher achievements on retention and transfer than naive-EB and mixed-EB. Even though the data showed decrease of the cognitive load on the type of materials and EB, there were no significant differences on the cognitive load. We should consider a positive effect of types of presenting learning materials and EB enhancing capabilities of solving ill-structured problems in real life.

• Asia Marketing Journal
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• v.17 no.1
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• pp.27-53
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• 2015

Learning organization has been an important issue in both management and marketing areas. Also learning capability is a key construct of innovation process in a firm. Especially, in marketing context, several researchers have studied market-based learning and its relation with performance. Previous studies have shown that market-based learning has a positive impact on overall firm performance. However, there has been inconsistency in the concept of market-based learning itself and its relationships with antecedents and consequences. Given this conflicting and inconsistent results of previous research, this study has two main objectives. First, this paper proposed a conceptual framework that marketbased learning has two types of processes and each types of market-based learning will generate different types of performance. Second, the mediating role of marketing capability in learning-performance link is proposed. The proposed conceptual framework shows that organizations which have marketbased learning for innovation management can enjoy ambidextrous firm performance on both side of effectiveness and efficiency via marketing capability. Moreover our research model proposes key drivers of market based organizational learning.

• The Journal of Sustainable Design and Educational Environment Research
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• v.19 no.1
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• pp.13-24
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• 2020

The purpose of this study is to analyze and match future teaching-learning methods with learning-space types as customized not only by school grade or grade groups, but also by learning modality. As a result, the following six teaching-learning methods were identified as future teaching-learning methods: flipped learning, deeper learning, collaborative learning, learning through immersive virtual reality, playful learning, and learning through OER(Open Educational Resources). There were also six learning-space types that were identified: playing and discovering space, a making and placement space, a presentation and sharing space, a space for independent study, space as a stage, and space as content(See Tables 8 and 11). Learning-space types and future teaching-learning methods were matched with 22 different types of learning modalities based on the presented degree of utilization by school grade or grade groups(See Table 13).

• East Asian mathematical journal
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• v.33 no.4
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• pp.413-429
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• 2017

This study is a basic study for developing a mathematical learning application program that can be used in smart devices for adaptive learning. We selected 20 mathematical learning applications including middle school contents and analyzed learning types. And we analyzed the contents and the learning process. As a result, most learning types of mathematics learning applications were problem-centered. Contents analysis results showed that the most applications have achievement goals. The factors that induce interest in learning were lacking and feedback was not provided sufficiently. Analysis of the learning process showed that most of the math learning applications were classified according to their purpose and characteristics.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.727-732
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• 2007

This paper is to investigate how types of presenting e-learning contents affect learning. The study examines learning outcome such as students' learning achievement, satisfaction, and perceived learning outcome of a course in liberal arts by three different types: VOD, WBI, and Text. The findings of this study will present the effectiveness of contents presentation type in e-learning. It is anticipated that the study will offer some suggestions to develop e-learning contents types for similar courses and further to develop effective contents types for various courses.

• Journal of the Korean Society of Safety
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• v.34 no.6
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• pp.50-57
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• 2019

In this study, various types of deep learning models that have been proposed recently are classified according to data input / output types and analyzed to find the deep learning model suitable for constructing a crack detection model. First the deep learning models are classified into image classification model, object segmentation model, object detection model, and instance segmentation model. ResNet-101, DeepLab V2, Faster R-CNN, and Mask R-CNN were selected as representative deep learning model of each type. For the comparison, ResNet-101 was implemented for all the types of deep learning model as a backbone network which serves as a main feature extractor. The four types of deep learning models were trained with 500 crack images taken from real concrete structures and collected from the Internet. The four types of deep learning models showed high accuracy above 94% during the training. Comparative evaluation was conducted using 40 images taken from real concrete structures. The performance of each type of deep learning model was measured using precision and recall. In the experimental result, Mask R-CNN, an instance segmentation deep learning model showed the highest precision and recall on crack detection. Qualitative analysis also shows that Mask R-CNN could detect crack shapes most similarly to the real crack shapes.