• Journal of The Korean Association For Science Education
• /
• v.24 no.1
• /
• pp.171-182
• /
• 2004

The purpose of this study is to analyze lesson plans from third to sixth grades of science and to find out teaching strategies in respects of learning functions provided by preservice elementary teachers in education university. On the whole, to control students' learning process preservice teachers used more shared-regulation strategy than strong teacher-regulation one. Teaching activities for regulative learning function were most used in strategy of strong teacher-regulation, and in strategy of shared-regulation those for cognitive learning functions were most used. But teaching activities for affective learning functions were used a little considered in both teaching strategies. In introduction step of instruction, affective and regulative learning functions were more instructed by strong teacher-regulation strategy and cognitive learning functions were more instructed by shared-regulation strategy. The affective, cognitive, and regulative learning functions were largely planned by shared-regulation teaching strategy in development. The regulative learning functions were planned by strong teacher-regulation strategy than by shared-regulation strategy and affective learning functions were considered a little bit in consolidation. There was a tendency that strong teacherregulation strategy was increased in lessons for fifth and sixth grade.

• IE interfaces
• /
• v.19 no.4
• /
• pp.324-332
• /
• 2006

It is believed that each learner has a preferred method to acquire and manage knowledge according to her/his learning style which influences learning achievement directly. The purpose of this paper is to statistically analyze relationships among individual learning styles, tutoring functions, and learning achievement in an e-learning environment. 524 survey results from participants of enterprise e-learning classes are classified into total group and superior group. T-Test and ANOVA analyses are carried between learning style and learning achievement and between learning style and preferred tutoring functions. The analysis results show that individual learning styles do not contribute to learning achievement while they are strongly related to preferences for some of tutoring functions. These results can be used to identify limitation of current e-learning practice and design better e-learning systems, especially, supporting appropriate tutoring functions for different types of learners.

• ETRI Journal
• /
• v.15 no.2
• /
• pp.35-51
• /
• 1993

This paper presents function approximation based on nonparametric estimation. As an estimation model of function approximation, a three layered network composed of input, hidden and output layers is considered. The input and output layers have linear activation units while the hidden layer has nonlinear activation units or kernel functions which have the characteristics of bounds and locality. Using this type of network, a many-to-one function is synthesized over the domain of the input space by a number of kernel functions. In this network, we have to estimate the necessary number of kernel functions as well as the parameters associated with kernel functions. For this purpose, a new method of parameter estimation in which linear learning rule is applied between hidden and output layers while nonlinear (piecewise-linear) learning rule is applied between input and hidden layers, is considered. The linear learning rule updates the output weights between hidden and output layers based on the Linear Minimization of Mean Square Error (LMMSE) sense in the space of kernel functions while the nonlinear learning rule updates the parameters of kernel functions based on the gradient of the actual output of network with respect to the parameters (especially, the shape) of kernel functions. This approach of parameter adaptation provides near optimal values of the parameters associated with kernel functions in the sense of minimizing mean square error. As a result, the suggested nonparametric estimation provides an efficient way of function approximation from the view point of the number of kernel functions as well as learning speed.

• Journal of the Korean Data and Information Science Society
• /
• v.14 no.4
• /
• pp.863-875
• /
• 2003

The existing e-learning systems have short functions for learners to lead their self-directed learning activities because those systems have not been integrated with functions supporting activities of learners, instructors and operators. Therefore, we designed and implemented an efficient e-learning system having fully integrated functions to let learners induce their active learning, instructors teach learners effectively and evaluate their learning activities, and operators handle curriculum affairs and system environments.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.1
• /
• pp.1-15
• /
• 2023

The aim of this study is to identify intelligent learning support functions in Learning Management System (LMS) to support university student learning activities during the transition from face-to-face classes to online learning. To accomplish this, we investigated the perceptions of students on the levels of importance and urgency toward learning support functions of LMS powered with Artificial Intelligent (AI) technology and analyzed the differences in perception according to student characteristics. As a result of this study, the function that students considered to be the most important and felt an urgent need to adopt was to give automated grading and feedback for their writing assignments. The functions with the next highest score in importance and urgency were related to receiving customized feedback and help on task performance processed as well as results in the learning progress. In addition, students view a function to receive customized feedback according to their own learning plan and progress and to receive suggestions for improvement by diagnosing their strengths and weaknesses to be both vitally important and urgently needed. On the other hand, the learning support function of LMS, which was ranked as low importance and urgency, was a function that analyzed the interaction between professors and students and between fellow students. It is expected that the results of this student needs analysis will be helpful in deriving the contents of learning support functions that should be developed as well as providing basic information for prioritizing when applying AI technology to implement learner-centered LMS in the future.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.34 no.1
• /
• pp.209-238
• /
• 2023

This study aims to propose the main learning contents, functions and activation plans for building an e-learning platform for libraries through a literature review, case analysis and expert survey. Through the literature review, it was found that libraries must play a role in providing high-quality online education for users in the e-learning ecosystem. Based on the previous studies, a learning function analysis tool was developed for the analysis of the library's e-learning platform. Based on this, the learning contents, learning functions and characteristics of library e-learning platforms were analyzed, and expert surveys and interviews were conducted. As a results, the construction of a platform for effectively applying learning processes and technology is essential for the library's sustainable e-learning services. The contents that should be provided for characteristics of library education, reading guidance, information literacy instruction, library usage instruction, and the latest IT technologies. And The main learning functions include the ability to conduct video lectures and real-time classes among learning types, and learning activity support functions, a cloud platform support function and a personalized environment support function. Additionally, suggested re-education for library staff to improve their technical skills and the formation of an e-learning team.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.5
• /
• pp.63-68
• /
• 2022

Autonomous driving technology has recently made great progress with the introduction of deep reinforcement learning. In order to effectively use deep reinforcement learning, it is important to select the appropriate activation function. In the meantime, many activation functions have been presented, but they show different performance depending on the environment to be applied. This paper compares and evaluates the performance of 12 activation functions to see which activation functions are effective when using reinforcement learning to learn autonomous driving on highways. To this end, a performance evaluation method was presented and the average reward value of each activation function was compared. As a result, when using GELU, the highest average reward could be obtained, and SiLU showed the lowest performance. The average reward difference between the two activation functions was 20%.

• Research in Mathematical Education
• /
• v.7 no.3
• /
• pp.191-209
• /
• 2003

In this paper, we present a new environment of learning and teaching of trigonometric, exponential and logarithmic functions, the most difficult parts for students to learn among functions, through sound and music, students like the most. First, by using sound and music, we try to arouse student's interest. Second, we let students see and hear properties of transcendental functions so that students can understand and remember them easily. Finally we encourage students to compose their favorite song using transcendental functions so that they can experience the practicality of transcendental functions.

• Journal of The Korean Association of Information Education
• /
• v.26 no.1
• /
• pp.23-34
• /
• 2022

Teachers should be able to reorganize the curriculum according to the student level, reorganize textbooks freely, and distribute them to students. However, current paper-textbooks are difficult to modify or edit some contents and distribute them to students, also current digital textbooks are grouped into units, so the order or educational resources cannot be reconstructed. In addition, The digital textbooks are difficult to update external links or the latest resources, and to contain various multimedia materials or high-definition realistic content due to capacity limitations. Therefore, this study presented functions: teaching and learning and evaluation functions, resources search and sharing functions, learning records and analysis functions, screen showing and printing functions, so that teachers can provide customized learning by level to students using digital textbooks. Through the expert Delphi survey, detailed functions for each area were divided into teachers and students. We proposed expanding and developing digital textbooks to various subjects, and distributing various teaching and learning models using digital textbooks.

• Journal of Information Processing Systems
• /
• v.16 no.5
• /
• pp.1074-1082
• /
• 2020

Recently, research has been actively conducted to create artificial intelligence agents that learn games through reinforcement learning. There are several factors that determine performance when the agent learns a game, but using any of the activation functions is also an important factor. This paper compares and evaluates which activation function gets the best results if the agent learns the game through reinforcement learning in the 2D racing game environment. We built the agent using a reinforcement learning algorithm and a neural network. We evaluated the activation functions in the network by switching them together. We measured the reward, the output of the advantage function, and the output of the loss function while training and testing. As a result of performance evaluation, we found out the best activation function for the agent to learn the game. The difference between the best and the worst was 35.4%.