• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.142-148
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• 2003

Reinforcement learning is considered as an important tool for robotic learning in unknown/uncertain environments. In this paper, we propose an evaluation function expressed in a vector form to realize multi-dimensional reinforcement learning. The novel feature of the proposed method is that learning one behavior induces parallel learning of other behaviors though the objectives of each behavior are different. In brief, all behaviors watch other behaviors from a critical point of view. Therefore, in the proposed method, there is cross-criticism and parallel learning that make the multi-dimensional learning process more efficient. By ap-plying the proposed learning method, we carried out multi-dimensional evaluation (reward) and multi-dimensional learning simultaneously in one trial. A special neural network (Q-net), in which the weights and the output are represented by vectors, is proposed to realize a critic net-work for Q-learning. The proposed learning method is applied for behavior planning of mobile robots.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.62-68
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• 2022

Evaluation as learning is important for the learner competency test, and the applicable method is studied. Assessment is the role of diagnosing the current learner's status and facilitating learning through appropriate feedback. The system is insufficient to enable process-oriented evaluation in small educational institute. Focusing on becoming familiar with the AI through experience can end up simply learning how to use the tools or just playing with them rather than achieving ultimate goals of AI education. In a previous study, the experience way of AI education with PLAY model was proposed, but the assessment stage is insufficient. In this paper, we propose ELAS (Experiential K-12 AI education Learning Assessment System) for small educational institute. In order to apply the Assessment factor in in this system, the AI-factor is selected by researching the goals of the current SW education and AI education. The proposed system consists of 4 modules as Assessment-factor agent, Self-assessment agent, Question-bank agent and Assessment -analysis agent. Self-assessment learning is a powerful mechanism for improving learning for students. ELAS is extended with the experiential way of AI education model of previous study, and the teacher designs the assessment through the ELAS system. ELAS enables teachers of small institutes to automate analysis and manage data accumulation following their learning purpose. With this, it is possible to adjust the learning difficulty in curriculum design to make better for your purpose.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.245-252
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• 2013

We developed a system which supports the functions of real-time evaluation and feedback for smart learning. The system is consisted of an application for tablet PC and smart phone and the server, and the client exchanges data with the server through wireless communication. Whereby, the proposed system enabled realtime interaction and feedback between learner and teacher or between learners. As a result, the instruction for each learner's level is available using the system, and then it could enhance the level of academic achievement and learning interest.

• Journal of the Ergonomics Society of Korea
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• v.34 no.6
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• pp.597-607
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• 2015

Objective: The purpose of this study is to identify the effects of sign language video location in e-learning system for the hearing-impaired. Background: E-learning education is a good way to resolve the inequality of education for the disabled. Providing a sign language video in e-learning education for the hearing-impaired is very important for their learning. Although the location of sign language video is an important factor in the design of the video, the effect of its location in learning using the e-learning system was not studied. Method: In order to identify the effect of sign language video location on the learning of the hearing-impaired using the e-learning system, the prototypes of the system with different locations were developed. Eighteen people with hearing impairment participated in this experiment. Learning presence, learning immersion, and learning satisfaction were used to measure learning effects with sign language video location. Results: Bottom right position was more preferred through preference evaluation for sign language video location. The learning effect with sign language video location (bottom-left and bottom-right) was not significant. That is, the effects of learning presence, immersion, and satisfaction were not statistically significant with video location. Conclusion: From this study, the following have to be considered in e-learning system design for the hearing-impaired. Although the location of a sign language video is not a significant factor from the experiment, the bottom right position in the design is proposed because learning presence and satisfaction is slightly higher at the bottom right position, and the position is preferred from subjective evaluation. From the analysis of interview data, it was also proposed that the design of a sign language video should be improved for the hearing-impaired. Application: The result of this study can be applied to the e-learning system design for the hearing-impaired.

• Journal of Engineering Education Research
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• v.23 no.2
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• pp.24-30
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• 2020

This paper proposes the approaches to the evaluation of learning using concepts of artificial intelligence. Among various techniques, deep learning algorithm is employed to achieve quantitative results of evaluation. In particular, this paper focuses on the process-based evaluation instead of the result-based one using face expression. The expression is simply acquired by digital camera that records face expression when students solve sample test problems. Face expressions are trained using convolutional neural network (CNN) model followed by classification of expression data into three categories, i.e., easy, neutral, difficult. To substantiate the proposed approach, the simulation results show promising results, and this work is expected to open opportunities for intelligent evaluation system in the future.

• The Journal of Korean Association of Computer Education
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• v.3 no.1
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• pp.43-50
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• 2000

It is said that traditional formative evaluation method does not fit in web based learning system because of inefficiency and improper data collecting techniques. This study is to demonstrate alternative formative evaluation method fit in web based learning system. In alternative evaluation, Participant, data collecting techniques and data are different from each web based program development process. As a conclusion, this alternative evaluation method may promote effectiveness and quality of web based program.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.425-436
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• 2006

The e-learning system in which the learning is carried out by predefined procedures cannot offer proper learning suitable to the capability of individual learner. To solve this problem, SCORM sequencing can be used to define various learning procedures according to the capabilities of learners. Currently the sequencing is designed by teachers or learning contents producers to regularize the learning program. However, the predefined sequencing may not reflect the characteristics of the learning group. If inappropriate sequencing is designed it may cause the unnecessary repetition of learning. In this paper, we propose an automated evaluation system in which dynamic sequencing is applied. The dynamic sequencing reflects the evaluation results to the standard scores used by sequencing. By changing the standard scores, the sequencing changes dynamically according to the evaluation results of a learning group. Through several experiments, we verified that the proposed learning system that uses the dynamic sequencing is effective for providing the proper learning procedures suitable to the capabilities of learners.

• The Journal of the Korea Contents Association
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• v.18 no.3
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• pp.354-360
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• 2018

Recently, the computer aided learning system has promoted a new educational concept and education system. The purpose of this study is to construct a theoretical model for the epistemic frame and evaluation tool which is emphasized according to the 21st century. Specifically, first, this study conducted a domain analysis of epistemic frame. Second, this study developed an evaluation tool to measure epistemic frame. Finally, the evaluation tool is examined in terms of validity and reliability using factor analysis and Cronbach's alpha. As a result, the theoretical model was presented through the consultation of the Advisory Group and the evaluation tool was empirically validated. We expect that this study will provide a useful information to researchers and practitioners who want to develop a computer based learning tool for learning epistemic frame.

• Journal of Service Research and Studies
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• v.11 no.4
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• pp.67-76
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• 2021

The importance of smart learning is increasing as the speed of development of non-face-to-face services increases due to the influence of COVID-19. This study is the user satisfaction evaluation model that utilizes the causal relationship between variables used for evaluation, focusing on the usability evaluation results of the learning disability intervention service (www.basic-edu.net) according to the need to evaluate the use satisfaction of the smart learning system. To this end, theoretical studies were conducted on smart learning and learning disability intervention services, www.basic-edu.net, usability evaluation of learning disability intervention systems, and use satisfaction evaluation models. And based on the results, a hypothesis was presented on the user satisfaction evaluation model of the smart learning system. The experimental method allowed 40 students and parents across the country to use the www.basic-edu.net service and was evaluated for its usability. In addition, using this data, the hypothesis was verified using regression analysis based on four variables: ease of use, interest, self-learning, and satisfaction with use. As a result of the hypothesis verification, it was found that the causal relationship of all hypotheses from H1 to H4 was significant.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.3
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• pp.305-314
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• 2001

In this paper, we construct an automatic evaluation system of psychological feeling for corporate identity (CI) symbol mark based on a fuzzy neural network technique. The system is modelled by trainable fuzzy inference rules with several input variables (qualitative and quantitative design components of CI symbol mark) and a single output variable (consumer's feeling). The back propagation learning algorithm, which is a conventional learning method of multilayer feedforward neural networks, is used for parameter identification of the fuzzy inference system. The learning ability to train data and the generalization ability to test data are evaluated for the proposed evaluation system by computer simulations.