• 한국멀티미디어학회논문지
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• 제24권4호
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• pp.593-600
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• 2021

In this paper, we present the FlappyBird Competition System (FCS) implementation, a competition-based automated assessment system used in an entry-level artificial intelligence (AI) course at a university. The proposed system provides an evaluation method suitable for AI courses while taking advantage of automated assessment methods. Students are to design a neural network structure, train the weights, and tune hyperparameters using the given reinforcement learning code to improve the overall performance of game AI. Students participate using the resulting trained model during the competition, and the system automatically calculates the final score based on the ranking. The user evaluation conducted after the semester ends shows that our competition-based automated assessment system promotes active participation and inspires students to be interested and motivated to learn AI. Using FCS, the instructor significantly reduces the amount of time required for assessment.

• ETRI Journal
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• 제46권1호
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• pp.48-58
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• 2024

This paper presents the development of language tutoring systems for nonnative speakers by leveraging advanced end-to-end automatic speech recognition (ASR) and proficiency evaluation. Given the frequent errors in non-native speech, high-performance spontaneous speech recognition must be applied. Our systems accurately evaluate pronunciation and speaking fluency and provide feedback on errors by relying on precise transcriptions. End-to-end ASR is implemented and enhanced by using diverse non-native speaker speech data for model training. For performance enhancement, we combine semisupervised and transfer learning techniques using labeled and unlabeled speech data. Automatic proficiency evaluation is performed by a model trained to maximize the statistical correlation between the fluency score manually determined by a human expert and a calculated fluency score. We developed an English tutoring system for Korean elementary students called EBS AI Peng-Talk and a Korean tutoring system for foreigners called KSI Korean AI Tutor. Both systems were deployed by South Korean government agencies.

• International Journal of Internet, Broadcasting and Communication
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• 제12권3호
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• pp.108-115
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• 2020

Blended learning is a teaching method utilizing all the advantages in 'on and off-line' learning circumstances in order to enhance the learning effect and efficiency, more than the simple use of online factors in the classroom education. In this paper, we present the realization and simulation of algorithm for the realtime evaluation of low-grade and high-grade subjects in order to implement smart e-learning system, considering a lecture intelligibility. In order to grasp the levels of student's intelligibility, we simulated a function that automatically summarizes the study contents of class given by a lecturer. Especially, in administrator mode of smart e-learning system, we suggested and simulated a system in order to help the lecturer to easily manage the student's grades, and we have provided software to tell the student's intelligibility of lecture, analyzed the rate of incorrect answers, automatic judgment of lecture intelligibility and judge the weakest subject.

• International Journal of Contents
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• 제5권1호
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• pp.51-55
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• 2009

In this paper, we present a structure of personalized e-Learning system to study for a test formalized by uniform multiple-choice using on/off line mixed estimations as is the case of Driver :s License Test in Korea. Using the system a candidate can study toward the license through the Internet (and/or mobile instruments) within the personalized concept based on IRT(item response theory). The system accurately estimates user's ability parameter and dynamically offers optimal evaluation problems and learning contents according to the estimated ability so that the user can take possession of the license in shorter time. In order to establish the personalized e-Learning concepts, we build up 3 databases and 2 agents in this system. Content DB maintains learning contents for studying toward the license as the shape of objects separated by concept-unit. Item-bank DB manages items with their parameters such as difficulties, discriminations, and guessing factors, which are firmly related to the learning contents in Content DB through the concept of object parameters. User profile DB maintains users' status information, item responses, and ability parameters. With these DB formations, Interface agent processes user ID, password, status information, and various queries generated by learners. In addition, it hooks up user's item response with Selection & Feedback agent. On the other hand, Selection & Feedback agent offers problems and content objects according to the corresponding user's ability parameter, and re-estimates the ability parameter to activate dynamic personalized learning situation and so forth.

• 융합정보논문지
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• 제9권12호
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• pp.252-263
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• 2019

본 연구의 목적은 플립러닝 교수-학습법을 적용하고 대학생들의 인식과 학업성취 평가를 알아보기 위해 시도되었다. 단일군 치위생학과 재학생 27명을 대상으로 치과방사선학의 이론 수업에 4주 동안 적용하였다. 자료수집은 1학기 수업이 끝나고 이루어졌으며 수집된 자료는 SPSS 18.0을 이용하여 빈도와 평균 그리고 내용분석을 실시하였다. 연구결과 수업전반에 대한 인식은 긍정적 반응이었으며 학업성취평가는 통계적으로 유의하지 않았다. 플립러닝-교수학습방법에 대한 학생들의 인식은 높은 긍정으로 나타났다. 효과적인 교육 프로그램임이 확인되었다. 그러나 학업성취평가 통계적으로 유의하지 않았고 학습방법에 따른 평가시스템이 달라야 할 필요가 있다고 사료된다.

• 산업경영시스템학회지
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• 제44권3호
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• pp.33-38
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• 2021

Recently, transfer learning techniques with a base convolutional neural network (CNN) model have widely gained acceptance in early detection and classification of crop diseases to increase agricultural productivity with reducing disease spread. The transfer learning techniques based classifiers generally achieve over 90% of classification accuracy for crop diseases using dataset of crop leaf images (e.g., PlantVillage dataset), but they have ability to classify only the pre-trained diseases. This paper provides with an evaluation scheme on selecting an effective base CNN model for crop disease transfer learning with regard to the accuracy of trained target crops as well as of untrained target crops. First, we present transfer learning models called CDC (crop disease classification) architecture including widely used base (pre-trained) CNN models. We evaluate each performance of seven base CNN models for four untrained crops. The results of performance evaluation show that the DenseNet201 is one of the best base CNN models.

• 청정기술
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• 제28권2호
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• pp.138-146
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• 2022

Electricity has become a factor that dramatically affects the market economy. The day-ahead system marginal price determines electricity prices, and system marginal price forecasting is critical in maintaining energy management systems. There have been several studies using mathematics and machine learning models to forecast the system marginal price, but few studies have been conducted to develop, compare, and analyze various machine learning and deep learning models based on a data-driven framework. Therefore, in this study, different machine learning algorithms (i.e., autoregressive-based models such as the autoregressive integrated moving average model) and deep learning networks (i.e., recurrent neural network-based models such as the long short-term memory and gated recurrent unit model) are considered and integrated evaluation metrics including a forecasting test and information criteria are proposed to discern the optimal forecasting model. A case study of South Korea using long-term time-series system marginal price data from 2016 to 2021 was applied to the developed framework. The results of the study indicate that the autoregressive integrated moving average model (R-squared score: 0.97) and the gated recurrent unit model (R-squared score: 0.94) are appropriate for system marginal price forecasting. This study is expected to contribute significantly to energy management systems and the suggested framework can be explicitly applied for renewable energy networks.

• 한국항공운항학회지
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• 제27권3호
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• pp.45-53
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• 2019

The purpose of this study is to provide a brief overview of the helicopter pilot training system applied to the Army, and to examine what factors positively affect the successful flight training of helicopter pilots. For this purpose, we analyzed the correlations between various factors such as individual characteristics, selection factors, flight aptitude evaluation, theoretical subjects test, and self-life evaluation. As a result, it was found that only the flight experience was influential on the individual characteristics at the beginning of the training course, and the learning achievement represented by the test of theoretical subjects was positively influenced throughout the flight training course. This reaffirms the fact that an individual's high level of motivation or effort influences his flight training performance. These results are expected to be useful indicators for future development of pilot selection system and pilot training system.

• 공학교육연구
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• 제16권1호
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• pp.35-44
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• 2013

The purpose of this study is to develop an examination system for an e-learning quality manager's certificate which is composed of subjects, criteria, method of examination. The task model of e-learning quality manager was modify and task/knowledge/skill matrix was developed to design the examination system through conferences of DACUM committee and an advisory committee. And a survey was carry out to analyze validity of contents of the examination system. The major findings were as the follow: First, occupational specification, job specification, task specification and task/knowledge/skill matrix were developed. Second, examination subjects were developed based on task/knowledge/skill matrix, which were "Basis of e-Learning and plan of service", "Expulsion and management of e-learning infrastructure", "Development of e-learning contents", "Operation and evaluation of e-learning service". Third, the criteria and methods of examination for an e-learning quality manager's certificate were developed, which is composed of test type, the sum of test items, test time and acceptable standards.

• 정보처리학회논문지A
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• 제10A권4호
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• pp.321-330
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• 2003

본 연구에서는 학습자들의 학습 과정을 모니터링하여 분석된 학습 특성에 따라 다르게 학습내용을 동적으로 구성하여 제공하는 에이젼트 기반의 적응적 교수 시스템을 구현하고 있다. 또한 학습자들의 능력을 평가하고 각 수준에 맞는 학습내용을 제공하기 위해 퍼지 개념을 이용하고 있다. 이를 위해, 코스웨어 설계시 학습목표의 중요도, 학습내용의 난이도, 학습목표와 학습내용과의 관련도에 따라 퍼지 수준 집합을 구성하고 이를 기반으로 학습자의 수준에 맞는 내용을 제공한다. 본 논문에서는 에이젼트를 이용하여 학습자들의 학습 상태를 지속적으로 모니터링하고, 평가 단계에서 학습자가 오답을 냈을 경우 적절한 힌트를 추론하여 제공하며, 분석된 학습 특성과 평가 결과에 따라 학습 내용을 동적으로 구성하여 줌으로서 적응적 교수 시스템을 효과적으로 구현하고 있다. 또한 퍼지 집합에 의한 수준별 학습 내용의 제공과 평가 결과는 학습과정에 나타나는 여러 가지 다양하고 불확실한 요소들을 고려하여 처리함으로써 보다 융통성 있는 교수 학습 방법을 제공할 수 있도록 한다.