• International Journal of Advanced Culture Technology
• /
• 제8권4호
• /
• pp.235-241
• /
• 2020

Artificial intelligence and machine learning are used in many parts of our daily lives, but the basic processes and concepts are barely exposed to most people. Understanding these basic concepts is becoming increasingly important as kids don't have the opportunity to explore AI processes and improve their understanding of basic machine learning concepts and their essential components. Machine learning educational tools can help children easily understand artificial intelligence and machine learning. In this paper, we examine machine learning education tools and compare their features.

• 대한화학회지
• /
• 제66권6호
• /
• pp.472-492
• /
• 2022

본 연구는 온-오프라인 혼합 학습환경에서 중등과학교사의 학습환경 특이적인 PCK 요소 및 하위요소 탐색을 목적으로 하였다. 중등과학교사 12명을 대상으로 설문, 개별 면담, 수업 관찰 자료를 수집하여 PCK 이론적 틀을 기반으로 연역적으로 분석하고 다시 귀납적 분석을 통해 그 범주를 정교화하였다. 온-오프라인 혼합 학습환경에서 본 연구 교사들의 PCK는 요소별로 학습환경 특이성이 다르고 학습환경 특이성에 따라 PCK 요소별 하위요소가 다른 것으로 나타났다. 온라인 학습환경 특이적인 과학 교수 지향으로 '과학 개념 학습' 목표 지향과 '강의식 수업'의 과학 교수-학습 지향이 있었다. 온-오프라인 혼합 학습환경 특이적인 교육과정에 관한 지식에는 '교육과정 재구성'이 있었으며, 온라인 학습환경 특이적인 교육과정에 관한 지식에는 '학습 목표 선정', '교육과정 자료'가 있었다. 온라인 학습환경 특이적인 과학 교수전략에 관한 지식에는 '과학 주제 특이적 전략', '과학 교과 특이적 전략', '상호작용 전략'이 있었다. 코로나 19 이후 오프라인 학습환경 특이적인 과학 교수전략에 관한 지식에는 '과학 주제 특이적 전략', '상호작용 전략'이 있었다. 온라인 학습환경 특이적인 학생의 과학 학습에 관한 지식에는 '학습을 위한 선지식', '학습 어려움', '학습 동기 및 흥미', '학습 다양성'이 있었으며, 코로나 19 이후 오프라인 학습환경 특이적인 학생의 과학 학습에 관한 지식에는 '학습 어려움'만 있었다. 과학 학습 평가에 관한 지식은 온-오프라인 혼합 학습환경 특이적인 지식과 온라인 학습환경 특이적인 지식이 있었으며, 각각 '평가 내용'과 '평가 방법'이 있었다.

• 전기학회논문지P
• /
• 제59권1호
• /
• pp.29-34
• /
• 2010

This paper presents an intelligent learning controller for repetitive walking motion of biped walking robot. The proposed learning controller consists of an iterative learning controller and a direct learning controller. In the iterative learning controller, the PID feedback controller takes part in stabilizing the learning control system while the feedforward learning controller plays a role in compensating for the nonlinearity of uncertain biped walking robot. In the direct learning controller, the desired learning input for new joint trajectories with different time scales from the learned ones is generated directly based on the previous learned input profiles obtained from the iterative learning process. The effectiveness and tracking performance of the proposed learning controller to biped robotic motion is shown by mathematical analysis and computer simulation with 12 DOF biped walking robot.

• 아동학회지
• /
• 제25권4호
• /
• pp.163-175
• /
• 2004

In this study, 63 university seniors majoring Child Studies were in an 8-week Web Based Instruction (WBI) program. Student characteristics of learning motivation, self-regulatory learning strategy, and learning style (Kolb, 1985) were the independent variables. Learning effects as dependent variables were measured by paper test and work assessment. Spearman's $\rho$ was calculated and tests of rank order difference were used for the data analysis. Results showed that learning motivation and self-regulatory learning strategy had meaningful positive relations with learning effects on the paper test score. Learning effects showed differences by learning style. These findings indicated that the learner's characteristics should be considered in the design and development of more effective WBI environments.

• International Journal of Human Ecology
• /
• 제10권1호
• /
• pp.99-112
• /
• 2009

This study explored the consistency in service-learning courses through comparing course syllabi and faculty survey in order to incorporate a service-learning course into the Home Economics practicum. The first step was to examine how consistent were between the reasons for choice of service-learning and importance of overall civic learning goals, between the importance of civic learning goals and educational objectives on syllabus, and between planned activities and accomplished activities. This study collected the descriptive and quantitative data from the syllabi for service-learning courses and a faculty survey at Texas Tech University. The major findings were that there was meaningful consistency between: the reasons for choosing service-learning and the importance of overall civic learning goals, the importance of civic learning goals and educational objectives, and planned activities on syllabus assignment and accomplished activities on the faculty survey related to course components. Future research regarding service-learning course design would be required in detail, and practice in designing service-learning courses would be consistent between the syllabus and performance in actual courses.

• 대한방사선기술학회지:방사선기술과학
• /
• 제45권6호
• /
• pp.515-522
• /
• 2022

The aim of the study was analyzed effect of the interaction with contents (IC), learning satisfaction (LS) and learning achievement (LA) through evaluation of the self-directed learning ability (SDLA) and immersion in learning (IL) for online learning application in the radiation therapy. A total of fifty university students who completed the radiation therapy course were be surveyed. There was significant positive correlation with the IC and the intention to continue using (ICU) in SDLA, and IC, LS, LA, and ICU in LC. The online learning application could be increase the satisfaction and achievement of radiation therapy learning.

• Educational Technology International
• /
• 제14권2호
• /
• pp.189-213
• /
• 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.

• 한국멀티미디어학회논문지
• /
• 제20권8호
• /
• pp.1395-1405
• /
• 2017

In this paper, we analyses heart beat data to identify subjects stress state (binary) using heart rate variability (HRV) features extracted from heart beat data of the subjects and implement supervised machine learning techniques to create the mental stress classifier. There are four steps need to be done: data acquisition, data processing (HRV analysis), features selection, and machine learning, before doing performance measurement. There are 56 features generated from the HRV Analysis module with several of them are selected (using own algorithm) after computing the Pearson Correlation Matrix (p-values). The results of the list of selected features compared with all features data are compared by its model error after training using several machine learning techniques: support vector machine, decision tree, and discriminant analysis. SVM model and decision tree model with using selected features shows close results compared to using all recording by only 1% difference. Meanwhile, the discriminant analysis differs about 5%. All the machine learning method used in this works have 90% maximum average accuracy.

• 정보교육학회논문지
• /
• 제16권1호
• /
• pp.81-89
• /
• 2012

스마트러닝 품질은 전통적인 교육보다 복잡하고 다양한 요인으로 구성된다. 본 논문에서는 스마트러닝 품질을 콘텐츠, 시스템, 서비스측면에서 살펴보고 문헌연구와 표적집단면접법(FGI)에 의해서 스마트러닝 품질요인을 분류하였다. 설문조사는 리커트식 5점 척도에 의하여 사용자들이 품질요인의 만족도와 중요도를 상대적으로 평가하도록 하였다. 설문지는 39문항으로 구성하였으며 불성실하게 응답한 설문지 8부를 제외하고 112부가 최종분석을 위하여 활용되었다. 수집된 데이터는 SPSS 18.0을 활용하여 통계적으로 분석되었으며, 실증적 검증을 위해서 중요도-만족도 분석이 활용되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제15권6호
• /
• pp.2188-2203
• /
• 2021

With the rapid development of mobile Internet, smart phones have been widely popularized, among which Android platform dominates. Due to it is open source, malware on the Android platform is rampant. In order to improve the efficiency of malware detection, this paper proposes deep learning Android malicious detection system based on behavior features. First of all, the detection system adopts the static analysis method to extract different types of behavior features from Android applications, and extract sensitive behavior features through Term frequency-inverse Document Frequency algorithm for each extracted behavior feature to construct detection features through unified abstract expression. Secondly, Long Short-Term Memory neural network model is established to select and learn from the extracted attributes and the learned attributes are used to detect Android malicious applications, Analysis and further optimization of the application behavior parameters, so as to build a deep learning Android malicious detection method based on feature analysis. We use different types of features to evaluate our method and compare it with various machine learning-based methods. Study shows that it outperforms most existing machine learning based approaches and detects 95.31% of the malware.