• 제목/요약/키워드: End-to-end learning

검색결과 1,139건 처리시간 0.028초

The Effect of Using WhatsApp on EFL Students' Medical English Vocabulary Learning During the Covid-19 Pandemic

  • Saud Alenezi;Elias Bensalem
    • International Journal of Computer Science & Network Security
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    • 제24권2호
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    • pp.143-149
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    • 2024
  • The role of social networking mobile applications such as WhatsApp in enhancing second language vocabulary learning among English language learners continues to be a subject of interest for many scholars. The current study aimed at examining medical English vocabulary learning among undergraduate students using WhatsApp compared to learning vocabulary via the Blackboard platform during the Covid-19 pandemic. To this end, 108 medical students (51 males, 57 females) enrolled in a first semester English for a specific English course participated in the study. A quasi-experimental design was adopted for two groups. Fifty-three students participated in the WhatsApp group and 55 students formed the Blackboard group. A pretest-posttest design was employed to collect data. Results of t-test scores did not show a significant difference between the WhatsApp and Blackboard groups on a vocabulary test. Results of a survey that measured students' opinion of the use of WhatsApp as a platform for learning new vocabulary showed positive perceptions since participants thought that WhatsApp enhanced their learning experience.

The Hidden Object Searching Method for Distributed Autonomous Robotic Systems

  • Yoon, Han-Ul;Lee, Dong-Hoon;Sim, Kwee-Bo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1044-1047
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    • 2005
  • In this paper, we present the strategy of object search for distributed autonomous robotic systems (DARS). The DARS are the systems that consist of multiple autonomous robotic agents to whom required functions are distributed. For instance, the agents should recognize their surrounding at where they are located and generate some rules to act upon by themselves. In this paper, we introduce the strategy for multiple DARS robots to search a hidden object at the unknown area. First, we present an area-based action making process to determine the direction change of the robots during their maneuvers. Second, we also present Q learning adaptation to enhance the area-based action making process. Third, we introduce the coordinate system to represent a robot's current location. In the end of this paper, we show experimental results using hexagon-based Q learning to find the hidden object.

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Wikispaces: A Social Constructivist Approach to Flipped Learning in Higher Education Contexts

  • Ha, Myung-Jeong
    • International Journal of Contents
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    • 제12권4호
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    • pp.62-68
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    • 2016
  • This paper describes an attempt to integrate flip teaching into a language classroom by adopting wikispaces as an online learning platform. The purpose of this study is to examine student perceptions of the effectiveness of using video lectures and wikispaces to foster active participation and collaborative learning. Flipped learning was implemented in an English writing class over one semester. Participants were 27 low intermediate level Korean university students. Data collection methods included background questionnaires at the beginning of the semester, learning experience questionnaires at the end of the semester, and semi-structured interviews with 6 focal participants. Because of the significance of video lectures in flip teaching, oCam was used for making weekly online lectures as a way of pre-class activities. Every week, online lectures were posted on the school LMS system (moodle). Every week, participants met in a computer room to perform in-class activities. Both in-class activities and post-class activities were managed by wikispaces. The results indicate that the flipped classroom facilitated student learning in the writing class. More than 53% of the respondents felt that it was useful to develop writing skills in a flipped classroom. Particularly, students felt that the video lectures prior to the class helped them improve their grammar skills. However, with respect to their satisfaction with collaborative works, about 44% of the participants responded positively. Similarly, 44% of the participants felt that in-class group work helped them interact with the other group members. Considering these results, this paper concludes with pedagogical suggestions and implications for further research.

수학 교육에서 열린 교수 학습의 실천적 방법 연구 (A Study on the Practical Methods of Open Teaching and Loaming in Mathematics Education)

  • 임문규
    • 한국초등수학교육학회지
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    • 제1권1호
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    • pp.17-32
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    • 1997
  • 오늘날 우리나라에서는 열린 교육이 이론과 실제의 양면에서 연구되고 실천되어 오고 있다. 본고에서는 초등학교 수학 교육에서 실용적으로 사용될 수 있는 열린 교육의 학습 지도 방법 세 가지를 소개하였는데, 이들은 ‘오픈 엔드 어프로치,’ ‘문제에서 문제로,’ 그리고 ‘문제 설정’이다. 이들 세 가지 학습 지도 방법 각각에 대하여 그 의미를 분석하고, 구체적인 지도 계획을 제시한 다음, 학생들의 실제 활동의 예를 보였다.

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A Suggestion on Using Animated Movie as Learning Materials for University Liberal Arts English Classes

  • Kim, HyeJeong
    • International Journal of Advanced Culture Technology
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    • 제10권2호
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    • pp.98-105
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    • 2022
  • This study's purpose is to suggest a pedagogical method based on using animated movie in liberal arts English classes and to examine the direction that using animated movie as learning material should take. To this end, in this study, the content understanding and expression concentration stages using animated movie are presented. After students learned in class through animated movie, two tests were conducted to investigate the change in learners' acquisition of English expressions. As a result, subjects' learning of English expressions showed a significant improvement over time. An open-ended questionnaire was also conducted to ascertain learners' satisfaction level and their perceptions of classes using animated movie, with learners' satisfaction found to be high overall (77.1%). Students identified the reasons for their high satisfaction rate as the following: "fun and a touching story", "beneficial composition of textbooks", "efficient teaching methods", "sympathetic topics", and "appropriate difficulty". When using video media in class, instructors should maximize and leverage the advantages of video media, which are rich both in context and in their linguistic aspects.

Instructional Design in the Cyber Classroom for Secondary Students' Basic English Language Competence

  • Chang, Kyung-Suk;Pae, Jue-Kyoung;Jeon, Young-Joo
    • International Journal of Contents
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    • 제12권2호
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    • pp.49-57
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    • 2016
  • This paper aims to explore instructional design of a cyber classroom for secondary students' basic English language competence. A paucity of support for low or under achieving students' English learning exists particularly at the secondary level. In order to bridge the gap, there has been demand for online educational resources considered to be an effective tool in improving students' self-directed learning and motivation. This study employs a comprehensive approach to instructional design for the asynchronous cyber classroom with the underlying premise that different learning theories can be applied in a complementary manner to serve different pedagogical purposes best. Gagné's conditions of learning theory, Bruner's constructivist theory, Carroll's minimalist theory, and Vygotsky's social cognitive development theory serve as the basis for designing instruction and selecting appropriate media. The ADDIE model is used to develop online teaching and learning materials. Twenty-five key grammatical features were selected through the analysis of the national curriculum of English, being grouped into five units. Each feature is covered in one cyber asynchronous class. An Integration Class is given at the end of every five classes for synthesis, where students can practice grammatical features in a communicative context. Related theories, pedagogical practices, and practical web-design strategies for cyber Basic English classes are discussed with suggestions for research, practice and policy to support self-directed learning through a cyber class.

중학생을 대상으로 한 수학적 의사소통의 지도 효과에 관한 연구 (Effects of communication in learning middle grade school Mathematics)

  • 김선희;이종희
    • 대한수학교육학회지:수학교육학연구
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    • 제8권1호
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    • pp.145-162
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    • 1998
  • This study investigated the effect of teaching mathematical communication in mathematics learning. Cooperative learning, mathematics pin pals, and writing a mathematics diary were used to teach how to communicate mathematically. The experimental group was assigned to cooperate in class, to write a mathematics diary at the end of each class, and to exchange the mathematics pen pals once a week. The control group was taught by the traditional teaching method. The results were analyzed quantitatively and qualitatively. The learning achievement between the two groups was performed with pretests and posttests. And after this study, mathematics pen pals, video protocol and open-ended test were analyzed. The results of this study are the following: 1. There were little differences in learning achievement test between the group taught through communication and those not. And there were little differences in the results of achievement test between the two groups-high and low level classes.2. Cooperative learning, writing a mathematics diary and mathematics pen pals were effective as methods of teaching communication mathematically. The analysis of mathematics pen pals which is to investigate student's writing abilities showed that pen pal partners were improved in QCAI communication levels. There was a significant difference between the two groups in open-ended test. This means that communication learning has an effect on the tests for mathematical thought, reasoning, and creative thought. The analysis of video protocol showed that four students in a cooperative group were improved in their speaking and listening abilities.

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Leveraging Big Data for Spark Deep Learning to Predict Rating

  • Mishra, Monika;Kang, Mingoo;Woo, Jongwook
    • 인터넷정보학회논문지
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    • 제21권6호
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    • pp.33-39
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    • 2020
  • The paper is to build recommendation systems leveraging Deep Learning and Big Data platform, Spark to predict item ratings of the Amazon e-commerce site. Recommendation system in e-commerce has become extremely popular in recent years and it is very important for both customers and sellers in daily life. It means providing the users with products and services they are interested in. Therecommendation systems need users' previous shopping activities and digital footprints to make best recommendation purpose for next item shopping. We developed the recommendation models in Amazon AWS Cloud services to predict the users' ratings for the items with the massive data set of Amazon customer reviews. We also present Big Data architecture to afford the large scale data set for storing and computation. And, we adopted deep learning for machine learning community as it is known that it has higher accuracy for the massive data set. In the end, a comparative conclusion in terms of the accuracy as well as the performance is illustrated with the Deep Learning architecture with Spark ML and the traditional Big Data architecture, Spark ML alone.

In-Process Cutter Runout Compensation Using Repetitive Learning Control

  • Joon Hwang;Chung, Eui-Sik
    • International Journal of Precision Engineering and Manufacturing
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    • 제4권4호
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    • pp.13-18
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    • 2003
  • This paper presents the in-process compensation to control cutter ronout and to improve the machined surface quality. Cutter ronout compensation system consists of the micro-positioning servo system with piezoelectric actuator which is embeded in the sliding table to manipulate radial depth of cut in real-time. Cutting force feedback control was proposed in the angle domain based upon repetitive learning control strategy to eliminate chip load variation in end milling process. Micro-positioning control due to adaptive actuation force response improves the machined surface quality by cutter ronout compensation.

Improved ensemble machine learning framework for seismic fragility analysis of concrete shear wall system

  • Sangwoo Lee;Shinyoung Kwag;Bu-seog Ju
    • Computers and Concrete
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    • 제32권3호
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    • pp.313-326
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    • 2023
  • The seismic safety of the shear wall structure can be assessed through seismic fragility analysis, which requires high computational costs in estimating seismic demands. Accordingly, machine learning methods have been applied to such fragility analyses in recent years to reduce the numerical analysis cost, but it still remains a challenging task. Therefore, this study uses the ensemble machine learning method to present an improved framework for developing a more accurate seismic demand model than the existing ones. To this end, a rank-based selection method that enables determining an excellent model among several single machine learning models is presented. In addition, an index that can evaluate the degree of overfitting/underfitting of each model for the selection of an excellent single model is suggested. Furthermore, based on the selected single machine learning model, we propose a method to derive a more accurate ensemble model based on the bagging method. As a result, the seismic demand model for which the proposed framework is applied shows about 3-17% better prediction performance than the existing single machine learning models. Finally, the seismic fragility obtained from the proposed framework shows better accuracy than the existing fragility methods.