• Title/Summary/Keyword: Profile Learning

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Latent Profile Analysis of Medical Students' Use of Motivational Regulation Strategies for Online Learning (온라인 학습에서 의과대학생의 동기조절 프로파일 유형에 따른 인지학습과 학습몰입 간 관계 분석)

  • Yun, Heoncheol;Kim, Seon;Chung, Eun-Kyung
    • Korean Medical Education Review
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    • v.23 no.2
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    • pp.118-127
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    • 2021
  • Due to the coronavirus disease 2019 pandemic, the new norm of online learning has been recognized as core to medical institutions for academic continuity, and students are expected to be motivated and engaged in learning while maintaining distance from other peers and educators. To facilitate students' and educators' newly defined roles in online medical education settings, it is crucial to understand how students are actively motivated and engaged in learning. Hence, this study explored medical students' motivational regulation profiles and examined the effects of motivational regulation strategies (MRS) on cognitive learning and learning engagement for online learning. Data were collected after the end of the first semester in 2020 from a sample of 334 medical students enrolled at a public university school of medicine. Latent profile analysis indicated three subgroups with different motivational regulation profiles: the low-profile, medium-profile, and high-profile groups. Regarding different MRS patterns in the high-profile group, mastery self-talk, performance approach self-talk, and the self-consequating strategy appeared to be most applicable for regulating learners' motivation. Analysis of variance showed that the profile groups with higher levels of MRS use were connected to a higher willingness to use cognitive learning strategies and a higher degree of engagement in online learning. The findings of this study emphasize the use of specific sets of MRS to support learning motivation and the need to design effective self-regulated learning environments in online medical education settings.

Study on the Pad Wear Profile Based on the Conditioner Swing Using Deep Learning for CMP Pad Conditioning (CMP 패드 컨디셔닝에서 딥러닝을 활용한 컨디셔너 스윙에 따른 패드 마모 프로파일에 관한 연구)

  • Byeonghun Park;Haeseong Hwang;Hyunseop Lee
    • Tribology and Lubricants
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    • v.40 no.2
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    • pp.67-70
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    • 2024
  • Chemical mechanical planarization (CMP) is an essential process for ensuring high integration when manufacturing semiconductor devices. CMP mainly requires the use of polyurethane-based polishing pads as an ultraprecise process to achieve mechanical material removal and the required chemical reactions. A diamond disk performs pad conditioning to remove processing residues on the pad surface and maintain sufficient surface roughness during CMP. However, the diamond grits attached to the disk cause uneven wear of the pad, leading to the poor uniformity of material removal during CMP. This study investigates the pad wear rate profile according to the swing motion of the conditioner during swing-arm-type CMP conditioning using deep learning. During conditioning, the motion of the swing arm is independently controlled in eight zones of the same pad radius. The experiment includes six swingmotion conditions to obtain actual data on the pad wear rate profile, and deep learning learns the pad wear rate profile obtained in the experiment. The absolute average error rate between the experimental values and learning results is 0.01%. This finding confirms that the experimental results can be well represented by learning. Pad wear rate profile prediction using the learning results reveals good agreement between the predicted and experimental values.

A Deep Learning Model for Predicting User Personality Using Social Media Profile Images

  • Kanchana, T.S.;Zoraida, B.S.E.
    • International Journal of Computer Science & Network Security
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    • v.22 no.11
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    • pp.265-271
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    • 2022
  • Social media is a form of communication based on the internet to share information through content and images. Their choice of profile images and type of image they post can be closely connected to their personality. The user posted images are designated as personality traits. The objective of this study is to predict five factor model personality dimensions from profile images by using deep learning and neural networks. Developed a deep learning framework-based neural network for personality prediction. The personality types of the Big Five Factor model can be quantified from user profile images. To measure the effectiveness, proposed two models using convolution Neural Networks to classify each personality of the user. Done performance analysis among two different models for efficiently predict personality traits from profile image. It was found that VGG-69 CNN models are best performing models for producing the classification accuracy of 91% to predict user personality traits.

Case Study: A Preservice Teacher's Belief Changes Represented as Constructivist Profile

  • Kwak, Young-Sun
    • Journal of The Korean Association For Science Education
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    • v.21 no.5
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    • pp.795-821
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    • 2001
  • This Qualitative study investigated a preservice teacher's developing views of learning with the influence of constructivist epistemology taught in the Math, Science, and Technology Education (MSAT) Master of Education (M. Ed.) preservice teacher education program. The MSAT teacher education program employs constructivist aspects of teacher education and generates applications of constructivism to the practice of teaching, as revealed by faculty interview data. It is important at this point to emphasize that there are significant epistemological and ontological differences between different versions of educational constructivism (i.e., individual, radical, and social constructivism) and that these differences imply different pedagogical practices. For the 16 preservice teachers included in a larger study, the epistemological and ontological characteristics for each teacher's developing views of learning were identified through four in-depth interviews. Data from interviews were used to construct a constructivist profile for each preservice teacher's views of learning (i.e., a profile containing ontological beliefs, epistemological commitments, and pedagogical beliefs). Of the sixteen participants in the larger study, five significantly changed ontological and epistemological beliefs and eleven did not. Profile changes for the five who did change also resulted in changes in their conceptions of science teaching and learning (CSTL). In this article, one of the five teachers case was presented with rich quotes. This case study documents how a preservice teacher transferred his ontological and epistemological beliefs to his pedagogical beliefs and maintained the consistency between his philosophical beliefs and CSTL. It also demonstrated implications that changes in components for an educational constructivist profile have for a preservice teacher's view of himself as teacher. Data indicated the possibility that a constructivist-oriented preservice teacher education program can influence students' conceptions of science teaching and learning by explicitly introducing constructivism as an epistemology rather than as a specific method of instruction. Implications for both instructional practices of teacher education programmes and research are discussed.

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Construction on e-learning Platform of Smart Phone Environment (스마트폰 환경에서의 e-learning 플랫폼의 구축)

  • Pyo, Sung-Bae
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.11
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    • pp.125-132
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    • 2012
  • In recent years, a variety of learning content construction utilizing the smart phone is coming. In this paper, we investigate on overall trends and movements in e-learning performance at University. And system developed a e-learning platform consisting of smart phone portal, learning management system(LMS), and learning content management system(LCMS). Throughout the experiment, each of the components of the e-learning were implemented. LMS was implemented more efficiently using a user profile evaluation system for qualification.

Intelligent learning system based on the profile of learner (학습자 프로파일 기반의 지능형 학습 시스템)

  • Cho, Tae-Kyung
    • Journal of Digital Convergence
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    • v.14 no.2
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    • pp.227-233
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    • 2016
  • Typical Web-based learning system is operating the variety of learning contents. However, it is not easy to efficiently select appropriate learning contents. In this paper, we propose a learning content delivery method that can provide the most suitable preferences and feedback to the learner. By analyzing the profile of the learner, it determines the positive feedback and evaluation to be provided to the learner. The result of applying learning techniques were applied to provide the best learning content to adaptively out the form. The proposed method appears as a learning experience and learning outcomes are higher after a study was conducted to suggest that could help in the learning progress of the students themselves. This paper are applied to real learners. And the learners using the system were surveyed by the questionnaire on learning experience and learning outcomes were analyzed.

A latent Profile Analysis of Students' Learning Motivation Profiles on Entrepreneurial Educational Motivation and Entrepreneurial Intentions and Type of Entrepreneurship (대학생 창업교육동기에 대한 사람중심접근법 : 잠재프로파일 유형에 따른 창업의도 및 창업유형)

  • Oh, Hyun Sung;Byun, Ji-Yeon;Kim, Jun Soo
    • The Journal of the Korea Contents Association
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    • v.20 no.9
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    • pp.365-379
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    • 2020
  • The purpose of this study identifies the patterns of students' learning motivation profiles on entrepreneurial educational motivation among a sample of university students from one of the Korean national university(n=614). This study also examines the relationship between students' learning motivation profiles and entrepreneurial intention and types of entrepreneurship. In order to explore the types of leaning motivation profiles, a latent profile analysis was employed. Result from LPA revealed five distinct types of learning motivation profiles fit the data best, and these five profiles are compared with students' entrepreneurial intentions and types of entrepreneurship. Results showed that Profiles (profile 5 and 4-high goal orientation) are associated with the higher level of entrepreneurial intention. Regarding the type of entrepreneurship, the majority of all students are interested in individual and co-entrepreneurship with friend regardless of the patterns of profiles.

Profile Analysis of Elementary School Students' Smart Device Usage

  • SUK, Youmi;CHO, Young Hoan;JEONG, Dae Hong
    • Educational Technology International
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    • v.18 no.1
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    • pp.27-47
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    • 2017
  • Smart devices have a variety of affordances to foster meaningful learning in elementary school. For the design of smart learning environments, more research is needed to understand students' smart device usage and their perception of learning with smart devices. In order to capture smart device usage profiles among elementary school students in South Korea, this study carried out Latent Profile Analysis with three constructs: information search, communication, and study. Participants (n=253), who ranged from the fourth to the sixth grade students, were classified into three profiles of smart device usage: low-activity, communication, and high-activity groups. The smart device usage profiles varied depending on smartphone usage experience, and the profiles were significantly related with smart device addiction, not with smart device usage ability. Perceptions of smart education were also significantly associated with the profiles. The high-activity group showed more positive attitudes toward smart education than the others, but no significant difference was found in regard to negative attitudes. Based on the findings, this study discussed implications for the use of smart devices in elementary school.

Adaptive Learning System using Real-time Learner Profiling (실시간 학습자 프로파일링을 이용한 적응적 학습 시스템)

  • Yang, Yeong-Wook;Yu, Won-Hee;Lim, Heui-Seok
    • Journal of Digital Convergence
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    • v.12 no.2
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    • pp.467-473
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    • 2014
  • Adaptive learning system means a system that provides adaptively learning materials according to the learning needs of learners. It consists of expert model, instructional model and student model. Expert model is that stores information which is to be taught. Student model stores the data of learning history and learning information of students. Instructional model provides necessary learning materials for actual leaners. This paper has constructed student model through learner's profile information and instructional model through dynamic scenario construction. After that, We have developed adaptively to provide learning to learners by constructing suitable dynamic scenario based on learners profile information. In the end, satisfaction result about this system showed a high degree of satisfaction and 88%.

Discovery of Preference through Learning Profile for Content-based Filtering (내용 기반 필터링을 위한 프로파일 학습에 의한 선호도 발견)

  • Chung, Kyung-Yong;Jo, Sun-Moon
    • The Journal of the Korea Contents Association
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    • v.8 no.2
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    • pp.1-8
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    • 2008
  • The information system in which users can utilize to control and to get the filtered information efficiently has appeared. Content-based filtering can reflect content information, and it provides recommendation by comparing the feature information about item and the profile of preference. This has the shortcoming of the varying accuracy of prediction depending on teaming method. This paper suggests the discovery of preference through learning the profile for the content-based filtering. This study improves the accuracy of recommendation through learning the profile according to granting the preference of 6 levels to estimated value in order to solve the problem. Finally, to evaluate the performance of the proposed method, this study applies to MovieLens dataset, and it is compared with the performance of previous studies.