• Title/Summary/Keyword: Learning support

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Mediating Effects of the Functions of Parent's Social Networks between Parent's Socioeconomic Status and Parent Involvement: Comparison of Single-mother and Two-parent Families (한부모 어머니의 사회·경제적 배경과 교육적 관여의 관계에서 사회관계망 기능의 매개효과: 양부모 가정 어머니와의 비교 연구)

  • Shin, Hae Jin;Han, In Young
    • The Korean Journal of Woman Psychology
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    • v.16 no.3
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    • pp.401-422
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    • 2011
  • The present study investigated the mediating effects of parents' social networks on the relationship between parents' socioeconomic status and parent involvement. Parent involvement in the current study was composed of home-based and school-based involvement. Home-based involvement includes providing learning environment at home, guiding child's study habits, and providing educational and financial support. School-based involvement includes supporting child's school-related activities, participating at parent meetings and volunteering, and home-school communication. The subjects were 132 single mothers and 164 mothers from two-parent families, whose children are fifth and sixth graders in Seoul and Incheon. Structural Equational Modeling was used for the analysis by adopting SPSS 18.0 and AMOS 18.0. The results showed that single mothers and mothers from two-parent families differ in their structural models. For mothers from two-parent families, socioeconomic status was directly related to home-based and school-based involvement. In contrast, single mother's socioeconomic status only influenced home-based and school-based involvement indirectly through the functional aspects of mother's social networks. The results suggest that parent counseling and parent education programs might be more effective if they encouraged single mothers to exchange resources through their social networks in order to promote parent involvement in elementary schools.

A Study on the Improvement of Utilization through Recognition of Virtual Training Content Operating Institutions (가상훈련 콘텐츠 운영기관 인식을 통한 활용도 제고방안 연구)

  • Miseok Yang;Chang Heon Oh
    • Journal of Practical Engineering Education
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    • v.14 no.3
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    • pp.479-489
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    • 2022
  • In order to understand how to increase the use of virtual training content at K University's online lifelong education institute, this study examined the use experience, content recognition, field practice replacement, and requirements, focusing on the examples of operating institutions. To this end, 12 institutions that operated virtual training contents distributed by the K University Online Lifelong Education Center in 2020 were selected for in-depth interviews and qualitative analysis was conducted on the interviews of 11 institutions. As a result of the analysis, first, the experience of using the contents of the virtual training operating institution was aimed at changing the educational environment, supplementing theoretical learning, and improving the sense of practice. Second, according to a survey on the recognition of virtual training content, if the importance and utilization of the content are high, it can be replaced by on-site practice in non-face-to-face classes, such as experiences of facilities and equipment, attracting interest and attention. Third, in many cases, the perception of replacement for field practice is not unreasonable to use as a pre-training material for field practice, but it is difficult to replace field practice. Fourth, content quality improvements can be summarized as content quality improvement, content access and manipulation improvement, dedicated device development, training for instructors, and curriculum systematization. Fifth, institutional requirements include improving the quality of virtual training content itself, equipment support, curriculum systemization and characterization, systematic curriculum and detailed content sharing, detailed guidance on using virtual training content, introducing how to use content, and recruiting instructors. This study is meaningful in that it sought ways to improve the utilization of virtual training content based on the perception of virtual training content operating institutions.

Adverse Effects on EEGs and Bio-Signals Coupling on Improving Machine Learning-Based Classification Performances

  • SuJin Bak
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.10
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    • pp.133-153
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    • 2023
  • In this paper, we propose a novel approach to investigating brain-signal measurement technology using Electroencephalography (EEG). Traditionally, researchers have combined EEG signals with bio-signals (BSs) to enhance the classification performance of emotional states. Our objective was to explore the synergistic effects of coupling EEG and BSs, and determine whether the combination of EEG+BS improves the classification accuracy of emotional states compared to using EEG alone or combining EEG with pseudo-random signals (PS) generated arbitrarily by random generators. Employing four feature extraction methods, we examined four combinations: EEG alone, EG+BS, EEG+BS+PS, and EEG+PS, utilizing data from two widely-used open datasets. Emotional states (task versus rest states) were classified using Support Vector Machine (SVM) and Long Short-Term Memory (LSTM) classifiers. Our results revealed that when using the highest accuracy SVM-FFT, the average error rates of EEG+BS were 4.7% and 6.5% higher than those of EEG+PS and EEG alone, respectively. We also conducted a thorough analysis of EEG+BS by combining numerous PSs. The error rate of EEG+BS+PS displayed a V-shaped curve, initially decreasing due to the deep double descent phenomenon, followed by an increase attributed to the curse of dimensionality. Consequently, our findings suggest that the combination of EEG+BS may not always yield promising classification performance.

GPT-enabled SNS Sentence writing support system Based on Image Object and Meta Information (이미지 객체 및 메타정보 기반 GPT 활용 SNS 문장 작성 보조 시스템)

  • Dong-Hee Lee;Mikyeong Moon;Bong-Jun, Choi
    • Journal of the Institute of Convergence Signal Processing
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    • v.24 no.3
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    • pp.160-165
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    • 2023
  • In this study, we propose an SNS sentence writing assistance system that utilizes YOLO and GPT to assist users in writing texts with images, such as SNS. We utilize the YOLO model to extract objects from images inserted during writing, and also extract meta-information such as GPS information and creation time information, and use them as prompt values for GPT. To use the YOLO model, we trained it on form image data, and the mAP score of the model is about 0.25 on average. GPT was trained on 1,000 blog text data with the topic of 'restaurant reviews', and the model trained in this study was used to generate sentences with two types of keywords extracted from the images. A survey was conducted to evaluate the practicality of the generated sentences, and a closed-ended survey was conducted to clearly analyze the survey results. There were three evaluation items for the questionnaire by providing the inserted image and keyword sentences. The results showed that the keywords in the images generated meaningful sentences. Through this study, we found that the accuracy of image-based sentence generation depends on the relationship between image keywords and GPT learning contents.

A Study on Real-time Autonomous Driving Simulation System Construction based on Digital Twin - Focused on Busan EDC - (디지털트윈 기반 실시간 자율주행 시뮬레이션 시스템 구축 방안 연구 - 부산 EDC 중심으로 -)

  • Kim, Min-Soo;Park, Jong-Hyun;Sim, Min-Seok
    • Journal of Cadastre & Land InformatiX
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    • v.53 no.2
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    • pp.53-66
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    • 2023
  • Recently, there has been a significant interest in the development of autonomous driving simulation environment based on digital twin. In the development of such digital twin-based simulation environment, many researches has been conducted not only performance and functionality validation of autonomous driving, but also generation of virtual training data for deep learning. However, such digital twin-based autonomous driving simulation system has the problem of requiring a significant amount of time and cost for the system development and the data construction. Therefore, in this research, we aim to propose a method for rapidly designing and implementing a digital twin-based autonomous driving simulation system, using only the existing 3D models and high-definition map. Specifically, we propose a method for integrating 3D model of FBX and NGII HD Map for the Busan EDC area into CARLA, and a method for adding and modifying CARLA functions. The results of this research show that it is possible to rapidly design and implement the simulation system at a low cost by using the existing 3D models and NGII HD map. Also, the results show that our system can support various functions such as simulation scenario configuration, user-defined driving, and real-time simulation of traffic light states. We expect that usability of the system will be significantly improved when it is applied to broader geographical area in the future.

A Framework Development for Sketched Data-Driven Building Information Model Creation to Support Efficient Space Configuration and Building Performance Analysis (효율적 공간 형상화 및 건물성능분석을 위한 스케치 정보 기반 BIM 모델 자동생성 프레임워크 개발)

  • Kong, ByungChan;Jeong, WoonSeong
    • Korean Journal of Construction Engineering and Management
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    • v.25 no.1
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    • pp.50-61
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    • 2024
  • The market for compact houses is growing due to the demand for floor plans prioritizing user needs. However, clients often have difficulty communicating their spatial requirements to professionals including architects because they lack the means to provide evidence, such as spatial configurations or cost estimates. This research aims to create a framework that can translate sketched data-driven spatial requirements into 3D building components in BIM models to facilitate spatial understanding and provide building performance analysis to aid in budgeting in the early design phase. The research process includes developing a process model, implementing, and validating the framework. The process model describes the data flow within the framework and identifies the required functionality. Implementation involves creating systems and user interfaces to integrate various systems. The validation verifies that the framework can automatically convert sketched space requirements into walls, floors, and roofs in a BIM model. The framework can also automatically calculate material and energy costs based on the BIM model. The developed frame enables clients to efficiently create 3D building components based on the sketched data and facilitates users to understand the space and analyze the building performance through the created BIM models.

Field Perception Analysis on Policy Outcomes of Academic Libraries (국내 대학도서관 정책 성과에 대한 현장 인식 조사)

  • Jongwook Lee;Woojin Kang;Youngmi Jung
    • Journal of Korean Library and Information Science Society
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    • v.54 no.4
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    • pp.415-436
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    • 2023
  • In this study, we aimed to examine the level of implementation of the second comprehensive plan for promoting academic libraries (2019-2023) by analyzing key statistics of academic libraries and gathering perceptions from library staff. We analyzed the changes in major statistical indicators of libraries over the past five years. Additionally, we surveyed library staff to understand their overall perceptions of the plan and their attitudes towards the 17 sub-tasks outlined in it. The analysis of 369 survey responses revealed several key findings. Firstly, most respondents comprehended the plan well and frequently utilized it for developing their libraries' development and implementation plans. Secondly, the IPA results indicated that regardless of the type of university, there should be a continuous focus on facility improvement, teaching-learning support, and expanding access to academic resources. Efforts to develop library policies and strengthen human and financial resources were identified as crucial. Thirdly, four-year universities particularly emphasized the importance of expanding access to international academic resources compared to junior colleges. Conversely, junior colleges perceived foundational skill-building programs and inclusive services as more significant than four-year universities. The application of the IPA diagonal model revealed that the performance levels of all sub-tasks were lower than their perceived importance levels, suggesting the need for strategies to enhance effectiveness in future comprehensive plan formulation.

Automatic scoring of mathematics descriptive assessment using random forest algorithm (랜덤 포레스트 알고리즘을 활용한 수학 서술형 자동 채점)

  • Inyong Choi;Hwa Kyung Kim;In Woo Chung;Min Ho Song
    • The Mathematical Education
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    • v.63 no.2
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    • pp.165-186
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    • 2024
  • Despite the growing attention on artificial intelligence-based automated scoring technology as a support method for the introduction of descriptive items in school environments and large-scale assessments, there is a noticeable lack of foundational research in mathematics compared to other subjects. This study developed an automated scoring model for two descriptive items in first-year middle school mathematics using the Random Forest algorithm, evaluated its performance, and explored ways to enhance this performance. The accuracy of the final models for the two items was found to be between 0.95 to 1.00 and 0.73 to 0.89, respectively, which is relatively high compared to automated scoring models in other subjects. We discovered that the strategic selection of the number of evaluation categories, taking into account the amount of data, is crucial for the effective development and performance of automated scoring models. Additionally, text preprocessing by mathematics education experts proved effective in improving both the performance and interpretability of the automated scoring model. Selecting a vectorization method that matches the characteristics of the items and data was identified as one way to enhance model performance. Furthermore, we confirmed that oversampling is a useful method to supplement performance in situations where practical limitations hinder balanced data collection. To enhance educational utility, further research is needed on how to utilize feature importance derived from the Random Forest-based automated scoring model to generate useful information for teaching and learning, such as feedback. This study is significant as foundational research in the field of mathematics descriptive automatic scoring, and there is a need for various subsequent studies through close collaboration between AI experts and math education experts.

A Study on the Intelligent Online Judging System Using User-Based Collaborative Filtering

  • Hyun Woo Kim;Hye Jin Yun;Kwihoon Kim
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.1
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    • pp.273-285
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    • 2024
  • With the active utilization of Online Judge (OJ) systems in the field of education, various studies utilizing learner data have emerged. This research proposes a problem recommendation based on a user-based collaborative filtering approach with learner data to support learners in their problem selection. Assistance in learners' problem selection within the OJ system is crucial for enhancing the effectiveness of education as it impacts the learning path. To achieve this, this system identifies learners with similar problem-solving tendencies and utilizes their problem-solving history. The proposed technique has been implemented on an OJ site in the fields of algorithms and programming, operated by the Chungbuk Education Research and Information Institute. The technique's service utility and usability were assessed through expert reviews using the Delphi technique. Additionally, it was piloted with site users, and an analysis of the ratio of correctness revealed approximately a 16% higher submission rate for recommended problems compared to the overall submissions. A survey targeting users who used the recommended problems yielded a 78% response rate, with the majority indicating that the feature was helpful. However, low selection rates of recommended problems and low response rates within the subset of users who used recommended problems highlight the need for future research focusing on improving accessibility, enhancing user feedback collection, and diversifying learner data analysis.

Parents' Perceptions of Cognitive Rehabilitation for Children With Developmental Disabilities: A Mixed-Method Approach of Phenomenological Methodology and Word Cloud Analysis (발달장애 아동 부모의 인지재활 경험에 대한 질적 연구: 워드 클라우드 분석과 현상학적 연구 방법 혼합설계)

  • Ju, Yu-Mi;Kim, Young-Geun;Lee, Hee-Ryoung;Hong, Seung-Pyo;Han, Dae-Sung
    • Therapeutic Science for Rehabilitation
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    • v.13 no.1
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    • pp.49-63
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    • 2024
  • Objective : The purpose of this study was to investigate parental perspectives on cognitive rehabilitation using a combination of phenomenological research methodology and word cloud analysis. Methods : Interviews were conducted with five parents of children with developmental disabilities. Word cloud analysis was conducted using Python, and five researchers analyzed the meaning units and themes using phenomenological methods. Words with high frequency were considered as a heuristic tool. Results : A total of 43 meaning units and nine components related to the phenomenon of cognitive rehabilitation were derived, and three themes were finalized. The main themes encompassed the definition of cognitive rehabilitation, challenges associated with cognitive rehabilitation, and factors influencing the selection of a cognitive rehabilitation institute. Cognitive rehabilitation emerged as a treatment focused on improving learning, daily functioning, and cognitive abilities in children with developmental disabilities. The perceived issues with cognitive rehabilitation pertained to treatment methods, therapist expertise, and associated costs. In addition, parents highlighted the importance of therapist expertise, humane personality, and affordability of cost and schedule when choosing a cognitive rehabilitation institute. Conclusion : Parents expressed expectations for substantial improvements in their children's daily functioning through cognitive rehabilitation. However, challenges were identified in clinical practices. Going forward, we expect that cognitive rehabilitation will evolve into a better therapeutic support service addressing the concerns raised by parents.