• 제목/요약/키워드: Feedback-State Learning

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CARE Model-based Math Learning Coaching Model Development Study (CARE 모델 기반 수학학습 코칭 모델 개발 연구)

  • Kim, Jung Hyun;Ko, Ho Kyoung
    • Communications of Mathematical Education
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    • v.36 no.4
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    • pp.511-533
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    • 2022
  • The purpose of this study is to develop a learning coaching model suitable for the mathematics subject by reflecting the characteristics of the mathematics subject and the mathematics teaching/learning process in the CARE learning coaching model that supports students' self-directed learning. The mathematics learning coaching model developed in this study is a 'step' and 'element' to apply coaching, and a 'strategy' for carrying out it. Mathematics learning coaching model evaluated rapport, trust, state management, and math pre-test as elements of 'creating a comfortable atmosphere', and problem recognition, hypercognition, restructuring, initiative, and math learning ability as elements of 'improving perception'. Self-efficacy, learning readiness, confirmation (feedback) as elements of the 'reawakening of learning immersion' stage, voluntary motivation and success experiences as elements of the 'empowerment' stage, and various math learning strategies to perform each element presented. The math learning coaching model can be used to help math teachers motivate students to learn and help students solve their own problems.

Customization and Autonomy : Characteristics of the Ideal Design Studio Instructor in Design Education

  • Cho, Ji Young
    • Architectural research
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    • v.15 no.3
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    • pp.123-132
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    • 2013
  • Design studio is a unique type of course in architecture and interior design education, in which learning is based on student-instructor interaction and learning by doing; yet little research has been conducted on student perceptions of the ideal design studio instructor. The purpose of this paper was to identify characteristics of the ideal studio instructor from student perspectives. Three award-winning design studio instructors' studio activities were observed, and the three instructors and their 40 students were interviewed. As a result, characteristics in four categories were identified. The author argues that providing customized feedback and allowing student autonomy are the two distinct characteristics that students value in design studio as compared to students in other fields or type of courses. The findings provide valuable insights to design educators who would like to strengthen their teaching studios by listening to student voices.

Development of educational software for beam loading analysis using pen-based user interfaces

  • Suh, Yong S.
    • Journal of Computational Design and Engineering
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    • v.1 no.1
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    • pp.67-77
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    • 2014
  • Most engineering software tools use typical menu-based user interfaces, and they may not be suitable for learning tools because the solution processes are hidden and students can only see the results. An educational tool for simple beam analyses is developed using a pen-based user interface with a computer so students can write and sketch by hand. The geometry of beam sections is sketched, and a shape matching technique is used to recognize the sketch. Various beam loads are added by sketching gestures or writing singularity functions. Students sketch the distributions of the loadings by sketching the graphs, and they are automatically checked and the system provides aids in grading the graphs. Students receive interactive graphical feedback for better learning experiences while they are working on solving the problems.

Control of Seesaw balancing using decision boundary based on classification method

  • Uurtsaikh, Luvsansambuu;Tengis, Tserendondog;Batmunkh, Amar
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.2
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    • pp.11-18
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    • 2019
  • One of the key objectives of control systems is to maintain a system in a specific stable state. To achieve this goal, a variety of control techniques can be used and it is often uses a feedback control method. As known this kind of control methods requires mathematical model of the system. This article presents seesaw unstable system with two propellers which are controlled without use of a mathematical model instead. The goal was to control it using training data. For system control we use a logistic regression technique which is one of machine learning method. We tested our controller on the real model created in our laboratory and the experimental results show that instability of the seesaw system can be fixed at a given angle using the decision boundary estimated from the classification method. The results show that this control method for structural equilibrium can be used with relatively more accuracy of the decision boundary.

Analysis for Practical use as a Learning Diagnostic Assessment Instruments through the Knowledge State Analysis Method (지식상태분석법을 이용한 학습 진단평가도구로의 활용성 분석)

  • Park, Sang-Tae;Lee, Hee-Bok;Jeong, Kee-Ju;Kim, Seok-Cheon
    • Journal of The Korean Association For Science Education
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    • v.27 no.4
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    • pp.346-353
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    • 2007
  • In order to be efficient in teaching, a teacher should understand the current learner's level through diagnostic evaluation. This study has examined the major issues arising from the noble diagnostic assessment tool based on the theory of knowledge space. The knowledge state analysis method is actualizing the theory of knowledge space for practical use. The knowledge state analysis method is very advantageous when a certain group or individual student's knowledge structure is analyzed especially for strong hierarchical subjects such as mathematics, physics, chemistry, etc. Students' knowledge state helps design an efficient teaching plan by referring their hierarchical knowledge structure. The knowledge state analysis method can be enhanced by computer due to fast data processing. In addition, each student's knowledge can be improved effectively through individualistic feedback depending on individualized knowledge structure. In this study, we have developed a diagnostic assessment test for measuring student's learning outcome which is unattainable from the conventional examination. The diagnostic assessment test was administered to middle school students and analyzed by the knowledge state analysis method. The analyzed results show that students' knowledge structure after learning found to be more structured and well-defined than the knowledge structure before the learning.

Deep Learning Methods for Recognition of Orchard Crops' Diseases

  • Sabitov, Baratbek;Biibsunova, Saltanat;Kashkaroeva, Altyn;Biibosunov, Bolotbek
    • International Journal of Computer Science & Network Security
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    • v.22 no.10
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    • pp.257-261
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    • 2022
  • Diseases of agricultural plants in recent years have spread greatly across the regions of the Kyrgyz Republic and pose a serious threat to the yield of many crops. The consequences of it can greatly affect the food security for an entire country. Due to force majeure, abnormal cases in climatic conditions, the annual incomes of many farmers and agricultural producers can be destroyed locally. Along with this, the rapid detection of plant diseases also remains difficult in many parts of the regions due to the lack of necessary infrastructure. In this case, it is possible to pave the way for the diagnosis of diseases with the help of the latest achievements due to the possibilities of feedback from the farmer - developer in the formation and updating of the database of sick and healthy plants with the help of advances in computer vision, developing on the basis of machine and deep learning. Currently, model training is increasingly used already on publicly available datasets, i.e. it has become popular to build new models already on trained models. The latter is called as transfer training and is developing very quickly. Using a publicly available data set from PlantVillage, which consists of 54,306 or NewPlantVillage with a data volumed with 87,356 images of sick and healthy plant leaves collected under controlled conditions, it is possible to build a deep convolutional neural network to identify 14 types of crops and 26 diseases. At the same time, the trained model can achieve an accuracy of more than 99% on a specially selected test set.

Academic Interests of Korean Students: Description, Diagnosis, & Prescription (한국 학생의 학업에 대한 흥미: 실태, 진단 및 처방)

  • Sung-il Kim;Misun Yoon;Yeon-hee So
    • Korean Journal of Culture and Social Issue
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    • v.14 no.1_spc
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    • pp.187-221
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    • 2008
  • Although academic interest, the intersection of cognition, emotion, and motivation, is a primary goal of learning and mediates the effects of learning, the present learning environment is full of impeding factors which undermine learner's interests in learning situation. The purpose of this study is to examine current state of academic interests of Korean students and to identify several potential causes of developmental declines in academic interests. It has been consistently found that academic interests in various school subjects decrease with age and grade in school. Three potentially contributing factors to the observed loss of academic interests are mainly discussed: deprived autonomy, severe competition, and normative evaluation. Based on theories on interest and motivation, and empirical findings, various prescriptions are also suggested for designing an interest-based learning environment in order to trigger and enhance learner's academic interests.

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The Position Control of Excavator's Attachment using Multi-layer Neural Network (다층 신경 회로망을 이용한 굴삭기의 위치 제어)

  • Seo, Sam-Joon;Kwon, Dai-Ik;Seo, Ho-Joon;Park, Gwi-Tae;Kim, Dong-Sik
    • Proceedings of the KIEE Conference
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    • 1995.07b
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    • pp.705-709
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    • 1995
  • The objective of this study is to design a multi-layer neural network which controls the position of excavator's attachment. In this paper, a dynamic controller has been developed based on an error back-propagation(BP) neural network. Since the neural network can model an arbitrary nonlinear mapping, it was used as a commanded feedforward input generator. A PD feedback controller is used in parallel with the feedforward neural network to train the system. The neural network was trained by the current state of the excavator as well as the PD feedback error. By using the BP network as a feedforward controller, no a priori knowledge on system dynamics is need. Computer simulation results demonstrate such powerful characteristics of the proposed controller as adaptation to changing environment, robustness to disturbancen and performance improvement with the on-line learning in the position control of excavator attachment.

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A Study on the Factors Affecting Flow in e-Learning Environment - Focusing on Interaction Factors and Affordance - (이러닝 환경에서 몰입에 영향을 미치는 요인 연구 -상호작용 요인과 어포던스 요인을 중심으로-)

  • Lee, So-Young;Kim, Hyung-Jun
    • The Journal of the Korea Contents Association
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    • v.19 no.10
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    • pp.522-534
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    • 2019
  • The purpose of this study is to investigate the interaction factors(learning motivation, concrete feedback, learner's control) and affordance factors (aesthetics, playfulness, stability) that influence flow in e - learning. This study collected 236 survey data from e-learning users. The data was analyzed the statistical relationships among the variables using the SPSS21 and AMOS21. The measurement model was reliable and valid, and the structual model was good. The result shows that interaction factors (concrete feedback, learner's control) and affordance factor (playfulness) influence on flow. Flow has a significant effect on satisfaction. Especially the effect of playfulness on flow is meaningful. Playfulness is one of the most important factors leading to the flow state of humans. The contribution of this study is to find the factors influencing flow in the interaction between learners and computer in e-learning. It can be used to provide an entertainment experience that can enhance the satisfaction of consumers in the Internet environment by finding the antecedents that affect the flow in computer - human interaction.

A Study on the Current Status and Improvement Plans for e-Learning Utilization Using the Delphi Technique: Focusing on Scuba Diving Education

  • Sung-Soo Park
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.5
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    • pp.143-153
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    • 2024
  • This study aims to analyze both the current utilization of e-learning in the scuba diving education sector and the possible improvements by using Delphi analysis. The study administered three rounds of Delphi surveys with 25 specialists, including business executives and educational leaders from scuba diving centers and resorts affiliated with organizations that conduct scuba diving education through e-learning. The comparative analysis of the state of e-learning utilization and factors for improvement revealed significant insights. In terms of expected benefits, the analysis highlighted an increase in user convenience, temporal flexibility in learning activities, and easy access to products. However, it identified major issues such as the simplistic mandatory exams, inadequate professional depth in the feedback provided, and a lack of bidirectional communication between learners and instructors. Recommendations for improvements included enhancing communication through various online communities, conducting mandatory exams offline, and developing a variety of content. Conducting regular program quality evaluations, integrating with various diving communities, and assigning dedicated tutors were deemed crucial factors for future development.