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Статті в журналах з теми "Demonstration Learning"

Автор: Grafiati

Опубліковано: 7 червня 2025

Оновлено: 2 серпня 2025

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1

Junaesih, Junaesih, Ajeng Kurniawati, and Humairoh Humairoh. "Application of the Demonstration Learning Model to Improve Student Learning Outcomes in Class 4 Social Sciences Lessons at State Elementary School 15 Serang." Jurnal Primagraha 3, no. 02 (2022): 53–63. http://dx.doi.org/10.59605/jp.v3i02.671.

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Анотація:

This research discusses the implementation of the demonstration method to improve student learning outcomes. Library research method with a qualitative descriptive approach. The results of this research from several theses and journals show that the demonstration method can improve student learning outcomes. Demonstration is a mode of presenting lessons by demonstrating and demonstrating to students a particular process, situation or object, either actually or just an imitation. The purpose of teaching using the demonstration model is a way of presenting lessons by demonstrating and demonstrat

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2

Defi Antika and Kharis Sulaiman Hasri. "Implementation of Silent Demonstration Learning Strategy to Improve Elementary Madrasah Students' Learning Outcomes." Journal of Contemporary Islamic Primary Education 2, no. 3 (2024): 164–69. https://doi.org/10.61253/jcipe.v2i3.299.

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This study aims to describe the implementation of Silent Demonstration for MI/SD students and how this activity can integrate students to think critically, creatively, communicatively, and collaboratively. This research uses a type of qualitative research with descriptive methods. Descriptive research, that is, research conducted to determine the value of the independent variable, either one variable or more (independent) without making comparisons or connecting with other variables. Qualitative collection techniques usually use observation, interviews, and documentation. The demonstration str

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3

Chernova, S., and M. Veloso. "Interactive Policy Learning through Confidence-Based Autonomy." Journal of Artificial Intelligence Research 34 (January 23, 2009): 1–25. http://dx.doi.org/10.1613/jair.2584.

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We present Confidence-Based Autonomy (CBA), an interactive algorithm for policy learning from demonstration. The CBA algorithm consists of two components which take advantage of the complimentary abilities of humans and computer agents. The first component, Confident Execution, enables the agent to identify states in which demonstration is required, to request a demonstration from the human teacher and to learn a policy based on the acquired data. The algorithm selects demonstrations based on a measure of action selection confidence, and our results show that using Confident Execution the agen

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4

Birlson, O., and M. Singleton. "The Demonstration Kitchen: Gauging Participant Learning in Cooking Demonstrations." Journal of the Academy of Nutrition and Dietetics 117, no. 10 (2017): A139. http://dx.doi.org/10.1016/j.jand.2017.08.076.

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5

Zha, Yantian, Lin Guan, and Subbarao Kambhampati. "Learning from Ambiguous Demonstrations with Self-Explanation Guided Reinforcement Learning." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 9 (2024): 10395–403. http://dx.doi.org/10.1609/aaai.v38i9.28907.

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Анотація:

Our work aims at efficiently leveraging ambiguous demonstrations for the training of a reinforcement learning (RL) agent. An ambiguous demonstration can usually be interpreted in multiple ways, which severely hinders the RL agent from learning stably and efficiently. Since an optimal demonstration may also suffer from being ambiguous, previous works that combine RL and learning from demonstration (RLfD works) may not work well. Inspired by how humans handle such situations, we propose to use self-explanation (an agent generates explanations for itself) to recognize valuable high-level relation

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6

Mantahari Pohan. "Upaya Meningkatan Hasil Belajar IPA Melalui Model Pembelajaran Demonstarasi Pada Siswa Kelas VI SDN 027 Danau Lancang Kecamatan Tapung Hulu Kabupaten Kampar." Journal Innovation In Education 1, no. 1 (2023): 06–12. http://dx.doi.org/10.59841/inoved.v2i1.993.

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Анотація:

Demonstration is a very effective model, because it helps students to find answers on their own based on correct facts or data. The demonstration method is a method of presenting lessons by demonstrating and demonstrating to students a particular process, situation or object, either actually or just an imitation. As a presentation method, demonstration cannot be separated from verbal explanation by the teacher. Based on the results of data analysis and discussion, it can show some of the progress achieved during learning, both through classical learning, group learning results, and learning ou

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7

Gorbenko, Anna, and Vladimir Popov. "Mechanical Research with Intelligent Avatars for Robot Learning from Demonstration." Advanced Materials Research 952 (May 2014): 287–90. http://dx.doi.org/10.4028/www.scientific.net/amr.952.287.

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Анотація:

It is well known that learning from demonstration has many attractive points for both learner and teacher. However, the quality of such learning depends crucially from the system of understanding of human demonstrations. In this paper, we consider an approach to design intelligent avatars for robot learning from demonstration. Also, we present experimental results for intelligent avatar mediated learning from demonstration.

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8

Zhang, Ning, Tao Qi, and Yongjia Zhao. "Real-Time Learning and Recognition of Assembly Activities Based on Virtual Reality Demonstration." Sensors 21, no. 18 (2021): 6201. http://dx.doi.org/10.3390/s21186201.

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Анотація:

Teaching robots to learn through human demonstrations is a natural and direct method, and virtual reality technology is an effective way to achieve fast and realistic demonstrations. In this paper, we construct a virtual reality demonstration system that uses virtual reality equipment for assembly activities demonstration, and using the motion data of the virtual demonstration system, the human demonstration is deduced into an activity sequence that can be performed by the robot. Through experimentation, the virtual reality demonstration system in this paper can achieve a 95% correct rate of a

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9

Laka, Diana Siska. "THE INFLUENCE OF THE DEMONSTRATION METHOD ON THE LEARNING MOTIVATION OF CLASS VI STUDENTS OFSDN 078553 ORLIN, SOUTH NIAS REGENCY ONINDONESIAN LANGUAGE SUBJECTS." Journal of Learning on History and Social Sciences 1, no. 4 (2024): 36–44. https://doi.org/10.61796/ejlhss.v1i4.509.

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Анотація:

The demonstration method is very important in teaching because it makes abstract concepts more concrete and easier for students to understand. In addition, demonstrations involve students directly in the learning process. They can see, hear, and often participate in demonstrations, which helps improve information retention. Meanwhile, motivating students is one of the most important aspects of effective teaching. This research aims to determine the effect of the demonstration method on the learning motivation of class VI students at SDN 078553 Orlin in Indonesian language subjects. The method

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10

Billard, Aude, and Roland Siegwart. "Robot learning from demonstration." Robotics and Autonomous Systems 47, no. 2-3 (2004): 65–67. http://dx.doi.org/10.1016/j.robot.2004.03.001.

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11

Billard, Aude, and Daniel Grollman. "Robot learning by demonstration." Scholarpedia 8, no. 12 (2013): 3824. http://dx.doi.org/10.4249/scholarpedia.3824.

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12

Feng, Shengyu, and Yiming Yang. "SORREL: Suboptimal-Demonstration-Guided Reinforcement Learning for Learning to Branch." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 11 (2025): 11212–20. https://doi.org/10.1609/aaai.v39i11.33219.

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Анотація:

Mixed Integer Linear Program (MILP) solvers are mostly built upon a Branch-and-Bound (B&B) algorithm, where the efficiency of traditional solvers heavily depends on hand-crafted heuristics for branching. The past few years have witnessed the increasing popularity of data-driven approaches to automatically learn these heuristics. However, the success of these methods is highly dependent on the availability of high-quality demonstrations, which requires either the development of near-optimal heuristics or a time-consuming sampling process. This paper averts this challenge by proposing Subopt

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13

Forbes, Maxwell, Michael Chung, Maya Cakmak, and Rajesh Rao. "Robot Programming by Demonstration with Crowdsourced Action Fixes." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2 (September 5, 2014): 67–76. http://dx.doi.org/10.1609/hcomp.v2i1.13164.

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Programming by Demonstration (PbD) can allow end-users to teach robots new actions simply by demonstrating them. However, learning generalizable actions requires a large number of demonstrations that is unreasonable to expect from end-users. In this paper, we explore the idea of using crowdsourcing to collect action demonstrations from the crowd. We propose a PbD framework in which the end-user provides an initial seed demonstration, and then the robot searches for scenarios in which the action will not work and requests the crowd to fix the action for these scenarios. We use instance-based le

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14

Ingram, Julie, Hannah Chiswell, Jane Mills, et al. "Enabling learning in demonstration farms: a literature review." International Journal of Agricultural Extension 2018 (December 12, 2018): 29–42. https://doi.org/10.5281/zenodo.6619865.

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Анотація:

Demonstration farms have a long tradition and have proved to be an effective means of supporting farmers in problem solving at the farm level. The new demands of complex and uncertain agricultural systems call for a renewed understanding of the approaches used and the concepts that underpin them, in particular those relating to farmer learning in the demonstration. A multi-faceted demonstration ‘learning system’ creates different contexts or conditions that enable learning. Of these contexts and conditions, structural and functional characteristics provide a good framework for anal

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15

Suomalainen, Markku, Fares J. Abu-dakka, and Ville Kyrki. "Imitation learning-based framework for learning 6-D linear compliant motions." Autonomous Robots 45, no. 3 (2021): 389–405. http://dx.doi.org/10.1007/s10514-021-09971-y.

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AbstractWe present a novel method for learning from demonstration 6-D tasks that can be modeled as a sequence of linear motions and compliances. The focus of this paper is the learning of a single linear primitive, many of which can be sequenced to perform more complex tasks. The presented method learns from demonstrations how to take advantage of mechanical gradients in in-contact tasks, such as assembly, both for translations and rotations, without any prior information. The method assumes there exists a desired linear direction in 6-D which, if followed by the manipulator, leads the robot’s

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16

Husain, Halimah, and Wardana Wardana. "IMPLEMENTASI STRATEGI DEMONSTRASI DALAM PEMBELAJARAN PENDIDIKAN AGAMA ISLAM DI SMP NEGERI 2 SINJAI TIMUR KABUPATEN SINJAI." AL-QAYYIMAH: Jurnal Pendidikan Islam 4, no. 2 (2021): 213–35. http://dx.doi.org/10.30863/aqym.v4i2.2039.

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This paper discusses the implementation of demonstration strategies in learning Islamic education in junior high schools. Aims to reveal about the implementation of the demonstration strategy in Islamic Religious Education learning and its contribution at SMP Negeri 2 Sinjai Timur, Sinjai Regency. This research is included in the type of field research with a qualitative method approach. The data were obtained using several instruments, namely; observation guide, interview guide, and documentation tool. The results showed that the demonstration method is a method that uses demonstrations to cl

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17

Karimi, Sara, Sahar Asadi, and Amir H. Payberah. "SCORE: Skill-Conditioned Online Reinforcement Learning." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 20, no. 1 (2024): 189–98. http://dx.doi.org/10.1609/aiide.v20i1.31879.

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Анотація:

Solving complex long-horizon tasks through Reinforcement Learning (RL) from scratch presents challenges related to efficient exploration. Two common approaches to reduce complexity and enhance exploration efficiency are (i) integrating learning-from-demonstration techniques with online RL, where the prior knowledge acquired from demonstrations is used to guide exploration, refine representations, or tailor reward functions, and (ii) using representation learning to facilitate state abstraction. In this study, we present Skill-Conditioned Online REinforcement Learning (SCORE), a novel approach

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18

Laka, Diana Siska, and Ulil Azmi. "ON THE LEARNING MOTIVATION OF CLASS VI STUDENTS OF SDN 078553 ORLIN, SOUTH NIAS REGENCY ON INDONESIAN LANGUAGE SUBJECTS." European Journal of Learning on History and Social Sciences 1, no. 4 (2024): 36–44. http://dx.doi.org/10.61796/ejlhss.v1i4.509.

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Анотація:

The demonstration method is very important in teaching because it makes abstract concepts more concrete and easier for students to understand. In addition, demonstrations involve students directly in the learning process. They can see, hear, and often participate in demonstrations, which helps improve information retention. Meanwhile, motivating students is one of the most important aspects of effective teaching. This research aims to determine the effect of the demonstration method on the learning motivation of class VI students at SDN 078553 Orlin in Indonesian language subjects. The method

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19

Hinrichs, Thomas, and Kenneth Forbus. "Learning Qualitative Models by Demonstration." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (2021): 207–13. http://dx.doi.org/10.1609/aaai.v26i1.8153.

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Creating software agents that learn interactively requires the ability to learn from a small number of trials, extracting general, flexible knowledge that can drive behavior from observation and interaction. We claim that qualitative models provide a useful intermediate level of causal representation for dynamic domains, including the formulation of strategies and tactics. We argue that qualitative models are quickly learnable, and enable model-based reasoning techniques to be used to recognize, operationalize, and construct more strategic knowledge. This paper describes an approach to increme

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20

Nicolescu, Monica, Odest Chadwicke Jenkins, Adam Olenderski, and Eric Fritzinger. "Learning behavior fusion from demonstration." Interaction Studies 9, no. 2 (2008): 319–52. http://dx.doi.org/10.1075/is.9.2.09nic.

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Анотація:

A critical challenge in robot learning from demonstration is the ability to map the behavior of the trainer onto a robot’s existing repertoire of basic/primitive capabilities. In part, this problem is due to the fact that the observed behavior of the teacher may consist of a combination (or superposition) of the robot’s individual primitives. The problem becomes more complex when the task involves temporal sequences of goals. We introduce an autonomous control architecture that allows for learning of hierarchical task representations, in which: (1) every goal is achieved through a linear super

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21

Chi, Mingshan, Yufeng Yao, Yaxin Liu, Yiqian Teng, and Ming Zhong. "Learning motion primitives from demonstration." Advances in Mechanical Engineering 9, no. 12 (2017): 168781401773726. http://dx.doi.org/10.1177/1687814017737260.

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22

Akgun, Baris, Maya Cakmak, Karl Jiang, and Andrea L. Thomaz. "Keyframe-based Learning from Demonstration." International Journal of Social Robotics 4, no. 4 (2012): 343–55. http://dx.doi.org/10.1007/s12369-012-0160-0.

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23

Lestari, Mariana, Sutiyono Sutiyono, Priono Priono, and Susanto Susanto. "Pembelajaran Demonstrasi di Pendidikan Keagamaan Buddha." Jurnal Maitreyawira 5, no. 2 (2024): 1–6. https://doi.org/10.69607/p5k36x17.

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Анотація:

The demonstrative approach to enhance student learning outcomes is covered in this study. Presenting teachings to pupils by showing them a specific procedure, circumstance, or item whether authentic or merely an imitation is known as the disclosure approach. Demonstrations as a presentation technique are inextricably linked to the teacher's spoken explanations. Demonstrations can offer more tangible learning materials, even though the role of the students is the only thing that needs to be taken into account. Demonstrations can be utilized to help expository and inquiry tactics succeed in appr

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24

GAO, T., D. D. DMITRIEV, and K. A. NEUSYPIN. "STATISTICAL LEARNING OF ROBOTIC DEMONSTRATION TRAJECTORIES BASED ON MULTICRITERIA SEGMENTATION AND MULTI-DEMONSTRATION ALIGNMENT (HSMM)." Computational Nanotechnology 12, no. 1 (2025): 34–47. https://doi.org/10.33693/2313-223x-2025-12-1-34-47.

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Statistical Learning of Robotic Demo Trajectories Based on Multicriteria Segmentation and Multi-Demonstration Alignment (HSMM) addresses complex tasks in human-robot interaction and intelligent manufacturing. The research goal of this study is to automatically extract generalized key segments from multiple robotic demonstration trajectories in the absence of prior annotations and establish statistical and parametric models for universal trajectory reproduction across diverse tasks and conditions. To achieve this, the research tasks include multicriteria segmentation (speed, curvature, accelera

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25

Ghavami, Akbar, Hossein Samadi, Amir Dana, and Saeed Ghorbani. "Effects of observing real, animated and combined model on learning cognitive and motor levels of basketball jump shot in children." Biomedical Human Kinetics 14, no. 1 (2021): 54–60. http://dx.doi.org/10.2478/bhk-2022-0007.

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Abstract Study aim: The purpose of the present study was to investigate the effects of observing the real, animated and combined model demonstrations on cognitive and motor learning of a basketball jump shot. Material and methods: Forty-five subjects with mean age of (11.03 ± 1.7) were randomly divided into three groups: real, animated and combined model demonstrations. Subjects were asked to perform basketball jump shot task during a four-step process. In total, participants shot 150 shots (10 shots in the pretest, 120 shots and 40 observations in the practice phase, and 10 shots in the postt

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26

Yang, Zeguo, Mantian Li, Fusheng Zha, Xin Wang, Pengfei Wang, and Wei Guo. "Imitation learning of a wheeled mobile manipulator based on dynamical movement primitives." Industrial Robot: the international journal of robotics research and application 48, no. 4 (2021): 556–68. http://dx.doi.org/10.1108/ir-11-2020-0255.

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Purpose This paper aims to introduce an imitation learning framework for a wheeled mobile manipulator based on dynamical movement primitives (DMPs). A novel mobile manipulator with the capability to learn from demonstration is introduced. Then, this study explains the whole process for a wheeled mobile manipulator to learn a demonstrated task and generalize to new situations. Two visual tracking controllers are designed for recording human demonstrations and monitoring robot operations. The study clarifies how human demonstrations can be learned and generalized to new situations by a wheel mob

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27

Manrique-Cordoba, Juliana, Miguel Ángel de la Casa-Lillo, and José María Sabater-Navarro. "N-Dimensional Reduction Algorithm for Learning from Demonstration Path Planning." Sensors 25, no. 7 (2025): 2145. https://doi.org/10.3390/s25072145.

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This paper presents an n-dimensional reduction algorithm for Learning from Demonstration (LfD) for robotic path planning, addressing the complexity of high-dimensional data. The method extends the Douglas–Peucker algorithm by incorporating velocity and orientation alongside position, enabling more precise trajectory simplification. A magnitude-based normalization process preserves proportional relationships across dimensions, and the reduced dataset is used to train Hidden Markov Models (HMMs), where continuous trajectories are discretized into identifier sequences. The algorithm is evaluated

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28

Hafridarli, Hafridarli. "Meningkatkan Hasil Belajar Siswa dengan Metode Demonstrasi pada Permainan Bola Basket di Sekolah Dasar." Gelanggang Olahraga: Jurnal Pendidikan Jasmani dan Olahraga (JPJO) 1, no. 2 (2018): 84–95. http://dx.doi.org/10.31539/jpjo.v1i2.169.

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The purpose of this study is to improve student learning outcomes on basketball games with demonstration methods for students of class 5 SDN 22 Koto Baru. Research methods that researchers use for classroom action research is action research conducted in the classroom to improve student learning outcomes. This study was conducted in 2 cycles. Each cycle consists of planning, implementation, observation, and reflection. This research was conducted at SDN 22 Koto Baru. This research was conducted in August with the november 2017 in 5 C SDN 22 Koto Baru class, the result of the research shows tha

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29

Azizah, Rismatul, Lia Yuliati, and Eny Latifa. "Kemampuan Pemecahan Masalah Melalui Pembelajaran Interactive Demonstration Siswa Kelas X SMA pada Materi Kalor." Jurnal Pendidikan Fisika dan Teknologi 2, no. 2 (2017): 55. http://dx.doi.org/10.29303/jpft.v2i2.289.

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Анотація:

The application of teacher centered learning in classroom is causing the underdevelopment of students problem solving ability and students activity in learning. Interactive demonstration is an active learning model developed by Wenning. Through interactive demonstrations, students can use the basic intellectual process skills that includes predicting, explaining, estimating, acquiring and processing data, formulating and revising scientific explanations using logic and evidence, and recognizing and analyzing alterative xplanations and models. The purpose of this research is to determine the ef

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30

Mesterjon, Suwarni, Rulismi Dwi, and Supama. "Evaluation of Demonstration Learning Models in Improving Vocational Student Learning Outcomes." Education Quarterly Reviews 6, no. 3 (2023): 173–80. https://doi.org/10.31014/aior.1993.06.03.772.

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Анотація:

Technology 4.0 is currently developing rapidly, which has been used in various fields. One of them is as a tool in the field of education. The use of technology in the 4.0 era in learning is a necessity, including digital simulation learning. The use of Technology 4.0 in the world of education, especially in learning, will have an impact on the teaching and learning process to become more creative and competitive. Of course, in its implementation, it is necessary to evaluate the achievement of the learning model that has been implemented before. So this study aims to evaluate the application o

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31

Khoirunnisa, Ummul, and Chusnul Chotimah. "Efektivitas Penerapan Metode Demonstrasi di SMP Negeri 2 Gudo Jombang." JoEMS (Journal of Education and Management Studies) 5, no. 4 (2022): 8–11. http://dx.doi.org/10.32764/joems.v5i4.721.

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Анотація:

The demonstration method is a teaching and learning method that is suitable for creating a conducive teaching and learning situation. This demonstration method is a learning method by demonstrating items, events, rules, and the sequence of activities, either directly or through the use of teaching media that are relevant to the subject or material presented. Methods This research uses a qualitative research approach. Data collection techniques in this study were observation, interviews and documentation. The results of this study indicate that the implementation of teaching and learning situat

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32

Rizal Muhaimin, Arisul Ulumuddin, and Suyoto Suyoto. "Penerapan Metode Demonstrasi Pada Pembelajaran Menulis Teks Eksplanasi Peserta Didik Kelas VIII SMPN 31 Semarang Tahun Ajaran 2023/ 2024." Simpati 1, no. 4 (2023): 193–200. http://dx.doi.org/10.59024/simpati.v1i4.474.

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Анотація:

This research is motivated to show the lack of enthusiasm of students in learning activities, especially Indonesian learning. Learning activities Indonesian, students lack focus so that it causes boredom during learning. So a special method is needed to foster the enthusiasm of students so that the learning process can take place well. The demonstration method is a teaching method by demonstrating goods, events, rules, and sequences in carrying out activities, directly and using teaching media that are relevant to the subject matter or material that has been presented. Based on this background

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33

Riungu, Claris, Harro Maat, and Marrit Van Den Berg. "High-yielding seeds in unyielding environments: Examining the learning process of maize and bean producers in eastern and midwestern Uganda." Outlook on Agriculture 50, no. 4 (2021): 418–40. http://dx.doi.org/10.1177/00307270211054112.

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This paper examines the learning process by which farmers come to a decision to use newly introduced seeds which were promoted through demonstration plots in midwestern and eastern regions of Uganda. Framed as social and material interactions, we investigated the learning process of the demonstration plots using data from focus group discussions, interviews and a survey amongst 983 individuals. The results reveal several constraints that impede learning, resulting in an overall low awareness and adoption of the introduced seeds. Some of the most prominent constraints resulted from the selectio

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34

Sena, Aran, and Matthew Howard. "Quantifying teaching behavior in robot learning from demonstration." International Journal of Robotics Research 39, no. 1 (2019): 54–72. http://dx.doi.org/10.1177/0278364919884623.

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Анотація:

Learning from demonstration allows for rapid deployment of robot manipulators to a great many tasks, by relying on a person showing the robot what to do rather than programming it. While this approach provides many opportunities, measuring, evaluating, and improving the person’s teaching ability has remained largely unexplored in robot manipulation research. To this end, a model for learning from demonstration is presented here that incorporates the teacher’s understanding of, and influence on, the learner. The proposed model is used to clarify the teacher’s objectives during learning from dem

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35

Hwang, Pin-Jui, Chen-Chien Hsu, Po-Yung Chou, Wei-Yen Wang, and Cheng-Hung Lin. "Vision-Based Learning from Demonstration System for Robot Arms." Sensors 22, no. 7 (2022): 2678. http://dx.doi.org/10.3390/s22072678.

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Robotic arms have been widely used in various industries and have the advantages of cost savings, high productivity, and efficiency. Although robotic arms are good at increasing efficiency in repetitive tasks, they still need to be re-programmed and optimized when new tasks are to be deployed, resulting in detrimental downtime and high cost. It is therefore the objective of this paper to present a learning from demonstration (LfD) robotic system to provide a more intuitive way for robots to efficiently perform tasks through learning from human demonstration on the basis of two major components

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Martha, Dina, Hartati Hartati, and Zulfiati Syahrial. "Pengaruh Metode Pembelajaran Dan Kecerdasan Interpersonal Terhadap Kompetensi Komunikasi Terapeutik Mahasiswa Program DIII Kebidanan Stikes Mitra Ria Husada Cibubur." JTP - Jurnal Teknologi Pendidikan 20, no. 1 (2018): 1–12. http://dx.doi.org/10.21009/jtp.v20i1.7834.

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This study aims to determine the method of learning and interpersonal intelligence to therapeutic communication competence of DIII students Obstetrics STIKes Mitra RIA Husada. Learning methods are placed on bedside teaching methods, coaching methods and demonstrations. The method used in this research is experiment with treatment design level 3 x 2 with sample 48 student. The summary of this research is: 1) Bedside teaching methods can improve therapeutic communication better than coaching methods and methods of demonstration; 2) Coaching learning method can improve therapeutic communication b

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Suwarno, Hadi, Noor Fatirul Achmad, and Adi Walujo SDjoko. "The Influence of Demonstration Method Vs Discussion Method and Learning Motivation on Chassis Maintenance and Repair of Class XII Students at SMK PGRI 1 Gresik." International Journal of Social Science and Human Research 07, no. 12 (2024): 9135–48. https://doi.org/10.5281/zenodo.14511744.

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The purpose of this study is to describe the application of the demonstration method vs. the discussion method on student learning outcomes, this study also seeks differences between students who have high motivation and low motivation towards improving student learning outcomes and seeks interactions between learning methods and learning motivation towards improving student learning outcomes on the material of chassis maintenance and repair in class XII at SMK PGRI 1 Gresik. The results and conclusions in this study are that (1) there is a difference in achievement between students who are gi

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Duc, Tho Nguyen, Chanh Minh Tran, Phan Xuan Tan, and Eiji Kamioka. "Generative Adversarial Network for Imitation Learning from Single Demonstration." Baghdad Science Journal 18, no. 4(Suppl.) (2021): 1350. http://dx.doi.org/10.21123/bsj.2021.18.4(suppl.).1350.

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Imitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The propos

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Grant, Margaret. "Online demonstration experiments as experiential learning." Proceedings of the Linguistic Society of America 9, no. 3 (2024): 5855. http://dx.doi.org/10.3765/plsa.v9i3.5855.

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Demonstration experiments are commonly used as a teaching tool in courses in experimental linguistics, cognitive psychology and cognitive science. This paper presents an inquiry into the impact of participating in demonstration experiments on student learning. This inquiry frames demonstration experiments as a form of experiential learning. As such, the experiment exercises were designed following the Co-Constructed Developmental Teaching Theory (Shenk & Cruikshank 2015), a model of experiential teaching inspired by the cognitive neuroscience of learning. One demonstration experiment exerc

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Muslimah, Siti. "Upaya Meningkatkan Hasil Belajar Fikih Materi Perawatan Jenazah melalui Metode Demonstrasi di MTs Negeri 3 Kulon Progo." Jurnal Pendidikan Madrasah 4, no. 2 (2020): 243–48. http://dx.doi.org/10.14421/jpm.2019.42-12.

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This research focuses on improving the results of fiqh learning by demonstration method to increase the value that has not reached the KKM at MTsN 3 Kulon Progo. This research uses class action research methods to describe the process and learning outcomes through demonstration methods implemented in the form of cycles. Data collection is done through interviews, observation sheets, tests and documentation. Data on student learning outcomes is obtained through tests, then compared to the minimum standards that are indicators of successful research, i.e. most students (+ 75%) Obtain a value of

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Murdiyah, Murdiyah. "Improving Student Learning Outcomes Through the Application of Demonstration Methods in Science Learning At SMP Negeri 17 Palu." Pinisi Journal of Education and Management 2, no. 2 (2023): 165. http://dx.doi.org/10.26858/pjoem.v2i2.53364.

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The demonstration method is a way of presenting lessons by demonstrating or demonstrating to students a particular process, situation, or object being studied, either actually or imitation, which is often accompanied by an oral explanation. With the demonstration method, the process of students' acceptance of the lesson will be more deeply impressive, thus forming a good and perfect understanding. Therefore, the aim of this research is to find out how the demonstration method is implemented so that it can improve the activities and learning outcomes of class IX A science lessons at SMP Negeri

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Xue, Xianfa, Lei Zuo, and Ning Wang. "A Robot Human-Like Learning Framework Applied to Unknown Environment Interaction." Complexity 2022 (March 1, 2022): 1–10. http://dx.doi.org/10.1155/2022/5648826.

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Learning from demonstration (LfD) is one of the promising approaches for fast robot programming. Most learning systems learn both movements and stiffness profiles from human demonstrations. However, they rarely consider the unknown environment interaction. In this paper, a robot human-like learning framework is proposed, where it can learn human skills through demonstration and complete the interaction task with an unknown environment. Firstly, the desired trajectory was generated by dynamic movement primitive (DMP) based on human demonstration. Then, an adaptive optimal admittance control sch

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Nur Pebrianti, Eka, Ade Suherman, and Lili Dianah. "The Effect of Demonstration Model to Social Studies Learning Outcomes." SAHUR Journal 1, no. 1 (2024): 21–27. https://doi.org/10.31980/sahur.v1i1.2032.

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This research is backgrounded by the low learning outcomes of students in social studies subjects because the learning outcomes in social studies subjects because the learning is still teacher-centred and the low number of teacher participating in training on the development of learning methods. One of the efforts in overcoming this is the need for innovative and effective learning methods, one of which is by using demonstration learning methods. This type of research uses a quantitative approach with a quasi-experimental method with a Nonequivalent Control Group Design design with a pretest-p

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Kase, Kei, Noboru Matsumoto, and Tetsuya Ogata. "Leveraging Motor Babbling for Efficient Robot Learning." Journal of Robotics and Mechatronics 33, no. 5 (2021): 1063–74. http://dx.doi.org/10.20965/jrm.2021.p1063.

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Deep robotic learning by learning from demonstration allows robots to mimic a given demonstration and generalize their performance to unknown task setups. However, this generalization ability is heavily affected by the number of demonstrations, which can be costly to manually generate. Without sufficient demonstrations, robots tend to overfit to the available demonstrations and lose the robustness offered by deep learning. Applying the concept of motor babbling – a process similar to that by which human infants move their bodies randomly to obtain proprioception – is also effective for allowin

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Sun, Yin-Tung Albert, Hsin-Chang Lin, Po-Yen Wu, and Jung-Tang Huang. "Learning by Watching via Keypoint Extraction and Imitation Learning." Machines 10, no. 11 (2022): 1049. http://dx.doi.org/10.3390/machines10111049.

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In recent years, the use of reinforcement learning and imitation learning to complete robot control tasks have become more popular. Demonstration and learning by experts have always been the goal of researchers. However, the lack of action data has been a significant limitation to learning by human demonstration. We propose an architecture based on a new 3D keypoint tracking model and generative adversarial imitation learning to learn from expert demonstrations. We used 3D keypoint tracking to make up for the lack of action data in simple images and then used image-to-image conversion to conve

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Putri, Yulinda Ariska Mela, Mauren Gita Miranti, Sri Handajani, and Niken Purwidiani. "Implementation of Video Demonstration of Foodstuffs Chop in Direct Learning Setting for Vocational High Schools Students." EduLine: Journal of Education and Learning Innovation 3, no. 2 (2023): 254–62. http://dx.doi.org/10.35877/454ri.eduline1780.

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Video demonstrations are applied corresponding to direct learning and provide support for students to have complete knowledge that requires repetition in the domination of the concept. This study analyzes the influence of implementing video demonstrations in the direct learning setting of foodstuffs chop on the knowledge level and the performance level learning outcomes. Forty students of the 11th culinary class at SMKN 1 Cerme Gresik were involved in this quantitative study using a pretest-posttest design. This study employed observation and test methods using observation sheets of learning i

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Munoz, J., Arif Ozgelen, and Elizabeth Sklar. "Learning from Demonstration in Spatial Exploration." Proceedings of the AAAI Conference on Artificial Intelligence 25, no. 1 (2011): 1878–79. http://dx.doi.org/10.1609/aaai.v25i1.8000.

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We present the initial stage of our research on Learning from Demonstration algorithms. We have implemented an algorithm based on Confident Execution, one of the components of the Confidence-Based Autonomy algorithm developed by Chernova and Veloso. Our preliminary experiments were conducted first in simulation and then using a Sony AIBO ERS-7 robot. So far, our robot has been able to learn crude navigation strategies, despite limited trials. We are currently working on improving our implementation by including additional features that describe more broadly the state of the agent. Our long ter

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Billing, Erik A., and Thomas Hellström. "A Formalism for Learning from Demonstration*." Paladyn, Journal of Behavioral Robotics 1, no. 1 (2010): 1–13. http://dx.doi.org/10.2478/s13230-010-0001-5.

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Michini, Bernard, Thomas J. Walsh, Ali-Akbar Agha-Mohammadi, and Jonathan P. How. "Bayesian Nonparametric Reward Learning From Demonstration." IEEE Transactions on Robotics 31, no. 2 (2015): 369–86. http://dx.doi.org/10.1109/tro.2015.2405593.

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Ramsey, Linda L., Jeffrey Walczyk, William C. Deese, and Danny Eddy. "Using Demonstration Assessments to Improve Learning." Journal of Chemical Education 77, no. 11 (2000): 1511. http://dx.doi.org/10.1021/ed077p1511.

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