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Journal articles on the topic 'Strategy-Based learning'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Ahmad, Gufran. "Instructional Strategy Based on Associative Relevance Improves e-Learning." International Journal of e-Education, e-Business, e-Management and e-Learning 5, no. 3 (2015): 165–72. http://dx.doi.org/10.17706/ijeeee.2015.5.3.165-172.

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Naw, Naw. "Work-based learning: A learning strategy in support of the Myanmar education framework." Universal Academic Research Journal 4, no. 1 (2022): 22–31. http://dx.doi.org/10.17220/tuara.2022.01.03.

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3

Bahrudin, Ida Aryanie, and Maizam Alias. "A Review on Exploratory based Learning Implementation by Integrating Technology Strategy in Teaching and Learning." International Journal of Psychosocial Rehabilitation 24, no. 03 (2020): 657–64. http://dx.doi.org/10.37200/ijpr/v24i3/pr200822.

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López, María Mercedes López. "Project-based Learning Strategy: An Innovative Proposal for Local Education System." International Journal of Psychosocial Rehabilitation 24, no. 1 (2020): 1666–81. http://dx.doi.org/10.37200/ijpr/v24i1/pr200267.

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Ramirez-Velarde, Raul, Nia Alexandrov, Raul Perez-Cazares, and Carlos Barba-Jimenez. "Mathematical Modelling Based Learning Strategy." Procedia Computer Science 51 (2015): 1694–704. http://dx.doi.org/10.1016/j.procs.2015.05.307.

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Rorong, Ferdy Dj, and Diane M. Tengker. "Learning Japanese "Kaiwa" Based on Strategy." Budapest International Research and Critics in Linguistics and Education (BirLE) Journal 2, no. 4 (2019): 594–602. http://dx.doi.org/10.33258/birle.v2i4.680.

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This study regarding the learning Japanese “Kaiwa” based on strategy. The result shows that strategies are grouped into direct strategies and indirect strategies. By using strategies that are in accordance with the wishes and character of the learner, maximum results can be achieved in learning any language. In Quantum Teaching it is said that humans teach 10% of what is read, 20% of what is heard, 30% of what is seen, 50% of what is seen and heard 70% of what is said and 90% of what is said and done because education will be effective when we accept the theory and be accompanied by exercises.

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Nayak, B. Satheesha, and K. V. Soumya. "Keyword based learning (KBL): a novel teaching/learning strategy." South-East Asian Journal of Medical Education 6, no. 2 (2012): 48. http://dx.doi.org/10.4038/seajme.v6i2.170.

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Tan, Chunxi, Ruijian Han, Rougang Ye, and Kani Chen. "Adaptive Learning Recommendation Strategy Based on Deep Q-learning." Applied Psychological Measurement 44, no. 4 (2019): 251–66. http://dx.doi.org/10.1177/0146621619858674.

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Personalized recommendation system has been widely adopted in E-learning field that is adaptive to each learner’s own learning pace. With full utilization of learning behavior data, psychometric assessment models keep track of the learner’s proficiency on knowledge points, and then, the well-designed recommendation strategy selects a sequence of actions to meet the objective of maximizing learner’s learning efficiency. This article proposes a novel adaptive recommendation strategy under the framework of reinforcement learning. The proposed strategy is realized by the deep Q-learning algorithms

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Mumtaz, Sadaf, and Rabia Latif. "Learning through debate during problem-based learning: an active learning strategy." Advances in Physiology Education 41, no. 3 (2017): 390–94. http://dx.doi.org/10.1152/advan.00157.2016.

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We explored medical student’s views and perceptions of a series of debates conducted during problem-based learning (PBL) practiced as a part of the Spiral curriculum at the Imam Abdulrahman Bin Faisal University, Saudi Arabia. A series of debates were employed during PBL sessions for second-year female medical students, over the period 2014–2016. Each cohort of students was randomly split into 10 small PBL groups and exposed to weekly PBL activity. Within each group, the students were divided into a proposition half and an opposition half. Students were given 1 wk for debate preparation. The s

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Rodríguez-Sandoval, Eduardo, Édgar Mauricio Vargas-Solano, and Janeth Luna-Cortés. "Assessment of the "project-based learning" strategy." Educación y Educadores 13, no. 1 (2010): 13–25. http://dx.doi.org/10.5294/edu.2010.13.1.1.

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Min, Huaqing, Chang'an Yi, Ronghua Luo, Sheng Bi, Xiaowen Shen, and Yuguang Yan. "Affordance Learning Based on Subtask's Optimal Strategy." International Journal of Advanced Robotic Systems 12, no. 8 (2015): 111. http://dx.doi.org/10.5772/61087.

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12

Chen, Shun, and Lei Ge. "A learning-based strategy for portfolio selection." International Review of Economics & Finance 71 (January 2021): 936–42. http://dx.doi.org/10.1016/j.iref.2020.07.010.

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Napitupulu, Selviana, David Manalu, and Sanggam Siahaan. "Scientific Approach-Based English Learning Strategy (SABELS)." New Educational Review 56, no. 2 (2019): 41–52. http://dx.doi.org/10.15804/tner.19.56.2.03.

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Lira, Ana Luisa Brandão de Carvalho, and Marcos Venícios de Oliveira Lopes. "Nursing diagnosis: educational strategy based on problem-based learning." Revista Latino-Americana de Enfermagem 19, no. 4 (2011): 936–43. http://dx.doi.org/10.1590/s0104-11692011000400012.

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This study aimed to evaluate the effectiveness of a teaching strategy on nursing diagnoses based on problem-based learning in the performance of clinical reasoning and diagnostic trial of undergraduate students. Experimental study conducted in two phases: content validation of problems and implementation of educational strategy. The results showed improvement in the data pooling ability of students in the experimental group. It is concluded that the strategy put in practice exerted a positive influence.

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15

Li, Xinyu, Xiaoguang Gao, and Chenfeng Wang. "A Novel BN Learning Algorithm Based on Block Learning Strategy." Sensors 20, no. 21 (2020): 6357. http://dx.doi.org/10.3390/s20216357.

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Learning accurate Bayesian Network (BN) structures of high-dimensional and sparse data is difficult because of high computation complexity. To learn the accurate structure for high-dimensional and sparse data faster, this paper adopts a divide and conquer strategy and proposes a block learning algorithm with a mutual information based K-means algorithm (BLMKM algorithm). This method utilizes an improved K-means algorithm to block the nodes in BN and a maximum minimum parents and children (MMPC) algorithm to obtain the whole skeleton of BN and find possible graph structures based on separated b

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16

Sari, Dwi Rosita. "PROBLEM BASED LEARNING." Lingual: Journal of Language and Culture 9, no. 1 (2020): 39. http://dx.doi.org/10.24843/ljlc.2020.v09.i01.p07.

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The aims of research are (1) The implementation of Problem Based Learning strategy to teach speaking descriptive text (2) To find the problems of Problem Based Learning strategy to teach speaking descriptive text (3) To know the solutions of the Problem Based Learning strategy to teach speaking descriptive text. The type of this research is descriptive qualitative research and researcher uses case study in answering the problem of the research. This research takes the seventh grade students of SMPN 1 Bendo, Kabupaten Magetan in term 2018/2019. The results of research show that the implementati

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Rahimi, Merak, and Atefeh Allahyari. "Effects of Multimedia Learning Combined With Strategy-Based Instruction on Vocabulary Learning and Strategy Use." SAGE Open 9, no. 2 (2019): 215824401984408. http://dx.doi.org/10.1177/2158244019844081.

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18

Tarigan, Ratelit. "INFLUENCE STRATEGY LEARNING BASED PROBLEMS WITH THE CONVENTIONAL LEARNING TO STUDENT LEARNING OUTCOMES." Jurnal Pendidikan Fisika 2, no. 1 (2013): 68. http://dx.doi.org/10.22611/jpf.v2i1.4339.

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This study aims to determine the differences in learning outcomes of students who use learning strategies based on problems with the conventional instructional strategies in the subject matter and measuring student learning activities when using learning strategies based on problems with conventional learning. The study was quasi-experimental. The population is all class X Semester Gasal SMA Swasta Martadinata consisting of 9 classes. Sampling was done by cluster random sampling by taking 2 classes of 9th grade classes were randomly ie X-7 as the experimental class and numbered 34, the class X

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19

Park, Sung-Mi. "Development of Learning Strategy e-Learning Contents based on the Storytelling." Journal of Fisheries and Marine Sciences Education 24, no. 2 (2012): 272–85. http://dx.doi.org/10.13000/jfmse.2012.24.2.272.

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20

Zhu, Yonghai. "Symbolic Learning Strategy based on Symbol Literacy Improvement." Research Journal of Applied Sciences, Engineering and Technology 6, no. 1 (2013): 144–48. http://dx.doi.org/10.19026/rjaset.6.4049.

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21

.G, Singaravelu. "Discussion Based Fish Bowl Strategy in Learning Psychology." i-manager’s Journal on Educational Psychology 1, no. 1 (2007): 61–63. http://dx.doi.org/10.26634/jpsy.1.1.462.

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22

Xu, Guiping, Quanlong Cui, Xiaohu Shi, et al. "Particle swarm optimization based on dimensional learning strategy." Swarm and Evolutionary Computation 45 (March 2019): 33–51. http://dx.doi.org/10.1016/j.swevo.2018.12.009.

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23

Kouamé, Saouré, Gokhan Turgut, and Serge Poisson De Haro. "Strategy Teaching With Hybrid Problem Based Learning Method." Academy of Management Proceedings 2019, no. 1 (2019): 15122. http://dx.doi.org/10.5465/ambpp.2019.15122abstract.

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24

Qu, Zhaowei, Rong Cui, Qizhu Song, and Sixing Yin. "Predictive spectrum sensing strategy based on reinforcement learning." China Communications 11, no. 10 (2014): 117–25. http://dx.doi.org/10.1109/cc.2014.6969800.

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25

Rider, Elizabeth A., and Valentina Brashers. "Team-based learning: a strategy for interprofessional collaboration." Medical Education 40, no. 5 (2006): 486–87. http://dx.doi.org/10.1111/j.1365-2929.2006.02434.x.

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26

Lumbantoruan, Jagar. "ART LEARNING STRATEGY BASED ON DIRECTIVE INSTRUCTION MODEL." Komposisi: Jurnal Pendidikan Bahasa, Sastra, dan Seni 17, no. 1 (2016): 19. http://dx.doi.org/10.24036/komposisi.v17i1.8413.

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This article aims to describe the development strategy of art based instruction directive instruction. Learning development strategy is realized through design planning and systematic learning system to solve learning problems. This can be done by adopting relevant learning models. Directive Instruction as a model is done by creating a lesson plan, ie identifying topics, determining learning objectives, and selecting examples and problems. The process of learning planning for a directive instruction model starts from identifying one specific skill desired by educators and learners to be unders

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27

Kavaliou, A. V., and A. V. Hromava. "Strategy Design Method Based on Corporate Learning System." Science & Technique 19, no. 2 (2020): 119–24. http://dx.doi.org/10.21122/2227-1031-2020-19-2-119-124.

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The paper proposes a method for a strategy design that corresponds to concept of dynamic capabilities. The advan-tages and disadvantages of the methods of strategy design used by various schools of strategic management are demonstrated. The authors postulate inconsistency between a new stage of scientific knowledge and the related technique of strategic analysis and strategy design methods. The purpose of the article is to develop a method for creation a strategy based on a learning system as a key element of a competitive advantage in the concept of dynamic abilities. The method compares favo

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28

Zhang, Kai, Ou Li, Bai Wei Yang, and Yang Liu. "A New Q-Learning Based Spectrum Access Strategy." Applied Mechanics and Materials 380-384 (August 2013): 1920–23. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1920.

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To optimize the opportunistic spectrum access strategy, a new Q-Learning based spectrum access strategy is proposed. The strategy can lead secondary user to select channels with maximum cumulative reward, and maximize secondary user throughput. From the simulation results, compared with random selection algorithm, the algorithm does not require prior knowledge or prediction models of the channel environment, yet can still select the optimal channel adaptively, improve the secondary user capability and attain to the convergence in short time.

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29

Chen, Yanjun, Kun Liu, Yuantao Xie, and Mingyu Hu. "Financial Trading Strategy System Based on Machine Learning." Mathematical Problems in Engineering 2020 (July 28, 2020): 1–13. http://dx.doi.org/10.1155/2020/3589198.

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The long-term and short-term volatilities of financial market, combined with the complex influence of linear and nonlinear information, make the prediction of stock price extremely difficult. This paper breaks away from the traditional research framework of increasing the number of explanatory variables to improve the explanatory ability of multifactor model and provides a new financial trading strategy system by introducing Light Gradient Boosting Machine (LightGBM) algorithm into stock price prediction and by constructing the minimum variance portfolio of mean-variance model with Conditional

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30

Okubo, Yumiko, Naoko Ishiguro, Taiyo Suganuma, et al. "Team-Based Learning, a Learning Strategy for Clinical Reasoning, in Students with Problem-Based Learning Tutorial Experiences." Tohoku Journal of Experimental Medicine 227, no. 1 (2012): 23–29. http://dx.doi.org/10.1620/tjem.227.23.

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31

Okubo, Yumiko, Naoko Ishiguro, Taiyo Suganuma, et al. "Team-Based Learning, a Learning Strategy for Clinical Reasoning, in Students with Problem-Based Learning Tutorial Experiences." Tohoku Journal of Experimental Medicine 240, no. 2 (2016): 181. http://dx.doi.org/10.1620/tjem.240.181.

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32

Aleksandravičiūtė, Birutė, and Kęstutis Liekis. "Modern Learning Strategies in Higher Education: Team-Based Learning." Acta Paedagogica Vilnensia 44 (September 1, 2020): 141–51. http://dx.doi.org/10.15388/actpaed.44.10.

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Team-based learning is a student-orientated active learning strategy created by Lary Michaelsen in 1979. Team-based learning is widely used not only in the United States of America, but all around the world: in Asian, European, and Middle Eastern universities and colleges. It is extremely popular in biomedicine as well as in social sciences. It is, unfortunately, rare in Lithuanian higher education. There is a large network of team-based learning strategy consultants in Singapore, Japan, Australia, the Netherlands, the United Kingdom, Uruguay, and North America.Research aim: to introduce the t

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33

Karpin, Karpin, and Ai Mahmudatussa’adah. "Student Response - Based Learning: A Strategy for Improving Student Participation in Learning." Innovation of Vocational Technology Education 16, no. 1 (2020): 42–52. http://dx.doi.org/10.17509/invotec.v16i1.23512.

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In the context of 21st century learning, to achieve meaningful learning processes, one of the important elements is interaction. Student response - based learning can be used to actively involve students in the learning process. The study focused on stages of the learning process based on student responses and student responses to the learning. Formulation of the research problem is following: (1) how are the stages of the learning process based on student responses to increasing student participation in learning ?; (2) how is the student response to student response based learning? The resear

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34

Gorghiu, Gabriel, Luminiţa Mihaela Drăghicescu, Sorin Cristea, Ana-Maria Petrescu, and Laura Monica Gorghiu. "Problem-based Learning - An Efficient Learning Strategy in the Science Lessons Context." Procedia - Social and Behavioral Sciences 191 (June 2015): 1865–70. http://dx.doi.org/10.1016/j.sbspro.2015.04.570.

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35

Nakanishi, Yoshifumi. "Relationship between Self-Efficacy and Learning Strategy in the Probrem-based Learning." Proceedings of the Annual Convention of the Japanese Psychological Association 79 (September 22, 2015): 2EV—127–2EV—127. http://dx.doi.org/10.4992/pacjpa.79.0_2ev-127.

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36

Klašnja-Milićević, Aleksandra, Boban Vesin, Mirjana Ivanović, and Zoran Budimac. "E-Learning personalization based on hybrid recommendation strategy and learning style identification." Computers & Education 56, no. 3 (2011): 885–99. http://dx.doi.org/10.1016/j.compedu.2010.11.001.

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37

Jiang, Xinchao, Hu Wang, Yu Li, and Kangjia Mo. "Machine Learning based parameter tuning strategy for MMC based topology optimization." Advances in Engineering Software 149 (November 2020): 102841. http://dx.doi.org/10.1016/j.advengsoft.2020.102841.

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38

Jin, Hongbin, Hao Li, Yanyan Ma, and Xi Fang. "Fireworks Algorithm Based on Opposition-Based Learning and Quantum Optimization Strategy." Journal of Physics: Conference Series 1550 (May 2020): 022013. http://dx.doi.org/10.1088/1742-6596/1550/2/022013.

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39

Kanakubo, Masaaki, and Masafumi Hagiwara. "Strategy Acquisition for Games Based on Simplified Reinforcement Learning Using a Strategy Network." Journal of Advanced Computational Intelligence and Intelligent Informatics 9, no. 2 (2005): 203–10. http://dx.doi.org/10.20965/jaciii.2005.p0203.

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We propose a simplified form of reinforcement learning (RL) for game strategy acquisition using a strategy network. RL has been applied to a number of games, such as backgammon, checkers, etc. However, the application of RL to Othello or Shogi, which have very large state spaces, is more difficult because these games take a very long time to learning. The proposed strategy network is composed of N lines from N nodes on the game board with a single evaluation node as a 2-layer perceptron. These nodes denote all possible states of every square on the game board and can easily represent the evalu

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40

Kusumawati, Ratih, and Akhmad Nayazik. "Developing Mathematics Learning Strategy Module Based on Journal Review." Al-Jabar : Jurnal Pendidikan Matematika 9, no. 2 (2018): 111–20. http://dx.doi.org/10.24042/ajpm.v9i2.3110.

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Pre-service teachers need to know the variety of learning methods and they should have the ability to plan learning strategies as well. This study aims to develop a module of mathematics learning strategy based on the review of articles published from 2014–2018. This study was conducted using Borg & Gall development model and the quality criteria used referred to Nieveen (valid, practical, and effective). The result shows that the module has met the validity criteria of 3.4, practical criteria of 82%, and it also has fulfilled the criteria of effectiveness. This module is recommended as a

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41

Liang, Haiqing. "A Precision Advertising Strategy Based on Deep Reinforcement Learning." Ingénierie des systèmes d information 25, no. 3 (2020): 379–403. http://dx.doi.org/10.18280/isi.250316.

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42

Khudair, Bassam Abu. "The Relationship Learning and Knowledge Based View of Strategy." Open Journal of Business and Management 06, no. 02 (2018): 333–48. http://dx.doi.org/10.4236/ojbm.2018.62024.

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43

Chen, Xin, Dong Chen, Mouyi Weng, Yi Jiang, Guo-Wei Wei, and Feng Pan. "Topology-Based Machine Learning Strategy for Cluster Structure Prediction." Journal of Physical Chemistry Letters 11, no. 11 (2020): 4392–401. http://dx.doi.org/10.1021/acs.jpclett.0c00974.

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44

梁, 敏. "Disease Prediction Models Based on Hybrid Deep Learning Strategy." Artificial Intelligence and Robotics Research 09, no. 01 (2020): 16–23. http://dx.doi.org/10.12677/airr.2020.91003.

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45

Ramírez-Cadena, M., R. Vargas-Rodríguez, R. Morales-Menéndez, and F. Guedea. "Educational Strategy Based on Active Learning For Mechatronics Labs." IFAC Proceedings Volumes 41, no. 2 (2008): 851–56. http://dx.doi.org/10.3182/20080706-5-kr-1001.00146.

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46

Jong, BinShyan, TsongWuu Lin, YuLung Wu, and Teyi Chan. "Diagnostic and remedial learning strategy based on conceptual graphs." Journal of Computer Assisted Learning 20, no. 5 (2004): 377–86. http://dx.doi.org/10.1111/j.1365-2729.2004.00097.x.

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47

Corander, Jukka, Mats Gyllenberg, and Timo Koski. "Bayesian model learning based on a parallel MCMC strategy." Statistics and Computing 16, no. 4 (2006): 355–62. http://dx.doi.org/10.1007/s11222-006-9391-y.

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48

Zhang, Shidong, Chao Wang, Junsan Zhang, Youxiang Duan, Xinhong You, and Peiying Zhang. "Network Resource Allocation Strategy Based on Deep Reinforcement Learning." IEEE Open Journal of the Computer Society 1 (2020): 86–94. http://dx.doi.org/10.1109/ojcs.2020.3000330.

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49

Rahayu, S., I. G. Mertha, K. A. Hadi, G. Gunawan, and H. Hikmawati. "VCD Development of Innovative Character-Based Learning Models as Learning Media in Learning Strategy Courses." Journal of Physics: Conference Series 1779, no. 1 (2021): 012053. http://dx.doi.org/10.1088/1742-6596/1779/1/012053.

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Ritonga, Rudi, Hendri Marhadi, Zariul Antosa, and Eva Astuti Mulyani. "Development of Humor Learning: Learning Strategy Increasing Learning Result of Student Class IV Primary School." JOURNAL OF TEACHING AND LEARNING IN ELEMENTARY EDUCATION (JTLEE) 1, no. 1 (2018): 60. http://dx.doi.org/10.33578/jtlee.v1i1.5395.

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Learning by using learning strategies that have been adapted to the characteristics of teachers and students, of course have more value.This study aims to develop a humor based learning strategy that creates active learning, creative and fun, is the goal of the research undertaken. This research is RnD (Research and Development ) which use 4- D development model (Define, Design, Develope, and Disseminate ). However, this stage of research has not yet done the dissemination of learning device development outcomes. The research instruments are questionnaires of teacher and student needs, observa

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