Journal articles: 'Visual problem solving'

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Beveridge, M., and E. Parkins. "Visual representation in analogical problem solving." Memory & Cognition 15, no. 3 (May 1987): 230–37. http://dx.doi.org/10.3758/bf03197721.

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Campbell, K. Jennifer, Kevin F. Collis, and Jane M. Watson. "Visual processing during mathematical problem solving." Educational Studies in Mathematics 28, no. 2 (March 1995): 177–94. http://dx.doi.org/10.1007/bf01295792.

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Davies, Jim, Nancy J. Nersessian, and Ashok K. Goel. "Visual Models in Analogical Problem Solving." Foundations of Science 10, no. 1 (March 2005): 133–52. http://dx.doi.org/10.1007/s10699-005-3009-2.

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Ruliani, Iva Desi, Nizaruddin Nizaruddin, and Yanuar Hery Murtianto. "Profile Analysis of Mathematical Problem Solving Abilities with Krulik & Rudnick Stages Judging from Medium Visual Representation." JIPM (Jurnal Ilmiah Pendidikan Matematika) 7, no. 1 (September 7, 2018): 22. http://dx.doi.org/10.25273/jipm.v7i1.2123.

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The ability to solve mathematical problems is very important in learning math and everyday life. According to Krulik & Rudnick there are 5 stages of problem solving that is Read, Explore, Select A Strategy, Solve And Look Back. Mathematical problems require multiple representational skills to communicate problems, one of which is visual representation. Trigonometry is one of the materials that uses visual representation. This research is a qualitative descriptive research that aims to describe the ability of problem solving mathematics with Krulik & Rudnick stages in terms of visual representation. The study was conducted in MAN 2 Brebes. Determination of Subjects in this study using Purposive Sampling. Research instruments used to obtain the required data are visual representation and problem-solving tests, and interview guidelines. The data obtained were analyzed based on the Krulik & Rudnick problem solving indicator. Subjects in this study were subjects with moderate visual representation. Based on the results, problem solving ability of the subject is not fully fulfilled. Subjects with visual representations are able to do problem solving well that is solving the problem through a concept that is understood without visualization of the image. Subjects with visual representations are having a schematic visual representation type.

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Polivanova, N. I. "Visual Image Regulation in Joint Problem-solving." Soviet Psychology 28, no. 5 (September 1990): 54–68. http://dx.doi.org/10.2753/rpo1061-0405280554.

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Lovett, Andrew, and Kenneth Forbus. "Modeling visual problem solving as analogical reasoning." Psychological Review 124, no. 1 (2017): 60–90. http://dx.doi.org/10.1037/rev0000039.

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GOLDSCHMIDT, GABRIELA. "SERIAL SKETCHING: VISUAL PROBLEM SOLVING IN DESIGNING." Cybernetics and Systems 23, no. 2 (March 1992): 191–219. http://dx.doi.org/10.1080/01969729208927457.

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Hortin, John A., Robert L. Ohlsen, and Barbara S. Newhouse. "Research for Teachers on Visual Thinking to Solve Verbal Problems." Journal of Educational Technology Systems 13, no. 4 (June 1985): 299–303. http://dx.doi.org/10.2190/hj8h-fyv6-2a0g-p8h2.

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If graduate students are given training in visual thinking, they will be able to use visual thinking for solving verbal problems. One hundred thirty-three graduate students participated in this study to determine whether students could be taught how to use images of the mind for problem solving. Two important activities were stressed: 1) imagery for problem solving and 2) the active participation from students. The authors believe that their study shows the importance of allowing students to use imagery in the problem solving process.

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Sholihah, Ummu, and Maryono Maryono. "Students’ visual thinking ability in solving the integral problem." JRAMathEdu (Journal of Research and Advances in Mathematics Education) 5, no. 2 (June 27, 2020): 175–86. http://dx.doi.org/10.23917/jramathedu.v5i2.10286.

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Visual thinking plays an essential role in solving problems and in learning mathematics. Many students do not understand how to graphically or geometrically represent problems and solve algebra problems. Visual thinking is the ability, process, and results of creating, interpreting, using, and imagining images and diagrams on paper or with technological tools, describing and communicating information and ideas, developing ideas, and understanding improvement. This research describes students’ visual thinking ability to solve integral problems. The approach used in this study was descriptive qualitative. The subjects in this study were three students from the Department of Mathematics Education at the State Islamic Institute of Tulungagung. The data were collected by using tests and interviews. The steps to analyze the data were categorization, reduction, exposure, interpretation, and conclusion. Based on the analysis of students’ visual thinking skills in solving integral problems, there were three levels of visual thinking: semi-local visual, local visual, and global visual. At the semi-local visual level, students could only understand algebraically, and they have not shown it graphically at all. Meanwhile, at the local visual level, they have already understood geometry as an alternative language and been able graphically represented problems or concepts, even though it was not perfectly done yet. While on a global visual level, they could perfectly visualize visual thinking indicators, understand algebra and geometry as alternative languages for problem-solving, extract specific information from diagrams, graph problems, and use them to solve problems perfectly.

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Beveridge, M., and E. Parkins. "Erratum to: Visual representation in analogical problem solving." Memory & Cognition 15, no. 5 (September 1987): 461. http://dx.doi.org/10.3758/bf03197736.

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Darmadi, Sanusi, E. Wihardjo, Karim, Suprianto, and S. Prayitno. "Male students’ visual reasoning in solving mathematical problem." Journal of Physics: Conference Series 1538 (May 2020): 012086. http://dx.doi.org/10.1088/1742-6596/1538/1/012086.

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Wichert, Andreas, João Dias Pereira, and Paulo Carreira. "Visual search light model for mental problem solving." Neurocomputing 71, no. 13-15 (August 2008): 2806–22. http://dx.doi.org/10.1016/j.neucom.2007.08.019.

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Scott, John. "Visual representations in problem solving and decision-making." International Journal of Management and Decision Making 9, no. 3 (2008): 266. http://dx.doi.org/10.1504/ijmdm.2008.017409.

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Widodo, S. A., Darhim, and T. Ikhwanudin. "Improving mathematical problem solving skills through visual media." Journal of Physics: Conference Series 948 (January 2018): 012004. http://dx.doi.org/10.1088/1742-6596/948/1/012004.

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Hatzi, Ourania, Dimitris Vrakas, Nick Bassiliades, Dimosthenis Anagnostopoulos, and Ioannis Vlahavas. "A visual programming system for automated problem solving." Expert Systems with Applications 37, no. 6 (June 2010): 4611–25. http://dx.doi.org/10.1016/j.eswa.2009.12.047.

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Englard, Lisa. "Raise the bar on problem solving." Teaching Children Mathematics 17, no. 3 (October 2010): 156–63. http://dx.doi.org/10.5951/tcm.17.3.0156.

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Bennett, Albert B., and Eugene Maier. "A Visual Approach to Solving Mixture Problems." Mathematics Teacher 89, no. 2 (February 1996): 108–11. http://dx.doi.org/10.5951/mt.89.2.0108.

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In the Curriculum and Evaluation Standards for School Mathematics (NCTM 1989), the 9–12 standards call for a shift from a curriculum dominated by memorization of isolated facts and procedures to one that emphasizes conceptual understandings, multiple representations and connections, mathematical modeling, and mathematical problem solving. One approach that affords opportunities for achieving these objectives is the use of diagrams and drawings. The familiar saying “A picture is worth a thousand words” could well be modified for mathematics to “A picture is worth a thousand numbers.” As an example of visual approaches in algebra, this article uses diagrams to solve mixture problems.

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Casakin, Hernan P., and Gabriela Goldschmidt. "Reasoning by Visual Analogy in Design Problem-Solving: The Role of Guidance." Environment and Planning B: Planning and Design 27, no. 1 (February 2000): 105–19. http://dx.doi.org/10.1068/b2565.

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The use of analogy, including visual analogy, is a powerful problem-solving strategy that can help explain new problems in terms of familiar ones. There is evidence that problem-solvers have difficulty in making spontaneous use of this strategy, despite its proven effectiveness. However, guidance to use it greatly increases accessibility to analogy in problem-solving. In the design domain, evidence of the use of analogy has hitherto been mostly anecdotal. Our goal in this paper is to show through empirical data that analogy can be effective in facilitating design problem-solving, especially when explicit instructions for its use are given.

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Shaw, Emily J., Edwin C. Selby, and John C. Houtz. "Problem Solving Style and Beliefs about Teaching, Learning, and Problem Solving." Creativity Research Journal 21, no. 4 (November 9, 2009): 394–99. http://dx.doi.org/10.1080/10400410903359798.

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Proboretno, Setyaning, and Pradnyo Wijayanti. "Representasi Matematis Siswa SMP dalam Meyelesaikan Masalah Segiempat Ditinjau dari Perbedaan Jenis Kelamin." MATHEdunesa 8, no. 3 (August 12, 2019): 472–76. http://dx.doi.org/10.26740/mathedunesa.v8n3.p472-476.

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Mathematical representation has an important role to help students understand and solve quadrilateral problems in mathematics learning. Students will use different forms of mathematical representation to solve a quadrilateral problem. This allows that the form of mathematical representation used by male and female students is different. The purpose of this study was to describe the mathematical representation of male and female junior high school students in solving quadrilateral problems. This research is classified into descriptive qualitative research using test and interview methods. The results of this study indicate that male students use visual-spatial representations in the form of images to represent an object that is in the problem solving test. In addition, they use visual-spatial representations and formal-notational representations to reveal information about a problem. During the problem solving process, dominant male students use formal-notational representation. They also explained verbally each step of the completion in detail and in order. Dominant female students use formal-notational representation to write information and solve a problem. To represent an object in a problem solving test, they use visual-spatial representations. Female students also use verbal representations to explain each step of solving problems.Keywords: mathematical representation, quadrilateral problems, gender

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van Meeuwen, Ludo W., Halszka Jarodzka, Saskia Brand-Gruwel, Paul A. Kirschner, Jeano J. P. R. de Bock, and Jeroen J. G. van Merriënboer. "Identification of effective visual problem solving strategies in a complex visual domain." Learning and Instruction 32 (August 2014): 10–21. http://dx.doi.org/10.1016/j.learninstruc.2014.01.004.

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Minassian, A., and W. Perry. "Visual scanning and complex problem solving deficits in schizophrenia." Schizophrenia Research 60, no. 1 (March 2003): 267–68. http://dx.doi.org/10.1016/s0920-9964(03)80416-4.

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Xia, Meng, Min Xu, Chuan‐en Lin, Ta Ying Cheng, Huamin Qu, and Xiaojuan Ma. "SeqDynamics: Visual Analytics for Evaluating Online Problem‐solving Dynamics." Computer Graphics Forum 39, no. 3 (June 2020): 511–22. http://dx.doi.org/10.1111/cgf.13998.

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Haataja, Eeva, Enrique Garcia Moreno-Esteva, Visajaani Salonen, Anu Laine, Miika Toivanen, and Markku S. Hannula. "Teacher's visual attention when scaffolding collaborative mathematical problem solving." Teaching and Teacher Education 86 (November 2019): 102877. http://dx.doi.org/10.1016/j.tate.2019.102877.

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Bennett, Jack A., and James F. Strickland. "Pizzas and Problem Solving: Using Visual Representations in Mathematics." Middle School Journal 21, no. 4 (March 1990): 10–13. http://dx.doi.org/10.1080/00940771.1990.11495076.

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Hegarty, Mary, and Maria Kozhevnikov. "Types of visual–spatial representations and mathematical problem solving." Journal of Educational Psychology 91, no. 4 (December 1999): 684–89. http://dx.doi.org/10.1037/0022-0663.91.4.684.

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Mustafar, Faiz, Michael A. Harvey, Abbas Khani, József Arató, and Gregor Rainer. "Divergent Solutions to Visual Problem Solving across Mammalian Species." eneuro 5, no. 4 (July 2018): ENEURO.0167–18.2018. http://dx.doi.org/10.1523/eneuro.0167-18.2018.

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Cybulski, Jacob L., Susan Keller, Lemai Nguyen, and Dilal Saundage. "Creative problem solving in digital space using visual analytics." Computers in Human Behavior 42 (January 2015): 20–35. http://dx.doi.org/10.1016/j.chb.2013.10.061.

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Crowley, Rebecca S., and Olga Medvedeva. "An intelligent tutoring system for visual classification problem solving." Artificial Intelligence in Medicine 36, no. 1 (January 2006): 85–117. http://dx.doi.org/10.1016/j.artmed.2005.01.005.

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Arsalidou, Marie, Vinod Goel, and Juan Pascual-Leone. "Neural correlates of visual problem solving and task demand." Brain and Cognition 67 (June 2008): 12. http://dx.doi.org/10.1016/j.bandc.2008.02.016.

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Miller, Laurie A., and Lynette J. Tippett. "Effects of focal brain lesions on visual problem-solving." Neuropsychologia 34, no. 5 (May 1996): 387–98. http://dx.doi.org/10.1016/0028-3932(95)00116-6.

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Triutami, Tabita Wahyu, Uun Hariyanti, Dwi Novitasari, Ratna Yulis Tyaningsih, and Junaidi Junaidi. "High Visual-Spatial Intelligence Students’ Creativity in Solving PISA Problems." JTAM (Jurnal Teori dan Aplikasi Matematika) 5, no. 1 (April 17, 2021): 36. http://dx.doi.org/10.31764/jtam.v5i1.3280.

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Creativity is very necessary for learning mathematics, especially when solving geometry problems. This research aims to describe 4th year mathematics education students’ creativity in solving geometry problems. Creativity in this research is focused on fluency, flexibility, and originality of student anwer when solving geometry problems. This research is an explorative descriptive research through a qualitative approach. The participants were 7 fourth year mathematics education students of state University in Mataram, who have a high level of visual-spatial intelligence. The data was collected by written test and interview. The test consisted of two open-ended geometry problems about transforming 3-dimensional images into 2-dimensional images and making 2-dimensional images with a predetermined circumference. The problems are modification of the 2006 PISA test. The result showed that subjects with high visual-spatial intelligence levels met all indicators of creativity. In solving problems that meet the aspects of fluency, flexibility and originality, they combine mental rotation and mental visualization abilities and include using their visual experience by modifying the information obtained and the initial problem solving ideas obtained. This also enables them to produce original problem solutions. The results of this research can be used as an illustration and a guideline to assess students’ creativity with high visual-spatial intelligence level.

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Pratama, A. R., D. R. S. Saputro, and Riyadi. "Problem solving of student with visual impairment related to mathematical literacy problem." Journal of Physics: Conference Series 1008 (April 2018): 012068. http://dx.doi.org/10.1088/1742-6596/1008/1/012068.

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Febriyanti, Hesti, and Heni Pujiastuti. "Analisis Pemecahan Masalah Siswa Ditinjau dari Gaya Belajar." JUMLAHKU: Jurnal Matematika Ilmiah STKIP Muhammadiyah Kuningan 6, no. 1 (June 5, 2020): 50–65. http://dx.doi.org/10.33222/jumlahku.v6i1.947.

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Abstrak Penelitian ini bertujuan untuk mengetahui pemecahan masalah dari masing-masing gaya belajar yang berbeda. Penelitian ini termasuk dalam penelitian deskriptif-kualitatif. Popuasi yang diambil dalam penelitian ini adalah siswa SMPN 1 Kibin tahun ajaran 2019/2020. Teknik pengambilan sampel penelitian menggunakan teknik cluster random sampling. Instrumen yang digunakan dalam penelitian ini berupa kuesioner, tes, wawancara, dan peneliti. Data mengenai menganalisis pemecahan masalah diambil dari kuesioner dan tes. Hasilnya didapat gaya belajar visual mendominasi. Kemudian 1 siswa dari gaya belajar yang berbeda dijadikan sampel untuk di wawancara. Hasil analisis menunjukkan pemecahan masalah setiap siswa berbeda karena dipengaruhi oleh gaya belajar. Gaya belajar visual dalam pemecahan masalah cenderung menekankan pada soal tes dan mencari informasi yang mendetail untuk memecahkan masalah. Gaya belajar auditorial dalam memecahkan masalah cenderung mengandalkan ingatan ketika pembelajaran. Gaya belajar kinestetik dalam pemecahan masalah cenderung memahaminya terlebih dahulu, kemudian dikonstruksikan dalam kehidupan sehari-hari. Dari hasil tersebut dapat disimpulkan bahwa gaya belajar memegang peranan penting dalam pemecahan masalah. Kata kunci : Pemecahan masalah; Gaya belajar visual; Gaya belajar auditorial; Gaya belajar kinestetik Abstract This study aims to determine the problem solving of each different learning style. This research is included in descriptive-qualitative research. Populations taken in this study were students of SMPN 1 Kibin 2019/2020 school year. The research sampling technique used cluster random sampling technique. The instruments used in this study were in the form of questionnaires, tests, interviews, and researchers. Data regarding analyzing problem solving is taken from questionnaires and tests. The result is that the visual learning style is dominated. Then 1 student from a different learning style is sampled to be interviewed. The analysis shows that each student's problem solving is different because it is influenced by learning styles. Visual learning styles in problem solving tend to emphasize test questions and look for detailed information to solve problems. Auditory learning styles in solving problems tend to rely on memories when learning. Kinesthetic learning styles in problem solving tend to understand them first, then constructed in daily life. From these results it can be concluded that the learning style plays an important role in problem solving. Keywords: Problem solving; Visual learning style; Auditory learning style; Kinesthetic learning style

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Dou, Wenwen, Caroline Ziemkiewicz, Lane Harrison, Dong Hyun Jeong, William Ribarsky, Xiaoyu Wang, and Remco Chang. "Toward a deeper understanding of the relationship between interaction constraints and visual isomorphs." Information Visualization 11, no. 3 (February 20, 2012): 222–36. http://dx.doi.org/10.1177/1473871611433712.

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Interaction and manual manipulation have been shown in cognitive science literature to play a critical role in problem solving. Given different types of interactions or constraints on interactions, a problem can appear to have different degrees of difficulty. While this relationship between interaction and problem solving has been well studied in the cognitive science literatures, the visual analytics community has yet to exploit this understanding for analytical problem solving. In this paper, we hypothesize that constraints on interactions and constraints encoded in visual representations can lead to strategies of varying effectiveness during problem solving. To test our hypothesis, we conducted a user study in which participants were given different levels of interaction constraints when solving a simple mathematic game called number scrabble. Number scrabble is known to have an optimal visual problem isomorph, and the goal of this study is to learn if and how the participants could derive the isomorph and to analyze the strategies that the participants utilize in solving the problem. Our results indicate that constraints on interactions do affect problem solving, and that although the optimal visual isomorph is difficult to derive, certain interaction constraints can lead to a higher chance of deriving the isomorph.

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Inastuti, I. Gusti Ayu Sinta, Sri Subarinah, Eka Kurniawan, and Amrullah Amrullah. "Analisis Kemampuan Pemecahan Masalah Pola Bilangan Ditinjau Dari Gaya Belajar." Griya Journal of Mathematics Education and Application 1, no. 1 (March 25, 2021): 66–80. http://dx.doi.org/10.29303/griya.v1i1.4.

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The purpose of this study was to determine eighth grade student problem-solving ability on number pattern material. This study was held academic year focused on assessing students learning styles. The methods used in this study were questionnaires, tests, and interviews. The results showed that class VIII students consisted of 26 students had visual learning styles, 24 students had auditory styles and 16 students had kinesthetic styles. Subjects taken in this study were 2 students from each learning style, then the subject was given a test to describe the number pattern material and conducted an interview. As a result, based on the analysis of the problem-solving ability stages, students with visual and auditory learning styles were able to reach the stage of understanding the question / problem, designing and choosing a solution strategy, and solving problems with a mathematical model, but have not yet reached the stage of re-checking the solutions obtained. On the contrary, Students with a kinesthetic learning style have been able to reach the stage of understanding the question / problem, but have not been able to reach the stage of designing and choosing a solution strategy, or solving problems with mathematical models, and even re-checking the solutions obtained. This shows that the problem solving ability of students with visual and auditory learning styles is better than students with kinesthetic learning styles.

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Pratiwi, Maulidna Wahyu, and Rooselyna Ekawati. "Students’ Open-Ended Problem Solving Strategy Based on Visual-spatial and Logical-mathematical Intelligence." MATHEdunesa 8, no. 3 (August 16, 2019): 507–11. http://dx.doi.org/10.26740/mathedunesa.v8n3.p507-511.

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Problem solving and intelligence are connected each other. Every student has their own different intelligence. Intelligence affect students’ problem solving strategy. This research aimed at describing the strategy of geometry open-ended problem solving of visual-spatial and logical-mathematical student. This research includes as descriptive research with qualitative approach. The research subjects consists of two students which are one student with visual-spatial and one student with logical-mathematical intelligence. The result shows that student of visual-spatial can understand and solve the problem, however lack to pay attention to the word description, while student of logical-mathematical can solve the problem with attend all of the information as well. In solving problem, student of visual-spatial and logical-mathematical can connect the given information to gain new information, which is that strategy called as logical reasoning strategy. Then, student of visual-spatial and logical-mathematical use the known formula to gain new equation, which is called as write an equation strategy. At the last solution, student of visual-spatial disposed to use table which is called as draw a picture or model strategy. While student of logical-mathematical disposed to do try and error to get the solution, which is called guess and check strategy.Keywords: strategy of problem solving, geometry open-ended problem, visual-spatial intelligence, logical-mathematical intelligence

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Diamond, Lindsay L. "Problem Solving Using Visual Support for Young Children With Autism." Intervention in School and Clinic 54, no. 2 (April 5, 2018): 106–10. http://dx.doi.org/10.1177/1053451218765234.

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Children with autism spectrum disorder may experience different levels of social and behavior deficits in the early elementary years. Behavioral deficits may impact the development of appropriate interpersonal problem-solving skills and peer acceptance, supporting the need for instructional support. This column discusses the implementation of a visual support poster to facilitate the development of problem-solving skills during social and academic instruction for young children with autism.

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S, Syaharuddin. "DESCRIPTION OF STUDENTS’ MATHEMATICS PROBLEM SOLVING RELATION IN CONCEPTS UNDERSTANDNG FROM EVALUATED LEARNING STYLES AT CLASS VIII SMPN 4 BINAMU JENEPONTO DISTRICT." Celebes Education Review 1, no. 1 (May 1, 2019): 12–18. http://dx.doi.org/10.37541/cer.v1i1.87.

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The research is descriptive quantitative-qualitative approach. Quantitative approach used in analyzing how the relationship between problem-solving skills with students' understanding of the concept. While the qualitative approach used in describing how the problem-solving skills class VIII SMP Negeri 4 Binamu Jeneponto in relation to understanding the concept in terms of learning styles. This study, data were collected through the initial observation, the provision of learning styles questionnaire, test understanding of concepts, and problem-solving ability tests and structured interviews. Data were analyzed using Chi Square analyze the association between mathematical problem solving skills with an understanding of the concept in terms of students' learning styles. The results showed that there is an association between the ability of solving math problems with understanding the concept of student stylish visual learning the value of χ2 count = 21,000 and significance (Asymp. Sig. (2-sided)) = 0.000 and there is an association between the ability of solving mathematical problems with the understanding of the concept auditory learning style student with χ2 value and significance count = 17.967 (Asymp. Sig. (2-sided)) = 0.000. Students with visual and auditory learning style can solve the problems SPLDV given by the troubleshooting steps Polya because it may be posisible students have an understanding of the SPLDV.

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Kim, So Hee, Kwangho Lee, and Mi Young Ku. "The Fourth Graders' Visual Representation in Mathematics Problem Solving Process." Education of Primary School Mathematics 16, no. 3 (December 31, 2013): 285–301. http://dx.doi.org/10.7468/jksmec.2013.16.3.285.

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Siegle, Del. "Developing Student Programming and Problem-Solving Skills with Visual Basic." Gifted Child Today 32, no. 4 (October 2009): 24–29. http://dx.doi.org/10.1177/107621750903200408.

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Korhonen, Pekka J., and Jukka Laakso. "A visual interactive method for solving the multiple criteria problem." European Journal of Operational Research 24, no. 2 (February 1986): 277–87. http://dx.doi.org/10.1016/0377-2217(86)90050-0.

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Root, Jenny R., Sarah K. Cox, and Stephanie Gonzalez. "Using Modified Schema-Based Instruction with Technology-Based Supports to Teach Data Analysis." Research and Practice for Persons with Severe Disabilities 44, no. 1 (February 21, 2019): 53–68. http://dx.doi.org/10.1177/1540796919833915.

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Data analysis inherently requires problem solving, yet it is the most understudied mathematical skill for individuals with extensive support needs. The current study taught elementary students with extensive support needs (i.e., autism and intellectual disability) to solve math word problems requiring analysis of scaled pictographs through modified schema-based instruction on an iPad. Results of the single-case multiple probe across participants design found a functional relation between the iPad-based math intervention and math problem solving, with a large effect size (Tau-U = .96) confirming visual analysis. In addition, participants were able to generalize problem-solving skills when they were presented with data analysis problems from grade-level social studies textbooks and visual supports were faded. Implications for practice and future research in teaching mathematics to learners with extensive support needs are discussed.

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Jamhari, Muhammad, Syarifuddin Syarifuddin, and Herbert Sipahutar. "THE EFFECTS OF VISUAL MAPPING AND SCIENCE-RELATED ATTITUDES ON STUDENTS’ CRITICAL THINKING AND PROBLEM SOLVING SKILLS." BIOTIK: Jurnal Ilmiah Biologi Teknologi dan Kependidikan 8, no. 2 (January 7, 2021): 146. http://dx.doi.org/10.22373/biotik.v8i2.8060.

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The aims of this study were to find out: (1) the effects of visual mapping on students’ critical thinking skills, (2) the effects of science-related attitudes on students’ critical thinking skills, (3) the interactions between visual mapping and science-related attitudes on students’ critical thinking skills, (4) the effects of visual mapping on students’ problem solving skills, (5) the effects of science-related attitudes on students’ problem solving skills, and (6) the interactions between visual mapping and science-related attitudes on students’ problem solving skills. This study was conducted at MAN 1 Tanjung Pura, totally 141 students. It was a quasi-experimental technique by using a pretest-posttest experimental group with 4x2 factorial design. The technique of data analysis was processed by the Two-Way ANOVA and followed by Duncan’s Multiple Range Test. The results showed that: (1) there were the significant effects of visual mapping on students’ critical thinking skills (F=87.082; P=0.000), (2) there were the significant effects of science-related attitudes on students’ critical thinking skills (F=2.493; P=0.040), (3) there were the interactions between visual mapping and science-related attitudes on students’ critical thinking skills (F=2.037; P=0.000), (4) there were the significant effects of visual mapping on students’ problem solving skills (F=94.214; P=0.000), (5) there were the significant effects of science-related attitudes on students’ problem solving skills (F=3.397; P=0.031), and (6) there were the interactions between visual mapping and science-related attitudes on students’ problem solving skills (F=2.195; P=0.000).

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Hitalessy, Merlin, Wilmintjie Mataheru, and Carolina Selfisina Ayal. "REPRESENTASI MATEMATIS SISWA DALAM PEMECAHAN MASALAH PERBANDINGAN TRIGONOMETRI PADA SEGITIGA SIKU-SIKU DITINJAU DARI KECERDASAN LOGIS MATEMATIS, LINGUISTIK DAN VISUAL SPASIAL." Jurnal Magister Pendidikan Matematika (JUMADIKA) 2, no. 1 (July 14, 2020): 1–15. http://dx.doi.org/10.30598/jumadikavol2iss1year2020page1-15.

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One of the skills needed in learning mathematics is the ability to solve mathematical problems. In solving problems in mathematics learning, mathematical representation is needed by students in the problem solving process. Students tend to use mathematical representations, but sometimes they don't understand what they are doing. In general, mathematical representations also play an important role in improving mathematical competence. Beside the ability of representation, students also have intelligence, including mathematical logical intelligence, linguistics and visual spatial. This research is descriptive with qualitative approach that aimed to describe the complete mathematical representation of vocational high school students in solving a quadratic equation in terms. The research phase begins with the selection of research subjects were determined by gender and math skills test results were similar. Having chosen the subject and the continuation of the problem solving quadratic equations and interviews. The validity of the data using a triangulation of time that is giving the task of solving a quadratic equation are equal at different times. The results of this study as the mathematic description shows that vocational high school students in solving quadratic equations problem according to Polya step problem solving

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Putra, Army Al Islami Ali, Nonoh Siti Aminah, and Ahmad Marzuki. "Analysis of Students’ Multiple representation-based Problem - solving Skills." Journal of Educational Science and Technology (EST) 6, no. 1 (February 27, 2020): 99. http://dx.doi.org/10.26858/est.v6i1.11196.

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This study aims to analyze the profile of students’ problem - solving skills based on multiple representation in senior high school. Problem - solving skills in solving multiple representation are very important in learning Physics. The subjects of this study were 101 students of class XII MAN 1 Ngawi. The method used in this research was quantitative descriptive method. Indicators of the problem - solving abilities that were used included approaches, visuals, applications, and procedures. The types of representation in this research instrument were verbal, figures, graphic and mathematic. The results showed that the problem - solving skills related to the indicator of approach with the form of multiple representation questions got percentages of 36% (verbal), 42% (figural), 24% (graphical), and 43% (mathematical). The visual indicators showed the percentages of 44, 29, 38, and 0 for verbal, figural, graphical, and mathematical respectively. Then the indicators of procedures obtained 36% for the verbal, 30% for the figures, 35% for the graphics, and 0% for the mathematics. Thus, it can be concluded that problem - solving skills possessed by students are different in terms of the percentage each indicator got in the multiple representation test.

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Segal, Eliaz. "Incubation in Insight Problem Solving." Creativity Research Journal 16, no. 1 (March 2004): 141–48. http://dx.doi.org/10.1207/s15326934crj1601_13.

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Csikszentmihalyi, Mihaly. "On Runco's Problem Finding, Problem Solving, and Creativity." Creativity Research Journal 9, no. 2 (April 1, 1996): 267–68. http://dx.doi.org/10.1207/s15326934crj0902&3_11.

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Shambaugh, Neal. "Future Design: Impossible Problem Solving by Novices." Design Principles and Practices: An International Journal—Annual Review 2, no. 3 (2008): 13–20. http://dx.doi.org/10.18848/1833-1874/cgp/v02i03/37562.

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Chubaievskyi, Vitaliy Ivanovich, Katerina Alekseevna Palahuta, and Alona Mykolayivna Desiako. "TECHNOLOGIES OF MULTILEVEL STRUCTURES MODELLING ON THE EXAMPLE OF THE PROBLEM OF COMPLETING PRODUCTS." SCIENTIFIC BULLETIN OF POLISSIA, no. 2(18) (2019): 6–14. http://dx.doi.org/10.25140/2410-9576-2019-2(18)-6-14.

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Urgency of the research. One of the typical tasks encountered in the de-signing of intelligent systems is modelling of the multilevel structures for solving various applied problems. Target setting. Consideration the possibilities of the language of artificial intelligence Visual Prolog for the implementation of recursive technology-based on the example of solving a multi-level task of product configuration. Actual scientific researches and issues analysis. Such scientists as Biletsky O. B., Lytvyn V. V., Chery S., Gottlob G., Luger G. F., Russell G.F. made significant contribution to the development of the theory, methodology of artificial intelligence application for solving problems in the field of economics. Uninvestigated parts of general matters defining. At the same time, insufficient scientific works highlight the features of the introduction of modern means of artificial intelligence for solving multilevel economic problems. The research objective. Analyze existing approaches to solving multi-level tasks. To propose an effective tool for solving multilevel tasks using artificial intelligence language Visual Prolog. The statement of basic materials. The problem of modeling of multilevel structures in intellectual systems on the basis of iterative and recursive technologies on the example of the problem of components is considered. The main characteristics of such structures are presented, their complexity is determined and the necessity of finding effective methods for their presentation and processing in the memory of the machine is given. There are two important paradigms in the development of recursive technologies: functional and logical programming. We consider the corresponding languages of artificial intelligence: Lisp and Prolog, their heirs and the most powerful language of Visual Prolog. The classical well-known iterative algorithm and the recursive program on the Prologue of solving the problem of the components of the internal combustion engine, as well as the recursive program on Visual Prolog, developed by the authors of the article, are given. Their comparison is made from the position of using the number of structures for the presentation of the information base, the cost of memory for their preservation, the complexity of developing and debugging the program, the ease of perception of their work. Conclusions. The power of the language Visual Prolog is emphasized, which is especially manifested in the tasks of processing multi-level structures.

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Journal articles on the topic 'Visual problem solving'

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