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    생태계 요소 간 상호작용에 대한 블록 기반 컴퓨터 모델링에서 초등학생들의 인식적, 개념적 측면 탐색 = Exploring Epistemic and Conceptual Aspects of Elementary Students Through Block-Based Computational Modeling of Interaction among Various Components of an Ecosystem

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    https://www.riss.kr/link?id=A109283865

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    Recent studies suggest that computational models help students maintain a productive line of modeling while interacting with them as non-human participants. This qualitative case study explored how elementary school students used an block coding-based computational model to construct the ecosystem model which represents complex interaction among biotic and abiotic elements and the scientific practices they used to create a more sustainable model. For this study, 6th grade students were guided to act like scientists to predict and modify the ecosystem using one of the computational models, Starlogo-nova. This study found that the computational model was able to stimulate students' scientific practice positively. First, the computational model can facilitate students' creation, evaluation, and revision of the ecosystem models. Second, the computational model can help students formulate theories for more sustainable the ecosystem models. Based on the results of the study, this study concluded that the computer model should be used in future science education.
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    Recent studies suggest that computational models help students maintain a productive line of modeling while interacting with them as non-human participants. This qualitative case study explored how elementary school students used an block coding-based...

    Recent studies suggest that computational models help students maintain a productive line of modeling while interacting with them as non-human participants. This qualitative case study explored how elementary school students used an block coding-based computational model to construct the ecosystem model which represents complex interaction among biotic and abiotic elements and the scientific practices they used to create a more sustainable model. For this study, 6th grade students were guided to act like scientists to predict and modify the ecosystem using one of the computational models, Starlogo-nova. This study found that the computational model was able to stimulate students' scientific practice positively. First, the computational model can facilitate students' creation, evaluation, and revision of the ecosystem models. Second, the computational model can help students formulate theories for more sustainable the ecosystem models. Based on the results of the study, this study concluded that the computer model should be used in future science education.

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    참고문헌 (Reference)

    1 Bielik, T., "Working together : Integrating computational modeling approaches to investigate complex phenomena" 30 : 40-57, 2021

    2 Braun, V., "Using thematic analysis in psychology" 3 (3): 77-101, 2006

    3 Krüger, J. T., "Two comparative studies of computer simulations and experiments as learning tools in school and out-of-school education" 50 : 169-197, 2022

    4 Wilensky, U., "Thinking in levels : A dynamic systems perspective to making sense of the world" 8 (8): 3-19, 1999

    5 Xiang, L., "Supporting three-dimensional learning on ecosystems using an agent-based computer model" 31 : 473-489, 2022

    6 Ke, L., "Supporting students’ meaningful engagement in scientific modeling through epistemolgical messages : A case study of contrasting teaching approaches" 58 (58): 335-365, 2021

    7 Puttick, G., "So, we kind of started from scratch, no pun intended : What can students learn from designing games?" 61 (61): 772-808, 2023

    8 Sengupta, P., "Programming in K-12 science classrooms" 58 (58): 33-35, 2015

    9 Scherr, R. E., "Productivity of"collisions generate heat"for reconciling an energy model with mechanistic reasoning : A case study" 11 (11): 1-16, 2015

    10 NGSS Lead States., "Next Generation Science Standards : For States, by States" National Academies Press 2013

    1 Bielik, T., "Working together : Integrating computational modeling approaches to investigate complex phenomena" 30 : 40-57, 2021

    2 Braun, V., "Using thematic analysis in psychology" 3 (3): 77-101, 2006

    3 Krüger, J. T., "Two comparative studies of computer simulations and experiments as learning tools in school and out-of-school education" 50 : 169-197, 2022

    4 Wilensky, U., "Thinking in levels : A dynamic systems perspective to making sense of the world" 8 (8): 3-19, 1999

    5 Xiang, L., "Supporting three-dimensional learning on ecosystems using an agent-based computer model" 31 : 473-489, 2022

    6 Ke, L., "Supporting students’ meaningful engagement in scientific modeling through epistemolgical messages : A case study of contrasting teaching approaches" 58 (58): 335-365, 2021

    7 Puttick, G., "So, we kind of started from scratch, no pun intended : What can students learn from designing games?" 61 (61): 772-808, 2023

    8 Sengupta, P., "Programming in K-12 science classrooms" 58 (58): 33-35, 2015

    9 Scherr, R. E., "Productivity of"collisions generate heat"for reconciling an energy model with mechanistic reasoning : A case study" 11 (11): 1-16, 2015

    10 NGSS Lead States., "Next Generation Science Standards : For States, by States" National Academies Press 2013

    11 Coll, R. K., "Models and Modeling" Springer 3-21, 2011

    12 Sengupta, P., "Integrating computational thinking with K-12 science education using agent-based computation : A theoretical framework" 18 (18): 351-380, 2013

    13 Nguyen, H., "Impact of computer modeling on learning and teaching systems thinking" 58 (58): 661-688, 2021

    14 Schwarz, C. V., "Helping Students Make Sense of the World Using Next Generation Science and Engineering Practices" NSTA Press 2017

    15 Shim, S. Y., "Framing negotiation : Dynamics of epistemological and positional framing in small groups during scientific modeling" 102 (102): 128-152, 2018

    16 엄장희 ; 김희백, "Exploring the agency of a student leader in collaborative scientific modeling classes in an elementary school" 41 (41): 339-358, 2021

    17 양윤영 ; 김재근, "Exploring challenges and suggestions faced by pre-service biology teachers in developing a Netlogo practical program for an ecology course" 52 (52): 13-31, 2024

    18 Wagh, A., "Evobuild : A quickstart toolkit for programming agent-based models of evolutionary processes" 27 : 131-146, 2018

    19 Pierson, A. E., "Emotional configurations in STEM classrooms : Braiding feelings, sensemaking, and practices in extended investigations" 107 (107): 1126-1162, 2023

    20 한문현 ; 김희백, "Elementary students’ reasoning patterns represented in constructing models of ‘Food web and food pyramid’" 31 (31): 71-83, 2012

    21 Shute, V. J., "Demystifying computational thinking" 22 : 142-158, 2017

    22 Weintrop, D., "Defining computational thinking for mathematics and science classrooms" 25 (25): 127-147, 2016

    23 엄장희 ; 김희백, "Changes in teaching practices of elementary school teachers in scientific modeling classes : Focused on modeling pedagogical content knowledge(PCK)" 40 (40): 543-563, 2020

    24 Rachmatuullah, A., "Building a computational model of food webs : Impacts on middle school students’ computational and systems thinking skills" 59 (59): 585-618, 2022

    25 Corbin, J., "Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory" Sage publications 2014

    26 Pierson, A. E., "Balancing the environment : Computational models as interactive participants in a STEM classroom" 29 : 101-119, 2020

    27 Wilkerson, M., "Balancing curricular and pedagogical needs in computational construction kits : Lessons from the DeltaTick project" 99 (99): 465-499, 2015

    28 Tang, X., "Assessing computational thinking: A systematic review of empirical studies" 148 : 1-22, 2020

    29 조헌국, "A tutorial for applying machine learning to the science education for the gifted : Focus on the daily temperature of Seoul" 13 (13): 133-149, 2021

    30 신원섭, "A case study on application of artificial intelligence convergence education in elementary biological classification learning" 39 (39): 284-295, 2020

    31 Ministry of Education [MOE], "2022 Reformed Science Curriculum" Ministry of Education 2022

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