Analysis of the Cognitive Level of Meta-modeling Knowledge Components of Science Gifted Students Through Modeling Practice

被引:0
|
作者
Kim, Kihyang [1 ]
Paik, Seoung-Hey [2 ]
机构
[1] Sejong Acad Sci & Arts, Sejong 30099, South Korea
[2] Korea Natl Univ Educ, Dept Chem Educ, Cheongju 28173, South Korea
关键词
Meta-modeling knowledge; Anomalies; Model variability; Model multiplicity; Modeling process; Modeling practice; TEACHERS VIEWS; PROGRESSION; CONCEPTIONS;
D O I
10.5012/jkcs.2023.67.1.42
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The purpose of this study is to obtain basic data for constructing a modeling practice program integrated with meta-modeling knowledge by analyzing the cognition level for each meta-modeling knowledge components through model-ing practice in the context of the chemistry discipline content. A chemistry teacher conducted inquiry-based modeling prac-tice including anomalous phenomena for 16 students in the second year of a science gifted school, and in order to analyze the cognition level for each of the three meta-modeling knowledge components such as model variability, model multiplicity, and modeling process, the inquiry notes recorded by the students and observation note recorded by the researcher were used for analysis. The recognition level was classified from 0 to 3 levels. As a result of the analysis, it was found that the cognition level of the modeling process was the highest and the cognition level of the multiplicity of the model was the lowest. The cause of the low recognitive level of model variability is closely related to students' perception of conceptual models as objec-tive facts. The cause of the low cognitive level of model multiplicity has to do with the belief that there can only be one cor-rect model for a given phenomenon. Students elaborated conceptual models using symbolic models such as chemical symbols, but lacked recognition of the importance of data interpretation affecting the entire modeling process. It is necessary to intro-duce preliminary activities that can explicitly guide the nature of the model, and guide the importance of data interpretation through specific examples. Training to consider and verify the acceptability of the proposed model from a different point of view than mine should be done through a modeling practice program.
引用
收藏
页码:42 / 53
页数:12
相关论文
共 50 条
  • [1] Exploring the Progression of Meta-Modeling Knowledge (MMK) and Relationship between MMK Progression Level and Actual Practice for Science Gifted
    Kim, Jung-Eun
    Kim, Sungki
    Paik, Seoung-Hey
    JOURNAL OF THE KOREAN CHEMICAL SOCIETY-DAEHAN HWAHAK HOE JEE, 2020, 64 (02): : 111 - 118
  • [2] High School Students' Meta-Modeling Knowledge
    Fortus, David
    Shwartz, Yael
    Rosenfeld, Sherman
    RESEARCH IN SCIENCE EDUCATION, 2016, 46 (06) : 787 - 810
  • [3] High School Students’ Meta-Modeling Knowledge
    David Fortus
    Yael Shwartz
    Sherman Rosenfeld
    Research in Science Education, 2016, 46 : 787 - 810
  • [4] Investigating the dimensions of modeling competence among preservice science teachers: Meta-modeling knowledge, modeling practice, and modeling product
    Goehner, Maximilian Felix
    Bielik, Tom
    Krell, Moritz
    JOURNAL OF RESEARCH IN SCIENCE TEACHING, 2022, 59 (08) : 1354 - 1387
  • [5] Modeling and meta-modeling of software components
    Plasil, Frantisek
    Hnetynka, Petr
    SERA 2008: 6TH ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING RESEARCH, MANAGEMENT AND APPLICATIONS, PROCEEDINGS, 2008, : XVII - XVIII
  • [6] Capturing high-level requirements of information dashboards' components through meta-modeling
    Vazquez-Ingelmo, Andrea
    Garcia-Penalvo, Francisco J.
    Theron, Roberto
    TEEM'19: SEVENTH INTERNATIONAL CONFERENCE ON TECHNOLOGICAL ECOSYSTEMS FOR ENHANCING MULTICULTURALITY, 2019, : 815 - 821
  • [7] A meta-modeling environment for cooperative knowledge management
    Rubart, J
    Wang, WG
    Haake, JM
    METAINFORMATICS, 2002, 2641 : 18 - 28
  • [8] Imposing modeling rules on industrial applications through meta-modeling
    Fröhlich, P
    Hu, ZJ
    Schoelzke, M
    CONCEPTUAL MODELING FOR NEW INFORMATION SYSTEMS TECHNOLOGIES, 2002, 2465 : 166 - 182
  • [9] The power of MOF-based meta-modeling of components
    Hnetynka, Petr
    Plasil, Frantisek
    PROCEEDINGS OF THE 2008 ADVANCED SOFTWARE ENGINEERING & ITS APPLICATIONS, 2008, : 67 - +
  • [10] Meta-modeling framework: A new approach to manage meta-modelbase and modeling knowledge
    Malhotra, Rashmi
    KNOWLEDGE-BASED SYSTEMS, 2008, 21 (01) : 6 - 37