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Educational Computer Modelling in Natural Sciences Education: Chemistry and Biology Aspects

EasyChair Preprint no. 4334

15 pagesDate: October 9, 2020


The article analyzes the research that addresses the issue of using computer models in the educational process. It covers the aspects of the use of com-puter modelling in natural sciences subjects, namely: chemistry, biology. It analyzes the students’ interest in choosing a future profession, connected with chemistry and biology. The article offers the definition and substantia-tion of the model of educational computer pattern and the definition of its components (graphic, mathematical, strategic, animation) and features (mono-subject, poly-subject / simulation, play-based, algorithmic / poster, la-boratory, quest / variant / character-based / achievable). It substantiates the stages of designing a research task. It covers the methodical basics of com-puter modelling in the implementation of a STEM lesson in chemistry. It de-scribes the methodological basics of using computer modelling to work inde-pendently at the lessons of biology. The present research also summarizes the results of the teacher survey on the usefulness and ease of use of com-puter modelling in the educational process. The priorities of the students in the study of subjects of the natural and mathematical cycle are determined. Computer modelling is found to be an effective tool for improving the quali-ty of science education that requires the development of a teacher training system, cognitive tasks and organizational foundations of the educational process.

Keyphrases: Biology, Chemistry, CMODS, Educational Computer Modelling, ICT in education, natural sciences, simulation, STEM, teacher development

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Svitlana Lytvynova and Mariia Medvedieva},
  title = {Educational Computer Modelling in Natural Sciences Education: Chemistry and Biology Aspects},
  howpublished = {EasyChair Preprint no. 4334},

  year = {EasyChair, 2020}}
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