Teaching Strategy of Chemistry Concepts Based on Deep Learning

Authors

  • Xinling Yang Henan University / College of Chemistry and Molecular Sciences

DOI:

https://doi.org/10.14738/assrj.106.14913

Keywords:

chemistry concept, teaching strategy, deep learning

Abstract

Deep learning is a meaningful learning process in which students are fully engaged, successful, and developed around challenging learning topics. Based on deep learning, this paper discusses the teaching strategies of chemical concepts such as summary, analogy, deductive reasoning, and multiple representations, as well as the application cases of strategy implementation, and introduces in detail the application of multiple representation strategies and the requirements of each representation method.

References

Nelson, P.G.: Basic chemical concepts. Chemistry Education Research and Practice. 4(1), 19–24 (2003).

Goh, G. B.; Hodas, N. O.; Vishnu, A. Deep learning for computational chemistry. J. Comput. Chem. 2017, 38, 1291– 1307.

慧敏,鲁静,张文华,毛建明.概念图在化学教学中应用的中外研究对比——基于CiteSpace的知识图谱可视 化分析[J].化学教育(中英文),2021,42(05):97-103.

Gilbert J K and Treagust D 2009 Multiple Representation in Chemichal Education 4th ed. Dordrecht: Springer.

Santos V and Arroio A 2016 The representational levels : Influences and contributions to research in chemical education J. Turkish Sci. Educ. 13 1 p. 3–18.

Jaber L Z and Boujaoude S 2011 A macro–micro–symbolic teaching to promote relational understanding of chemical reactions Int. J. Sci. Educ. 34 7 p. 973–998.

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Published

2023-06-26

How to Cite

Yang, X. (2023). Teaching Strategy of Chemistry Concepts Based on Deep Learning. Advances in Social Sciences Research Journal, 10(6), 427–432. https://doi.org/10.14738/assrj.106.14913