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Application of Neuroscience in C Language Teaching Research

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DOI: 10.23977/appep.2024.050522 | Downloads: 18 | Views: 666

Author(s)

Donghui Liu 1

Affiliation(s)

1 Department of Computers, Lianyungang Teachers' College, Lianyungang, 222000, China

Corresponding Author

Donghui Liu

ABSTRACT

With the increasing integration of computer science into educational curricula, the efficacy of C language instruction, a cornerstone of programming, has become a focal point for educators and researchers alike. This study investigates the potential of applying neuroscientific insights to the teaching of C language, aiming to optimize students' cognitive processing and academic achievements. By dissecting the tenets of cognitive load theory and exploring techniques to enhance memory and comprehension, the research presents a suite of innovative teaching frameworks. These frameworks are crafted to mitigate the cognitive demands on students, facilitate a profound understanding of programming concepts, and solidify the encoding of long-term memory. The study's findings suggest that the fusion of neuroscience with C language pedagogy not only enriches the learning experience but also significantly bolsters students' programming capabilities. This interdisciplinary approach provides a compelling strategy for enhancing educational methodologies in computer science, offering a blueprint for future curriculum development and instructional practices. The implications of these findings are far-reaching, potentially transforming the way C language and other programming languages are taught, and setting a precedent for a more cognitively aligned and effective learning paradigm. 

KEYWORDS

Neuroscience, C Language, Deep Learning

CITE THIS PAPER

Donghui Liu, Application of Neuroscience in C Language Teaching Research. Applied & Educational Psychology (2024) Vol. 5: 158-162. DOI: http://dx.doi.org/10.23977/appep.2024.050522.

REFERENCES

[1] Kandel, E. R., Schwartz, J. H., Jessell, T. M., Siegelbaum, S. A., & Hudspeth, A. J. Principles of Neural Science (5th ed.). New York: McGraw-Hill Education. 2013, 5-10
[2] Sweller, J. Cognitive load during problem solving: Effects on learning. Cognitive Science, 1988, 12(2), 257-285.
[3] Cooper, S., Dann, W., & Pausch, R. Alice: A 2-D interactive animator for teaching programming. Journal of Computing Sciences in Colleges, 2003, 19(2), 130-136.

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