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Language Gene Network Patterns May Facilitate Relationship Setting-up between Language Genotypes and Students' Class-Performance

Wei Xia 1 and Zhizhou Zhang 2
1. School of Languages and Literature, Harbin Institute of Technology, Weihai, China
2. School of Marine Science and Technology, Harbin Institute of Technology, Weihai, China
Abstract—How individual biological phenotypes are encoded by genome sequences will be elucidated more and more in the post-genomic era. Especially, the relationship between language abilities and language genes is to be decoded inevitably. In this article, it is conceptualized that different language ability-related class-performance of students is largely encoded by different combinations of a cluster of language genes. Any two persons have the same set of language genes, but each language gene holds different variations or mutations in its DNA sequence in the human population, and these variations brings up differential influence on the gene’s function. The combinations of such variations in different language genes set up the molecular basis of the fact that almost every person is different from each other in the context of language abilities and performances. Some mutations in the key language genes (such as FOXP1 and FOXP2) are found to lead to severe language disorders, but for most students, only mild mutations or variations exist in their language genes, thus demonstrating normal language ability but differential levels of class-performance. Biological technology will gradually help to finish DNA sequences of every student, pinpoint his defects in some language genes, figure out his advantage and shortcoming, and thus promote a series of individualized approach for teaching and education. 
 
Index Terms—language gene, language ability, individualized, teaching, education

Cite: Wei Xia and Zhizhou Zhang, "Language Gene Network Patterns May Facilitate Relationship Setting-up between Language Genotypes and Students' Class-Performance," International Journal of Learning and Teaching, Vol. 3, No. 4, pp. 259-263, December 2017. doi: 10.18178/ijlt.3.4.259-263
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