Background Information:

Different cultures around the world prioritize different subject areas by giving them more time in the curricula. Interestingly enough, there is relatively little variation in the actual domain areas themselves, however (Tokuhama-Espinosa, 2014). While the debate on the ideal curriculum structure is still on going (McKernan & McKernan, 2013), the cornerstones of all formal educational programs around the world are Language and Math skills (Pinar, 2013). Among countries that conduct national exams, there are none that neglect these two domain areas; these are the only two universally tested subjects due to the foundations they lay for other academic fields (Martin & Mullis, 2013), including history, art, the natural, social, computer and hard sciences, which all depend on Language and Math skills.

The earlier an academic competency is introduced to a learner, and the stronger its subsequent constructivist development, the more likely is a positive learning outcome in that competency (Tokuhama-Espinosa, 2014). That is, a student needs to have experiences that develop skills in a logical order to strengthen neural pathways for future learning (Galván, 2010; Karmiloff‐Smith, 2009). It is for this reason that early language exposure to good models is vital for competent development. The stimulation of language development (vocabulary, correct word order, etc.) by parents begins in the home and is generally developed further in regular school settings by trained professionals. Similarly, pre-numeracy skills (articulating quantity, symbol to meaning relations, etc.) aid in the development of a child’s “number sense” (Dehaene, 1997) and are cultivated in a similar pattern (Campbell, 2005). High quality early childhood education can play an important role in the effective development of early academic skills development (Campbell, Pungello, Burchinal, Kainz, Pan, Wasik & Ramey, 2012).

Improved neuroimaging has provided new insights into the great variety of neural networks that are prerequisites for reading and basic math (i.e., Clements & Sarama, 2009; Dehaene, 2009). While our understanding of the human brain is still in its infancy, better technology and more detailed studies provide insights not yet incorporated into general teachers’ pedagogical knowledge, which should now be considered. There are at least 12 neural networks related to pre-literacy skills, which coincidently overlap onto circuits related to pre-numeracy skills. Additionally, there are four networks that relate to affective factors and learning. This yields a total of at least 16 neural networks needed for a child to successfully learn Math and Language (Tokuhama-Espinosa & Rivera, 2013).

The Problem:

It is not known how and to what extent current teaching methods reinforce fundamental neural circuits necessary for the development of Language and Math skills. It is also not known how and to what extent early stimulation provided by proper activities helps learning. It is also not known how the lack of proper stimulation leads to learning gaps or deficits in the constructivist development of skills sets in Language and Math that contribute to specific learning problems.

Hypothesis:

It is hypothesized that if specific methodologies, activities and classroom strategies can be better aligned to strengthen these key neural circuits, teaching can become more efficient, children can meet with more success, and the frequent gaps found in early childhood education that tend to widen and spread throughout the educational experience can be reduced.

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