cognitive learning mechanisms

Teaching reading - CEP 903 10.5.07

• Statistical learning, as introduced by Saffran (2003), suggests that language is shaped by human learning mechanisms rather than innate brain structures. We learn to predict statistical probability by becoming familiar with sequences in language. For example, presenting the word ‘the’ or ‘a’ in text serves as a cue, helping us predict that a noun will follow it. Therefore, an increase in language experience increases our ability to confirm certain language probabilities. Teachers can utilize Saffran’s work when teaching reading to students by exposing them to print at an early age, focusing on language concepts such as phonetic features, word boundaries, and syntax.

• Embodiment refers to a concept claiming that we learn in our bodies and interact with our environment to obtain knowledge. Our behavior is a result of encoding perceptions. In a study conducted by Noice and Noice (2001), for example, movement facilitated recall even without intent because environmental cues provided scaffolding. Their finding suggests that active experiencing helps create meaning and enhances memory because real actions have properties that language descriptions do not. Teaching reading that utilizes embodiment could include role playing parts of a story or using concrete objects and hands-on experiments to help students visualize abstract concepts (Noice and Noice, 2001; Gentner, 2002).

• Test-enhanced learning suggests that testing students on material is more effective for retaining information in long term memory than repeated studying of the material (Roediger, 2006). Studying (or rereading) is different than retrieving information from our brains (testing) because the latter allows us to practice the skill actually required on future tests. Knowing this, an effective approach for teaching would be to expose students to reading material and administer periodic testing over the material. Students who are taught by this method would have the opportunity to demonstrate what they have learned on multiple occasions, each time strengthening their knowledge of the material.

• Maternal elaboration is found to effect child elaboration and memory over time (Reese, 1993). Utilizing elaborative techniques provides scaffolding for the learner in which he/she is able to re-experience learning the information each time a new elaboration is introduced. Reese’s findings provide implications for teaching in that they suggest effective ways for teachers and students to interact. Teaching by elaboration rather than repetition would provide bidirectional scaffolding that ultimately increases teacher-student interaction, facilitating communication and recall of information. In other words, asking a variety of questions over reading material allows the learner to make more connections in the brain because more resources are being activated whereas repeating the same question often does not provide adequate scaffolding for the learner.

• Glenberg’s memory model describes memory as being embodied by combining different sets of actions together (1997). In order to remember something, we either use clamping to ignore memories and attend to the environment or use suppression to decrease our current perception and enhance memories. Limitations on learning according to Glenberg are based on possible next steps that we know to be true because of our experiences. For example, in repetition priming of language, our previous exposure to reading material facilitates our current ability to process it. Teaching implications that utilize repetition priming are related to our ability to statistically predict language (Saffran, 2003) and mesh concepts (Glenberg, 1997). Teaching students to remember what they read can be modeled after repetition priming by creating multiple opportunities for students to associate concepts by meshing related words. For example, presenting the word ‘volcano’ and allowing students to choose from a list of words that are related to the word primes ‘magma’ or ‘lava’ but not ‘dog’ or ‘cat.’ ‘Magma’ and ‘lava’ are likely stored in the same category in the brain whereas ‘dog’ and ‘cat’ are not; therefore, memory retrieval is strengthened.

Empirical evidence

Brain research provides compelling evidence for learning and development in that it gives specific examples of how bidirectional change affects brain development (Nelson, 1997). As a basic explanation of Nelson’s findings, we know that learning and thinking equal brain change. Bidirectional change can be described as experiences that lead to brain change and a changed brain that leads to changed experiences. For example, an infant brain possesses great capacity for change because neurons in the brain are initially uncommitted. Once connected, the neurons become stronger and neuroplasticity decreases. As a result, each experience sets limits for later change.

Infancy can be considered a foundation for future learning in which boundaries for brain development are set by a range of reaction. An infant’s range of reaction puts constraints on intellectual ability and positive or negative results are manifested by environmental influences. Range of reaction could be determined by a number of factors. Stressful pregnancy and malnutrition are biological influences that contribute to decreased brain development. Poor parenting and lack of exposure to educational materials are environmental influences that contribute to negative bidirectional change. In each case, fewer opportunities are available for high intellectual ability.

Brain research has clear implications for education in that it gives teachers hope that the brain has plasticity. At the same time, it supports the notion that parents have a crucial role in shaping healthy early learning experiences. Furthermore, it allows teachers to understand why children have different intellectual abilities and behave differently. Brain research confirms that early intervention is more effective than later intervention because it provides more opportunity for positive brain change and experience.

Unlike the convincing evidence found in Nelson’s research, Reese’s evidence suggesting that maternal elaboration is an effective technique for facilitating childrens’ memory is less compelling (1993). According to Reese, highly elaborative mothers facilitate child elaboration and memory of information. The evidence supporting this claim argues that elaboration creates scaffolding for recalling past events and that a child is able to contribute more information about these events if the mother is elaborative.

The first problem with these findings is that they are ungeneralizable. The study results show that high elaborative style is associated with girls more than boys. If boys are exposed to less elaboration, they will inevitably become less elaborative as an adult. In other words, socializing girls to elaborate more begins as a small difference that becomes magnified over time. As a result, dads are likely to be much less elaborative. This brings me to my next criticism. Father elaboration style was not addressed perhaps because it would fail to support that the concept of high elaboration style is generalizable. This study also fails to take environmental factors into consideration. Ability to use elaboration clues may vary according to a child’s ability to block out distracting information in the environment. If memory is enhanced by scaffolding, it seems that it should be worsened by irrelevant cues in the environment. Finally, misleading elaborations may foster the recall of inaccurate information; therefore, high elaboration style from a misinformed source may hinder rather than help recall accurate information.