大腦與學習思維方式
 

雖然大多數學術背景都是一般常用的框架模式，學習風格或方式還是依照于個體的發展基礎。學習就是“獲取與這個世界相關知識的過程”，至于學習風格，個體怎樣形成習慣性地回應關于經驗方式的模式，反映出了一系列的態度，情感回應，偏好和習慣。它是基于我們如何相互影響過程，從我們的環境進而深入影響我們之上的，除了對學習風格提出了大致的觀點，這篇文章也闡明了由那些支持自我功能存在的模型而導致的差異。

對學習風格達到初步的理解需要具備一些關于大腦功能的知識。通常來說，特殊的腦部位置與其特殊的功能相關。大腦的左半球和右半球用的是不同的策略，個人解析分類為要不就是左腦學習者要不就是右腦學習者。一個出色的中央處理器（左腦）更喜歡按一步步地順序格式來學習。從細節入手能促使技能概念的理解。同時中央處理器（右腦）更傾向于從大致的概念先開始，再深入細節。
 

Learning Styles and the Brain 

 

Although most commonly framed in academic contexts, learning style lies at the foundation of individual identity and development. Learning, "the process of acquiring knowledge about the world" (1) and learning style, "...the sum of the patterns of how individuals develop habitual ways of responding to experience" (2) reflect an array of attitudes,emotional responses, preferences and habits. It is the basis of how we interact with, process and are subsequently affected by inputs from our environment. In addition to providing a general overview of learning styles, this paper makes the claim that distinctions resulting from these models support the existence of the I-function. 

 

A preliminary understanding of learning styles requires some knowledge of brain functioning. Currently, specific cerebral locations are associated with particular functions. The left and right hemispheres of the brain employ different strategies that classify individuals as either analytic (left) or global (right) learners. "A successive processor (left) prefers to learn in a step-by-step sequential format, beginning with details leading to a conceptual understanding of a skill. A simultaneous processor (right) prefers to learn beginning with the general concept and then going on to specifics." (2) Constructing learning style along these lines has dictated classroom methods for decades. Traditional pedagogy has long favored the left-sided student, emphasizing accurate, rational and sequential thought. Right-sided learners, with a proclivity towards a spontaneous, random, and visual style, possess a mode that is undervalued and often stifled. 

 

Current theories of human learning contend that learning occurs via two independent systems in the brain, the implicit (non-declarative) and explicit (declarative). One primary distinction that results from this model is between a learning style that involves the encoding of information as instances, or specific fragments, as compared to abstract rules. (4) Implicit learning occurs through the memorization of instances that one encounters during the learning process, whereas explicit learning results from the generation and testing of hypotheses. Of particular interest is research that examines how a particular goal type affects whether implicit/instance based or explicit/rule based learning predominates. It was determined that goal specificity does in fact determine which type of learning occurs. Namely, a specific goal corresponds to instance learning while a non-specific goal results in rule learning. Superior learning of non-specific goal learners was demonstrated by enhanced ability to reach a specific goal in a post-learning test phase, to predict the computer's next response in a novel situation, to predict performance in familiar situations, and to describe the rule underlying the performed task. Conversely, specific goal learners transferred their learning less readily to novel specific goals at the test phase and were able to predict results in familiar situations but not in novel ones. (5) When learners were presented with dual goals, instance learning, but not rule learning was observed. #p#分頁標題#e#

 

Proposed explanations for these findings provide some insight into how the pattern of a particular learning style expresses itself in the brain. Research suggests that by having no specific goal individuals are encouraged to explore "hypotheses space," whereas a specific goal leads to a journey through personal "instance space." This reinforces the model of brain organization as consisting of different "information gaps" that are subsequently filled depending upon the experiences, interests, and goals of the learner. These holes constitute an internal filing system whose use is task dependent. Many theories based on this construction contend that "Instance learning...results in a look-up table in which individual instances are stored in memory. ...The lack of a specific goal means that subjects have no guidance as to how to search the instance space...therefore subjects may use exploration of rule space to direct their search...."(5) Conversely, the generation, exploration and testing of hypotheses characterize rule space. Interestingly, it is also proposed that when presented with a dual learning goal, the individuals' memory capacity is overloaded, thereby preventing rule learning. 

 

Another distinction that arises from the dissociated implicit vs. explicit model is the notion that learning occurs both with and without awareness. "One system is explicit and conscious, involving the limbic and neocortex parts of the brain ... (whereas) implicit memory can be received, stored, and recovered without the participation of the limbic system and outside the conscious awareness of the individual...(and) provide an array of non-conscious ways to respond to the world." (3) Implicit learning encompasses procedural knowledge (skills and habits), category-level knowledge (the ability to classify information based on natural categories and the implicit acquisition of rules often found in grammar), conditioning (learning a simple conditioned response, best understood in relation to emotions such as fear) and priming (the facilitated ability to identify or make judgments about target stimuli as a consequence of recent exposure to them. (3) It encompasses activities and attitudes that an individual can do or feel, but cannot explain. Alternatively, explicit learning is characterized as an active process in which people seek out the structure of any information that is presented to them, gain knowledge that is verbally reportable and includes hypothesis testing and problem solving. (6) 

 

An array of evidence supports the notion of two separate learning systems. Neural evidence from research with Parkinson patients suggests that procedural knowledge is acquired separate from declarative memory. Patients showed little difficulty with cognitive tasks such as recall and recognition. However, significant impairment was evident regarding non-cognitive skill based tasks. Further supporting evidence for two qualitatively distinct learning systems relates to category-level knowledge such as grammar. Few individuals can explain the abstract rules that guide their speech and writing, yet these rules have clearly been mastered. Conditioning, another demarcation of two learning systems, includes emotions, such as re/action to a threatening or distressing situation. Each learning system has significant impact on an individual and affects subsequent action. However, only one enables for personal reflection (explicit) whereas the other does not (implicit), raising interesting questions regarding the relationship between learning and awareness. #p#分頁標題#e#

 

The distinction between implicit and explicit learning cuts across clear definitions regarding the I-function. Implicit learning occurs without its participation whereas explicit learning does incorporate this element of the nervous system. This distinction further bolsters the claim that "you" are only a particular part of the nervous system, and that output can be caused with or without "your" involvement. In this regard, we have already considered the example of various motor outputs associated with a paraplegic; in the case of learning style this would include skills and emotional responses. Consciousness has historically been regarded as a higher cognitive process than non-conscious thought. As the storehouse of memories and actions that are pondered, processed and integrated into an individuals' subsequent behavior and ideas, it was considered to be the hallmark of evolving definitions of self. The role of non-conscious mental life in one's conscious experience and thought was disregarded in classical theory. Currently, however, it is widely accepted that who we are is dictated by a complex interaction of various learning systems. Research purports that perspective transformation, previously considered a process requiring critical reflection, also occurs via implicit learning. In fact, "Studies...have shown that giving attention to implicit memories through verbal processing...(actually) interferes with retrieval." (3) This theory promotes trusting in one's instincts and the value of the guiding force of feelings, and contends that acting and learning in the absence of concrete explanations is an equally important constituent element of self-identity as is conscious processing. 

 

Our understanding of the role of the I-function is reinforced by its participation in explicit learning. In the classroom, students are inundated with a plethora of information. Everyday we encounter innumerable inputs in the form of conversations or observations from which we learn. Why does a particular input speak to one individual and not another? Why do we often find ourselves particularly intrigued by material that somehow relates to our own experience? And why do we often seem to better retain and recall this information? The I-function serves as a model builder of what the rest of the nervous system is doing and how it relates to the world. Its presence during superior rule learning might indicate a correlation between the ability to incorporate material into one's own experience with degree of learning. Namely, we learn better when we can integrate information into our own experience of an experience, a process characteristic of the I-function. Also, non-specific goal learning leads to the generation and testing of hypotheses. As the basis of exploratory behavior and creativity, it is only expected that explicit learning correlates with the I-function. Similarly, the concept of the I-function as the basis of our intrinsic variability is also supported by its role in the learning process. When utilized in the context of non-specific goal and exploratory learning, we cannot predict either the endpoint or the method or path taken to get there. A specific goal correlates to a specific solution to a problem. Non-specific goal learning demonstrates the creativity and randomness inherent in any process that utilizes the I-function. #p#分頁標題#e#

 

A better understanding of learning styles has individual, community and societal implications. How we learn provides insight into how we interact with the environment, what lessons we glean, and how these experiences change subsequent behavior and attitudes. Individually, we can either consciously change these things, or appreciate how much of who we are is already rooted in the nervous system awaiting the opportunity for expression. Learning models enable students and educators to assess individual learning styles and to tailor strategies and experiences accordingly. Understanding the neuro-biological aspects of learning could provide critical insight for issues such as learning disabilities. Culture affects what particular style is fostered and preferred. Insight into this aspect of learning style might contribute towards understanding inequalities in the educational system that result, for example, in higher dropout rates for minority students, and make educational reform a more attainable goal. 

 

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