Teaching Thinking Skills: Exercising Cognitive Abilities - Essay Example

Teaching Thinking Skills: Exercising Cognitive Abilities Training children in thinking skills is, unfortunately, not a straightforward task. There is no good set of mental calisthenics a child can do to develop a certain set of mental muscles, and innate strength in one area often cannot transfer directly to ease weaknesses in other areas. The fact that training in abstract thinking skills does not guarantee their application to concrete problem solving presents a frustration for both teacher and student. However, there are many opportunities in the teacher’s relationship with the student to introduce thinking skills training, and when these opportunities are taken up, stronger students result. Problem solving is a broad category of thinking skills and usually calls upon many other knowledge domains. Though teachers attempt to teach problem solving skills, it may be more efficient to concentrate on other cognitive domains to emphasize the various skills a child might apply to problem solving. Logical reasoning is the step by step process of arriving at conclusions. The fewer operators (steps from A to B) involved, the easier it is for children to solve problems. As children develop their logical thinking skills, they go through many “aha” moments of insight until these moments are internalized and the process (hopefully) smoothes out in later years. Following on logical reasoning is statistical reasoning, which is best developed on a deliberate basis separate from other cognitive skill sets. It is difficult for children (and even adults) to translate statistical reasoning skills into other domains, but these skills are necessary in a great number of problems. Scientific reasoning combines both logic and statistics; by exposing children to a number of scientific problems and allowing them to exercise their reasoning skills, they can learn to apply knowledge across domains. Visual reasoning and creative thinking go hand in hand, with creative thinking bringing together exercise of cognitive skills and allowing those overlapping domains to interact and produce solutions to problems. Integrating instruction about thinking skills in the later academic years (grades 6-16) can be done deliberately and in a focused way. Younger children are developing their thought processes; by the time children hit middle school, their reasoning methods and processes are beginning to resemble adults. In addition, they have built up experiences both in real life problem solving and academic problem solving, and have had time to practice isolated skill sets. The teacher’s job then becomes easier, in some way; he or she can take an overall and integrated approach to reasoning skills, identify strengths and weaknesses, and bolster areas that may have gaps. Throughout this essay, examples of how to teach specific skills in the later academic years are included. Problem Solving: Applying Knowledge to New Situations Mayer (178) outlines three types of knowledge that often come into play during problem solving: facts, algorithms, and heuristics. Facts are readily available and relate to the problem at hand; occasionally the child will be asked to eliminate facts which don’t contribute to finding a good answer, but usually the facts are simply available. If they aren’t, the child may need to apply inductive reasoning or explore the environment further to generate them. Algorithms are sets of rules which produce answers; the child has either internalized these rules from past learning or experience or must produce them “on the spot” in order to solve the problem. Heuristics are a type of algorithm but are more general rules of thumb. Heuristics can be viewed as general strategies which could be applied to the problem to see if they work. Each one of these knowledge areas can be exercised, either separately or together. These three knowledge domains can be applied to direct problems, such as figuring out the meaning of a passage the child has just read, or they can be applied to social situations, which often create muddy waters for children. In middle schoolers, for instance, social algorithms can be clear statements of rules (“Don’t cheat on your homework”) or they can be deduced or inferred from situations (“Group work is not cheating, as long as everyone contributes to the work”). Heuristics comes into play with rules like the Golden Rule (“Do onto others as you would have them do to you”) or by experiencing similar situations (“If I have a hard time solving a math problem, Pedro can help because he is good at math”). Algorithms apply a past set of rules to a new situation, helping the child solve problems without going off in the wrong direction; heuristics involves searching memory and past experience for similar-seeming problems and applying this past solution to the current situation. Heuristics will often involve wrong answers, from which a child can learn new heuristics and algorithms (Mayer 178). In this way, multiple layers of reasoning build upon and compliment each other, leading to good conclusions. When attempting to illustrate problem solving, researchers often use the example of chess, perhaps the ultimate test of problem solving ability (Mayer 220-226). When one approaches the problem solving processes of children in middle school, chess is not a very good example (there are very, very few teenaged chess prodigies, though they do exist). Simpler game playing does exercise these skills (as long as the solution isn’t too simple). When teachers introduce friendly game playing into the classroom, children can sharpen their problem solving skills and have fun at the same time. Team games are even more interesting, because children can pool their cognitive resources in order to solve puzzles and exercise their problem solving skills. Thus it is easier to teach problem solving skills and for children to exercise those skills if games are involved and there is less pressure to produce a “correct” answer to a question. Problem solving involves breaking a question apart, adding reasoning, and presenting reasonable solutions. Often, more information is needed; in this case the child must formulate hypotheses and test them in order to have all the conditions needed at hand. Problems can be represented graphically through such syllogistic reasoning methods as Euler circles or Venn diagrams (Garnham and Oakhill 103-105) in which students relate disparate bits of information with each other through drawings. Older children who have had some practice at visual reasoning (discussed in a moment) especially benefit from drawing out the parts of a problem. The teacher can show students how to draw Euler circles, in which logical statements such as “Some A are B” are represented by overlapping circles. Venn diagrams take this visual representation one step further by shading or blacking out parts of the Euler circles, thus indicating that more conclusions can be drawn from the given data than straight assumptions (Mayer 119; Garnham and Oakhill 106). Many problems can be broken into manageable parts through such simple methods. Using visualization in this way during problem solving exercises helps the child to see how various parts of a problem fit together. Most children will take readily to graphic representations such as Euler circles and Venn diagrams, if these simple methods are explained and illustrated to them, and they are encouraged to use them during problem solving. Logical Reasoning: One Step at a Time Leads to an Answer Logical reasoning uses hypothesis testing, deductive reasoning, and inductive reasoning extensively. Children tend to look for positive confirmation of rules (Garnham and Oakhill 151). This simply means that our brains are wired to seek logic which supports the assumptions we already have—even when those assumptions turn out to be untrue and interfere with figuring out solutions. One important way teachers can exercise logical thinking skills is to stress conditionals and reordering of assumptions. For instance, in the natural language statement, “If snow were black, it wouldn’t look so pretty” (Garnham and Oakhill 85), the child can logically conclude the meaning of the word “pretty” because he or she already has experience with white snow. Older children in grades 6-12 have great experience with other types of conditionals (“If you complete all your homework on time, you will get a few bonus points”). Past high school and into the early college years, adult conditionals come into play during the logical reasoning process. Things become more complex when the conditions are reordered (“Do not stay up all night chatting with your friends on the Internet”) and when more than one condition must be met in order to find a solution to a problem (“Chatting with friends and watching TV waste time that could be used for completing your homework”). Encountering such problems allows the child to figure out how to apply what is learned in one situation to similar situations in the future; they learn to sort through conditions and determine how to solve each one, in order to solve the whole problem. Though children may arrive at logical conclusions using logical processes, there is often an “aha” moment in which a sudden insight leads to understanding (Fiske 37). Studies show that both adults and children will think through a problem on a subconscious level and on a conscious level, so they can sometimes articulate their thought processes and sometimes not. Visualization is important in logical reasoning; when children are presented with a logic problem to solve, they will succeed in finding the answer more readily if they are also instructed to visualize the problem’s parts and inter-relate them with each other. Asking children to think things through, and giving them time to do so, is important so they can comfortably find solutions to problems. The steps in logical reasoning are difficult for an adult to remember—as children grow older, they are exercising their nascent logical reasoning skills, so they are learning through trial and error. Statistical Reasoning: More than 2+2=4 Teaching children statistical reasoning skills is not an easy task (Nisbett 137). Because statistics has its own rules which can be completely unrelated to the rules of language, it requires learning a set of systems which apply to numbers and interpretations of numbers (Garnham and Oakhill 153). The more training a person has in statistics, the more likely they are to transfer those skills to other problems. For instance, Nisbett (138) details experiments where subjects were told that a traveler returns to restaurants which served her an excellent meal on the first visit, but she finds the second visit is not as satisfying. When asked why this might be, subjects with little statistical training (which would be typical of a middle school-aged child) tend to answer that cooks change frequently, what Nisbett refers to as “deterministic” conclusions. Subjects with great amounts of statistical training (as might be true of a grade 13-16 aged young adult, depending on their educational background) answered the same question with statistical answers: she is disappointed on her second visit because there are more inconsistent restaurants which serve an occasional excellent meal than consistently excellent restaurants. Essentially, both trained and non-trained subjects were talking about chance, but the trained subjects knew how to think about chance in this hypothetical situation and explain its role in the restaurant problem. Thus, teachers must make a deliberate effort to teach children statistical reasoning skills and will often need to point out that statistical reasoning can be applied to situations, at least until the children learn mastery. Children tend to view problems in a straightforward manner (Kuhn, et al. 45), and when theories match readily with the facts at hand they can apply their statistical knowledge more easily. When they are working within a specific knowledge domain (such as language only, or math only) their thinking can build upon itself to find solutions to questions in front of them. However, when the teacher asks them to cross domains (solve word problems, or explain the meaning of data) they have trouble translating between domains. A child may understand the meaning of statistics gathered during an experiment or exploration but may not have the words to explain their meaning in an understandable way. This presents a frustration for both the child and the teacher; teaching children the skill to cross domains should be introduced slowly and deliberately as children begin to master each individual domain. Then, cross over situations can be presented in which the child exercises skill on one area and applies it to other areas. When statistical reasoning sticks to the numbers, children go through a certain process to apply their knowledge to solving mathematical problems. Knowing the heuristics behind a proposed solution is very helpful (Mayer 477). If a child is given a certain set of data and told in general how to manipulate it, he or she will find the answer more readily than a child who is left to figure out the basic rules. Scientific Reasoning: Formal Rules for Understanding Systems Scientific reasoning makes great use of deduction. One way to teach children strong deductive skills is to present them with a specific set of information and ask them to solve a problem or test a hypothesis—to combine aspects of the experience through addition and subtraction of information (Mayer 117, 133). For instance, begin by presenting children with information that applies to one model and over time, put their thinking skills to work by presenting information that could apply to more than one model, or even to no model. This allows them to work through problems in a step-by-step manner. Scientific discoveries are often made through this step by step reasoning process and hypothesis testing. “Formal discipline training” has been practiced by educators for literally thousands of years (Nisbett 298-299). Plato encouraged the teaching of mathematical rules, and more recently, Piaget thought of learning as the application of abstract rules of deductive logic. There are some subjects (such as math and science) that are more readily given to scientific types of reasoning skills: straightforward, deductive, and formal rules tend to lead to the best results. Of course, this is not always true; scientific reasoning involves a lot of creative thinking once the child has internalized the basic rules of science. Knowing these rules does not transfer directly into other domains such as social interactions or physical manipulation of the environment, but using scientific strategies can solve many problems at least satisfactorily. As children move from middle school to high school and beyond, their study of the sciences tends to be compartmentalized (biology, chemistry, physics, etc. studied independently of one another). The same types of scientific reasoning processes are used in each type of science, but the subject matter may confuse the reasoning process unless the teacher deliberately points out that the reasoning is the same across scientific domains. Visual Reasoning and Creative Thinking Leveraging the power of a child’s imagination is exciting and creative. In fact, the fewer restrictions a teacher puts on the child’s visual reasoning processes, the better (Fiske 21). If the teacher introduces thought experiments in which a child mentally manipulates shapes or patterns which he or she can see or touch before the experiment, gives the children time to explore the shapes or patterns, and presents them with a “finished product” to aim toward, visual reasoning skills can be sharpened. Alternatively, the child can be asked to invent models from disparate parts, as shown in the following experiment. Fiske (22-31) presented test subjects with randomly chosen forms and asked them to create finished products with their imaginations. After viewing the forms for several seconds, the subjects closed their eyes for two minutes and mentally manipulated the objects into a recognizable form which they could name when asked. When presented with a small square, a large square, and a triangle, the subject could assemble them into the outline of a house. A circle, the capital letter D, and a figure 8 could be manipulated into a smiley face. In addition to being fun experiments for children, this type of exercise sharpens visual reasoning skills and allows the child to use his or her imagination to figure out how seemingly unrelated things can work together to create a recognizable finished product. Kuhn et al. found that children form inferences that are less valid than adults (67). In fact, most children form invalid inferences as a matter of course, but over time they develop the skill to recognize important factors and apply them to situations. Children tend to be socially adept to some degree, but physical domains such as manipulating objects or interacting with the environment are weak until they are closer to being adults (70). In other words, children draw incorrect conclusions about the meaning of elements within their environments. Interestingly, children showed more signs of inclusive inference (including ideas or objects in the reasoning) than exclusion of ideas or objects, which is important for teachers to realize. The child will show better creative thinking ability if there is just enough evidence to form a valid conclusion, but they may stumble when asked to eliminate information in order to properly answer questions. In addition, since they lack experience, they may eliminate evidence improperly because they can’t see the whole picture of the problem. Likewise, older children are better able to sort through and eliminate information as needed. Both inductive and deductive reasoning are used in creative thinking. Rules can be learned (or figured out in probabilistic ways) but they do not always apply exactly in 100 percent of similar situations. This is where strong inductive reasoning skills come in handy; the child can test hypotheses based on known experience and a set of facts, and determine if the rules apply in a given situation. Humans tend to categorize and organize knowledge (Nisbett 61; Mayer 91). By presenting children with many opportunities to categorize learning, the teacher helps them develop creative thinking skills. Generalizations are important, but so are specifics. At the broadest level, a child’s academic career builds from one year to the next and creates a system of knowledge acquisition. Experience in kindergarten with sorting objects by color is called up in middle school when children learn the classifications of plants and animals. Creative thinking comes into play with plants or animals which are not easily classified, or when shades of color are introduced to the kindergartener. Concluding Remarks It is important to note that attitudes and beliefs play a large role in the success or failure of teaching reasoning skills (Mayer 477). If a child believes that problems are difficult, they will be more difficult. By the same token, if a child believes he or she lacks the skill to manipulate numbers or the creative power to visualize problem solutions, he or she will find these types of reasoning more difficult. Teachers must fight against children’s attitudes and beliefs about themselves on a daily basis, and must take these internal states into account when teaching reasoning skills to a room full of children. Each one will naturally be at a certain place in cognitive growth, and each one will artificially be limited by past experiences and what they believe about themselves. The situation is made all the more complex during middle school when children are forming a social image of themselves as well as an academic image; these two may be inseparable for the young teenager, and a social image may unnecessarily impact the academic achievement of the child. Introducing games into problem solving situations is a good way to allow children to exercise these skills in a positively competitive or team oriented way. Practicing problem solving in social situations helps children develop a reliable set of heuristics they can apply to many situations. Introducing logical reasoning into learning situations allows children to develop their deductive and inductive skills and helps them meet with problem solving success on a regular basis. Using statistical or mathematical problems, as well as those requiring scientific reasoning, shows children how to apply their logical skills to the everyday world. Finally, encourage visual thinking and creative reasoning where ever possible, because children are successful at using their imaginations to solve problems, though they may not have the skill to reliably apply creativity on a regular basis. Teachers find it easier to instruct children on straightforward sets of facts and direct relationships between disparate parts of a problem. Teaching cognitive skills may not be straightforward, but opportunities for learning these important processes come up on a moment by moment basis. The teacher just has to pay attention—and ask the students to pay attention—to situations in which a learned skill set may be applied. Leaving room for creative thinking is always appropriate as well. Works Cited Finke, R. Creative Imagery. Hillsdale, NJ: LEA, 1990. Garnham, A. and Oakhill, J. Thinking and Reasoning. Cambridge, MA: Blackwell Publishers, 1994. Kuhn, D., Garcia-Mila, M., Zohar, A., and Anderson, C. Strategies of Knowledge Acquisition. Monographs of the Society for Research in Child Development No. 245, Vol. 60, No. 4, 1995. Mayer, R. Thinking, Problem Solving and Cognition. 2nd edition. New York: W.H. Freeman and Company, 1992. Nisbett, R. Rules for Reasoning. Hillsdale, NJ: LEA, 1993. Read More