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Greeno (1973) has proposed a memory model for problem solving. The three main components of his model are: (1) short—term memory, in which the external description of the problem is input, (2) long-term memory, which stores past experience such as facts, algorithms, heuristics, and related problems, and (3) working memory, by which the information from STM and LTM interact and the solution route is generated and tested. A description of the problem, including the initial state, the goal state, and the legal operators, is introduced into working memory by way of short—term memory. Past experience about how to solve the problem enters working memory from LTM. More information from the outside world may be required as problem solving progresses; hence the problem solver may pay attention to different aspects of the presented information and that the generation of new problem states in working memory may require more old information from past experience. According to Greeno’s model, working memory involves both the internal representation of the problem and the construction of links between givens and unknowns.

Large amounts of information can be stored permanently in long—term memory, whereas only limited amounts of information can be temporarily held in short—term memory. Information is also decoded from LTM; that is a specific piece of well-learned information is located in LTM (for example, recognizing that 2 is an even number.) One can also hold information in STM. In this case, the individual consciously thinks about remembering information at one instance, such as hearing a list of numbers and being able to recite them in order. When manipulation information occurs in STM, the individual performs simple operations on information that is being held in STM (for example, comparing two numbers to determine whether or not they are equal.)

Byers and Eriwanger (1985) claim that memory plays an essential role in the understanding of mathematics and hence problem solving. Silver (1980) further demonstrates that good problem solvers tend to have reasonably accurate recall of problem details. His findings suggest that good problem solvers differ with respect to the degree in which they can remember and utilize structural information obtained from a problem solution. Using these empirical findings and the models presented earlier, it would be advantageous to learn some memory techniques in order to improve upon the problem solving process.

To improve memory three basics should be adhered to in order to obtain optimal effectiveness (Klatzky, 1975). First, the material should be given as close as possible before the time when the action is required. It may be of no use to remind someone as he leaves home to buy bread on his way home from work. Second, the reminder should be active rather than passive. A passive reminder in a diary is useless if the user forgets to consult the diary. Third, specific reminders for the particular actions are required. A string around the finger may remind someone that something is to be remembered but not what is to be remembered.

Chapman and Crompton (1978) studied the effects of humor on memory retention. They discovered that humor does not actually affect the encoding of information into memory stores, but rather that when an individual reflects upon a joke or humorous incident which occurred during the learning of information that certain aspects of the message are unwittingly rehearsed. The authors also found that the employment of humor is likely to generate a relatively high attention level. In short, there are some benefits derived from humorous presentations of material; however to encase with humor or to interpret with humor an otherwise serious message is a poor strategy that can impair the retention of the message.

In researching the effects of messages broadcast to the general public, Wagenaar (1978) concludes that information is poorly recalled, even shortly after its presentation. The problem lies in the composition of these messages because the listener is usually forced to store and reproduce the message just as a list of nonsense material. Consequently, recall is much better when the material allows for processes such as selection prior to storage and reconstruction in the recall stage. Wagenaar recommends that the listener be provided with a general schema that can be easily remembered. For example, in studying the presentation of weather information, he suggests that a general schema/synopsis of the entire weather situation be presented prior to going into the specific weather details. If such a schemata cannot be found, then one should not attempt to present the whole bulk of information since the listener will not store more than a few highlights. It is not effective to include too much extraneous information during the presentation. Finally, long messages should be constructed in such a way that selection of relevant clauses is facilitated (for example, breaking up a weather forecast into regional forecasts.)

Morris (1978) provides evidence for the effectiveness of certain mnemonic devices. He discovered that using first letter mnemonics (for example, using the acronym HOMES to remember the five Great Lakes), contributed to a dramatic improvement in performance when the items were well known and the order needed to be retained; however the mnemonic device did not help in the learning of new unrelated lists of items. Morris does provide evidence for the effectiveness of certain mnemonic devices. Association or the linking together of items to be remembered did not improve recall, but it did provide an opportunity for associating apparently disconnected items.

Should one listen to Baroque or to the Beatles or to nothing at all while filling the memory banks (e.g., while studying)? Thomas (1978) addresses the effects of noise (or music, if you will) on memory and concludes the following: First, noise during encoding facilitates recall after a delay of 24 hours. Second, facilitation can also be achieved by subjecting subjects to a short period of noise-induced arousal prior to recall, particulary for material originally learned in quiet confines. Third, noise levels of 65 dB (conversation level) appear to be optimal for immediate recall, moderate noise levels have no effect on recall, and high intensities have a detrimental effect on recall. The author states that “. . .as noise intensity increases, subjects adopt differing strategies in an attempt to maintain a high level of successful performance and that at very high noise intensities the strategies often break down. . .“ (p333). Furthermore, Schroeder and Ostrander (1979) draw upon numerous research projects and conclude that by listening to slow rhythmic music (for example, Baroque) at sixty beats per minute in 4/4 time while reciting information in time to the music, one can significantly increase his retention and recall of the information.

Anderson (1980) suggests the following techniques for the improvement one’s memory. (1) Consolidate the material into units of manageable size, and sub-classify or cross-classify the information if the number of units exceeds five. (2) Tie the information together via images, word associations, and/or rules. (3) Cue the information by associating it with specially arranged or naturally occurring stimuli. (4) Continually repeat the information until new associations are well established. (5) Over learn the material, and continue repetition until errors are no longer incurred. (6) Practice actively recalling the information to strengthen and test the actual retrieval plan itself. (7) Distribute practice and take short breaks between practice sessions.

Finally, when attempting to memorize lists or formulas, Bransford and Stein (1984) suggest the following: (1) Rehearse the item a number of times as it is read. (2) Rehearse items in groups (while reading the third item, go back and rehearse it with the second and first items). (3) Organize the items into conceptual categories. (4) Make up a story that links each of the items to be learned. (5) Form vivid images or mental pictures of objects.


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