Networking vs. Rote Learning Strategies in Concept Acquisition James Canelos William Taylor James Altschuld
James Canelos is research associate in the College of Engineering, Pennsylvania State University, Univer- sity Park, PA 16802. William Taylor and James Altschuld are assistant professors of education at Ohio State University, Columbus, OH 43210.
Following presentation of a slide-tape instructional program, the performance of subjects in two learning strategy groups- networking and rote- was compared to a control group on a concept learning task and a spatial learning task. Networking proved more effective than rote learning and the control group on both tasks; networking also allowed for improved retention over time [in this case, one week]. This article reviews some of the research on learning strategies and suggests how the network strategy can enhance learning in academic situations.
ECTJ, VOL. 30, NO. 3, PAGES 141-149 ISSN 0148-5806
This study examined the effects of two content-independent learning strategies, the Networking Strategy and the Rote Strategy, and two levels of visual complex- ity, simple line drawings and color illustra- tions, when subjects received a slide-tape instructional program about the human heart. Learning strategies differed in the amount of cognitive processing they caused during learning. The slide sets in the in- structional programs differed in the com- plexity of visual information. The delayed retention of the instructional content was also of interest in this study.
LITERATURE AND RATIONALE
A number of experimental research efforts in instruction and learning have demon- strated an increasing interest in the practical applications of cognitive learning strategies (O'Neil, 1978; O'Neil & Spielberger, 1979; Canelos, 1982; Dansereau, 1978; Dwyer, 1978). This applied research, which has evolved from basic research in experimental psychology and cognitive psychology, has stressed cognitive learning strategies of a content-independent nature. The content- independent learning strategy, as the name implies, is relatively independent of in- structional content. Instructional technol- ogy learning strategies in the past have tended to be content specific, or were em- bedded in the instructional environment. The operational purpose of the content-inde-
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pendent learning strategy is to improve the learner's general information processing (e.g., learning) by facilitating the following cognitive operations: 1. abstraction--separating relevant from ir-
relevant information; 2. encoding--assimilating relevant informa-
tion into the existing cognitive structure; and
3. retrieval--recalling available information in the cognitive structure for a given mental operation.
A content-independent learning strategy, as described here, operationally relates to the cognitive (e.g., mental) manipulations of to-be-learned information by the learner (Dansereau, Long, McDonald, Actkinson, Ellis, Collins, Williams, & Evans, 1975).
Content-independent learning strategy studies that use mental imagery as the basis of strategies for experimental groups have demonstrated significant increases in learn- ing over control groups (Paivio, 1969; An- derson & Hidde, 1971; Persensky & Senter, 1970; Rasco, Tennyson, & Boutwell, 1975). Following a review of the literature on men- tal imagery and learning, Hilgard and Bower (1975) concluded that learning strat- egies instructing learners to form vivid mental imagery of information gave exper- imental groups a significant learning advan- tage over control groups, usually by mean differences of 1.5 to 3 times greater. Rigney (1978) investigated the relationship be- tween cognitive representational systems (e.g., imagery, sequential, dual-coding), innate information processing strategies, and training learners on specific learning strategies, and concluded that a learning strategy approach to improving student learning would be effective in school learn- ing situations. Rigney (1978) concluded:
Self-imposed cognitive strategies are always al- ternatives to instructional systems with built-in instructional strategies of which the student is never aware. Teaching students how to learn and how to retrieve what has been learned, as the primary objective, might be done best by an in- structional system, and having been taught these skills, students might profit more from an in- structional system with the primary objective of teaching content. (p. 170)
While learners can be taught to use spe- cific information processing strategies that
relate operationally to the mental repre- sentational systems, a number of naturally occurring information processing strategies have been identified. Gagne (1977) consid- ers naturally occurring learning strategies to be an acquired skill. These learning or cog- nitive strategies regulate all aspects of in- formation processing. Analogous to the operations of an executive program in a computer, the learner's naturally acquired information processing strategies have a di- rect effect on the abstraction, encoding, and retrieval of information. As learners de- velop their store of intellectual skills and verbal knowledge, they are developing methods of self-regulating internal proces- ses related to learning (Gagne & Briggs, 1974). These self-regulating processes ("learning how to learn" behavior) repre- sent their acquisition of innate learning strategies.
Bower (1972) has identified several natu- rally evolving learning strategies. The most common learning strategy learners use when acquiring new information is to dis- cover if the new information is similar to something the learners already have stored in their knowledge structure. Bartlett (1932) called this mental process an "effort after meaning." In this situation, the learner will make an attempt to convert unknown in- formation into known information by matching new information to existing knowledge. Another strategy Bower dis- cusses is the generative rule strategy. Bow- er's generative rule strategy is actually a concept rule, and operates like a conceptual categorizing system. In other words, a con- ceptual rule, or concept, is actually a device which the learner uses to efficiently categorize information from the environ- ment. The generative rule strategy tends to provide two specific cognitive functions, according to Bower: (1) a decision rule to decide how to classify in memory a given item, and (2) a constraining function to de- termine at which point search through memory should terminate.
A third naturally occurring strategy Bower identified in learners is the mnemonic pegword system, sometimes called a peg-mnemonic or mnemonic de- vice. When using a peg-mnemonic, the learner will first learn a set of "pre-informa-
NETWORKING VS. ROTE LEARNING "143
tion," such as a simple rhyme (e.g., a rhyme mnemonic method), prior to beginning the learning task. This prelearned set of "cogni- tive pegs" will then facilitate memorizing additional information. This facilitation will occur because the cognitive pegs provide the learner with a cognitive framework to relate new information to. For example, when using the loci mnemonic method, an individual will take advantage of informa- tion stored in memory of imaged locations of some well-known place, such as his home. If the individual is attempting to re- member a grocery list, he simply rehearses the list by forming an image of each grocery item into a specific location of his mentally imaged home. For example, "a loaf of bread may be imaged as tilling up the kitchen, a gallon of milk may be imaged as filling up the refrigerator, or a bottle of shampoo may be imaged as an animated shampoo bottle taking a shower." The peg-mnemonic sys- tem is a powerful retrieval system that provides the learner with a method of en- coding information and a set of well-estab- lished cues for later retrieval of information. Bower (1972) concludes: "Such pegword systems can be shown to be exceedingly effective devices for boosting recall, typi- cally doubling or tripling the percentages recalled compared to uninstructed free re- call controls," (p. 114).
Bower (1972) also considered an addi- tional learning strategy, which he referred to as the hierarchical retrieval strategy. As the name implies, the hierarchical strategy requires the learner to encode information into a network of logically related data, forming a distinct hierarchy of new infor- mation. The hierarchy could be semantic (e.g., verbal, proportional) or imaged, or some combination of both. In a verbal hierarchy, semantic inclusive category labels and subordinate related facts form a network or hierarchy of interrelated infor- mation.
Collins and Quillian (1969) suggested that a set of to-be-learned information about animals may be stored in a hierarchy of in- clusive category labels with their related, subordinate facts under them to form a memory cluster or network. For example, a hierarchy could include the inclusive labels of ANIMAL, BIRD, CANARY, FISH, and
SALMON. Under each of these inclusive categories are the subordinate related facts, specific to each superordinate name or lable (e.g., SALMON: pink, edible, protein). Of course, this entire network could be imaged into a combination of labels and images. The semantic category labels serve as the cues allowing retrieval of related facts, which in this instance are examples and attributes of the category label. For exam- ple, if the learner recalls the semantic label, ANIMAL, it is likely that he will also re- member the related attributes of MOVES, SKIN, EATS, BREATHES, which would then lead him to the next cue in the net- work, BIRD, and the subsequent retrieval of the attributes for this category, and so on until all the information is retrieved. The formation of such a mental hierarchy would allow information to be stored in a logically related cluster of data with "built-in" re- trieval cues. In a study by Bower, Clark, Lesgold, and Winzenz (1969), recall of a large list of items was greatly facilitated if the experimenter organized the information to be acquired into networks of related sets of information.
It is likely that other naturally occurring, idiosyncratic learning strategies exist that vary in effectiveness contingent upon the learner's intelligence. However, it is safe to conclude that learners do develop learning strategies on their own. Such learning strat- egies operationally relate to the cognitive mental representation systems of imagery storage and propositional storage. Addi- tionally, learners can be instructed on the use of cognitive learning strategies aimed at improving learning. Some learners may de- velop highly effective information proces- sing strategies, while others are left with low level methods, such as rote learning. Along this line Dansereau, Actkinson, and Long (1974) found that poorer students tended to memorize material in rote fash- ion. Consequently, such students tend to have great difficulty relating new material to available information in memory, since rote memorization makes conceptual inte- gration and transfer virtually impossible. Osler and Fivel (1961) reached a similar con- clusion. They found that middle-ability students produced incremental curves, while high-ability students produced in-
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sight curves. Incremental learning curves indicate stimulus-response type learning and are step-like in form. Insight curves indicate problem-solving or concept learn- ing and tend to show no step-like increase, only a sudden jump to criterion. Osier and Fivel concluded that high-ability students adopt a rule learning strategy leading to sudden correct solution, while middle- ability students engage in stimulus- response learning, which these researchers define as a rote learning strategy.
Presently, our schools do not provide students with instruction on learning strat- egies during the early school years. If stu- dents do not develop appropriate learning strategies on their own, they may be left at a significant learning disadvantage. Wein- stein (1978) points out:
We tell our students what to learn, but we say nothing about how to go about learning. The assumption that the abilities involved in learning are either innate or naturally acquired by every child is probably fallacious. (p. 32)
LEARNING STRATEGIES AND TESTING MEASURES
Two content-independent learning strate- gies were refined and evaluated, the net- working strategy and the rote strategy. The networking strategy was a combination of an imagery peg-mnemonic and a hierar- chical retrieval system, previously discussed with regard to Bower's (1972) work on strat- egies. The networking strategy was a re- finement of a learning strategy developed by Canelos (in press). The networking strategy had essentially three components that facilitated learning or information pro- cessing. The first was the use of imagery, which provides the learner with the process- ing advantage of dual-coding (the storage of an imagery code and propositional code, described by Hilgard & Bower, 1975). The second component was the use of a peg- mnemonic memory system, and the third component was the use of a hierarchical retrieval memory system.
Subjects were trained to use the network- ing strategy by following a set of instruc- tions read to them by the experimenter. The first part of the training session instructed subjects on how to form vivid mental im-
ages of information or events they had pre- viously experienced. The purpose of this was to demonstrate to subjects that they are capable of forming and manipulating vivid mental images, if instructed to do so.
In the second aspect of strategy training, subjects were required to learn a set of in- formation, in verbal and imagery form, that would serve as conceptual pegs for informa- tion to be acquired later. Subjects learned these conceptual pegs from a set of 16, 2 x 2 slides that showed, in illustration form, the parts making up a water filter pump sys- tem. There were 15 slides that described each part in illustration form and included a label for that part (e.g., see illustration of "output valve," see name; see illustration of "water intake," see name). There was one slide showing the overall water filter pump system with all the parts in the correct or- der. Subjects saw the slide set a number of times until they could list all the part names from memory. The experimenter then slowly read the part names, and each sub- ject was instructed to form a vivid mental image of the part named. It was imperative that all the part names and images were retained in memory since these served as the conceptual pegs for the instructional material to be learned later and formed the basis of the peg-mnemonic part of the strat- egy.
It should be noted that the visualized in- structional materials to-be-learned later consisted of a 2 x 2 slide-tape prog...