Guiding Principles of the Modern Red SchoolHouse Design:
Research-Based Solutions for 21^st Century Schools (continued)
By Sally B. Kilgore, Ph.D.

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What do we expect students to be able to do with what they learn?

Public debates about the best or worst instructional strategies give too little attention to what we want students to do with what

Best practices in instructional strategies differ depending on how one expects the learner to use what they are learning.

they learn. Yet, research evidence from the cognitive and neurosciences is fairly clear: Best practices in instructional strategies differ depending on how one expects the learner to use what they are learning. Do we want them to be able to recite, upon request, a given procedure or set of facts? Do we want them to do well on next week’s history test? Well sure, that’s great, but hardly enough for states to justify the investment of billions of taxpayers’ dollars. In the larger scheme of things, MRSH developers thought the American public would agree: Students should learn in ways that allow them to remember what they’ve learned for a long time, and to be able to use whatever they’ve learned in future academic pursuits as well as in their daily lives.

Remembering things: Steven Pinker, author of How the Mind Works (1997), notes that our brains are marvelously efficient machines; we remember what we use frequently—be it telephone numbers or basic addition facts. Cognitive scientists find that rehearsals are a critical activity for recalling facts and procedures.

Rehearsal strategies include what educators often refer to as “drill and kill”—a label that carries quite a bit of baggage. Bad reputation notwithstanding, there are appropriate times to use rehearsal strategies: when the knowledge or skills need to be used automatically and when the same signal or prompt will be used when that skill or knowledge is needed (Bransford, Brown, & Cocking, 1999; Hasselbring, Goin, & Bransford, 1987; Belmont & Butterfield, 1971; DeGroot, 1965). For instance, playing a musical instrument, driving a car, keyboarding, dribbling a basketball, and multiplying numbers as part of a larger mathematical problem require one to recall facts and procedures instantly, with no conscious reflection. Drivers who need to think through the physics of motion before they apply the brakes are dangerous. Applying brakes at the right time needs to be automatic.

Procedural knowledge is usually acquired through rehearsals. “‘I’ before ‘E’, except after ‘C,’ or when sounded like ‘A’ as in ‘neighbor’ and ‘weigh’” is a sentence that many of us learned in lieu of rehearsing every single word with adjacent “I’s” and “E’s.” And, silly as it seems, as a rule, it proves to be fairly effective. We could apply the rule in our writing until the spelling became automatic. Rehearsing this procedure allowed us to manage some fairly arbitrary spelling rules. Having math facts available to us automatically can be important in our consumer transactions, and they are essential in many negotiations in business. Of equal importance, automaticity of many skills is required for advanced learning in many fields (Beck, et al., 1991; Beck, McKeown, & Gromoll, 1989; LaBerge & Samuels, 1974).

Thus, if one wants to think that all learning involves the exhilaration of discovering new understandings about the universe, think again. Some essential parts of learning are about drill, diligence, and discipline.

For children, learning how to make your brain do what you want is empowering. Students who learn strategies, rather than just drills, for recalling information allow themselves to win twice: First, they remember what they need to know; second, they have strategies for the future (Brown & Campione, 1994, 1996; Linberg, 1980; Brown & DeLoache, 1978). Expert chess players, for instance, have an advantage because they rely upon recognizing the patterns of pieces on the board, not individual moves or the position of particular pieces (Bransford, Brown, & Cocking, 1999). Similarly, practice in recall that includes seemingly silly strategies can be applied in a variety of adult situations. Anyone over 40 would welcome a strategy for remembering the names of new acquaintances.

Relying exclusively, however, on rehearsals (i.e., practice, drill, and repetition without such strategies) can be a very time consuming way to teach and thus often inefficient. Moreover, only a limited part of what we want students to know and be able to do comes with the same signal or prompt in everyday life. So, educators should evaluate carefully how students will use the knowledge before relying solely on rehearsal of facts or procedures.

An early neuroscience experiment on memory (Craik & Tulving, 1975) sought to evaluate the effectiveness of various strategies that people used to remember things. The researchers considered three strategies: mnemonic, structural, and semantic. With mnemonic, people grouped the words they were to recall by sound: can, pan, ran, etc. For structural, participants grouped the words alphabetically. For semantic, words were grouped by meaning—say, all the animal names into one group, cooking utensils into another. Organizing words semantically proved to be the superior method. Thus, rates of memory are substantially better when words are grouped into categories with meaning.

Improving memory begins by improving understanding.

This experiment is one of many that points to one general finding: Improving memory begins by improving understanding. Thus, if you need to remember something for a long time, but it doesn’t need to be automatic, then understanding it (giving it meaning) is the best way to do it (Bransford, Brown, & Cocking, 1999; Schwartz, et. al., 1999; Brown & Day, 1984; Wertheimer, 1959).

In the cognitive sciences, the value of understanding in recall has long been in evidence. Katona’s classic studies from the 1960s, reported in Organizing and Memorizing (1967), provide some of the clearest evidence that if one understands a principle, one can remember it for a longer time than if one has merely memorized a procedure by repeating it numerous times.

Using card tricks, Katona conducted a series of experiments on long-term recall in an attempt to evaluate the efficacy of memorization versus understanding. He summarizes the issue quite succinctly:

Thus, research evidence is fairly clear: Nothing beats repetition, drill, and practice for those things one needs to do almost automatically long into our adulthood. When material is extended or complex, however, teaching for understanding is much more efficient—that is, our ability to remember is strong for a longer period of time with this method, and it takes less time to learn it than with rehearsal strategies.

In practice, MRSH encourages educators to individualize rehearsal activities, i.e., drill and practice. Establishing a learning environment that allows students to use computerized drill and practice customized to their specific weaknesses, or just flash cards and specifically designed games, is essential. Practice time should not only be individualized but also designed to fill slack time that usually occurs during the school day. Most of the class time that requires all students to focus on the same activity, on the other hand, should be devoted to interactions, presentations, and discussions that advance the understanding of concepts—where both long-term memory and the ability to use what we’ve learned are achieved.

Using what we’ve learned: Behaviorists conducted some of the first scientific research on learning in the early part of the 20^th Century. They began their work seeking to find out what types of rewards (or punishments) were most effective in creating desired response—and thus Pavlov’s famous dogs. Later, though, as they tightened their focus on human learning, they sought to figure out what types of stimulus brought the desired “response”—where the stimulus could be a question or a problem. They consistently failed to find evidence that people could transfer what they had learned in one context to a new situation. Their research showed that one needed to use the same stimuli to evoke the response, whether they were facts or procedures. So, for instance, a word problem used to evaluate mathematical knowledge needed to look quite similar to the problems students were given during instruction. In fact, some thought it was unfair to evaluate student learning unless the test used the same stimulus as that used when teaching a student (Cohen, 1987).

Not surprisingly, researchers and real folks did not find this a very satisfying outcome. That’s why research such as Katona’s was so important. After all, what’s the use in learning something if you are not able to apply it to new situations?

Thus, researchers began to focus on the problem of “transfer,” not only because adults who had learned many mathematical principles in formal schooling were seldom able to apply them in everyday life, but also because people who had never been to school developed some fairly sophisticated ways of counting things in daily life—yet, they, too, could not apply their strategies to new situations. Clearly, just learning about numbers in a “real life” situation would not create transfer any better than formal schooling (Scribner, 1990).

The process of transfer has analogies to a subject catalog at a library or a search engine for the Internet. In each case, a keyword or phrase should link us to relevant information. If the linkages in a catalog or search engine use only books (not journals, video, or other media) and only the titles of those books, a lot of relevant information is omitted. So a person interested in finding information about children’s health would discover only books that had those two words in the title. A good deal of information about children’s health would be left out. Similarly, our brains may supply only a few of the connections possible when asked to recall what we know about a topic. The stuff we forgot to include would be, to use the terminology of cognitive scientists, “inert” or inaccessible. And, what good does it do to know something if you can’t “call it up” when you need it?

Advocates of a constructivist approach to learning seek to address the problem of inert knowledge and, more generally, the challenges of teaching for understanding. Constructivists generally begin with the premise that each individual must construct his or her own meaning of concepts, linking prior knowledge to experiences with new concepts. Constructivists argue that learners should be actively engaged in authentic (or real-world) projects that allow them to acquire understandings that can be transferred to novel situations. Many teachers are encouraged to create real-world activities, such as a classroom store, to teach general principles of a discipline.

While it’s clear that the constructivist approach advances the cause of being able to apply what we know to new situations, research on teaching for application (or transfer) provides some cautionary tales. Simply providing students with experiences with “real life” situations where a concept is used is usually inadequate. Instead, such experiences must be combined with some approaches more commonly associated with the approach of behaviorists: Students need links with a bigger picture—some “teacher talk” that helps students make connections and organize the general principles evident in the specific application.

Research, then, shows that students need both of the approaches common to behaviorists and constructivists in order to be able to apply a concept to a new situation. Learning in a particular context needs to be generalized to a class of related problems with the similarities and differences articulated. For instance, if students are asked to design a playground, the experience needs to include more generalized reflection on the scientific principles used to design safe and enjoyable places for people. Then, students would be more able to apply the general principles to building, say, a shopping mall.

Good academic standards should help establish generalized principles that students need to learn from specific learning activities. And, good instruction requires that teachers help students make those connections.

An important fact must be kept in mind: When designing instruction that will enable students to apply what they’ve learned to new situations, the least effective method of instruction is one that merely teaches in one context or case (in fact, it can reduce students’ ability to transfer information). Just providing abstract principles is better, but learning those principles in multiple contexts is best (Bransford, Brown, & Cocking, 1999).

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