on the cultural, cognitive, language and literacy development of this vulnerable In other words, the gaps decrease in relation to the norming population. To capture the relationship between culture, cognition and language and the meanings produced by adult students in literacy process, we adopt ethnography as. Language and literacy in the context of brain, cognition, and culture One of the oldest debates in psychology is about the relationship.
Considerable progress has been made over the last two decades in understanding the nature and processes of learning and acquiring knowledge of specified content information. This research has, for the most part, not concerned itself with issues of language per se, nor has it been incorporated into discussion about English-language learners. There are some notable exceptions, however.
For example, research reviewed in Cocking and Mestre and discussed later in this chapter examines linguistic and cultural influences on learning mathematics. Fuson and Secada's study of particular mathematical topics and student learning extends our sense of the complexity of mathematical thinking and helps us interpret the teaching task with greater awareness.
Work by Rosebery et al. We refer to the body of research that we review as "primary-language content learning. Expanding the systematic study of some of these issues to include English-language learners will inform and expand the theory as well. The general perspective here is that of cognitive psychology. Cognitive theory, borrowing from the pioneering work of Piaget, provides educators a way of combining constructivism with systematic deep analyses of subject matter Page 64 Share Cite Suggested Citation: Cognitive analyses help reveal with special clarity a level of complexity in teaching and learning in subject areas.
But cognitive psychology and cognitive science cognitive psychology plus linguistics, philosophy, and artificial intelligence also suggest a level of complexity in teaching and learning not anticipated by Piagetians, behaviorists, or even activity theorists Cobb, ; Bruer, ; Resnick and Klopfer, ; Greeno and Simon, ; Simon and Kaplan, ; Wertsch, Empirical research on teaching and learning has paralleled the evolution of educational theory Bruer, As educational theory has expanded, so have the kinds of research questions posed.
Most recently, research questions influenced by cognitive theory have focused on the relationship between structure of knowledge, meaning organization, and representations of tasks and resources: How does the structure of prior mathematical knowledge and representation influence student thinking about decimals Heibert, ? How do students juggle the multiple layers and constraints of geographical notation to reason with and from a map Gregg, ?
How does self-explanation influence students' understanding and mental models of the circulatory system Chi et al.
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How do groups of students jointly construct effective explanations Leinhardt, ? Seeking answers to these kinds of subject matter questions, as well to questions concerned with language acquisition and development, may generate important insights concerning the education of second-language students.
Thus we suggest a program of research with second-language learners and their teachers that is extended to include cognitive approaches to subject matter learning, knowledge, and understanding. Because the ''problem" for the English-language learner has been considered as almost entirely language-based, much of the research has focused on language acquisition issues. But learning school subject matter and work skills involves building intricate networks of concept relations, structuring and restructuring understandings, connecting them to other understandings, and practicing multiple skills in multiple environments.
Therefore, more complex questions might fruitfully be asked about the nature of second-language students' learning, knowledge, and understanding of complex subject matter domains.
Discussion of complex questions of subject matter learning for English-language learners needs to be grounded in some assumptions about learning in general. The remainder of this section describes three assumptions drawn from cognitive analyses about school subject matter learning for primary-language content learning. These assumptions are context for much of the current research on school learning and apply to most students and most subject matter domains.
First, we assume that different subjects have different core structures or epistemologies, thus making different demands on the learner.
Third, we assume that prior knowledge plays a significant role in learning, not only in terms of where to start, but also in terms of the actual meanings attached to new information. Subject Matter Specificity Learning, knowledge, and understanding differ across subject matter. But these differences in subject matter are embedded in larger general similarities. Understanding, learning, and teaching earth science or social studies require the general ability to read English, to construct meaning, and to understand and follow spoken discussion.
They also require general capabilities of inferencing, placing examples into overarching constructs, and building causal chains. We now review several examples from the primary subject matter domains of mathematics, science, and history.
Analyses of mathematical learning and teaching have covered a variety of topics, from the earliest studies of counting Briars and Siegler, ; Gelman and Meck,to models of addition and subtraction Carpenter and Moser, ; Fuson, ; Resnick, ; Riley et al. These studies have extended our sense of the complexity of mathematical thinking and helped us interpret and undertake teaching tasks with greater awareness.
Research on buggy algorithms Brown and VanLehn, shows that these errors are quite systematic and can be used generatively to understand the student's mental model that produces a procedural bug.
In a very different kind of work, Lampert shows that to understand long-division problems, the student must grasp an underlying principle that includes fundamental multiplicative relationships. First, given a specific number of groups or peoplehow many belong in each group for a fixed number of items?
For example, with 6 people and 48 apples, how many apples go to each person? Second, given a specific number per group, how many groups can be formed for a fixed number of items? For example, with 8 people per minivan and 48 people, how many minivans are needed? In the first case, the divisor 6 people is a quantity, while the quotient is an intensive quantity 8 apples per person. In the second case, the divisor is an intensive quantity 8 per vanwhile the quotient is a quantity 6 vans.
Both questions make use of the same algorithmic system to solve the problem, namely division, and both are part of the system of multiplicative structures.
This consistency characterizes the efficiency of the mathematical discipline. Page 66 Share Cite Suggested Citation: Therefore, the efficiency of the algorithmic system may not be visible to all students, and the means of making the distinction visible must be developed with consideration for both linguistic and cultural issues.
Parallel research in science education exemplifies the epistemological differences among disciplines.
Language development and literacy
Theories are fundamental to science. The task of learning science is, in part, to understand those theories deeply enough to be able to map them to extant data in order to explain a particular phenomenon Ohlsson, Because of the disciplinary significance of theory, considerable educational research has been devoted to issues surrounding scientific theories, such as the difference between cohesive and fragmented intuitive scientific theories diSessa,systems of errors McKlosky,models of expert scientific problem solving Chi et al.
One aspect of the study of science that can be especially difficult for students is the deceptive simplicity of many of the theories. Take, for example, the principle of acceleration: The formula and theory seems simple at first glance.
However, in detailing how one determines the acceleration of any particular object, Reif shows the solution path as a progression through five separate substeps8 and points out that "substantial complexities [are] hidden in the declarative specification of the problem …[and that] even some of the individual steps of the procedural specification involve complex sub-processes" pp.
What might start out as a simple "plug the number into the formula" problem turns into a multilayered, means-end solution path, misleading students with its false impression of simplicity. History, as taught, usually lacks 8These steps include 1 find the velocity of the particle at time t, 2 find the velocity of the particle at a slightly later time t', 3 find the change in velocity, 4 find the ratio of velocity to time, and 5 repeat the calculations until the ratio approaches a limiting value that is constant.
Page 67 Share Cite Suggested Citation: When asked to recall salient information from such texts, students tend to construct erroneous connections among the facts presented in an effort to make them coherent. McKeown and Beck found that if the texts were revised so less was presumed about the students' knowledge of the material i.
The point of the above discussion has been to emphasize the fundamental epistemological differences among subject matters. These differences necessitate highly differentiated systems of complex knowledge for both students and their teachers.
While it is clear that at some level of abstraction, generalities across subject areas do exist, we believe these generalities are not sufficient to leapfrog the middle ground of differentiated knowledge.
Further, we suggest that a better understanding of this middle ground can enhance our understanding of the nature of both primary-language content learning and content learning in a second language.
In light of the epistemological distinctions among the various subjects, it may be that certain disciplines lend themselves more easily to the transfer of knowledge across languages, depending on the structure of knowledge within the domain, but the particular domains to which this would apply to are not readily apparent. For example, it would appear at first glance that mathematics knowledge should be readily transferable from language to language.
However, in light of the long-division example cited above and research in this area Cocking and Chipman, ; Myers and Milne,we can see that some of the deepest principles of a particular domain e. We have asserted that there are substantial differences among subject matter areas. For the most part, studies of English-language learners and their teachers seem to have ignored these distinctions, identifying a central problem facing these students as learning enough general language to enter mainstream classrooms.
Smoothing allows visualization of relationships between variables without making assumptions about the shape of the relationship.
We examined raw cognitive test scores by literacy tertiles. Chi-square tests for trend were performed to determine whether cognitive test scores changed in an incremental manner over literacy tertiles. We performed a series of linear regression analyses to evaluate relationships among literacy, education, and cognitive function: Results are reported as the increase in z-score per 10 words pronounced and per 5 years of education.
We performed additional analyses to determine whether our results were affected by age, sex, native language, or health-related covariates such as alcohol consumption, smoking, depression, or medical conditions.
We also performed a series of sensitivity analyses to determine whether our results differed among subgroups of the study population. Results Table 1 shows the characteristics of the study participants.
Ninety-two percent had 12 or more years of education. Study participants in the lowest, middle, and highest literacy tertiles pronounced a mean of 26 words range, 7—3339 words range, 34—44and 50 words range, 45—60 correctly, respectively. Cognitive test scores increased progressively with literacy tertile for all measures Table 2.
For example, study participants in the lowest, middle, and highest literacy tertiles scored In addition, the strength of the relationship between literacy and cognitive function was remarkably consistent across cognitive domains Figure 1. Smoothed graphs revealed that the association between literacy and cognitive function was linear for all cognitive measures Figure 2. For example, MMSE scores increased by approximately 0. However, when we considered literacy and education together in the same linear regression models, literacy was strongly associated with all 8 cognitive measures, whereas education was weakly associated with 3 measures and not associated with 5 measures.
These findings were unchanged by further adjustment for age, sex, native language, depression, and medical diagnoses Table 3. Our findings were similar in different subgroups of the study population e. In all subgroups, literacy was strongly associated with all measures of cognition in both unadjusted and adjusted analyses, whereas education was no longer associated with most cognitive measures after adjustment for literacy. Discussion We found that elderly persons with higher literacy scores performed better on all measures of cognition.
The association between literacy and cognition was linear, was largely unchanged by adjustment for years of education and other covariates, and was consistent across different subgroups of the cohort.
Our elderly participants with higher levels of education also performed better on most cognitive measures. However, when we included both literacy and education in the same statistical models, cognitive scores were associated much more strongly and consistently with literacy than with education. Our results are consistent with those of several previous studies that evaluated the relationship between literacy levels and measures of global cognitive function 9—1224 or intelligence 67.
Our results extend the findings of previous research to show that the relationship between literacy and cognitive function is present at higher literacy levels and is consistent across multiple cognitive domains. There are several possible explanations for the association between literacy and cognitive function.
The association could be a test bias, in which elderly persons with higher literacy levels perform better on cognitive tests because they are more adept at taking tests in general. However, we believe this is unlikely because our study population did not include any persons who were illiterate, and most study participants had graduated from high school.
Furthermore, our results were similar when we restricted our analyses to persons with 16 or more years of education i. Presumably, a test bias would be minimized in elders with high levels of education. Literacy also could reflect a person's innate level of cognitive ability or the effect of early life exposures and educational experiences. Previous studies have found that better mental ability at age 11 years 25 and more complex sentence structure at age 22 years 26 are associated with a reduced risk for dementia.
Alternatively, literacy could be causally associated with better cognitive function or could be a marker of other causal factors. For example, reading and writing could lead directly to enrichment of neural networks, which could enable persons with higher levels of literacy to have larger cognitive reserves and to process cognitive information more efficiently 3.
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