Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 351
How Students Learn: History, Mathematics, and Science in the Classroom 8 Teaching and Learning Functions Mindy Kalchman and Kenneth R. Koedinger This chapter focuses on teaching and learning mathematical functions.1 Functions are all around us, though students do not always realize this. For example, a functional relationship between quantities is at play when we are paying for gasoline by the gallon or fruit by the pound. We need functions for financial plans so we can calculate such things as accrued income and interest. Functions are important as well to interpretations of local and world demographics and population growth, which are critical for economic planning and development. Functions are even found in such familiar settings as baseball statistics and metric conversions. Algebraic tools allow us to express these functional relationships very efficiently; find the value of one thing (such as the gas price) when we know the value of the other (the number of gallons); and display a relationship visually in a way that allows us to quickly grasp the direction, magnitude, and rate of change in one variable over a range of values of the other. For simple problems such as determining gas prices, students’ existing knowledge of multiplication will usually allow them to calculate the cost for a specific amount of gas once they know the price per gallon (say, $2) with no problem. Students know that 2 gallons cost $4, 3 gallons cost $6, 4 gallons cost $8, and so on. While we can list each set of values, it is very efficient to say that for all values in gallons (which we call x by convention), the total cost (which we call y by convention), is equal to 2x. Writing y = 2x is a simple way of saying a great deal. As functional relationships become more complex, as in the growth of a population or the accumulation of interest over time, solutions are not so easily calculated because the base changes each period. In these situations,
OCR for page 352
How Students Learn: History, Mathematics, and Science in the Classroom algebraic tools allow highly complex problems to be solved and displayed in a way that provides a powerful image of change over time. Many students would be more than a little surprised at this description. Few students view algebra as a powerful toolkit that allows them to solve complex problems much more easily. Rather, they regard the algebra itself as the problem, and the toolkit as hopelessly complex. This result is not surprising given that algebra is often taught in ways that violate all three principles of learning set forth in How People Learn and highlighted in this volume. The first principle suggests the importance of building new knowledge on the foundation of students’ existing knowledge and understanding. Because students have many encounters with functional relationships in their everyday lives, they bring a great deal of relevant knowledge to the classroom. That knowledge can help students reason carefully through algebra problems. Box 8-1 suggests that a problem described in its everyday manifestation can be solved by many more students than the same problem presented only as a mathematical equation. Yet if the existing mathematics understandings students bring to the classroom are not linked to formal algebra learning, they will not be available to support new learning. The second principle of How People Learn argues that students need a strong conceptual understanding of function as well as procedural fluency. The new and very central concept introduced with functions is that of a dependent relationship: the value of one thing depends on, is determined by, or is a function of another. The kinds of problems we are dealing with no longer are focused on determining a specific value (the cost of 5 gallons of gas). They are now focused on the rule or expression that tells us how one thing (cost) is related to another (amount of gas). A “function” is formally defined in mathematics as “a set of ordered pairs of numbers (x, y) such that to each value of the first variable (x) there corresponds a unique value of the second variable (y).”2 Such a definition, while true, does not signal to students that they are beginning to learn about a new class of problems in which the value of one thing is determined by the value of another, and the rule that tells them how they are related. Within mathematics education, function has come to have a broader interpretation that refers not only to the formal definition, but also to the multiple ways in which functions can be written and described.3 Common ways of describing functions include tables, graphs, algebraic symbols, words, and problem situations. Each of these representations describes how the value of one variable is determined by the value of another. For instance, in a verbal problem situation such as “you get two dollars for every kilometer you walk in a walkathon,” the dollars earned depend on, are determined by, or are a function of the distance walked. Conceptually, students need to understand that these are different ways of describing the same relationship.
OCR for page 353
How Students Learn: History, Mathematics, and Science in the Classroom Good instruction is not just about developing students’ facility with performing various procedures, such as finding the value of y given x or creating a graph given an equation. Instruction should also help students develop a conceptual understanding of function, the ability to represent a function in a variety of ways, and fluency in moving among multiple representations of functions. The slope of the line as represented in an equation, for example, should have a “meaning” in the verbal description of the relationship between two variables, as well as a visual representation on a graph. The third principle of How People Learn suggests the importance of students’ engaging in metacognitive processes, monitoring their understanding as they go. Because mathematical relationships are generalized in algebra, students must operate at a higher level of abstraction than is typical of the mathematics they have generally encountered previously. At all levels of mathematics, students need to be engaged in monitoring their problem solving and reflecting on their solutions and strategies. But the metacognitive engagement is particularly important as mathematics becomes more abstract, because students will have few clues even when a solution has gone terribly awry if they are not actively engaged in sense making. When students’ conceptual understanding and metacognitive monitoring are weak, their efforts to solve even fairly simple algebra problems can, and often do, fail. Consider the problem in Figure 8-1a. How might students approach and respond to this problem? What graph-reading and table-building skills are required? Are such skills sufficient for a correct solution? If students lack a conceptual understanding of linear function, what errors might they make? Figure 8-1b shows an example student solution. What skills does this student exhibit? What does this student understand and not understand about functions? This student has shown that he knows how to construct a table of values and knows how to record in that table coordinate points he has determined to be on the graph. He also clearly recalls that an algorithm for finding the slope of the function is dividing the change in y(Δy) by the change in x(Δx). There are, however, significant problems with this solution that reveal this student’s weak conceptual understanding of functions. Problem: Make a table of values that would produce the function seen on page 356. First, and most superficially, the student (likely carelessly) mislabeled the coordinate for the y-intercept (0, 3) rather than (0, –3). This led him to make an error in calculating Δy by subtracting 0 from 3 rather than from –3. In so doing, he arrived at a value for the slope of the function that was negative—an impossible solution given that the graph is of an increasing linear function. This slip, by itself, is of less concern than the fact that the
OCR for page 354
How Students Learn: History, Mathematics, and Science in the Classroom BOX 8-1 Linking Formal Mathematical Understanding to Informal Reasoning Which of these problems is most difficult for a beginning algebra student? Story Problem When Ted got home from his waiter job, he multiplied his hourly wage by the 6 hours he worked that day. Then he added the $66 he made in tips and found he had earned $81.90. How much does Ted make per hour? Word Problem Starting with some number, if I multiply it by 6 and then add 66, I get 81.9. What number did I start with? Equation Solve for x: x * 6 + 66 = 81.90 Most teachers and researchers predict that students will have more difficulty correctly solving the story or word problem than the equation.4 They might explain this expectation by saying that a student needs to read the verbal problems (story and word) and then translate them into the equation. In fact, research investigating urban high school students’ performance on such problems found that on average, they scored 66 percent on the story problem, 62 percent on the word problem, and only 43 percent on the equation.5 In other words, students were more likely to solve the verbal problems correctly than the equation. Investigating students’ written work helps explain why. Students often solved the verbal problems without using the equation. For instance, some students used a generate-and-test strategy: They estimated a value for the hourly rate (e.g., $4/hour), computed the corresponding pay (e.g., $90), compared it against the given value ($81.90),
OCR for page 355
How Students Learn: History, Mathematics, and Science in the Classroom and repeated as needed. Other students used a more efficient unwind or working backwards strategy. They started with the final value of 81.9 and subtracted 66 to undo the last step of adding 66. Then they took the resulting 15.9 and divided by 6 to undo the first step of multiplying by 6. These strategies made the verbal problems easier than expected. But why were the equations difficult for students? Although experts in algebra may believe no reading is involved in equation solving, students do in fact need to learn how to read equations. The majority of student errors on equations can be attributed to difficulties in correctly comprehending the meaning of the equation.6 In the above equation, for example, many students added 6 and 66, but no student did so on the verbal problems. Besides providing some insight into how students think about algebraic problem solving, these studies illustrate how experts in an area such as algebra may have an “expert blind spot” for learning challenges beginners may experience. An expert blind spot occurs when someone skilled in an area overestimates the ease of learning its formalisms or jargon and underestimates learners’ informal understanding of its key ideas. As a result, too little attention is paid to linking formal mathematical understanding to informal reasoning. Looking closely at students’ work, the strategies they employ, and the errors they make, and even comparing their performance on similar kinds of problems, are some of the ways we can get past such blind spots and our natural tendency to think students think as we do. Such studies of student thinking contributed to the creation of a technology-enhanced algebra course, originally Pump Algebra Tutor and now Cognitive Tutor Algebra.7 That course includes an intelligent tutor that provides students with individualized assistance as they use multiple representations (words, tables, graphs, and equations) to analyze real-world problem situations. Numerous classroom studies have shown that this course significantly improves student achievement relative to alternative algebra courses (see www.carnegielearning.com/research). The course, which was based on basic research on learning science, is now in use in over 1,500 schools.
OCR for page 356
How Students Learn: History, Mathematics, and Science in the Classroom FIGURE 8-1 student did not recognize the inconsistency between the positive slope of the line and the negative slope in the equation. Even good mathematicians could make such a mistake, but they would likely monitor their work as they went along or reflect on the plausibility of the answer and detect the inconsistency. This student could have caught and corrected his error had he
OCR for page 357
How Students Learn: History, Mathematics, and Science in the Classroom acquired both fluency in interpreting the slope of a function from its equation (i.e., to see that it represents a decreasing function) and a reflective strategy for comparing features of different representations. A second, more fundamental error in the student’s solution was that the table of values does not represent a linear function. That is, there is not a constant change in y for every unit change in x. The first three coordinates in the student’s table were linear, but he then recorded (2.5, 0) as the fourth coordinate pair rather than (3, 0), which would have made the function linear. He appears to have estimated and recorded coordinate points by visually reading them off the graph without regard for whether the final table embodied linearity. Furthermore, the student did not realize that the equation he produced, , translates not only into a decreasing line, but also into a table of numbers that decreases by for every positive unit change in x. At a surface level, this student’s solution reflects some weaknesses in procedural knowledge, namely, getting the sign wrong on the y-intercept and imprecisely reading x-y coordinates off the graph. More important, however, these surface errors reflect a deeper weakness in the student’s conceptual understanding of function. The student either did not have or did not apply knowledge for interpreting key features (e.g., increasing or decreasing) of different function representations (e.g., graph, equation, table) and for using strategies for checking the consistency of these interpretations (e.g., all should be increasing). In general, the student’s work on this problem reflects an incomplete conceptual framework for linear functions, one that does not provide a solid foundation for fluid and flexible movement among a function’s representations. This student’s work is representative of the difficulties many secondary-level students have with such a problem after completing a traditional textbook unit on functions. In a study of learning and teaching functions, about 25 percent of students taking ninth- and eleventh-grade advanced mathematics courses made errors of this type—that is, providing a table of values that does not reflect a constant slope—following instruction on functions.8 This performance contrasts with that of ninth- and eleventh-grade mathematics students who solved this same problem after receiving instruction based on the curriculum described in this chapter. This group of students had an 88 percent success rate on the problem. Because these students had developed a deeper understanding of the concept of function, they knew that the y-values in a table must change by the same amount for every unit change in x for the function to be linear. The example in Figure 8-1c shows such thinking.
OCR for page 358
How Students Learn: History, Mathematics, and Science in the Classroom FIGURE 8-1 Problem: Make a table of values that would produce the function seen above. This student identified a possible y-intercept based on a reasonable scale for the y-axis. She then labeled the x- and y-axes, from which she determined coordinate pairs from the graph and recorded them in a table of values. She determined and recorded values that show a constant increase in y for every positive unit change in x. She also derived an equation for the function that not only corresponds to both the graph and the table, but also represents a linear relationship between x and y. How might one teach to achieve this kind of understanding? The goal of this chapter is to illustrate approaches to teaching functions that foster deep understanding and mathematical fluency. We emphasize the importance of designing thoughtful instructional approaches and curricula
OCR for page 359
How Students Learn: History, Mathematics, and Science in the Classroom that reflect the principles of How People Learn (as outlined in Chapter 1), as well as recent research on what it means to learn and understand functions in particular. We first describe our approach to addressing each of the three principles. We then provide three sample lessons that emphasize those principles in sequence. We hope that these examples provide interesting activi ties to try with students. More important, these activities incorporate important discoveries about student learning that teachers can use to design other instructional activities to achieve the same goals. ADDRESSING THE THREE PRINCIPLES Principle #1: Building on Prior Knowledge Principle 1 emphasizes the importance of students and teachers continually making links between students’ experiences outside the mathematics classroom and their school learning experiences. The understandings students bring to the classroom can be viewed in two ways: as their everyday, informal, experiential, out-of-school knowledge, and as their school-based or “instructional” knowledge. In the instructional approach illustrated here, students are introduced to function and its multiple representations by having their prior experiences and knowledge engaged in the context of a walkathon. This particular context was chosen because (1) students are familiar with money and distance as variable quantities, (2) they understand the contingency relationship between the variables, and (3) they are interested in and motivated by the rate at which money is earned. The use of a powerful instructional context, which we call a “bridging context,” is crucial here. We use this term because the context serves to bridge students’ numeric (equations) and spatial (graphic) understandings and to link their everyday experiences to lessons in the mathematics classroom. Following is an example of a classroom interaction that occurred during students’ first lesson on functions, showing how use of the walkathon context as an introduction to functions in multiple forms—real-world situation (walkathon), table, graph, verbal (“$1.00 for each kilometer”), situation-specific symbols ($ = 1 * km), and generic symbolic (y = x * 1)—accomplishes these bridging goals. Figures 8-2a through 8-2c show changes in the whiteboard as the lesson proceeded. Teacher What we’re looking at is, we’re looking at what we do to numbers, to one set of numbers, to get other numbers…. So how many of you have done something like a walkathon? A readathon? A swimathon? A bikeathon?
OCR for page 360
How Students Learn: History, Mathematics, and Science in the Classroom [Students raise their hands or nod.] So most of you… So I would say “Hi Tom [talking to a student in class], I’m going to raise money for such and such a charity and I’m going to walk ten kilometers.” Tom OK. Teacher Say you’re gonna sponsor me one dollar for every kilometer that I walk. So that’s sort of the first way that we can think about a function. It’s a rule. One dollar for every kilometer walked. So you have one dollar for each kilometer [writing “$1.00 for each kilometer” on the board while saying it]. So then what I do is I need to calculate how much money I’m gonna earn. And I have to start somewhere. So at zero kilometers how much money do I have Tom? How much are you gonna pay me if I collapse at the starting line? [Fills in the number 0 in the left-hand column of a table labeled “km”; the right-hand column is labeled “$”.] Tom None. Teacher So Tom, I managed to walk one kilometer [putting a “1” in the “km” column of the table of values below the “0”]…. Tom One dollar. Teacher One dollar [moving to the graph]. So I’m going to go over one kilometer and up one dollar [see Figure 8-2a]. FIGURE 8-2a Graphing a point from the table: “Over by one kilometer and up by one dollar.” The teacher uses everyday English (“up by”) and maintains connection with the situation by incorporating the units “kilometer” and “dollar.”
OCR for page 361
How Students Learn: History, Mathematics, and Science in the Classroom FIGURE 8-2b The teacher and students construct the table and graph point by point, and a line is then drawn. [Students continue to provide the dollar amounts for each of the successive kilometer values. Simple as it is, students are encouraged to describe the computation—”I multiply two kilometers by one to get two dollars.” The teacher fills in the table and graphs each coordinate pair. [The board is now as shown in Figure 8-2b.] Teacher Now, what I want you to try and do, first I want you to look at this [pointing to the table that goes from x = 0 to x = 10 for y = x] and tell me what’s happening here. Melissa You, like, earn one dollar every time you go up. Like it gets bigger by one every time. Teacher So every time you walk one kilometer you get one more dollar, right? [Makes “> 1” marks between successive “$” values in the table—see Figure 8-2c.] And if you look on the graph, every time I walk one kilometer I get one more dollar. [Makes “step” marks on the graph.] So now I want to come up with an equation, I want to come up with some way of using this symbol [pointing to the “km” header in the left-hand column of the table] and this symbol [pointing to the “$” header in the right-hand column of the table] to say the same thing, that for every kilometer I walk, let’s put it this way, the money I earn is gonna be equal to one times the number of kilometers I walk. Someone want to try that?
OCR for page 386
How Students Learn: History, Mathematics, and Science in the Classroom FIGURE 8-3 Sample computer screen. In this configuration, students can change the value of a, n, or b to effect immediate and automatic changes in the graph and the table. For example, if students change the value of b, just the y-intercept of the curve will change. If students change a or n to a positive value other than 1, the degree of steepness of the curve will change. If students change the value of a to a negative value, the curve will come down. All graphic patterns will be reflected in the table of values. Students must employ effective metacognitive strategies to negotiate and complete these computer activities. Opportunities for exploring, persevering, and knowing when and how to obtain help are abundant. Metacognitive activity is illustrated in the following situation, which has occurred among students from middle school through high school who have worked through these activities. When students are asked to change the parameters of y = x2 to make it curve down and go through a colored point that is in the lower right quadrant, their first intuition is often to make the exponent rather than the coefficient negative. When they make that change, they are surprised to find that the graph changes shape entirely and that a negative exponent will not
OCR for page 387
How Students Learn: History, Mathematics, and Science in the Classroom satisfy their needs. By trying a number of other possible alterations (persevering), some students discover that they need to change the coefficient of x2 rather than the exponent to a negative number to make the function curve down. It is then a matter of further exploration and discovery to find the correct value that will make the graph pass through the point in question. Some students, however, require support to discover this solution. Some try to subtract a value from x2 but are then reminded by the result they see on the computer screen that subtracting an amount from x2 causes a downward vertical shift of the graph. Drawing students’ attention to earlier exercises in which they multiplied the x in y = x by a negative number to make the numeric pattern and the graph go down encourages them to apply that same notion to y = x2. To follow up, we suggest emphasizing for students the numeric pattern in the tables of values for decreasing curves to show how the number pattern decreases with a negative coefficient but not with a negative exponent. Following is a typical exchange between the circulating teacher and a pair of students struggling with flipping the function y = x2 (i.e., reflecting it in the x-axis). This exchange illustrates the use of metacognitive prompting to help students supervise their own learning by suggesting the coordination of conclusions drawn from one representation (e.g., slope in linear functions) with those drawn from another (e.g., slope in power functions). Teacher How did you make a straight line come down or change direction? John We used minus. Teacher How did you use “minus”? Pete Oh yeah, we times it by minus something. Teacher So … how about here [pointing at the x2]? John We could times it by minus 2 [typing in x2 • -2]. There! It worked. Without metacognitive awareness and skills, students are at risk of missing important inconsistencies in their work and will not be in a position to self-correct or to move on to more advanced problem solving. The example shown earlier in Figure 8-1a involves a student not reflecting on the inconsistency between a negative slope in his equation and a positive slope in his graph. Another sort of difficulty may arise when students attempt to apply “rules” or algorithms they have been taught for simplifying a solution to a situation that in fact does not warrant such simplification or efficiency. For example, many high school mathematics students are taught that “you only really need two points to graph a straight line” or “if you know it’s a straight line, you only need two points.” The key phrase here is “if you know it’s a straight line.” In our research, we have found students applying
OCR for page 388
How Students Learn: History, Mathematics, and Science in the Classroom FIGURE 8-4 that two-point rule for graphing straight lines to the graphing of curved-line functions. In the example shown in Figure 8-4, an eleventh-grade advanced mathematics student who had been learning functions primarily from a textbook unit decided to calculate and plot only two points of the function y = x2 +1 and then to join them incorrectly with a straight line. This student had just finished a unit that included transformations of quadratic functions and thus presumably knew that y = x2 makes a parabola rather than a straight line. What this student did not know to perform, or at least exercise, was a metacognitive analysis of the problem that would have ruled out the application of the two-points rule for graphing this particular function. Summary of Principle #3 in the Context of Operating on y = x2. The general metacognitive opportunities for the computer activities in our curriculum are extensive. Students must develop and engage their skills involving prediction, error detection, and correction, as well as strategies for scientific inquiry such as hypothesis generating and testing. For instance, because there are innumerable combinations of y-intercept, coefficient, and exponent that will move y = x2 through each of the colored points, students must recognize and acknowledge alternative solution paths. Some students may fixate on the steepness of the curve and get as close to the colored points as possible by adjusting just the steepness of the curve (by changing either the exponent or the coefficient of x2) and then changing the y-intercept. Others may begin by selecting a manageable y-intercept and then adjust the steepness of the curve by changing the exponent or the coefficient. Others may use both strategies equally. Furthermore, students must constantly be pre-
OCR for page 389
How Students Learn: History, Mathematics, and Science in the Classroom dicting the shapes and behaviors of the functions with which they are working and adjusting and readjusting their expectations with respect to the mathematical properties and characteristics of linear and nonlinear functions. SUMMARY Sometimes mathematics instruction can lead to what we refer to as “ungrounded competence.” A student with ungrounded competence will display elements of sophisticated procedural or quantitative skills in some contexts, but in other contexts will make errors indicating a lack of conceptual or qualitative understanding underpinning these skills. The student solution shown earlier in Figure 8-1a illustrates such ungrounded competence. On the one hand, the student displays elements of sophisticated skills, including the slope formula and negative and fractional coefficients. On the other hand, the student displays a lack of coordinated conceptual understanding of linear functions and how they appear in graphical, tabular, and symbolic representations. In particular, he does not appear to be able to extract qualitative features such as linearity and the sign of the slope and to check that all three representations share these qualitative features. The curricular approach described in this chapter is based on cognitive principles and a detailed developmental model of student learning. It was designed to produce grounded competence whereby students can reason with and about multiple representations of mathematical functions flexibly and fluently. Experimental studies have shown that this curriculum is effective in improving student learning beyond that achieved by the same teachers using a more traditional curriculum. We hope that teachers will find the principles, developmental model, and instructional examples provided here useful in guiding their curriculum and teaching choices. We have presented three example lessons that were designed within one possible unifying context. Other lessons and contexts are possible and desirable, but these three examples illustrate some key points. For instance, students may learn more effectively when given a gradual introduction to ideas. Our curriculum employs three strategies for creating such a gradual introduction to ideas: Starting with a familiar context: Contexts that are familiar to students, such as the walkathon, allow them to draw on prior knowledge to think through a mathematical process or idea using a concrete example. Starting with simple content: To get at the essence of the idea while avoiding other, distracting difficulties, our curriculum starts with mathematical content that is as simple as possible—the function “you get one dollar for every kilometer you walk” (y = x).
OCR for page 390
How Students Learn: History, Mathematics, and Science in the Classroom Focusing on having students express concepts in their own language before learning and using conventional terminology: To the extent that a curriculum initially illustrates an idea in an unfamiliar context or with more-complex content, students may be less likely to be able to construct or invent their own language for the idea. Students may better understand and explain new ideas when they progress from thinking about those ideas using their own invented or natural language to thinking about them using formal conventional terms. A risk of simplicity and familiarity is that students may not acquire the full generality of relevant ideas and concepts. Our curriculum helps students acquire correct generalizations by constructing multiple representations for the same idea for the same problem at the same time. Students make comparisons and contrasts across representations. For example, they may compare the functions y = .5x, y = 2x, and y = 10x in different representations and consider how the change in slope looks in the graph and how the table and symbolic formula change from function to function. We also emphasize the use of multiple representations because it facilitates the necessary bridging between the spatial and numerical aspects of functions. Each representation has both spatial and numerical components, and students need experience with identifying and constructing how they are linked. As illustrated earlier in Figure 8-1a, a curriculum that does not take this multiple-representation approach can lead students to acquire shallow ideas about functions, slope, and linearity. The student whose response is shown in that figure had a superficial understanding of how tables and graphs are linked: he could read off points from the graph, but he lacked a deep understanding of the relationship between tables and graphs and the underlying idea of linearity. He did not see or “encode” the fact that because the graph is linear, equal changes in x must yield equal changes in y, and the values in the table must represent this critical characteristic of linearity. The curriculum presented in this chapter attempts to focus limited instructional time on core conceptual understanding by using multiple representations and generalizing from variations on just a few familiar contexts. The goal is to develop robust, generalizable knowledge, and there may be multiple pathways to this end. Because instructional time is limited, we decided to experiment with a primary emphasis on a single simple, real-world context for introducing function concepts instead of using multiple contexts or a single complex context. This is not to say that students would not benefit from a greater variety of contexts and some experience with rich, complex, real-world contexts. Other contexts that are relevant to students’ current real-world experience could help them build further on prior knowledge. Moreover, contexts that are relevant to students’ future real-world experiences, such as fixed and variable costs of production, could help them
OCR for page 391
How Students Learn: History, Mathematics, and Science in the Classroom in their later work life. Since our lessons can be accomplished in anywhere from 3 to 6 weeks (650 minutes), there is sufficient time for other activities to supplement and extend students’ experience. In addition to providing a gradual introduction to complex ideas, a key point illustrated by our lessons is that curriculum should be mathematically sound and targeted toward high standards. Although the lessons described here start gradually, they quickly progress to the point at which students work with and learn about sophisticated mathematical functions at or beyond what is typical for their grade level. For instance, students progress from functions such as y = x to y = 10 – .4x in their study of linear functions across lessons 1 to 3, and from y = x2 to y = (x – 2)2 + 4 in their study of nonlinear functions across lessons 4 to 8. We do not mean to suggest that this is the only curriculum that promotes a deep conceptual understanding of functions or that illustrates the principles of How People Learn. Indeed, it has important similarities, as well as differences, with other successful innovations in algebra instruction, such as the Jasper Woodbury series and Cognitive Tutor Algebra (previously called PUMP), both described in How People Learn. All of these programs build on students’ prior knowledge by using problem situations and making connections among multiple representations of function. However, whereas the Jasper Woodbury series emphasizes rich, complex, real-world contexts, the approach described in this chapter keeps the context simple to help students perceive and understand the richness and complexity of the underlying mathematical functions. And whereas Cognitive Tutor Algebra uses a wide variety of real-world contexts and provides intelligent computer tutor support, the approach described here uses spreadsheet technology and focuses on a single context within which a wide variety of content is illustrated. All of these curricula, however, stand in contrast to more traditional textbook-based curricula, which have focused on developing the numeric/ symbolic and spatial aspects of functions in isolation and without particular attention to the out-of-school knowledge that students bring to the classroom. Furthermore, these traditional approaches do not endeavor to connect the two sorts of understandings, which we have tried to show is an essential part of building a conceptual framework that underpins students’ learning of functions and ultimately their learning in related areas. ACKNOWLEDGMENTS Thanks to Ryan Baker, Brad Stephens, and Eric Knuth for helpful comments. Thanks to the McDonnell Foundation for funding.
OCR for page 392
How Students Learn: History, Mathematics, and Science in the Classroom NOTES 1. The study of functions, as we define it here, overlaps substantially with the topic of “algebra” traditionally taught in the United States in ninth grade, though national and many state standards now recommend that aspects of algebra be addressed in earlier grades (as is done in most other countries). Although functions are a critical piece of algebra, other aspects of algebra, such as equation solving, are not addressed in this chapter. 2. Thomas, 1972, p. 17. 3. Goldenberg, 1995; Leinhardt et al., 1990; Romberg et al., 1993. 4. Nathan and Koedinger, 2000. 5. Koedinger and Nathan, 2004. 6. Koedinger and Nathan, 2004. 7. Koedinger et al., 1997. 8. Kalchman, 2001. 9. Schoenfeld et al., 1993. 10. Schoenfeld et al., 1987. 11. Schoenfeld et al., 1998, p. 81. 12. Chi et al., 1981. 13. Chi et al., 1981; Schoenfeld et al., 1993. 14. Kalchman, 2001. REFERENCES Chi, M.T.H., Feltovich, P.J., and Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121-152. Goldenberg, E.P. (1995). Multiple representations: A vehicle for understanding. In D. Perkins, J. Schwartz, M. West, and M. Wiske (Eds.), Software goes to school: Teaching for understanding with new technologies (pp. 155-171). New York: Oxford University Press. Kalchman, M. (2001). Using a neo-Piagetian framework for learning and teaching mathematical functions. Doctoral Dissertation, Toronto, Ontario, University of Toronto. Koedinger, K.R., and Nathan, M.J. (2004). The real story behind story problems: Effects of representations on quantitative reasoning. Journal of the Learning Sciences, 13(2). Koedinger, K.R., Anderson, J.R., Hadley, W.H., and Mark, M.A. (1997). Intelligent tutoring goes to school in the big city. International Journal of Artificial Intelligence in Education, 8, 30-43. Leinhardt, G., Zaslavsky, O., and Stein, M. (1990). Functions, graphs, and graphing: Tasks, learning, and teaching. Review of Educational Research, 60(1), 1-64. Nathan, M.J., and Koedinger, K.R. (2000). Teachers’ and researchers’ beliefs of early algebra development. Journal for Research in Mathematics Education, 31(2), 168-190. Romberg, T., Fennema, E., and Carpenter, T.P. (1993). Integrating research on the graphical representation of functions. Mahwah, NJ: Lawrence Erlbaum Associates.
OCR for page 393
How Students Learn: History, Mathematics, and Science in the Classroom Schoenfeld, A.H. (1987). Cognitive science and mathematics education. Mahwah, NJ: Lawrence Erlbaum Associates. Schoenfeld, A.H. (1998). Reflections on a course in mathematical problem solving. In A.H. Schoenfeld, J. Kaput, and E. Dubinsky (Eds.), CBMS issues in mathematics education (vol. 7, pp. 81-99.) Washington, DC: Conference Board of the Mathematical Sciences. Schoenfeld, A.H., Smith J., and Arcavi A. (1993). Learning: The microgenetic analysis of one student’s evolving understanding of a complex subject matter. In R. Glaser (Ed.), Advances in Instructional Psychology (vol. 4, pp. 55-175). Mahwah, NJ: Lawrence Erlbaum Associates. Thomas, G.B. (1972). Calculus and analytic geometry. Reading, MA: Addison-Wesley. OTHER RELEVANT READINGS Bednarz, N., Kieran, C., and Lee, L. (1996). Approaches to algebra. Perspectives for research and teaching. Dordrecht, The Netherlands: Kluwer Academic Press. Confrey, J., and Smith, E. (1995). Splitting, co-variation, and their role in the development of exponential functions. Journal for Research in Mathematics Education, 26(1), 66-86. Janvier, C. (1987). Problems of representation in the teaching and learning of mathematics. Mahwah, NJ: Lawrence Erlbaum Associates. Kaput, J.J. (1989). Linking representations in the symbol systems of algebra. In S. Wagner and C. Kieran (Eds.), Research issues in the learning and teaching of algebra (pp. 167-181). Reston, VA: National Council of Teachers of Mathematics.
OCR for page 394
How Students Learn: History, Mathematics, and Science in the Classroom This page intentionally left blank.
OCR for page 395
How Students Learn: History, Mathematics, and Science in the Classroom Part III SCIENCE
OCR for page 396
How Students Learn: History, Mathematics, and Science in the Classroom This page intentionally left blank.