Chapter 2
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CHAPTER 2

REVIEW OF LITERATURE

    This chapter presents a review of the literature. The literature supported a qualitative study on the initial offering of the Advanced Placement (AP) Statistics course. Topics covered include theoretical construct, statistics education, AP statistics, technology in education, problem solving, and cooperative learning strategies.

Introduction

    The mathematics curriculum has remained unchanged over the last 50 years even though our society is constantly changing (Good, Murlyan, & McCaslin, 1992). Students graduating from high school today need the ability to reason and solve problems, communicate effectively by writing and speaking, and utilize technology in as many different ways as possible. Our society is more active and interactive than ever before. The demands of our current society mandates curricular change (AMATYC, 1995). To meet these demands, educators are moving from dispensing knowledge to facilitating active learning. Such a path shifts the focus on understanding rather than long, explicit derivations of meaningless mathematical results in a formal language (Cobb, 1997; Davis, 1992; Moore, 1997). Although students must develop basic mathematical skills, the processes, concepts, and understanding should take precedence (NCTM, 1989). When problem solving was integrated with active learning, deeper conceptual understandings were developed (AMATYC, 1995; NCTM, 1989). Also, AMATYC (1995) recommended that faculty provide a supportive learning environment and promote an appreciation of mathematics. In order to reflect that mathematics is an evolving, human endeavor, the way we teach and the way students learn needs to integrate interdisciplinary problem solving. According to Schoenfeld (1992) "problems can be related to real world experiences. But a more interesting aspect of problem solving involves finding patterns that can help understand the world around us" (p. 343).

Theoretical Construct

    Following Piaget’s influence, circa 1964, ideas and theories about learning changed (Ernest, 1996). Noddings (1990) described how researchers in various fields shifted from a behaviorist emphasis to a different learning theory. For example, some psychologists shifted their ontological position from behaviorism to a theory that connects cognitive activity and learning. This connection idea evolved into a learning theory called constructivism. More recently, mathematics educators and researchers applied constructivism to teaching and learning mathematics. Ernest (1996) stated that "constructivism is emerging as perhaps the major research paradigm in mathematics education" (p. 335).
    While details of this learning theory generated controversy and debate, most agreed on the basic premise that individuals constructed knowledge. Hatano (1996) suggested this construction of knowledge was unique, depending on the learners’ experiences, their ideas of reality, and their interpretation of these ideas. Therefore, each learner arrived with uniquely constructed mathematical ideas.
    Pedagogical implications were numerous and complicated. One aspect relevant to constructivist teaching was that learners constructed new knowledge by connecting new information to existing information (Cobb et al., 1990; Davis et al., 1990; Ernest, 1996; Hatano, 1996; Noddings, 1990; Shaughnessy, 1992; von Glasersfeld, 1992). If learners were expected to construct accurate ideas, teachers must consider each individuals’ preexisting cognitive structures and processes. One pedagogical goal, therefore, was to uncover students’ misconceptions and provide opportunities for them to construct (or reconstruct) sound mathematical concepts that incorporate their prior knowledge (Hiebert & Carpenter, 1992). However, creating pedagogical models that assisted students in correcting misconceptions and making these connections has been difficult. Rather than developing inflexible models reminiscent of behaviorism, constructivists have suggested pedagogical strategies that actively involve students in the learning process (Borasi, 1995; Cobb et al., 1990; Confrey, 1990; Davis et al., 1990; Ernest, 1996; Goldin & Kaput, 1996; Hatano, 1996; Hiebert & Carpenter, 1992; Noddings, 1990; Shaughnessy, 1992; von Glasersfeld, 1992).
    Adapting constructivist ideas to tangible teaching practices challenged educators. Researchers recommended a variety of ways to incorporate constructivist techniques into practical application. Goldin & Kaput (1996) discussed the importance of choosing problems and activities that represent the kinds of mathematical structures teachers want students to develop. They recommended students incorporate different types of mathematical thinking: connect mathematical meaning with respect to other domains, use appropriate skills and procedures, make abstract connections, and apply broad concepts to a smaller related set. Herscovics (1996) suggested that constructivist teachers present materials in a way that allowed students to "reconstruct, not reinvent" mathematical concepts (p. 375). He challenged teachers to remove the formal structure of mathematics that is frequently beyond students’ understanding. If a teacher could answer "What does it mean to understand" a given concept, he or she could work toward presenting the material in a way that conveys that meaning. Hatano (1996) also discussed practical implications of constructivist theory on teaching. He recommended that teachers allocate reasonable amounts of time on new information allowing students to reorganize existing structures. He argued that, even though connecting new ideas into existing thought patterns were time consuming, it was necessary if students were to construct accurate mathematical understandings. Overall, researchers agreed that teachers concerned with constructivist-based pedagogy should include activities, cooperative learning strategies, present mathematics as an interdisciplinary subject, and encourage students to use their individual skills and ideas.

A Model for Constructivist Teaching

    Confrey (1990) presented a model for constructivist-based teaching. The fundamental premise underlying the six components of her framework, was that "the skill the constructivist must truly develop is flexibility" (p. 108). She further suggested that the overall aim of a constructivist teacher is to provide opportunities for students to "develop their own cognition" (p. 110). This model was based on her belief that instruction should be designed to incorporate individual students’ views of learning. Her model required that the instructor attempt to understand the students’ background, viewpoint and misconceptions so he or she can assist the student in developing more accurate understandings.
    The first component of Confrey’s (1990) model involved students’ taking ownership of their own learning. She suggested that the instructor consistently require that students be responsible for their answers. She provided four techniques to help accomplish this task: ask students if they are right or wrong; require them to at least explain what they had attempted; act as a facilitator in problem solving; and involve students in assessing their own work. These techniques encouraged students to become aware of their thinking processes.
    As students learned to think about their own cognition, they developed reflective thought patterns. For the second element of her model, Confrey (1990) asserted that "reflection is the bootstrap for the construction of mathematical ideas" (p. 116). She presented three levels of questioning that focused on students’ awareness of their learning processes. First, the instructor asks students to rephrase or restate the problem. She explained that students cannot solve a problem until they identify what is actually being asked of them. Next, require the students to explain their work so the teacher could probe gaps in the individuals’ thinking. Guided by the teacher, students were led to reflect on their discrepancies and constructed appropriate connections. Last, after students have explained the procedure, they must defend their answer in a way that is consistent with their understanding of the problem and their procedure to produce the solution. Confrey believed this type of explanation required reflective processes.
    The third component of Confrey’s (1990) model pertained to the teacher’s ability to develop knowledge about the individual learners. To gain insight into the individual’s preconceived ideas, misconceptions, and thinking patterns, Confrey recommended that teachers work with students individually whenever possible. As teacher and student converse individually, the teacher can "try to aid the student in building a more powerful construction, from the student’s point of view" (p. 120).
    Confrey (1990) proposed "identification and negotiation of a tentative solution path" as the fourth component of her model (p. 120). She suggested, as teachers discover what was effective for one student, they attempted the same techniques with another student. However, these same techniques may not have been effective with another student and the teacher adapted to that individual’s ideas and thinking processes. She stated that the instructor must be flexible and resist rigid planning or structuring of what must occur in a given lesson. This may appear to lead to unreliable outcomes. However, the instructor can guide the discussions so that overall concepts are addressed.
    The fifth component involved reviewing the problem with the student. The purpose was to allow the student to reflect again, obtain overall understanding, and gain a sense of accomplishment. Confrey (1990) suggested this step is crucial for students to recognize future problems that might utilize similar solution processes.
    Last, the teacher must be committed to presenting the material in a rigorous manner. Using alternative ways to present and analyze concepts does not undermine what must be accomplished mathematically. Rather, alternative forms of instruction can provide opportunities for students to individually construct sound mathematical ideas.
    Overall, Confrey (1990) suggested that teachers focus on recognizing and understanding the individual’s ideas and thought processes that each student brings to the classroom. She outlined a model that provided a framework for the instructor to facilitate and direct discussion instead of lecture. The recommended techniques were designed to encourage students to take responsibility for their learning, become aware of what and how they learn, explain their course of action, and defend their answer. These techniques engaged students’ actively in the construction of their own mathematical learning.

Students’ Learning in a Constructivist Environment

    The learning theory of constructivism was student-centered. It emphasized the students’ individual view of reality, how they represented this view, and how they interpreted this view (Schoenfeld, 1992). Rather than attempting to transfer knowledge to learners, teachers focused on understanding the individuals’ ideas in order to assist them in constructing, or reconstructing, mathematical knowledge. Hatano (1996) asserted "that students construct mathematical knowledge by themselves can clearly be seen in procedural bugs and misconceptions" (p. 207). He further suggested these misconceptions evolve from their attempts to fit new ideas into existing, but conflicting, cognitive structures. Specifically, a misconception was invented by a learner as a result of trying to make sense of his or her limited experiences. Schoenfeld (1992) discussed how learning involved an overall context consisting of interlocking pieces. He stated that researchers have little understanding of how these pieces were constructed or how they were used to connect to each other. Borasi (1996) examined learning processes in constructivist environments. She concluded that students, with different abilities and backgrounds, who were taught mathematics in a constructivist manner were empowered to make mathematical connections.

Statistics Education

    As our world became more dependent upon technology and the application of rapidly changing information, statistics educators agreed that teaching statistics was increasingly more important (Cobb, 1992; Garfield, 1995; Moore, 1997; Shaughnessy, 1992). Statistics pervaded the American culture (Cobb, 1992). Citizens were bombarded with conclusions based on statistical analysis daily via the press. Corporations, all levels of government, and educational organizations made decisions based on the results of statistical studies. The increased use of statistics called for greater statistical understanding (Cobb, 1997; Moore, 1997; Shaughnessy, 1992). According the Shaughnessy (1992), whether we teach it or not, people will use and misuse statistics probably more than any other field of mathematics.
    Consistent with the current reform movement in mathematics education, statistics educators and researchers challenged teachers to examine their teaching practices. They recommended that teachers teach in a way that addresses different learning outcomes. Cobb (1992) suggested the goal in a statistics course was for students to emerge with the ability to read and understand statistics that are available in scientific publications, newspapers, and television. Shaughnessy (1992) wrote that all our students eventually become consumers and citizens in a society that uses statistics to communicate information and influence the masses. For educators, it was apparent the role and flavor of teaching statistics must reflect the challenges that society placed on our students and graduates (MAA, 1991; Velleman & Moore, 1996).
    Cobb (1997) suggested that a statistics course offers opportunities to investigate real world situations even though many courses fail to accomplish this. He further stated too many statistics courses were presented like traditional mathematics courses that stressed theory. He acknowledged that many teachers perceive that a "good" statistics course emphasized mathematical rigor rather than analytical thinking. However, researchers involved in statistics, envisioned statistics as a course in problem solving, rather than just traditional subject matter (Cobb, 1997; Garfield, 1995; Shaughnessy, 1992). Garfield (1995) described advantages of teaching from a problem solving perspective. If analysis was stressed, she claimed, then students learned that it was important to make claims, determine if their claims are appropriate, and defend their claims.
    Cobb (1997) suggested that statistical thinking was different from what was presented in traditional mathematical courses. Cobb and Moore (1997) explained that statistical analysis was always within context. Data were not just numbers, but numbers embedded within the context of a specific problem. Scheaffer (1992) expanded this and suggested that these contexts must be real to the students. He rejected the practice of investigating data from contrived textbook examples. He explained that for students to intelligently explore data, they do not need extensive knowledge of statistical methods, but rather, practice at deep analysis of legitimate, real world questions. Scheaffer’s reasoning was based on his belief that "the most important decisions in a student’s life will involve data. Thus it is initially important that students be taught to gather data intelligently and look carefully and critically at all data presented to them" ( p. 70). Cobb (1992) revealed a similar idea.

We believe students should appreciate how statistics is used in the endless cycle associated with the scientific method: we observe Nature and ask questions, we collect data that shed light on these questions, we analyze the data and compare them to what we previously thought, new questions are often raised, and on and on. This type of statistical thinking is central to education. (p. 36)

Other statistics teachers and researchers expressed the same idea that statistics courses should focus on data analysis and critical thinking using realistic questions (Hogg, 1992; Moore, 1997; Shaughnessy, 1992; Tukey, 1977; Velleman & Moore, 1996; Watkins et al., 1997). Overall, there was a consensus among statistics teachers and researchers that students must be exposed to analytical thinking in real world contexts.
    Even though statistical training was a necessary tool for reading and understanding information presented in day-to-day situations, many high school curricula did not include a statistics course. Those schools that did teach statistics, often presented it as a branch of mathematics emphasizing mathematical rigor and proofs rather than techniques of problem solving and analytical thinking. This emphasis on mathematical rigor often frustrated and alienated students (Gordon & Gordon, 1992; Willett & Singer, 1992). Therefore, in response to the growing demand for statistical literacy, the College Board implemented an AP Statistics course that utilizes a concept-oriented format.

AP Statistics

    The College Board recognized the growing interest in statistics education in college curricula and implemented an AP Statistics course in 1996-1997. The AP Statistics Test Development Committee, appointed by the College Board, recommended the inclusion of technology, projects and laboratories, cooperative group problem solving, and writing as a part of concept-oriented instruction and assessment. The Committee referred to concept-oriented instruction as a phrase to represent teaching strategies that "engage students in constructing their own knowledge" (College Entrance Examination Board, 1997, p. 10). These teaching strategies involved students in the learning process via activities.
    To incorporate activities into the classroom the Committee suggested that students gather data, interact with the data to create models, and generate and test hypotheses. The Committee further stipulated that as students participate in these activities, the teacher "serves in the role of a consultant, rather than a director" (p. 10). They stated two advantages of this pedagogical technique. First, when students gathered and analyzed their own data, they had the opportunity to think through problems, make decisions, and discuss their ideas with others. These first hand experiences allowed students to construct their own ideas and justify their processes by explaining their procedures. Second, these instructional strategies provided opportunities for students to make interdisciplinary connections to other academic subjects and with elements of the outside world (College Entrance Examination Board, 1997). Statisticians suggested that educators implement scenarios that emulate realistic interdisciplinary situations drawing on a variety of resources and connections to answer questions and solve problems (Cobb, 1997; Garfield, 1995; Moore, 1998; Shaughnessy, 1992). Moore (1998) explained that "statistics is by nature a methodological and interdisciplinary field that faces in many directions and interacts with many other professions and areas of study" (p. 10). The AP Statistics Test Development Committee acknowledged the changing role of statistics and developed a course whose foundation included concept-oriented instruction, active involvement of the students, and practical, interdisciplinary applications. Since the initial offering was in 1996-1997, there was no research available on the AP Statistics course.

Technology

    In the last 25 years, changes in technology have created a new learning environment for mathematics teachers and students. Not only have the speed and efficiency of computers and calculators increased dramatically, but also decreased prices have enabled more school systems and individuals to take advantage of modern equipment. For many educators, the increased availability of technology revolutionized the art of teaching mathematics and statistics (Cobb & Moore, 1997).
    The National Council of Teachers of Mathematics (NCTM; 1989), the Mathematical Association of America (MAA; 1991), and the American Mathematical Association of Two-Year Colleges (AMATYC; 1995) claimed that the use of technology was an essential part of an up-to-date curriculum. Due to the technology explosion in the 1980s and 1990s, more workers were expected to be mathematically literate (MAA, 1991). Simultaneously, more workers utilized computers or calculators. Supply and demand revolving around technology and statistics appeared to be circular. Mathematicians relied more on technology while the technical world increasingly expected people with greater mathematical skills and understandings. In addition to meeting the demands for this evolving aspect of our culture, technology could be utilized to explore, test hypotheses and discover patterns. Utilizing technology provided an opportunity for students to develop higher order thinking skills. AMATYC (1995) suggested that a mathematics classroom provided the natural and appropriate place for such learning to occur.
    Cobb (1992) suggested that technology could be used to enhance learning. He explained that computers and calculators present the information visually, allowing students to construct multiple representations. In addition, computers and calculators provided a vehicle for students to engage in exploratory data analysis (Cobb, 1992; Garfield, 1995; Moore, 1997; Scheaffer, 1992; Watkins et al., 1997). Tijms (1992) stated that the use of technology allowed students to explore, discover, and construct concepts on their own. He claimed that many fundamental concepts were difficult and students were more successful at understanding these ideas when they had direct experience and actual experimentation. Moore (1997) explained that using technology to perform automated calculations allowed teachers to focus on the conceptual components that were not automated. The MAA (1991) recommended the use of technology to "pose problems, explore patterns, test conjectures, conduct simulations, and organize and represent data" (p. 7). They explained that the exploration of mathematical ideas from different perspectives resulted in deeper mathematical understanding.
    Many statistics teachers recognized the abstraction of statistics and probability concepts. To help students understand these abstract ideas, computers and calculators simulated situations that displayed the inherent variation. Simulations could provide a tool for students to examine and discover solutions to problems whose variation is controlled by chance (MAA, 1991). However, Scheaffer (1992) cautioned that while simulations could lead students to stronger intuitive ideas about probability and statistics, the emphasis must remain on the mathematical concepts rather than the technological methods.
    Multimedia recently emerged as an option for technology-based instruction. A multimedia learning environment referred to using a computer, usually with a CD-Rom, to access text, sound, still images, video, animation, and computer simulations. Velleman and Moore (1996) discussed the advantages and disadvantages of implementing multimedia to teach statistics. The main advantages that multimedia offered were individualized instruction and simulations that engaged the learner actively. Students controlled the pace, repeated segments if necessary, and worked at their own convenience. However, Velleman and Moore (1996) also offered disadvantages. Video clips did not engage the learner actively. Spoken narrative, without interactive components attached, was likely to be ineffective. They expressed concern that students might not regard computer generated data as simulations of real world phenomena. Another disadvantage was the CD-ROM could not investigate students’ thinking nor probe misconceptions. However, Velleman and Moore (1996) stated that multimedia offered remarkable challenges and opportunities for teaching and learning statistics. No research was yet available on multimedia or its effects on students’ learning.
    Technology played a large role in the AP Statistics course. The Test Development Committee recommended the use of calculators, computers, and simulations (Watkins et al., 1997). They required the use of a graphing calculator for the AP Statistics exam. While they believed that computer utilization was a critical part of statistical analysis, the Committee recognized that all students did not have equal access to computers. Therefore, generic computer output was provided on the exam. Students were expected to be able to read, interpret, and analyze this output.
    Researchers no longer recommended that students memorize long, detailed formulas and compute laborious calculations (Borasi, 1995; Cobb, 1997; Davis, 1990; Dunham, 1994; Garfield, 1995; Hatano, 1996; Hoek, 1997; Konold, 1995; Moore, 1997; NCTM, 1989; NRC, 1989; Shaughnessy, 1992). Consistent with a shift in emphasis, statistics emerged as a flexible and creative course that utilized mathematical reasoning in order to analyze data. Students could interact with data to formulate, analyze, and alter a model more efficiently by using technology. While teachers facilitated the investigations, students individually explored realistic situations, constructed hypotheses, tested hypotheses, and made conclusions. By utilizing computers or calculators, data analysis actively involved students and provided a classroom environment where speculation and conversation were appropriate and appreciated. Constructivists recommended allowing students to investigate topics of their own interest and explore data using technology (Cobb et al., 1990; Confrey, 1990; Davis, 1990; Dunham, 1994; Schoenfeld, 1992; Shaughnessy, 1992).

Problem Solving

    One goal for mathematics educators was to teach students how to think, reason, and solve problems (AMATYC, 1995; NCTM, 1989; NRC, 1989). Although it was necessary to learn mathematical procedures, it was important for students to progress beyond the level of rote memorization and traditional textbook examples. Problem solving served as means for developing new skills, including reasoning, while practicing techniques. AMATYC (1995) wrote that

More emphasis should be placed on developing student understanding of concepts, helping them make connections among concepts, and building their reasoning skills in preparation for higher-level courses in mathematics and related fields. (p. 36)

Meaningful learning connected existing knowledge to new information. The challenge for educators was to provide experiences that facilitate this process (Cobb & Moore, 1997). Understanding occurred as learners integrated new and old information by making connections in a variety of ways (Brown & Borko, 1992; Hiebert & Carpenter, 1992). Effective pedagogical techniques presented new content so students could reason and relate it to what they already knew.
    Developing reasoning abilities was only one advantage of using problem solving techniques. Mathematics programs needed to provide an environment where students saw mathematics as an enriching and empowering discipline (AMATYC, 1995). Textbook examples were frequently uninteresting and out of date. How could students appreciate mathematics when it was only illustrated using rote memorization and manipulation of formulas that have no personal meaning? Mathematics could be presented using problem solving techniques related to history, sociology, business and other seemingly non-mathematical fields. Students could come to see mathematics as a broad, overlapping discipline that affects many aspects of life. If educators expect students to appreciate mathematics, instructors must move away from exercises that have no meaning, move away from artificial problems with "the right answer," and move toward the idea that mathematics is a process. As previously stated in this chapter, statistics is a discipline that easily incorporates problem solving, active involvement that assists students in developing reasoning skills, and interdisciplinary situations that allows students to see mathematics at work in their daily lives.

Cooperative Learning Strategies

    Consistent with constructivist theory, Lambert (1995) claimed students construct knowledge through classroom interaction. Small group instruction was a strategy frequently recommended to engage learners actively (Garfield, 1995; Good et al., 1992; MAA, 1991; NCTM, 1989).
    Noddings (1990) asserted that cooperative learning strategies provided the opportunity to achieve several goals. Allowing students to verbalize their own mathematical thoughts provided a unique learning opportunity. The MAA (1991) recommended that students respond to questions that encouraged conversation among students. Cobb (1992) suggested that students constructed deeper understandings when placed in small groups where they could "argue convincingly for their approach among conflicting ideas and methods" (p. 25). Lochhead (1991) connected group work to constructivist learning. He stated that group discussions allowed students to construct, evaluate, and modify their ideas. Noddings (1990) suggested that students also gained from others’ thought processes. When one student explained an idea to another student, both participants benefitted from the interaction. Sometimes students presented invalid arguments and the group assisted this individual reach more sound, mathematical justifications. Adams and Hamm (1996) concluded that students learned to assimilate new information and create new knowledge by interacting with others.
    Another advantage to group problem solving was that students could solve more difficult problems than they would be able to solve on their own (Good, Reys, Grouws, & Mulryan, 1989; Lambert, 1989). Borasi (1996) found that communication among students was a crucial component of group projects that were designed to expand students reasoning abilities. Velleman and Moore (1996) suggested that "students learn by participating in group discussions and cooperative problem solving" (p. 218). They explained that discussion, where students apply their knowledge to difficult and complicated scenarios, encouraged "higher order learning" (p. 218). Hoek (1997) concluded that students who received an experimental program that stressed cognitive strategies within cooperative groups scored higher on the Mathematical Reasoning Ability test. Brush (1996) also concluded that students who used cooperative strategies during mathematical instruction performed better on standardized tests. Researchers suggested that small group activities provided opportunities for students to construct deeper understanding by solving more complicated problems.
    Watkins et al. (1997) suggested that students did not appreciate the intricate details of statistical analysis until they encountered these details in realistic situations. Group projects could provide opportunities for students to experience statistical analysis. Watkins et al. (1997) recommended that AP Statistics students work in small groups to collect and analyze data. Group projects provided opportunities for students to discuss ideas, decisions and conclusions with other students and the instructor.

Summary

    This chapter presented a review of the literature. Based on the constructivist theory of learning, many educators advocated actively involving students in the learning process. The AP Statistics Test Development Committee recommended the use of technology, projects and cooperative group strategies, and assessment that incorporates writing. Statistics educators suggested using computers and calculators to facilitate students’ interaction with data. Active involvement could also be accomplished with projects, group problem solving, and technology-based simulations. No research had been conducted on the AP Statistics course. The next chapter presents the methodology for a qualitative study that investigated students’ learning in an AP Statistics course.