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CHAPTER 4
RESULTS
This research was an investigation of the initial offering of the
Advanced Placement (AP) Statistics course and students learning within this concept
oriented statistics class. Qualitative research methods were employed to describe the
genesis of the course and to investigate ideas students developed in a
concept-oriented classroom. Constructivism was the learning theory for the study
(Guba
& Lincoln, 1994).
This chapter reports analysis of the data. The researcher gathered data
to investigate the initial offering of the AP Statistics course and the effect of
concept-oriented instruction on students development of statistical ideas. Data
sources for the study included various materials relevant to this initial offering of the
AP Statistics course and two AP Statistics classes taught by the same instructor during
the first year (1996-1997). Information relevant to the initial offering included College
Board publications, interviews with Test Development Committee members, comments by other
teachers involved with the AP Statistics course and exam, Educational Testing Service
(ETS) AP test results, and interviews with the instructor. Two classes taught by the same
instructor contained 31 students. Data came from student artifacts gathered from bimonthly
project reports, test papers, audio taped project presentations, student interviews, and
field notes. Immediately following the administration of the nationwide AP Statistics
exam, 12 students were interviewed and audio taped individually
while discussing topics relating to the instructor, their specific class, and the AP exam.
Analysis of the data is presented using excerpts from all sources. Questions addressing
the initial offering of AP Statistics course precede discussion about the research site
for this specific academic year. When addressing questions about students learning,
I investigated patterns based on race, gender, and mathematical abilities. All student
writing quoted in this paper is unedited. Pseudonyms are used for all participants. As the
researcher, I was the primary research instrument. The research questions were:
1. What are the salient features of the AP Statistics course and the genesis of these
features?
2. What teaching strategies are effective in implementing the recommended pedagogy?
3. What effects do projects that employ cooperative group problem solving and writing
have on students development of statistical concepts?
4. How does gathering data effect students understanding of statistics?
5. What components of activity-based, concept-oriented instruction effect
students performance on the AP exam?
The Initial Offering of the AP Statistics Course
The first research question, regarding the salient features of the
AP Statistics course and the genesis of these features, emerged from the study. I
originally intended to focus only on student learning within a concept-oriented course.
However, as the year progressed and I became more involved in the overall AP experience, I
realized that a holistic description of the course could contribute to the study.
Therefore, in order to describe the course and its genesis, I researched a variety of
sources. I obtained pamphlets and booklets on AP Statistics published by the College Board
(see Appendix E). I selected the final member of my dissertation committee because he was
involved in the planning, development, and implementation of the initial offering of the
AP Statistics course. I corresponded with several other people who had been involved with
the creation of the course and the administration of the first exam: Richard L.
Scheaffer,
the Chief Faculty Consultant (CFC), members of the Test Development Committee, and Table
Leaders from the Reading. I subscribed to the AP Statistics listserv and printed relevant
comments. In addition, I referred to the listservs archives when necessary.
The AP Program
The Advanced Placement Program began in the early 1950s in response
to a concern within the educational community to provide appropriate courses for talented
high school students (Watkins et al., 1997). In 1954, the College Entrance Examination
Board voted to implement the AP Program. The College Board enlisted the Educational
Testing Service (ETS) to develop, administer, and grade the examinations. During these
first years, there were 11 courses available. By 1987, there were 15 courses offered.
Today, many subjects have more than one examination. In 1997, the following examinations
were offered: Art: History, Studio--General Portfolio, Studio--Drawing Portfolio; Biology;
Chemistry; Computer Science; English: Language and Composition, Literature and
Composition; French: Language, Literature; German Language; Government and Politics:
American, Comparative; History: American, European; Latin: Vergil, Catullus-Horace;
Mathematics: Calculus AB, Calculus BC; Music: Listening and Literature, Theory; Physics:
B, C-Mechanics, C-Electricity and Magnetism; Spanish: Language, Literature; and
Statistics.
AP Statistics
In the 1980s, officials at the College Board and ETS were concerned
that many students were not enrolling in a mathematics class in 12th grade. The AP
Statistics course evolved as a result of this interest in expanding AP offerings in
mathematics. Initial suggestions, as early as 1980, received little interest. At the
request of the Advanced Placement Calculus Test Development Committee, ETS and the College
Board conducted a feasibility study in 1987 to examine what course might be successful.
Questionnaires went to mathematics department chairs at 300 colleges and universities that
received AP Calculus scores in 1986 (Armstrong & Jones, 1987). Questions asked college
officials if they would grant credit and/or placement in multivariable calculus,
elementary statistics, discrete mathematics, applied matrix algebra, or linear algebra.
Questionnaires were also sent to 841 secondary school mathematics department chairs to
determine if they had an interest in offering an additional AP mathematics course
(Armstrong & Jones, 1987). ETS received and analyzed responses from 212 colleges and
541 schools. As a result of the first questionnaire, the second study targeted a
statistics course. Sixty-six out of 105 colleges surveyed indicated they would offer
credit and 72 out of 105 said they would offer placement for an AP Statistics course.
Therefore, the AP Statistics Task Force (1992) recommended that the College Board
implement an AP Statistics course in the 1995-96 academic year (Advanced Placement
Statistics Task Force, 1992). The Test Development Committee in Statistics was formed to
devise course materials and write the AP exam. The 1995-96 Test Development Committee in
Statistics consisted of the following: Rosemary A. Roberts, Bowdoin College, Brunswick,
Maine, Chair; Fred C. Djang, Choate Rosemary Hall, Wallingford, Connecticut; Kinley
Larntz, University of Minnesota, St. Paul; Christopher R. Olsen, George Washington High
School, Cedar Rapids, Iowa; Diann C. Resnick, Bellaire Senior High School, Texas; Richard
L. Scheaffer, University of Florida, Gainesville; Walter O. Walker, Eckerd College, St.
Petersburg, Florida; and Ann E. Watkins, California State University, Northridge. ETS
Consultants were James S. Armstrong, Jeffrey G. Haberstroh, and Michael A.
Ponisciak.
According to Jeff Haberstroh, of ETS, most committee members serve 3 or 4 years. In
1996-97 Kinley Larntz was replaced by two members: Daniel Teague, North Carolina School of
Science and Mathematics, Raleigh; and Jessica Utts, University of California-Davis, Davis.
The current committee (1997-98) lost Rosemary Roberts and added the following: Katherine
Halvorsen, Smith College, Northampton, Maine; and Roxy Peck, California Polytechnic
University-San Luis Obispo, California. As of June 1998, Ann Watkins is serving as the
chairperson. At the conclusion of the 1998 AP Reading, Roxy Peck replaced Richard L.
Scheaffer as the Chief Faculty Consultant.
In the AP Statistics Course Description, the Test Development Committee
provided recommendations to determine whether this course is appropriate for a student.
"The AP Statistics course is an excellent option for any student who has successfully
completed a second-year course in algebra," they suggested, "regardless of the
students intended college major" (College Entrance Examination Board, 1997, p.
2). With second-year algebra as the prerequisite course, students would most likely enroll
in AP Statistics as a junior or senior. Strong mathematical students could take this
course simultaneously with AP Calculus or AP Computer Science. Other students could choose
to take AP Statistics in lieu of precalculus or AP Calculus. The Test Development
Committee, however, recommended that any student interested in taking calculus in college
should complete precalculus in high school (College Entrance Examination Board, 1997).
The AP Statistics Test Development Committee provided an outline of the
course content (see Appendix F). This outline was published in the Advanced Placement
Course Description: Statistics (College Entrance Examination Board, 1997). The topics
were divided into four major themes: exploratory data analysis, planning a study,
probability, and statistical inference (College Entrance Examination Board, 1997).
Exploratory analysis included the use of graphs and summary statistics to determine
patterns and exceptional cases in data. Planning a study entailed posing or clarifying a
research question, providing details of data collection, and a method of analysis.
Probability was used to examine patterns of data and as a link to inference. Statistical
inference involved drawing conclusions from samples and making predictions about
populations.
The First AP Statistics Examination
On May 6, 1997, the first AP Statistics exam was administered
worldwide. Seven thousand, six hundred sixty-nine students sat for this exam. It consisted
of 35 multiple choice (MC) questions, five free response questions (FR), and one
investigative task (IT). The MC section was 90 minutes. The MC questions were equally
weighted and counted as half the total AP grade. MC questions were graded with a
correction factor to compensate for random guessing (College Entrance Examination Board,
1997). The FR and IT were combined in a 90-minute session. The FR was 3/8 and the IT 1/8
of the total AP grade. Grading of FR and IT questions followed a holistic rubric (see
Appendix G). According to Watkins, et al. (1997), "the response will be considered as
an entire package. Note that there are two aspects to the scoring: statistical knowledge
and communication of that knowledge" (p. 57). The Chief Faculty Consultant combined
section scores and then converted the total raw score to the programs five point
scale: (5) Extremely well qualified, (4) Well qualified, (3) Qualified, (2) Possible
qualified, and (1) No recommendation. In July 1997 grades were sent to students, their
high schools, and colleges they selected.
The First AP Statistics Reading
The Reading took place the second week of June 1997. Fifty-six
statistics educators gathered at the College of New Jersey in Trenton to read the FR and
IT sections. Since this was the initial statistics offering, the Reading site was located
near Princeton in case additional staff was needed. Richard L. Scheaffer, University of
Florida, served as the Chief Faculty Consultant (CFC). Rosemary Roberts, AP Statistics
Test Development Committee Chair, acted as Assistant Chief Faculty Consultant. The
remaining Committee members served as Table Leaders or Readers. Other Table Leaders were
Patti Collings, Chris Franklin, Brad Hartlaub, Duane Hinders, and Ken Koehler.
The College Board divided the United States into six regional offices:
Middle states, Midwest, New England, South, Southwest, and West. ETS sought to obtain
Readers representing each region by region, gender, ethnic background, and college or
secondary schools affiliation. Overall, ETS targeted 50% college--50% high school
participation. In 1997, more students registered for the AP Statistics exam than
originally anticipated. Therefore, ETS had to recruit approximately 20 extra Readers on
short notice. The result was approximately 60% high school and 40% college.
The CFC screened all applications for Table Leaders and Readers. Once
applicants were selected, the CFC submitted a form to the Performance Scoring Services at
ETS. Applicants were notified of dates and conditions of acceptance. The primary purpose
of the Table Leader was to ensure consistency in scoring. According to J. Haberstroh of
ETS (personal correspondence, February 10, 1998), criteria used to select Table Leaders
included experience with subject matter and an ability to work as a diplomatic
facilitator. For this Reading, all Table Leaders had also been involved with the
development of the AP Statistics course and exam. Subject matter background was equally
important for Readers. In addition, ETS sought a certain level of professionalism. J.
Haberstroh explained. "We want to have people who contribute to the overall
professional aspect of the process," he said (personal correspondence, February 10,
1998). Selected participants can serve as a Reader for up to six years. Table leaders can
serve an additional six years.
The Chief Faculty Consultant, Assistant Chief Faculty Consultant, and
Table Leaders arrived three days prior to the Reading. This leadership group prepared the
rubric that all Readers would use (see Appendix G). Prior to the Reading, the Chief
Faculty Consultant paired each Reader with a partner. During the Reading, all eight tables
sat six Readers and one Table Leader. To insure consistency, Table Leaders back read a
portion of graded papers from all Readers at his or her table. They also assisted when one
of his or her readers had questions regarding grading.
Test Development Committee Members Responses
I contacted all eight members of the Test Development Committee and
asked them to respond via E-mail to the same questions (see Appendix H). Unfortunately,
only four Committee members responded to this request. The Chief Faculty Consultant (CFC)
supplied The CFC Annual Report on AP Statistics.
The first question asked, "Did students perform as well on the
open-ended questions as you had expected? If not, what might be some possible reason for
poor performance?" Three said no and the fourth said he expected them to perform
miserably (HC, personal correspondence, October 1, 1997). One member believed
students performed poorly because "some of the students had never seen the
material" (ID, personal correspondence, October 5, 1997). All four members suggested
students and teachers lack experience with Free Response questions. Students need more
practice with writing as part of assessment, particularly stating assumptions and reasons
for choosing an analysis technique.
The second question probed Committee Members Reading experience
as it related to other teachers at the Reading. I asked, "What did you learn from
other teachers who were there as Readers, with regards to the course and their own
classroom preparation for the exam?" One member stated teachers "feel there is
plenty of time to teach the course, if the course is a year long, and not just one
block" (RF, personal correspondence, June 28, 1997). Another member wrote that the
Readers left with a better understanding of "what is to be expected. There is no
doubt now what assumptions are required for tests and the fact that they have to be
explicitly stated in a response" (ID, personal correspondence, October 5, 1997).
Readers use of a rubric was a significant piece of the grading process.
I asked Committee Members "What is your opinion/impression/reaction to the rubric and
holistic grading?" Two members suggested some Readers may have been skeptical. But by
the end of the Reading, everyone agreed it was fair, consistent, and a good method of
grading (HC, ID, RF, NA, personal correspondence). One member had experience grading the
AP Calculus exam using an analytical method. He said, "Holistic grading gives us an
opportunity to discuss the response made by each student so that we can come to an overall
conclusion about the students overall understanding of the questions and the
appropriateness of the answers" (RF, personal correspondence, June 28, 1997). One
member identified a specific advantage to using a rubric. "We saw students come up
with innovative ideas about the open-ended questions that enabled them to get quite a few
points," she said, "even though they did none of what we thought of as the
standard, obvious solution" (NA, personal correspondence, July 2, 1997).
Technology was an important element of the AP Statistics course.
Students were required to have a graphing calculator for the AP exam (College Entrance
Examination Board, 1997). I asked Committee Members if they are in favor of allowing
graphing calculators use during the examination. All four members responded
"yes." "As teachers, we cannot teach in one way and test another,"
says one member. "You cannot do statistics without technology. We have to test using
technology" (ID, personal correspondence, October 5, 1997). Another member, who was
in favor of using technology, suggested some portions of the exam could be given without
use of graphing calculators. "I am in favor of kids taking portions of the exam
without calculators," he wrote, "as this increases the kinds of questions that
can be asked" (RF, personal correspondence, June 28, 1997). One member expressed
concern about students using calculators to cheat.
Some sort of computational device is absolutely necessary for a statistics exam.
Predictably, some students misused and overused their calculators. Some Readers were a bit
discouraged by this, but those of use who have been teaching since the days before
calculators know students resort to mindless computation when they dont know what
else to do, whether or not they have a calculator. The bigger problem, which I wasnt
fully aware of until the Reading, was that students can download tremendous amounts of
textual information into a TI-83. That does bother me. This is supposed to be a closed
book test. We will have to figure out some way to deal with that. Clearing memories
isnt as flawless an idea as it might first appear. The students with TI-82's would
then lose the programs that make it emulate a TI-83. (NA, personal correspondence, July 2,
1997)
Overall, committee members supported the use of technology during the exam but were
willing to explore alternative applications.
Two other questions were presented to the Committee Members, but only
one yielded relevant information. I asked "What is your overall impression of the
initial offering of the course and the examination?" All four members stated
favorable impressions. One member noted that "the number of exams far exceeded our
projection and we had to scramble for Readers at the last minute, but I dont think
that hurt us" (RF, personal correspondence, June 28, 1997). Another felt "relief
that everything went so well and that so many students and teachers understand that
statistics is an important subject" (NA, personal correspondence, July, 2, 1997). One
member, who was involved with the course and the exam from the beginning, said, "I am
sure there is room for improvements, but considering how much work we did based on
hunches, estimation, and flat guesswork, I thought things went great!"
(HC, personal correspondence, October 1, 1997).
1997 AP Statistics Exam Results
Table 1 shows national, southern regional, and Georgia results by
number of students and percentage where the grades were reported to a college or
university. Additional information regarding national, regional, and state data is
available from ETS.
Table 1
1997 AP Statistics Exam Results Reported for the Nation, the Southern
Region and Georgia
National Southern Region
Georgia
AP Score Percent
Percent
Percent
5
15.7%
16.6%
20.0%
4
22.1%
19.6%
17.6%
3
24.4%
21.9%
23.8%
2
19.8%
20.3%
21.7%
1
18.0%
21.6%
16.8%
The AP Statistics Listserve
J. Swift, who was teaching statistics in Nanaimo, British Columbia
in the mid-1980s, initiated efforts to connect statistics teachers using phone/modems
through the Bulletin Board Systems (BBS) network (personal correspondence, February 4,
1998). The Woodrow Wilson National Fellowship Foundation month at Princeton in 1984
supported this type of communication and provided hardware for the BBS. In the early
1990s, changes in technology provided a more convenient and efficient method to open
communication lines among teachers. At this time, many teachers began to subscribe to the
List for Statistics at North Carolina State University, including J.C. Chappelle,
Brookestone School, Columbus, Georgia and J. Swift, Coordinator, Information Systems,
School District 70, Alberni, British Columbia, Canada. Both planned to teach the AP
Statistics course when it was introduced. J.C. Chappelle posted a message to the existing
Edstat listserv, sometime in 1993, suggesting that it might be useful to start a list
directed at the high school statistics teacher who was planning to teach the AP Statistics
course. J. Swift enlisted the help of the Education Technology Centre in British Columbia
to host the APStat Listserv and he began managing the list. According to Swift in April
1998, 644 have subscribed to the list and only the AP Computer Science list has more
subscribers (personal correspondence, April 11, 1998). Swift also indicated that since the
AP Statistics list proved to be so successful, the College Board initiated lists for other
AP subjects (personal correspondence, February 5, 1998).
The purpose of the APStat listserve was to provide academic support to
any teacher involved with the AP Statistics curriculum. Various topics were introduced
repeatedly as new teachers join the list. Two nonacademic topics reoccurred that created a
tremendous amount of debate. These topics were choice of textbook and choice of
technology.
The most frequent question that appeared from new teachers concerns
textbooks. There were two major types of statistics textbooks, traditional and
progressive. There were a variety of texts available of the traditional flavor. These
texts all presented the material in the approximately the same order, placed an emphasis
on probability, and provided data with detailed instructions on the type of analysis to
conduct. The other type of statistics books were more individual in their design. Some
progressive texts eliminated or reduced topics in the traditional texts (probability,
binomial distribution) and included topics not mentioned in most traditional texts
(sampling techniques, experimental design). Another difference in the two types of
textbooks was the organization. Traditional texts placed probability topics early and
bivariate data analysis later. Progressive texts emphasized exploratory data analysis,
including boxplots and normal probability plots. Overall, progressive textbooks shifted
the emphasis from calculations and formulas to conceptual understanding. Even though
several texts were recommended by the Test Development Committee, it appeared that this is
a common source of frustration and confusion to a novice AP Statistics teacher. This may
be because most of the texts recommended by the Committee were progressive texts that
require interaction with the data. It is possible that these recommended texts are
unfamiliar to a teacher who was taught from traditional texts. As this specific topic was
not stressed in my research, I did not emphasis these conversations while viewing the
listserve. However, those who participated in this discussion consistently recommended the
three texts available by David S. Moore (one text is coauthored with George McCabe) and
the other progressive texts, Devore and Peck, Siegel and Morgan, Waldrop, and Iman.
Another frequent topic of conversation revolved around technology. Since
the Test Development Committee recommended that students interact with data, the choice of
technology has become a significant issue. The contributors to the listserv fell in one of
two camps. The experienced teachers preferred either a graphing calculator (specifically
the TI-83) or the use of statistical software on a computer. While there was some
discussion about the choice of software, the most heated debate occurred with respect to
calculators versus computers.
Many high school teachers preferred a graphing calculator, specifically
the TI-83, because of the convenience and cost for the student. Texas Instruments provided
overhead screens that attach to a teaching calculator and enabled the instructor to
project the text to a wall screen. With this attachment, the instructor could use his or
her calculator while the students see the screen at the same time. This allowed students
to follow the sequence of instructions on their own unit simultaneously. Another advantage
of the calculator was availability and convenience. Students carried a graphing calculator
wherever they needed to. And, the calculator was not an overly expensive item to purchase.
Many campus bookstores sold or rented the calculator of the mathematics departments
choice. The computer offered neither of these advantages. A school had to provide a
classroom with computers or have a lab where the class could meet to utilize the
technology. In addition, unless the school arranged for a site license from the publisher,
students had to purchase software bundled with the text (although the software might not
cost as much as the graphing calculator). Unless a student had a computer at home, they
were forced to use the facilities at the time and convenience of the school. However, the
computer offered advantages the calculator did not. This was where the debate always led.
Many software packages allowed students to examine graphs and statistics simultaneously.
It was advantageous to view graphs side by side. It was easy to adjust the size and scale
of graphs. Computers offer printing as an option. In addition, most software packages
allow the user to analyze large data sets. The TI-83, for example, was restricted to data
sets of 999 observations. Statistical software easily handled much larger data sets.
Another technological advantage of the computer was the ability to download data sets from
the Internet. As our society becomes more dependent on technology services, such as the
World Wide Web, availability of data from the web will increase as an advantage.
Procalculator teachers responded with the idea that large data sets are not necessary. If
the goal was for the student to interact with the data, then allow them to gather the
data. There were effective ways to gather data during class: how many miles do you live
from school, age and height of both parents, number of children in the family, estimate
the length of a piece of string, and favorite car color. I observed that students enjoyed
working with data that had meaning for them. Large data sets obtained from a book or the
Internet frequently held no personal meaning for students in the classes I observed.
While the AP Statistics listserve provided a forum for discussion about
texts and technology, the most significant conversations concerned academic questions.
This listserve provided a non threatening forum for novice statistics teachers to ask
questions from more experienced instructors. Frequently the experts disagreed on academic
topics. Discussions involving ambiguous interpretations revealed the aspects of
statistical thinking that are difficult to master. Unlike other fields of mathematics,
statistics frequently involved subjective interpretations. For novice teacher, this was
frustrating and difficult. The attitude of contributing members was to assist anyone
seeking help. Several teachers posted other website addresses with related information,
including data sources, test questions, and project topics. Since students had access to
the listserve, listserve members have noted that test questions posted were not secure.
In May when the AP Statistics exam was being administered, the
listserve conversation was active. Initially, one teacher in the Far East raised the issue
of security. Since students in that time zone were physically administered the test
earlier, the likelihood of insecure test questions because a realistic problem. No one on
the listserve was able to contribute a solution but everyone became aware of the problem.
The week following the administration of all AP tests, teachers posted feedback from their
students. Overall, of the teachers who offered this feedback, most of their students
indicated the multiple choice section was straightforward and not difficult. The free
response section, which included one investigative task, received a variety of evaluations
from students. Some students thought these problems were not difficult, while other
students thought these problems were extremely challenging.
After teachers received ETS scores for their classes, many posted the
results to the listserv. While it was interesting to read these postings, the ETS national
scores published later verified a voluntary response bias. Many of the teachers who posted
their scores were at or above the national average for the number of 3s, 4s, and 5s.
The Instructor
Even though the purpose of this study focused on student learning,
finding an experienced teacher was the main criterion in choosing the research site.
Qualified instructors are an integral component of a successful AP course. (College
Entrance Examination Board, 1997; Watkins et al., 1997). The Test Development Committee
recommended that AP Statistics instructors complete at least one college-level statistics
course, and preferably two or more (Watkins et al., 1997). Lee completed two undergraduate
and three graduate courses in statistics. He had 20 years experience teaching statistics.
For this initial offering of AP Statistics, he taught all three sections that were offered
at the research site. In addition, he taught the Introduction to Statistics course
part-time at a local community college.
The second research question, what teaching strategies are effective in
implementing the recommended pedagogy, emerged from the study as a result of trying to
describe the AP Statistics course holistically. Originally, I did not intend on focusing
on the instructor as I considered student learning issues. However, during data analysis,
many issues emerged from the students that could only be addressed by investigation of the
teacher. To address these emergent issues, I referred to field notes that recorded
dialogues and interactions between the instructor and students, and among the students. In
addition, during academic year 1996-1997, Lee and I frequently discussed his techniques
and his motivating logic. I recorded notes of these discussions in a journal. After the
first year ended, I conducted a structured interview with Lee. But, much of the data that
addressed this question were gathered throughout the 1997-1998 academic year as he
responded to follow up questions that emerged during data analysis.
Lee
Lee is calm, patient, and relaxed. These personality traits are
apparent in his teaching. Several students in their interviews indicated the classroom
atmosphere was relaxed and comfortable. Students indicated they felt comfortable asking
questions in this learning environment.
Lee was the mathematics department chairperson. In this capacity, he
arranged teacher course assignments, approved students to take specially recommended
classes, interviewed prospective faculty members, obtained substitute teachers, selected
and/or approved textbooks and other materials, encouraged teacher involvement
professionally through organizations and training, attended official events representing
the mathematics department, and solved administrative problems.
He was a consultant for the College Board in AP Statistics. He
conducted workshops that are sponsored by the College Board for AP Statistics teachers.
These workshops covered the curriculum while placing an emphasis on activities that
instructors can use to facilitate conceptual understanding. College Board sponsored
workshops were offered annually in all regions of the country. Many of these one-day
workshops were offered during the academic year, but summer workshops were spread over 5
days.
Lee has been using concept-oriented instruction for the past 10 years.
He began experimenting with constructivist teaching techniques in the late 1980s after
attending several progressive workshops and institutes: Mathematics and Technology
Conference at Philips Exeter, Woodrow Wilson Modeling at Princeton, and Discrete Modeling
at the University of Maine. These workshops focused on interactive model building. He
stated that, given his mathematics modeling experiences, teaching statistics as an
interactive, concept-oriented course was a natural progression (personal correspondence,
March 17, 1998).
Constructivists advocated that teachers devise scenarios enabling
students to investigate, conjecture, and construct their own understandings (Confrey,
1990; Noddings, 1990). Lees teaching exemplified the constructivist learning theory
by placing students at the forefront of the learning process. For example, one day he gave
them a set of instructions, but did not tell them how to do any of the requested things.
Students discovered their own method, and then checked with others for verification (Field
Notes). Another day one student collected the data from the class and said, "I got
the data but what confidence level?" Lee responded, "I dont know,
youre the statistician." The following dialogue occurred in January. This
interaction typified Lees pedagogy.
Lee arrived in class with a small bag of chocolate chip cookies and gave one to each
student.
Lee: Estimate the number of chips in a cookie.
Student 1: How do we do this?
Lee: I dont know, you decide.
They count chocolate chips and report their data.
Lee: Okay, the mean is 7.333. So whats your answer?
Three separate students volunteered their confidence intervals.
Lee: What did you use?
Student 2: 95%
Five others agreed that 95% was appropriate.
Lee: T or z?
They all say t.
Lee: Why?
Three students chimed in: small sample size.
Student 3: We dont know the population standard deviation.
Lee: Are we comfortable using t? What should we be concerned about?
Student 2: Is it normal?
Lee: How can we determine this?
Student 5: Look at a normal probability plot.
Lee: Okay, so now with that, is it reasonably normal?
Student 6: Its pretty linear so the data should be normal.
Lee: What else can we do?
Student 4: Use chi-square.
Lee: What else can we do to test normality?
Student 7: Graph a histogram.
Lee: What would be a good scale?
Student 4: How about x-bar plus 3 standard deviations.
Lee: Ideally you ought to be thinking about these assumptions. Now, this cookie company
claims the average number of chips is greater than 7. Test this claim.
Student 3: The test statistic is 1.4084 and the p-value is 0.09.
Lee: Which means?
Students 8 and 9: Do not reject the null.
Lee: Which means?
Students 5 and 9: The cookie company is wrong.
At this point, Lee accessed the draw feature on the calculator.
Lee: What is this picture? What is the curve?
Student 5: A t-curve.
Lee: What t-curve?
Student 6: Our t-curve.
Lee: Is it the t-curve for the number of chocolate chips?
Several respond no.
Lee: For some standard t-curve?
Student 2 and 7: Yes
Lee: Which one?
Student 9: The one with 14 degrees of freedom.
Lee: What is 1.4084?
Student 6: Thats where the mean would appear on that curve.
Lee: Whats in the center?
Student 5: Zero.
Lee: What does this mean without referring to our problem?
Student 4: I thought it was the probability that it was random.
Lee: What does the shaded area mean?
Student 9: The probability that we would get that sample if the null was true. (Field
Notes)
This dialogue portrayed Lees belief that teachers should facilitate learning.
"I think allowing students to dig things out for themselves is important," Lee
said. "I think I force them to do that sometimes, kicking and screaming as they
go" (Interview). He frequently allowed the students to pursue misconceptions. He
posed a question to the class. When students offered incorrect ideas and solutions, rather
than correcting them, he would continue to prompt their inaccurate ideas. I asked about
this teaching technique:
Lee: I certainly think that my non answering of questions is a really valuable skill. I
also let them go toward the wrong answer. I think thats important because
thats the way theyre going to go anyway.
KR: How is that important to their learning?
Lee: Well, because I like to think that somewhere along the line theyre going to be
going off on their own directions. Theres only so much structure that can be applied
to their learning. Some of them may like the structure, but they just have to have ideas
of their own. And statistics lends itself to this sort of thing because theyve got
to think about all the situations and the conditions. As you talk and read about these
problems that seem sort of standard and four statisticians are discussing it, each one has
their own way of going about it. Were talking about above average high schools
students trying to know "the" way when the experts cant even agree.
(Interview)
As the researcher, I was interested in why Lee used this questioning technique to help
the students learn.
KR: What about the student who is in the class discussion, conversing back and forth
with you, and you let this misconception continue to go until he gets to the point where
he has backed himself into the corner where he realized hes gone down a blind path.
You did this repeatedly. So, how does that help them learn?
Lee: I think thats the only way in a lot of cases where they are ever going to
really think about most of the concepts. If I tell them exactly what to do on every
problem, everything will be just fine as long as they have exactly those problems that I
have taught them how to do that way. Theres just too many twists and if they have
never played with twists then they wont have any idea what to do.
KR: Why do you think allowing them to pursue their misconceptions while you go back and
forth with them is better than just turning to them and saying, heres the
correct answer. What do you think about the way they learn that your teaching method
supports their learning that way?
Lee: I guess my theory is that every student has his own vision of reality because they
tell me about it sometimes and its certainly not mine.
KR: Where did their view come from?
Lee: People figure out how to learn things however their brains work. I dont know
that I have thought about this much until lately. In lower school, we teach them these
algorithms about how to add and subtract. And for a lot of kids, the way we describe how
to do it, thats not how they think about it at all. Theyll do an amazing
convoluted system that gets them the right answers so obviously thats fine.
Apparently my method didnt make any sense. So I think thats just the way kids
do just about everything. So me laying down the rules, it may indeed be something they can
memorize and apply to the verbatim problem, but if its anything but
that, I dont know that they have a chance. Theyve just got to have experience
with playing around and trying to figure out what the concepts mean to them. Im sure
if I asked a lot of these kids some real standard questions, then they would explain them
in a way that would just boggle my mind. But if thats how they understand it, then
thats okay, as long as its not wrong. (Interview)
Consistent with constructivist views of teaching (Cobb et al., 1990; Confrey, 1990;
Davis et al., 1990; Hatano, 1996; Noddings, 1990; von Glasersfeld, 1992) and the Test
Development Committees recommended pedagogy (College Entrance Examination Board,
1997), Lee believed in actively involving students in the learning process. He involved
the students using a variety of activities, including gathering data in the classroom,
utilizing technology, and group problem solving. When asked about integrating activities
with lectures, he said,
Lee: I don't know that the best way to do it is necessarily to have nonstop activities
or nonstop lecture. I think there needs to be a nice mix of different kinds of things
going on.
KR: Why do you think that's important?
Lee: I think that an activity, whether its a simulation or something else, just
makes a lot of concepts much more concrete to students. The writing down of facts is just
a very different kind of way of learning something than seeing it happen with real data,
or actually quote, doing the problem unquote.
KR: So why a mix? Why not do the entire class using only activities?
Lee: Well because at some point if you allow every student to formulate all their own
learning through activities, obviously there can be mistakes. Statistics just generates
such different kinds of results and a lot of it is due to randomness, but somewhere along
the line you have to make it, you have to get them to focus on what the central notion is.
And if that doesn't come out, you have to help them along. Or their peers have to help
them along. I think that's part of our job too. We can let them go down the wrong path,
and play around, and form their own learning. But then we need to get them to say exactly
what it means and to make sure that is reasonably close to being correct.
Lee used a variety of techniques to cover material. His goal, however, was conceptual
understanding. During student interviews, many referred to their learning as conceptual. I
asked Lee how did the students come to know the idea of learning conceptually.
KR: In my interviews with your students, several of them mentioned conceptual learning.
Where do you think they got this notion of conceptual understanding?
Lee: I talked about the idea of concept versus application a lot. I would frequently ask
them, What does this mean? I tried to be clear that meaning was important and
forced them to answer this in class and on tests.
Kim: How did you do this?
Lee: In class, I would throw out questions that got to the underlying concepts. If they
didnt reply with that kind of answer, I would continue to prompt them until someone
figured out the correct meaning. On tests, I would ask questions where they couldnt
rely on the calculator for the answer. The wording would be such that they would have to
understand the meaning of the terms and context of the material to figure out the answer.
(personal correspondence, March 10, 1998)
Lee clearly stated his belief in the importance of involving students in the learning
experience. His goal was to provide an environment where students actively experienced
situations that helped them develop conceptual understanding.
Another pedagogical technique the instructor implemented involved
utilizing technology in the classroom. His knowledge and experience using the TI-83 was
extensive. Also, the students had used the TI-82 extensively in both Geometry and Algebra
with Transformations and Precalculus. When asked about the controversial technology issue,
the following ensued.
KR: What do you think of technology in this class?
Lee: I think having powerful technology available in the classroom allows the students to
focus on the important ideas and not the number crunching aspects of statistics.
KR: Your choice of technology is?
Lee: My choice of technology without question is the TI-83.
KR: What are the advantages you see for the TI-83 over a computer?
Lee: It's totally convenient in the fact that the kids have it in their hand at all times.
There is no need to run to the computer lab. Despite the comments by many college people
on the listserve, that life can't go on without a computer and that is the way it is done
[sic]. I still don't get it, I'm trying really hard. But beyond the fact that it handles
lots of data, and it prints really pretty pictures, I still don't see the advantages of a
computer over the calculator.
KR: The comment that seems to come up over and over on the listserve from those who prefer
computers, is that's what real statisticians use.
Lee: That's just an irrelevancy to me. The last comment that I saw on the listserv which I
thought was really good is that my students are quite comfortable with computers, whether
its through statistics or not is irrelevant. They are comfortable with computers, they are
comfortable with using packages. So in ten minutes, if they have never used Minitab, at
the end of the course after using the 83, I could say, now here's how Minitab does exactly
the same thing and they would not be shocked, surprised or amazed. I'm really trying hard
to understand. I think a lot of college people that say that the 83 isn't the same is
because they don't know what the 83 can do. I really believe that. In that sense, I feel
like I'm in a stronger position because I know what they both can do.
KR: So you don't feel in any way that your students missed anything from not working more
on the computer?
Lee: Not at all.
In the classes I observed, the instructor utilized the TI-83 graphing calculator,
instead of computer labs, for several reasons. First, the students had extensive
experience with the TI-82 and only needed to be taught the statistical features of the new
TI-83. Lee suggested convenience for the student, ease of calculations, and depth of data
analysis utilities as other reasons to use the TI-83.
A unique element of Lees classroom was the use of round tables
and chairs as opposed to rows of desks. Each table would accommodate four students. But,
students sat facing the front of the room so there were three students at most tables. I
asked Lee about this arrangement in his classroom.
KR: Why did you choose to arrange the room with round tables?
Lee: I believe that students by talking with each other tend to, they tend to clarify to
each other the idea that we as a class are attempting to explain. Their reality is not
exactly the same as mine. They have to translate my explanation into terms that make sense
to them.
KR: How do tables help facilitate this?
Lee: Proximity is obvious. Also, less implied structure. They feel comfortable. Tables
help facilitate them feeling comfortable talking to each other, even while Im
talking.
KR: How does this facilitate their learning?
Lee: I think the main thing is that they are put into a setting where they will discuss
concepts with each other. When they can explain their own understanding to each other,
that helps them understand.
Lee justified his use of round tables by stating the students were more comfortable
talking with each other and asking questions during class. He believed this is significant
to their learning process because they all learned when they assisted each other.
A Typical Day
Lee typically began class by introducing an activity, collecting
data, or presenting a problem. He allowed students to ask questions, answer questions, or
state their own ideas. These discussions were spontaneous and loosely organized. Often
questions or comments would lead them to investigate related topics in detail (Field
Notes). In a follow up interview, Lee explained why he was unconcerned if they were
seemingly off the subject.
They have their own personal understanding of the statistical ideas
they discover or that I present. Its very unlikely that many of my students
understand sampling distributions, the Central Limit Theorem, confidence intervals or
hypothesis tests in the same way and certainly not how I understand it. I think when
theyre allowed to discuss these ideas among themselves, they share their individual
notions of whats going on. Many of them do not think linearly (I certainly
dont), so other, seemingly unrelated ideas, are part of the discussion. And when
numerous versions of reality come together, I think everyone participating in the
discussion comes away with a better, or deeper, understanding of the concept. (personal
correspondence, April 2, 1998)
If students asked questions about specific homework problems, they
would address those issues. However, he did not solicit questions directly related to
homework assignments. "If homework questions get asked and answered, thats
ok," he said. "But its up to the kids to make me do that because
ultimately we will talk about the homework content during class" (personal
correspondence, March 23, 1998). Lee did cover the syllabus material thoroughly (Field
Notes).
Beginning in January, another type of typical day occurred weekly on
"project day." Students met with their groups and discussed their projects. Lee
was available for questions, but he did not circulate the room. If they needed
information, permission to go to the library, or statistical advice, they approached him.
He gave advice and made suggestions, but rarely gave them detailed instructions. I asked
Lee why he gave them vague answers to their questions about their projects. "I think
the project and my lack of guidance helped them to connect all the seemingly disparate
pieces of the statistical puzzle," he said. "Before the project, they probably
saw the ideas as being unconnected to much of reality" (personal correspondence,
March 17, 1998). Findings from students interviews support Lees idea that the
project did help students construct overall understandings of statistical concepts.
Lee as a Constructivist
Confrey (1990) proposed a model that connects classroom instruction
to the constructivist learning theory. This framework consisted of six components: the
promotion of student autonomy, the development of the reflective process, the construction
of case histories, the identification and negotiation of tentative solution paths, the
retracing and group discussion of the paths, and the adherence to the intent of the
materials (Confrey, 1990). Inherent in this framework was the teachers commitment to
active learning. Confrey suggested that the responsibility for and control over learning
must shift from the teacher to the student.
The first component necessary to shift responsibility to students
required that students make a commitment to their answers. To accomplish this
instructionally, teachers can ask students if their answers are correct, engage students
at least by requiring that they explain what they attempted, act primarily as a
facilitator, and/or involve students in evaluating their own work. Lee accomplished each
of these elements, although not with equal weight. The discussion began with a question,
posed by Lee or by a student. When another student answered the question, sometimes he
responded with a question, sometimes with silence allowing others to explain or refute,
and other times he probed that individual students thinking and forced him or her to
explain their idea (Field Notes). These interactions between Lee and his students were the
norm. This mode of instruction guided most classroom sessions.
Next, Confrey (1990) suggested that students must "modify and
adapt their constructions" (p. 116). She suggested that they face situations that are
problematic, take action to solve the problem, and examine their action to determine if
the problem has been resolved. Lees teaching included these strategies. He
frequently began class by distributing a handout or assigning a problem on the board.
Students worked at the round tables but usually sought to answer the question
individually. After an initial solo attempt, they consulted others by asking questions or
checking their answers. Their discussions focused on trying to determine whose answers,
and therefore procedures and processes, were accurate. Then, as a class, they discussed
and answered the question. Lee consistently forced them to explain what the problem was.
He then allowed students to describe their strategies and forced them to defend their
choice of strategy.
Confreys (1990) third component evolved from student teacher
interactions. She referred to the teachers familiarity of a students knowledge
and abilities as a "case history" (p. 118). She suggested that teachers learn
their students strategies and use this understanding to develop appropriate actions
toward their problem resolution. Lee was willing and interested in developing these case
histories with every student. Since he had the desire, small class sizes (14 students in
fourth period, 17 students in sixth period) made this easy. Some students, however, were
more open than others and Lees knowledge of their learning processes was more
detailed. His accomplishment of this became apparent in our informal conversations. When
we discussed a specific project, for example, he frequently conveyed insights into their
learning and processes that revealed how well he knew that student. He used this knowledge
to direct that student toward appropriate actions that would address his or her concern.
The fourth component of Confreys (1990) framework suggested that
teachers use case history knowledge and flexibility to adapt the class objectives
depending directly upon students questions and understandings. One of Lees
strengths as a teacher was flexibility. In our interview, he revealed that whenever
students digressed, he saw this as an opportunity to investigate their thinking. He was
never concerned that "getting off the subject" was that. He believed that
students questions and issues, which seemingly detracted from the days
purpose, were important to investigate. Many days, he admitted, he came to class with
little or no predetermined structure. He presented a problem and let the students
actions and responses determine where the investigation led. He was never concerned that
they would not eventually cover all the material. His saw his primary responsibility as
leading the class to investigate and discuss whatever they believed was relevant to the
problem and its solution.
Confreys (1990) fifth component involved reviewing the
students solutions. She suggested this provides a variety of positive opportunities
for students: reflecting on their process, looking at the specific problem holistically,
and contributing to a sense of accomplishment. It is unclear if this must be accomplished
on an individual basis. Lee provided these opportunities, but most frequently within the
group settings. After presenting problems or while reviewing corrected test papers, he
encouraged questions and discussion while leading them to an overall sense of the problem
and its solution.
The last component of Confreys (1990) framework required a
commitment from the teacher to the mathematics content. While the instructor might not
have a specific agenda of how to cover the material, it is essential that he or she had a
clear picture of the information that needed to be addressed. After observing Lee
extensively, it is easy to conclude that Lee was aware of the material required to cover
the syllabus and prepare his students for the AP Exam (Field Notes).
Overall, Confreys (1990) framework provided suggestions for
teachers willing to shift their pedagogy and emphasize student activity, construction, and
reflection. She admitted these techniques may appear to impede progress as related to
traditional teaching techniques to cover material. However, she believed the knowledge
constructed through these types of activities and processes was more accurate, more
meaningful, and more powerful.
Interviewed Participants
As the researcher, I was interested in the effect of
concept-oriented instruction as recommended by the AP Statistics Test Development
Committee. Lee and I examined a variety of characteristics to choose the specific
students. A total of 12 students were chosen to interview in depth. It was important to
obtain a diverse group of students representing all levels of the academic talent
spectrum. I was also interested in observing juniors and seniors, males and females.
Another important criterion for each student was to be outgoing and receptive to my
presence and research. For example, three boys sat at one table in fourth period who
rarely spoke to the instructor, the class or to me. These three students were easily
eliminated for their shyness. The instructor and I frequently engaged in conversations
concerning students academic abilities and other factors we thought might influence
students learning. For example, I was interested in the only sophomore student
taking his first AP class. His parents, however, would not sign the consent form and he
was eliminated.
It was important to select informants from both observed classes. The
atmosphere of these two classes was quite different. Fourth period students engaged in
discussions contained to their tables and students at neighboring tables. A student would
frequently converse with the instructor. Other students would join the conversation while
some continued to stay within the confines of their table. Sixth period, on the other
hand, was frequently loud and sometimes ignored the instructor altogether. They would be
engaged in statistical problem solving, yet would carry on conversations with students
across the room rather than enlisting the assistance of someone closer. The noise level of
this class was consistently higher than fourth period. Frequently, this class was behind
schedule with respect to the other two classes because they would slow down instruction of
the material. Therefore, two different groups from each class were targeted to study their
project progress in detail. I interviewed at least one member from each of the project
groups that were chosen. Listed below are the reasons that each participant was chosen.
Adam (AD): As a member of the mathematics team he represented the upper academic
spectrum for juniors. He enrolled in Calculus BC his senior year. He is of Indian decent.
Beverly (BH): She was a senior who was not recommended for the AP Statistics class. She
approached the mathematics chair, Lee, and requested permission to take this class. She
was the only student out of all 40 enrolled who had not taken Precalculus. She was
interviewed in detail to represent the group project BDL (Beverly, David, Lisa).
Carter (CF): He attended Governors Honor Program (GHP) the previous summer in
mathematics. His interest in mathematical theory and rigor were significant. He was an
African American junior who was recommended to take Calculus BC his senior year.
David (DW): He is also an African American male. Compared to the other 30 students, his
mathematical abilities were average. He enrolled in Calculus AB his senior year. His
attitude was excellent.
Ethan (EB): As a member of the debate team, he would frequently converse with the
instructor in a more detailed way than other students. He displayed stubbornness about
giving up before he believed he understood the concept. He was a junior of average
academic talent. He enrolled in Calculus AB for his senior year.
Fran (FE): She was selected because she had Calculus BC the prior year as a junior and
made a 5, the highest possible score, on that test. She falls on the upper end of the
academic scale and was a senior. She was the student selected to represent the group known
as FMN (Fran, Mark, Nancy).
Gretchen (GH): Academically, she represented a below average junior girl. However, her
interest in learning was strong. She asked the instructor many questions during class and
worked well with the other members at her table. She sparked my interest because she
sometimes had an idea of the concept, but would continue to question and pursue until
satisfied. She also consistently did the assigned homework. She was placed into Calculus
AB for her senior year. She was selected to represent the GRS (Gretchen, Rachel, and Sam)
group project.
Hanson (IF): His family heritage at this school was prominent. Academically, he fell in
the middle of the junior class and was recommended to take Calculus AB for the next year.
Ingrid (IS): She was chosen because she consistently indicated an interest in learning
statistics and expressed curiosity for my research. She was recommended to enroll in
Calculus BC this year. She was Hindu Indian. She was selected to describe the ITW (Ingrid,
Terry and Wesley) group project.
Josh (JK): He was chosen to represent the lower academic end for juniors. He was
recommended for Calculus AB his senior year.
Lisa (LB): She was chosen to represent the below average female junior. She enrolled in
Calculus AB her senior year. Like the others chosen for this academic reason, she worked
with others well, was not intimidated to ask questions of the instructor, and was
receptive to my presence.
Sam (SD): He represented a second generation Hindu Indian. Academically, he fell in the
mid range for junior males. He was recommended to take Calculus BC in his senior year.
These were all honors students and each junior was advised to take an AP Calculus class
their senior year. Overall, of the 12 students chosen, 5 were recommended to take Calculus
AB, 5 were recommended to take Calculus BC and 2 graduated. I interviewed 7 males and 5
females. Nine students interviewed attended sixth period and 4 attended fourth period.
Other students are quoted as members of the four selected groups: Mark, Nancy, Rachel,
Terry and Wesley.
The interviews were conducted the first 2 weeks following the
administration of the AP Statistics exam. I was concerned about their ability to recall
details on a test that was completed and, in many ways, no longer relevant to them.
Because seniors at this school completed their course requirements and graduated before
other classes are completed, I interviewed seniors first. Others were interviewed as early
as possible. Since I observed the classes for the entire academic year and knew the
students, I opted to audio tape only. Students were interviewed individually and
privately. For the interview, we simply found a quiet, secluded spot near the classroom.
Student interviews were conducted during class time. Every student appeared comfortable
during the interview. Several students who were not selected indicated interest in
participating.
I asked each participant interview questions designed to probe areas of
interest related to the research questions. Each student addressed the same questions (see
Appendix A), but not in the same order because "the sequence of questions varies with
each respondent, depending on prior answers" (Romberg, 1992). Frequently a student
would answer a question not yet asked, while others would stray off the topic altogether.
If they digressed, we explored their emerging ideas before returning to the list of
questions. Also, it was common for a student to respond, yet not directly answer the
question. I allowed them freedom to speak about whatever they felt important. I realized
some of this information was not relevant to my research questions, but it was critical
that they felt completely at ease to say what they wanted. In any of these events, I would
probe until I felt all questions had been answered or until I believed the student was
unable to provide the requested information.
The Students Perspective of Statistics
In each interview, I asked the students to tell me about their
statistics class. All 12 replied that the course was different from other mathematics
classes. Five students suggested the course material was more applied. "Math was
really different this year," Ingrid said. "Last year we were just totally
manipulating numbers. Thats all it was. If we were sitting there writing the
equation for a semicircle, ok, big deal. The thing about stat, I can admit that I saw the
point to it" (IS, Interview). Ethan expressed a similar opinion.
Its a lot clearer from the very beginning why, what the final
goal is when learning all these different steps. Whereas opposed normally [sic], you learn
all these steps and maybe eventually when you are done, you learn why youre doing
it. Here you know why you are doing what you are doing from the very beginning because you
just have the whole concept of trying to compare numbers that have been [sic], everything
seems like its just trying to make two numbers that are apples and oranges
comparable, whether its different numbers of samples or different characteristics and you
are trying to account for that. You know thats the goal the whole time and you can
kind of see how everything youre doing works toward that goal. (EB, Interview)
Gretchen agreed with Ethan and Ingrid. "We took problems of life,
like trying to figure out averages and things like that, real situations," Gretchen
said. "I liked it, because unlike precal I can see how it relates to life. It is
usable" (GR, Interview). Sam connected the practicality to a specific field of study.
It was more practical than other math classes. In precal and calculus, I dont see
any practical use to it. What are you going to do with a parabola or a derivative? At
least here you can actually tell where people get their numbers that they do and how they
make confidence intervals. If you ever study medical papers, thats all they have. My
sister is studying to become a doctor and she had to take a stat class to figure out what
all the intervals and stuff were. (SD, Interview)
Five out of 12 students interviewed described differences between statistics and other
mathematics classes related to practical applications.
Consistent with Lees teaching emphasis (Lee, Interview), seven
students reported the difference between statistics and other mathematics classes as
conceptual. Hanson stated this difference clearly. "It was just different from math
because it is very conceptual instead of working a set pattern," he said.
"Its like an English type of math. You describe things instead of solving for
them" (HF, Interview). Ethan described his idea of conceptual learning.
In other math classes you are doing math, like number crunching. But
here, a lot of the number crunching is a lot less important. You dont get equation
sheets in other classes because what youre learning is the equations. Here,
its not learning the equations, but what they mean. And, you have to know, its
a lot less clear. In other math its written in stone which equation you use. But
thats what the goal is here. Its not if you know these equations, but do you
know when to use them and how they work. Thats the biggest difference--not knowing
the equations but when to use them and how they work. (EB, Interview)
Sam explained a similar impression of statistics. "Its not solving
for this variable," he said. "Its more like, its not exactly what I
think of as math. You do have some numbers but its more important to understand the
concepts. In math usually its just plug in this number and you solve for x. Statistics is
more idea oriented" (SD, Interview). David reiterates this same idea. "He tried
to make us shy way from just punching numbers in the calculator," he said, "and
talked more about what it means, understanding what we were doing" (DW, Interview).
Adam expressed the same idea. "You could spend more of your time doing the concepts
instead of the nit picky details with it" (AD, Interview). Overall, half the students
interviewed suggested that statistics was more conceptually oriented than other
mathematics classes they had previously taken.
Five students stated a somewhat similar opinion by expressing that
statistical manipulations were unlike those in other mathematics classes. Adam stated his
opinion. "I guess you had to do a lot of reading as opposed to deriving, less
computation," (AD, Interview) he said. Josh had a different idea. "When you are
solving something you are not going to get an exact answer," (JK, Interview) he said.
Two students suggested that statistics is not mathematical. Fran was surprised.
KR: Tell me about the AP Statistics class
FE: I went into it and I thought it would be pretty math based. I thought it would be more
like you have a situation and you have to create a way to model the situation and analyze
it from the model. But then after the first couple of days I realized, I obviously had no
idea about the different statistical processes, I thought that was pretty math based. But
a lot of it, I was really surprised. It seemed at least to me 80% of the entire course was
not the same kind of math logic as it is for like calculus or prealgebra. Im better
at really concrete math, like those other classes.
Carter took this opinion one step further.
KR: Was there anything in this class that was similar to other math classes?
CF: I really didnt think so. This is the first math class that I have been able to
go into with a calculator and no paper and function and sometimes not even the calculator.
He would just give us a worksheet and all we would have to do, especially on the exam
preparatory worksheets we got the last half of the year it was so, it just seemed kind of
pointless to me that we could just for almost every answer on the page we could type
something in the calculator or draw back on some further knowledge to come up with an
obvious answer to the question without ever having to get out a pencil or conceptualize a
problem in your head and then write it down and then solve it. It just seemed that so
little of it actually had to do with math.
These two students who indicated that statistics was not mathematical had the best
mathematics background out of all three classes. Carter attended Governors Honors Program
the previous summer and Fran scored 5, the highest score, on the Calculus BC test the
previous academic year.
Attempting to get an idea of their overall attitude about mathematics
and statistics, I asked them what was their favorite class and if they liked statistics.
Nine students said they liked statistics and referred to the practical applications. The
mathematically weakest student explained her overall impression of AP Statistics.
Beverly: I liked it because what I got out of the class I think mostly, was a good
grasp of the general concepts. The people who had a stronger background, a more in depth
background than I did, probably got more of the nit picky stuff. I got more of a general
sense of what normality is, how to plan a statistical study, instead of the step by step
formulas. I think for myself, since I dont plan to become a mathematician, I plan to
teach high school English, it really served me well because I have a general grasp of
whats going on in this general area. I think it was a good class for me. (BH,
Interview)
Three students indicated they did not like statistics. These three were among the top
four mathematical students. They said they missed the rigor of pure mathematics and
proofs. These are the same two students who said statistics was not like other mathematics
classes. No race or gender patterns emerged regarding opinion of statistics.
The Projects
The third research question examined the effect that projects, that
employ cooperative group problem solving and writing, had on students development of
statistical concepts. The Test Development Committee recommended student projects as part
of the AP Statistics curriculum. The AP Statistics Course Description stated reasons to
include projects (College Entrance Examination Board, 1997).
Students working individually or in small groups can plan and perform data collection
and analyses where the teacher serves in the role of a consultant, rather than a director.
This approach gives students ample opportunity to think through problems, make decisions,
and share questions and conclusions with other students as well as with the teacher. (p.
10)
Following this recommendation, Lee included group projects as part of the curriculum.
Lee and I discussed at length the process, timing, goals, and grading for the students,
but he made most of the decisions. I asked Lee if I influenced his decisions regarding any
of these elements of the overall process. "Your only direct influence was writing the
specific questions on their progress reports," he said. "I would have made them
do something, but I let you take care of that part" (personal correspondence,
February 3, 1998). Therefore, questions on the bimonthly reports were designed to probe
and investigate their thought processes, decisions they made, and why (see Appendix I).
Lee assigned students to groups after asking students to specify whom
they would or would not like to work with. Lees concern was potential personality
conflicts, rather than a balance of mathematical abilities. Most of these students were
self-motivated and disciplined. He was not concerned about work load inequity. After
students submitted their preferences, he discussed the groupings with me. By this time,
several students had been identified for in depth interviewing. Lee and I conferred about
which groups would serve the purposive sampling. Two project groups from each researched
class were selected to investigate in detail.
Their projects consisted of formulating a research question, designing
the experiment, and conducting the statistical analysis. From January through April,
students met once a week with their groups in class and worked on their projects. During
these class periods, they had access to the computer lab, the Internet, the library, and
other resources on campus. Lee served as a consultant. He provided direction for students
when they needed assistance. I asked Lee why he chose to intervene as little as possible.
He responded with the following.
I truly want them to find their own way in the
project. I envision the
project (whether successfully or not) as a culmination and tying togetherof the AP
Statistics experience. It is a very global understanding I am aiming for and for every
detailed instruction I give them, the more localized the experience becomes. I wanted them
to experience the frustration and/or exhilaration of focusing on an interesting question,
designing a method and collecting the data to answer the question, analyzing the data, and
finally trying to make sense of the data to see if it truly helped to deal with the
original question. It's a monumental task for anyone, let alone 17-18 year olds, but it
removes statistics from the classroom and brings the subject to life. (personal
correspondence, April 14, 1998)
Data collection and analysis were conducted solely by the students. The guidelines for
their projects and accompanying poster followed the rules for the national high school
competition sponsored by the American Statistical Association (ASA; see Appendix J). On
April 15 and 16, 1997, each group gave presentations of their projects and posters to the
class. Lees assessment of their projects included their bimonthly project reports,
their oral presentation, and their written report. He graded holistically, encompassing
all three required assessment assignments.
Gathering Data from Students Projects
In order to address the third research question about how projects
that employ cooperative group problem solving and writing influence students
development of statistical concepts, I gathered bimonthly project reports, audio taped
project presentations, and asked the students a variety of interview questions.
All students submitted bimonthly reports to Lee describing their
progress. They were asked open-ended questions and each student answered them individually
(see Appendix I). Four groups were chosen to follow in detail. I was able to attend sixth
periods project days most weeks from January through April, but had limited direct
contact with fourth period. Regardless of whether or not I was there all four groups
individually audio taped the conversations each week when they met for project day. I
attended and audio taped the presentation of all four projects. One student from each
group was chosen to represent their project for interviewing. Lee provided copies of their
project reports that were submitted for traditional grading and the ASA project
competition. Data analysis is presented after each group project is described
individually. Acronyms, composed of the first letter of each members name in
alphabetical order, are used to distinguish one group from another.
Projects Construction and Analyses
Project FMN: A Study of Our Nations Economy and Its Economic Indicators
Project Construction. Fran, Mark and Nancy (FMN) began
with several project ideas. Initially, each team member gathered preliminary data on
different topics. They finally decided to investigate whether published economic
indicators accurately reflect changes in the American economy. "We have now selected
our problem and it is a comparison of the Consumer Price Index (CPI), Dow Jones Industrial
Average (DJIA), rate of inflation, and real Gross Domestic Product (GDP) to determine if
they are accurate determinants and reflections of the economy," Mark wrote (MB,
Project Report 2). They utilized the Internet and easily obtained historical CPI and GDP
data. After a frustrating search, "I found the Dow Jones weekly averages from 1910
until today," Nancy reported (NZ, Project Report 3). However, the following week,
"Our group suffered a small setback when I lost the disk with all the information on
it," Mark wrote (MB, Project Report 4). Later, Fran reported what they had
accomplished.
We have collected GDP and CPI for several years and recorded the data in MINITAB. We
have once again found the Dow Jones site we had. That data was on a weekly basis. Since
all of our other data is in the yearly form, we cannot really use the data as is. So Mark
is getting in touch with a source who is going to find the yearly breakdown on the Dow
Jones because we are spending too much time on the Internet. We have used MINITAB and
found the basic statistics breakdown for the CPI and the GDP. However, this is only the
easy part. Now we have to see how they are related. (FE, Project Report 6).
The next project report indicates they had collected the data and were involved in data
analysis. They reported problems with this stage also (Project Report 7, Frans
interview, project presentation). Fran described the problems and resolution in their
project presentation.
One of the problems we had was the units. We thought that you know, if everything was
in the same units it would be a lot easier for us, but GDP was in millions per year and
CPI is like an index thats just a percentage. So we thought that might be kind of a
problem because wed have to liked to have millions of dollars versus millions of
dollars. That way we could tell, we could base it on the economy, on the money circulating
through the economy. But we couldnt do that. After thinking about it, we decided
that it wasnt more of like, more money, how much money was in circulation, but how
did the growth look. (FE, Project Presentation)
The next stages of analysis involved comparisons by year. They ran correlations,
regression lines, compared slopes, and examined each indicator individually by year
looking for trends and outliers (Project Report 7, Project Presentation). In the
interview, I asked Fran how they knew to look at the growth by year.
KR: How did you decide to run them all against the year? How did you know to do that?
FE: I think just, we got all this info and we had it all by year. In looking at it, we
didnt have to do it between the two indicators for the first type of look. It just
intuitively made sense to see how it progressed over the years. It was natural to say that
first we needed to look at them by year.
KR: Did you plot time on the horizontal axis a lot, say in calculus and/or physics?
FE: Physics, yes, we did a lot. Calculus, not really. It could have been from physics, or
even government when we did a little section on economics. I mean a lot of it was money
and circulation or inflation versus time and that just seemed to fit here also.
While examining the data graphically, they noticed the curves for all three indicators
were similar. Initially this discovery confused them. "I think the difficult part was
when we were actually doing GDP to Dow Jones or CPI and they looked similar but were off.
We were confused. They looked so similar, just this way [sic] but not the same when
comparing the years," Fran said (FE, Interview). Fran decided to compare slopes to
test how similar the curves really were. In the interview, I asked her why she
investigated the slope.
KR: When you were looking at the stocks, to reanalyze the data, you stated in your
project presentation, I went back and looked at the curves based on the slopes
between 1960-1970. Then you stated that the slope was increasing. How did you know
to look at slopes?
FE: Thats probably something I picked up through calculus.
They also compared regression equations. Fran admitted that she expected all three
equations to be linear and similar. "I didnt know why we were linearizing
it," she said. "I guess I just had it in my mind that GDP versus Dow Jones would
be linear and all three indicators plotted against themselves would be linear because if
they are supposed to all indicate the economy, they should have the same kind of
conclusion" (FE, Interview). The graphical analysis led them to conclude that CPI and
GDP are modeled by similar cubic functions. "But the Dow Jones with the same curve,
after we thought about it, kind of had what we termed a time lag," Fran said.
"Because the Dow Jones is actually the stock market, and how do people respond to
what they see like [sic] increasing and decreasing and what they think will make them
money" (FE, Project Presentation).
While summarizing their project, Mark stated that including certain
variables could have improved their results.
I guess theres a lot of things we could have done to make it better. If we had
had time and also resources, we could have seen the effects of tax changes, seen the
effects of new government programs. Basically there are a lot of things that affect the
amount of real money--interest rates and stuff like that, that can affect the disposable
income that people have both to put in the stock market or just to spend which would
affect the CPI. So, we could have, if we had more time, we could have factored in all
those other things and probably come up with a better model. (MB, Project Presentation)
To conclude, they stated that the best economic indicators were GDP and CPI.
"Looking at the Dow Jones, if we shift the Dow Jones over a certain amount of time,
and by looking at slopes we found that actually it was almost the same," Fran stated.
"But the time lag means it is reacting to the economy, not predicting it" (FE,
Project Presentation).
Project Summary. This group sought to determine if various
economic indicators are accurate reflections of the overall American economy. They
gathered data from 1959- present from the Internet on the Consumer Price Index (CPI), the
Dow Jones Industrial Average (DJIA) and the Gross Domestic Product (GDP). They
hypothesized that if all three indicators represent the economy, these indicators should
highly correlate with each other. To analyze the data, they used computer software to
calculate descriptive statistics, including the mean, median, standard deviation and
graphical displays. They discussed variation in the data and made comparisons from one
data set to another. Attempting to model each data set and expecting each indicator to
have linear behavior led them to a conclusion. They decided that GDP and CPI were
immediate indicators of economic growth and decline, but the DJIA had a time lag. Based on
this they concluded that GDP and CPI were accurate economic predictors but the DJIA was
only a reflection of what had happened.
Project GRS: How Are You Feeling Today
Project Construction. Gretchen, Rachel, and Sam (GRS) began with lack of a consensus
for a project topic. By the second project report, they had agreed on a broad topic but
were aware of potential problems. Sam described the project goal.
We want to do a project on Seasonal Effective Disorder (SAD). We have begun research on
the topic by searching on the Internet, but some of it is irrelevant. We want to compare
how a person with SAD reacts to different weather and how a person who is supposedly
normal compares with the SAD person. (SD, Project Report 2)
They planned to write a questionnaire and administer it to people on different days
depending on the weather. Each member reported they would obtain a random sample of adults
and students (Project Report 2). At this stage they were aware of confounding variables.
Gretchen described their dilemma and a possible solution.
There are numerous reasons why people may be in a bad mood, and we may have problems
determining if the clouds cause the persons depression or if other events of the day
are the cause. To try to eliminate these confounding variables, we will ask the people if
there are any events that have made the day bad. (GR, Project Report 2)
By the third project report, GRS has confronted more obstacles as a result of modifying
their topic. Attempting to test psychologists claim that 10% of the population have SAD,
they were unsuccessful at "finding and contacting research groups that have dealt
with SAD" (GR, Project Report 3). Each member reported frustration again. Finally,
all members reported accomplishments. After discovering that SAD is not prevalent in the
South, they shifted their project emphasis to determine if weather effects mood of
students at their high school. They wrote the survey instrument and obtained a random
sample of students to survey. They expressed concern about students returning the surveys.
In the interview, I asked Gretchen why this was a concern.
KR: What about this voluntary response bias? How did you know this could be a problem?
GR: Sometimes in homeroom, we get surveys. I see people just throw them away or some of
them give them to other people who want to do them. So you might not even get who you
think you are getting. Then we offered them a reward and we knew it was a problem because
of the definition in the book. But from watching people in the past we knew we had to do
something. So we offered them a reward but didnt give them anything. (GR, Interview)
They sent questionnaires to the same students on days representing different types of
weather. At this point, they were unsure of how to analyze the data. Also, the process of
converting survey information to data in the computer was tedious (GR, RH, SD, Project
Report 5). In the next project report, Sam wrote that they identified some confounding
variables and decided how to control for them. "We have decided not to send out
questionnaires during exam time because most people will feel depressed," Sam wrote.
"Additionally, we have decided to only send out questionnaires on Tuesday, Wednesday
and Thursday. People feel either bad or good on Monday and Friday for no particular
reason" (SD, Project Report 7). Compiling data from the surveys consumed their time
for the next several weeks. Gretchen reacted to the data. "The peoples
responses are interesting," she says. "On the same day, some say the day is
beautiful while others say it is awful" (GR, Project Report 8). Rachel reported
frustration. "Today would be a great day for our surveys," she wrote, "but
tomorrow is Saturday" (RH, Project Report 8). After inputting data, they began
analysis. Gretchen described this process during the interview.
KR: Tell me about one specific part of the project, either because it was interesting
or difficult.
GR: I guess we had all these categorical variables and we wanted to do all these
quantitative things with it. It was hard. While we were doing it, we were just thinking
about how we can we get this put in the computer so that well be able to use it
easily or make sense. Then we got it, we were going, what are we supposed to do with it.
So it was really sort of hard to figure out how to translate that data into meaning
something in the class. We couldnt do a best fit like a lot of other people did
because we didnt have it, so we had to get creative on how, the ways that we were
comparing things and looking for associations. In order to find a correlation between all
the different grades we had to do a chi-squared test for all the different grades. It took
a lot longer to figure thats what we needed to do instead of just pressing a button
on Minitab and you get a graph which is what a lot of people were doing because they had
numbers and they could do that. And if they thought correlations, but we had to test for
differences. It wasnt necessarily creative but it just took longer to figure it out.
We couldnt do what we wanted to do or what we thought we could do.
KR: So how did you finally figure out how to analyze this categorical data?
GR: We just playing around with the tests and then we asked Lee, he told us to put it all
in one big test. We had lots of little chi-squares here, so we just put it all together to
get a general overall, not for breaking it down. We just figured it out from looking at
it. Sridar took it home and started playing with it and he came back with a problem. When
we began talking about it, it just all fell into place. Before we realized it wasnt
quantitative, I had tried to graph it and then realized no wonder this doesnt mean
anything when graphing it. After that we just began talking about to do with it. Then
Saturday night after we put everything in the computer, we just started doing
calculations. Once we started talking about it, it just naturally broke down to the tests.
(GR, Interview).
Their analysis included calculating correlations between variables, graphical
explorations, and chi-square tests. To present their results, they used bar charts showing
percentages of responses for each weather day--clear, cloudy, and raining. During their
class presentation, Gretchen stated one overall conclusion. "On the days where the
weather wasnt extreme, there was no perceived effect," she said. "But when
the weather became the extremes, in either direction, thats when the effects took
place. Thats when people really like notice the weather" (Project
Presentation). Sam summed up their analysis including weaknesses during the oral
presentation.
I guess we cant conclude anything, because you can see that most people just
responded three or four and they might have done that just because they were sick of the
surveys. But we can conclude that people think that the weather really changes their mood
in a big way on those two days, but the other two questions, I guess you could say that
those were the best indicators that we had to show that people really, [sic] weather
didnt really affect them. (SD, Project Presentation)
Project Summary. GRS investigated the effect of the
weather on a persons mood. To address this question, they wrote their own survey
instrument, devised a system to obtain a random sample (from a limited population), and
analyzed the collected data. Since the survey questions used the Likert scale, they
analyzed the categorical data using chi-square tests. They discussed problems with the
survey, voluntary response bias, and inconsistent answers. They concluded that people
perceive that weather effects their mood but the data did not support any association.
Project ITW: The Great Pricing Expose (That Failed)
Project Construction. From the beginning, these students wanted
to expose a social injustice. The initial project reports indicate all three students were
interested and enthusiastic about the same idea. As early as the second project reports,
they had a plan.
ITW hypothesized that prices are higher at lower income area grocery
stores. They believed that insurance rates are higher in lower income areas, driving costs
up, and that supply and demand principles bring prices down in suburbs. To test this
hypothesis, they formulated a plan to obtain an outside food pricing list and to stratify
the city based on income to obtain a random sample of grocery stores. Wesley explained why
they sought an externally created list of grocery items to compare. "Wed really
like to have our representative list of groceries come from a done study on what people
generally buy," he said. "Any list we compiled on our own would be biased"
(WB, Project Report 2). They were also aware of sampling issues. Ingrid discussed why
their initial plan required a random sample. "We need official information of
official income area divisions so that we can objectively compare one grocery store to
another based on income area," she said. "Hopefully, if we are able to obtain
this information, the data will be representative" (Project Report 2). They foresaw
the possibility of confounding variables and explained how to control for them. Scott
summarized these in his project report.
There is the problem that one brand of goods may not be present at one store. So, we
will record the prices of a number of goods and then analyze the ones that were at every
store. So, we will have to test a relatively large number of goods to avoid such
confounding variables as sales and shortages that will have an influence on prices. Also,
we will only go to one type of store (Kroger, most likely, as it is the most common) to
avoid a confounding variable: that our results may have been caused by store type and not
by income level. (TP, Project Report 2)
The next project reports state success at obtaining a grocery list
after exhausting many resources. However, obtaining all the information to generate a
random sample continues to elude them. Ingrid does not express frustration, yet what they
have obtained has been difficult.
When I called the Georgia Department of Labor, I was transferred a gazillion times
before someone finally told me to contact the local census bureau. The lady there said
each county is divided into about 60 tracts, with about 4000 people each, and that it
would be no problem to obtain the median household for each tract. However, she said we
needed to decide which counties we wanted and obtain the geographical tract maps from
Georgia Blueprint Company. (IS, Project Report 3)
They ordered and received these maps only to find out "they dont have any
street on them except for the borders" (IS, Project Report 4). After many phone
calls, Terry describes the process to help this latest problem.
We figured that because there are no streets on the tract maps, we were going to get a
city map and plot both the tracts and the Krogers on it. But, Ingrid called the Census
Bureau and they have a program downtown that will give you the tract when you type in
addresses. We are going there Wednesday after fourth period. (TP, Project Report 5)
The following week they reported more problems. Terry describes what happened.
"Many of our addresses were not included on the tracts because the tract match
program was for residences only and did not count businesses," he wrote. "So any
Kroger that is in a shopping mall, didnt show up. We will locate those on a city map
to determine the tract location" (TP, Project Report 5). However, this did not work
easily either. "We were finally forced to find several Krogers by calling the stores
to verify the exact location, a laborious process (Written Report)." Once they had
the locations of all the stores, they numbered each from 1-67 and generated a random
sample. Satisfied with the design, they split up to gather prices from the randomly
selected stores. After each student had been to a few different stores, they noticed all
the prices were identical. They reported frustration and disappointment (IS, TP, WB,
Project Report 7, Written Report). In their presentation, they stated the analysis they
would have conducted if the data had varied.
Project Summary. These students undertook an involved
process to answer a question of social value. They expressed sincere concern that grocery
store prices are higher in low-income areas where people cannot afford higher prices. They
based this hypothesis on economic principles of supply and demand, and insurance rates.
Determined to conduct a randomized sample, they went to extreme measures to collect random
data from the same grocery chain in various parts of the city. They relentlessly explored
various approaches to divide the city into income-based partitions and choose stores
representing three different income levels: high, medium and low. After this labor
intensive process of designing the experiment, they physically went to the chosen stores
to collect prices for various items. It was at this point they discovered the chain they
had chosen has fixed prices for all the stores in the area regardless of the neighborhood.
It was too late to redo the experiment so they presented their sampling and surveying
techniques.
Project BDL: Fast Food and High School Students
Project Construction. This project received Honorable
Mention in the American Statistical Association (ASA) Project competition (American
Statistical Association, 1997). Initial project reports reveal this groups intent to
investigate fast food restaurants and health issues. David describes their goal. "Our
area of interest is fast food restaurants and nutrition, dealing with their menu
items," he said. "We want to find out which major fast food chain can be
considered the most healthy and least healthy. We also want to survey students regarding
their preferences" (DW, Project Report 2). Beverly discussed the sample and survey.
"We plan to collect nutritional data from each restaurant (how were not
sure)," she wrote. "Then we will select 100 boys and 100 girls from both the
11th and 12th grades based on randomly generated numbers" (BH, Project Report 2).
During our interview, I asked Beverly why they targeted the upper two grades.
"Juniors and seniors can drive so they have more freedom about how often to eat fast
food," she responded (BH, Interview).
They spent the next several weeks gathering nutritional information from 10 fast food
restaurant chains. All three students reported problems gathering this data (BH, DW, LB,
Project Report 3). To obtain information unavailable on the Internet, they telephoned
local restaurants. Simultaneously, they are working on the sampling procedure. Beverly
reports they will not send surveys to other schools as originally planned. In our
interview, I asked her about this decision.
KR: In the fourth project report you refer to reducing the sample by eliminating other
schools and just concentrating on your school. What were the ramifications of this
decision?
BH: Well, first of all, it would have been really hard to get the data from the other
schools because we just didnt trust them to return stuff on time and do what we
really wanted. So in that respect, our data was more thorough from the school we could
study but we knew that in doing that, we couldnt say anything about any population
other than our own school.
They visited the registrars office to obtain homeroom lists and social security
numbers and were told they could not have access to this information. David described
their alternate plan. "As a group, we decided that those numbers were not
necessary," he wrote. "It would be just as easy to take the homeroom list and
just number the students 1-200 or whatever off that list and do the SRS off those numbers
instead of their ID numbers" (DW, Project Report 4). Beverly reported how they
obtained the random sample.
Once we had obtained the homeroom list, we went to the computer lab and scanned the
homeroom lists, so that we could cut and paste until we had separate lists of boys and
girls for each grade. I took the junior lists and Karen took the senior lists to divide up
and pick the SRS. In my spare time on Thursday, I sorted out the guys from the girls and
then numbered them and used the table of random numbers to pick the two SRSs. (BH,
Project Report 4)
After choosing students for the survey, they began work on the survey instrument. David
commented on this process. "We had to take into consideration what type of analysis
would be possible when we receive our SRS results," he wrote (DW, Project Report 5).
Beverly referred to difficulties with the survey. "The survey has been a debate
filled process, but we finally have something we think we can use. We decided we will do a
pilot to try it out" (BH, Project Report 5). In the interview, I asked Beverly why
they piloted the survey instrument. "Because we werent sure if our wording was
okay," she said. "It was really very difficult to decide, even once we had the
ideas for the questions. It was the wording that took us days to do and we still
didnt end up completely correct" (BH, Interview).
During the next week, the circulation of the quarterly campus
newspaper, the Herald, created an unforeseen problem. Beverly explained. "We had the
surveys ready to go out this week," she wrote, "but the Herald that came out on
Monday had a lot of information pertaining to our survey in it, fat grams and calories,
and we agreed it would definitely be confounding if we released the survey now" (BH,
Project Report 6). Lisa describes their reaction to this situation.
This week we had planned to get the surveys handed out, but because of the Herald
article, we decided to wait. Instead, we finalized our list of people to be sampled, gave
Lee the master copy to print out 250 copies, and gave a pilot survey in our class. We
played with the numbers and decided what hypothesis tests we will run and what kind of
relationships we will look for when we get our surveys. We needed to do all this anyway so
the Herald article probably wont make any difference after all. (LB, Project Report
6)
The next few weeks they circulated surveys and organized the data. Data analysis began.
They calculated means, standard deviations, minimums and maximums. They conducted
confidence intervals and hypothesis tests at the 95% confidence level. Analysis included
how many times per week for females versus males, favorite restaurant, student ratings of
how healthy each restaurant is, comparison of frequency versus perception of nutritional
level, and perception of nutritional level versus actual nutritional level. In
Beverlys interview I asked her about any problems they experienced analyzing data.
KR: David is talking about rating the restaurants from one to ten to test each
students perception of how healthy each restaurant is. What statistically is
difficult about what you were trying to do?
BH: Its really subjective. We realized in compiling the information two or three
days before the project was due that we were asking to rate the restaurant against just
that restaurant. And in the end we kind of compared the restaurants to each other. So that
part is really subjective. Theres really no basis for them to base it on other their
perception.
KR: So is there anything you can think of that you would do differently?
BH: Yes, I would go back and rate them, just ask them to rank them in order of preference
rather than rate each one separately on a scale of one to ten. For example, I would say
Subway was the healthiest and Taco Bell was the least healthy. In the end we realized that
was really what we wanted to know but we just didnt know the best about going about
it.
To try and answer this specific research question, they tested the actual ranking
against the students average for significant differences for each restaurant. They
stated overall conclusions in the written report.
No broad conclusions that enveloped every hypothesis test we ran could be found from
our results. Instead, the numbers proved that some restaurants are seen as too healthy,
others perceived as too unhealthy, and only a few are interpreted correctly by students.
These misconceptions are probably related to many variables, including advertising and the
marketing tactics of each restaurant. (Written Report)
The final question of their survey listed one menu item from four different
restaurants. The survey asked respondents to guess the number of fat grams for each item.
To address this portion of their analysis, they began their oral presentation with an
activity. As they were organizing their presentation materials, they offered a
Hardees biscuit to everyone who wanted one (including Lee and me). After everyone
consumed these biscuits, they asked us "How many fat grams do you think were in that
biscuit you just ate?" (Project Presentation). They collected data and organized it
using a stem-and-leaf plot on the board. During the interview, I asked Beverly why they
did this.
KR: Why did you bring biscuits in for everybody to eat when you did your presentation?
BH: As a surprise. To us it was like the Italian salad. People know that biscuits are
fatty. I mean look at them, theyre greasy and goody, yum yum. But when we found out
those biscuits had 21 grams of fat in them, we were floored and thought most other people
would be too.
KR: Where did you get the idea for the presentation to let everybody say how many fat
grams were in them and collect the data? Then later you did the same thing, gathered data
from the class, about the five items you put on the survey. Why did you do this?
BH: Ill take credit for the biscuits. I just realized this right now when talking to
you, in English were taught that its helpful to have a quirky introduction
sentence that will get the interest of the reader and make them want to keep reading. So
we thought if we started off with something that made them say, whoa, then their interest
might be held better for the rest of the material.
KR: Why did you go around the room and let everybody guess and then collect that data?
BH: Part of it is that is what we did on the survey. We also thought they could surprise
them some. If we had said, hey guys theres 21 grams of fat in the biscuit, it would
have, it just wouldnt have been the same. The impact would be stronger if they had
guessed first and they were 10 or 15 grams off and then get the answer.
KR: So do you think when Lee used this same technique on your class all year there ever
some instances where you experienced what you just described?
BH: Im sure we did. I can remember him handing out little sticky tabs that we had to
put our weight, or how far we lived from school on them.
KR: No, I mean if you had to think about something beforehand and then be given the
answer, did you learn something differently?
BH: I cant remember anything specific, but I feel sure that I did. Especially for me
because I know that is the kind of thing I would respond to, a little trick here and
there.
KR: Did you realize that you were imitating his teaching technique?
BH: No, I didnt have a clue. Here I am pulling English metaphors because I had no
idea. But now that I think about it, its obvious that thats what we did. (BH,
Interview)
Numerous times throughout the year Lee collected data from the class to actively
involve students. This group was unaware they modeled his pedagogy.
Project Summary. BDL studied issues related to fast food
consumption and misconceptions among high school students. After devising a method to
obtain a simple random sample from their high school, they wrote and piloted survey
questions. Data analysis included graphing techniques, regression analysis, confidence
intervals and hypothesis testing. During their class presentation, they were unaware that
they modeled one of Lees teaching techniques.
Projects Analyses
I asked one member from each group what they learned from the
project. Each student initially described the project and details related specifically to
their study. I probed them individually seeking to uncover how they learned general
statistical concepts. All four students referred to advantages of conducting statistical
analysis first hand.
Ingrid explained her experience. "Maybe because we were just
sitting there going because of this, because of this, this will work," she said.
"I think it helped because we were constantly thinking about statistics and having to
apply it" (IS, Interview). Fran reflected on real world applications.
A lot of the stat stuff that we did in class
was just a concept, I didnt see how it mattered. We didnt have any great
revelations from the project but we saw how it mattered in the real world. A lot of the
experiments that other people do, theyre just not as easy as they look. Design wise
ours was not too hard. Once we decided what to do, that part was pretty obvious. But the
analysis was not real easy. We really had to think about it and talk about it before we
figured anything out. (FE, Interview)
Gretchen explained how the project was different from studying the concepts in class.
"When you actually do it out, instead of simulating it, you find all the
problems," she said. "When you simulate a list of random numbers there is no
bias, theres no confounding variables. So it just helped identify what those things
really were" (GR, Interview). Beverly expressed an appreciation for statistical
applications in the real world and a deeper understanding of statistical concepts.
KR: What did you learn from the project?
BH: Overall, as far as stats and real life mixed together, how much data is surrounding us
all the time and all the different methods and techniques that we learned are being used
all the time. When we put together our own study, we experienced what others have done who
have put together data. And its tough. The knowledge we learned in the class, we
actually applied it. You can learn anything in class and just forget it a couple of weeks
later. But with the project it was positive reinforcement and basically engraved that
knowledge and techniques into our heads. And it helped us appreciate what companies and
others do that print out stats, it helped us see what they do.
KR: Anything else?
BH: Yes, because there is a difference between the collection of data and the presentation
of data [sic]. To do a whole project, you have to first get the data and then present it
but in the middle you have to sort it and do stuff. So when you are presenting it, you
have to have it organized and make sense. The numerical analysis gave meaning to all the
tools, like the null hypothesis and some of those other symbols. When you put it all
together in a project, thats when it becomes real. That's when it has meaning. (BH,
Interview)
Overall, no patterns emerged relating the effect of a group project on learning
specific statistical concepts. All projects were unique and learning outcomes varied.
However, students from all groups expressed that conducting the analysis did help solidify
their overall statistical understandings. Unfortunately, none of the four targeted
students participated in the writing of their project report. Thus, the effect of writing
was not addressed.
Students Gathering Project Data
There is widespread agreement among statisticians and educators that
students should interact more with data, including collecting their own data (College
Entrance Examination Board, 1997; Hogg, 1992; Moore, 1990; Watkins et al., 1997).
Therefore, the fourth research question addressed how did gathering data effect
students understanding of statistics. I gathered research data from copies of
project reports, transcripts of tape-recorded sessions of project days, and interviews.
Students responses to interview questions provide most of the information addressing
question two. I asked 12 students, "What did you learn from gathering data?"
Overall, five students responded about writing survey questions, four students referenced
the sampling procedure, and seven addressed the collection of data.
Of the six students who referred to the survey, five indicated it was
more difficult than they had expected. Carters reflection reveals that writing
survey items are an integral part of a rigorous statistics project.
I learned how difficult it is to, I learned more about the process of gathering data
[sic]. I learned that you need a whole lot of time to actually just sit down and visualize
what you want to do before you send out a survey, make sure that you dont create the
survey with more biases. So that if there are problems with it, you can say at least that
you didnt cause them and then you can look and examine other things. (CF, Interview)
Others articulated difficulty writing the survey questions. David explained why he was
challenged by this process.
When you are writing a question, after reading the chapter about how wording can
manipulate somebodys answer, looking at a question and seeing 50 different ways that
can be interpreted [sic]. Its kind of frustrating because every word has to be
concrete, no latitude for somebodys own insight at what you are trying to get at.
Each word has to be perfect, get to the point, no interpretation whatsoever and that was
difficult. (DW, Interview)
Beverly was also challenged with writing survey items. Her reflective process revealed
that wording can be critical in designing a survey.
KR: What did you learn about surveys?
BH: How hard it is to make questions to get what you want, trying to figure out what to
put on the dumb piece of paper. It surprised us how easy it was to do the random sampling
and pick the people. I thought that was going to be much more complicated and the survey
would be, heres a question, heres another question and just copy and go. But
it was really very difficult to decide, even once we had the ideas for the questions. It
was the wording that took us days to do and we still didnt end up completely
correct. Even the last thing, we realized that fat grams was a bad choice and we should
have done calories because thats something most people are more familiar with and a
lot of people interpreted it as that. We think that a lot of people read it as calories
instead of fat grams and that may have messed up our results. (BH, Interview)
Hanson revealed another relevant problem with designing survey instruments. His
groups project included subjective questions. Hanson suggested their data was
possibly biased and unreliable.
KR: What did you learn from gathering data?
HF: Setting it up wasnt hard. But making up the surveys, getting them back, typing
them into the spreadsheet was a pain. Its not very easy. If you are doing something
subjective like an opinion poll, there are a lot of answers that you arent sure if
you should use. You cant tell if people are being serious or if it was a joke. That
could be a big cause for error.
KR: So how did it help you learn statistics?
HF: The reason it was hard to get anything concrete is that the answers were so
subjective. Categorizing the answers was subjective. So we could kind of get a general
feel for it, but since it wasnt like a blood test that was either positive or
negative. Just plain numbers are easier to work with instead of yes, no, sometimes type
answers. So sometimes we had to use the same general field when we werent sure
thats what they meant, like are beautician and cosmetologist the same.
Josh was the only student interviewed who did not have trouble writing survey
questions. "Writing the questions wasnt hard," he explained, "because
we knew exactly what we were looking for" (JK, Interview). In general, five students
expressed difficulty writing survey items and one indicated otherwise. Those who found the
process challenging provided different elements that were perplexing.
When asked what they learned from gathering data, four students
referred to the sampling procedure. One thought the simple random sampling process was
easier than expected while two said the opposite. The other student, Ethan, did not refer
to ease or difficulty as he described their sampling procedure concisely and accurately.
KR: How did you choose whom you sent the survey to?
EB: We had a book of all the schools in Georgia and randomly chose pages with the
calculator and then we wrote down every school on that page. Usually there was only one
school on a page and we did 25 generations of a random number. It turned out being pretty
spread out geographically and was random. It would have been difficult to try and stratify
by size. It ended up being a good mix of schools. (EB, Interview)
Lisa and David (who worked on the same project) indicated complications conducting a
random sample. They compared the sampling activity to the classroom experience. "When
we were doing the surveys, I remember the simple random sample and having to do one. It
was different having to do it than just reading about it in class," Lisa said.
"It took a lot more time than I thought it would" (LB, Interview). David agreed
with Lisa.
KR: What did you learn from gathering your own data?
DW: Non response, wording of questions had to be perfect, how having a simple random
sample, having it totally randomized [sic].
KR: Was that part easier or harder than you expected?
DW: Probably harder than I expected because when you think about picking a random sample
out of your classmates, its kind of hard. You cant just go up and pick this guy or
that person. Everything has to be totally randomized. That was a little bit more difficult
than I thought. It was easier reading in the text book and understanding it than actually
do it yourself. (David, Interview)
Beverly was the only student who expressed the notion that sampling process was easier
than she anticipated. "It surprised me how easy it was to do the random sampling and
pick the people," she said (BH, Interview). Overall, only two students expressed the
sampling process as challenging. All but one, however, expressed an appreciation for the
difficulty and the necessity of writing concise, unbiased survey questions.
When asked about collecting data, six students referred to difficulties
obtaining information from outside sources. Adam responded that he needed to take more
initiative and responsibility.
KR: What did you learn from gathering data?
AD: We ran into a lot of problems with the data collection. We talked to department head
here, English department, and wanted the same paper, as many as we could from different
teachers, would she be willing to do it and she said yes [sic]. And she would contact her
teachers. We wanted every grade every level so we could see if there were any trends
across grades. But what ended up happening was she got really busy and lost track of time.
With like a week and a half to go, we had no data. So we just went to all our English
teachers and got what we could from them. So we had three sets of data from one class each
but one from each grade. But all the classes were honors or AP so we didnt get to
see if there was a trend from lower classes and not from ninth grade. Data collection
requires like sustained effort as opposed to expecting people just to comply. You have to
realize that other people, it might not be on their list of high priorities and you have
to make sure you get what you need. Next time, we would probably get permission from the
department head but contact each teacher on our own. And do more follow up to make sure
they are getting stuff done. (AD, Interview)
Carter also recalled problems gathering the information from their participants.
"And then the actual collection of data was a whole lot more difficult than I
imagined because people are so much less predictable than you would like them to be,"
he said. "We learned a lot about that" (CF, Interview). Josh explained the
obstacles his group had obtaining the information they needed to conduct their project.
Few people wanted to participate. It was a lot
of trouble getting people interested. When we called the schools, if they were public we
had to go to the county people and get permission, who then had to call and say it was all
right, then see if that school wanted to participate. It turned out, they would say they
would get back to us and we had to call them again several times. In the end we only got
about 5 schools out of the 60 that we had randomly picked. (JK, Interview)
Ethans group experienced similar problems when seeking to obtain permission prior
to data collection.
If youre going to try and collect the data, be real straightforward about it.
Dont ask people if you can collect the data, just send the packet. We tried to call
to get permission and we got sent all around. We got the best results in terms of
receiving the responses to those we just sent in a nice formal package. (EB, Interview)
Another group had the same difficulty obtaining basic information. They spent several
project days making phone calls and searching the Internet. Finally, they received
permission and drove to the U.S. Census Bureau to access their database. Ingrid recalled
their frustration.
KR: What did you learn from gathering data?
IS: Lots of things. We always assumed that the Internet was this magic place and whatever
you were looking for would be there. That was, we were all sort of familiar with the net
but we kept running into one roadblock after another. We spent the first two weeks just
doing that and not going anywhere. Finally, we started thinking about who could give us
the information we were looking for. Another problem was we didnt have a clear idea
of what we were looking for. We just knew we wanted to divide the city but werent
exactly sure what we wanted. Then we started calling people and that was another adventure
in itself. Its time consuming. Ninety-nine point ninety nine percent were not
willing to put the effort to help you. And most of them didnt have the information
and didnt seem to care. We got transferred everywhere, automated push one, push two.
It was frustrating. We finally go the census bureau and get the stuff we needed and it
went well from there. (IS, Interview)
Only Gretchen indicated that she enjoyed collecting data. She also suggested that the
groups who gathered information on the Internet did not share her experience.
I liked collecting the data and it helped define the whole experiment and bias stuff. I
dont think a lot of people that just got numbers off the Internet, that they quite
understood it the same way I did because I was dealing with it and trying to decide what
to do with information that we were getting. (GR, Interview)
Out of seven students who discussed collecting data, six reported frustrating
experiences. Only one student enjoyed this part of the process. Of the six who reported
frustration, five were male. The only student who enjoyed this process was female.
Overall, students who gathered data using survey instruments and
sampling techniques reported several types of complications. Five indicated writing survey
questions was difficult, two said the sampling procedure was harder then expected, and six
indicated problems gaining assistance while gathering their information. When asked what
they learned from gathering data, all 12 students mentioned at least one aspect of the
overall process. No overall patterns of race, gender, or mathematical abilities emerged.
Concept-Oriented Instruction and the AP Statistics Examination
Members of the AP Statistics Test Development Committee
designed a course that "adheres to the philosophy and methods of modern data
analysis"(College Entrance Examination Board, 1997, p. 9). This process of modern
data analysis involved interacting with data and a mathematical model. To address this
idea pedagogically, the Committee recommended instruction that includes the use of
technology, projects and laboratories, cooperative group problem solving, and writing.
Therefore, the fifth research question asked which components of activity-based,
concept-oriented instruction effect students performance on the AP exam? I asked 12
students questions about the exam and their preparation for it. The components of interest
are those recommended by the AP Statistics Test Development Committee. Each component is
analyzed individually.
The Projects Effect on the Exam
One component of the concept-oriented class that may have impacted
students performance on the AP Exam was their projects. During the interviews, I
asked each student directly if the project helped prepare them for the exam. Two students
said "no," two students indicated an indirect effect, and nine students believed
the project had a positive effect on preparation of the AP exam.
Ingrid and Ethan both expressed the idea of an indirect effect to
describe the impact of the project on preparation for the AP exam. "I think it helped
because we were just sitting there thinking because of this, because of this, this will
work," Ingrid said. " I think it helped because we were constantly thinking
about statistics and having to apply it. But not directly" (IS, Interview). Ethan
also indicated an indirect effect. "I dont know that it directly helped,"
he said, "but I think it helped you recall all the stuff we had done earlier in the
year" (EB, Interview).
Four of twelve students conveyed that the project helped prepare them
on specific parts of the AP exam. One student, Beverly, replied that the project had no
effect, but then explained to the contrary.
KR: Did all of this help prepare you for the exam?
BH: Well, um, not entirely a whole lot. There was one problem that was about fish in a
tank and you had to do a random sample and figure out how to place them in the tanks so
some of them were toward the warmer end and some toward the cooler end in a random way.
That question was a snap because of random sampling. If theres anything we do
understand it was that because did it. We did the numbering, we did the randomization
process. For math, it was a very hands-on process. Also, anything that had to do with
confidence intervals and t-tests because we did six hundred of them in the project. (BH,
Interview)
The other three students replied that the project helped them answer the open-ended
questions, specifically the Free Response question on experimental design and the
Investigative Task. Hansons opinion represents the overall idea that all three of
these students stated. I asked if the project prepared him for the exam.
Yes and no. It helped prepare for the designing an experiment question. It helped for
the investigative task a little bit because you know a little bit more what you are
looking for in a study than just seeing it because youve actually done and tried to
look for something. (HF, Interview)
Three students believed the project directly helped prepare them for the AP exam. Their
responses indicated the project gave them the opportunity to put many statistical ideas in
a larger, more comprehensive framework. "We got to deal with stuff, taking the raw
data, knowing how it was put together, because we were manipulating it ourselves,"
Josh said. "Then putting it into a report and interpreting it, it just really helped
to understand" (JK, Interview). Gretchens response reiterated Joshs idea.
"Yes, the project did help" she said, "because it tied everything wed
been doing all year together" (GR, Interview). Lisa agreed with Josh and Gretchen.
"I think it just really required that we use everything that we had done in
class," she responded. "It just kind of reviewed everything actually" (LB,
Interview).
Overall, out of 12 students asked if the project helped them prepare
for the AP exam, two said no, two stated an indirect effect, three suggested on overall
effect, and the other six pinpointed the exact effect the project had. No gender or race
patterns emerged. However, the two students who stated the project had no effect, Carter
and Fran, were the top mathematical students. The three students who perceived an overall
effect were three of the weakest four mathematically. In a study of the impact of calculus
reform, Ganter (1997) found similar results. She concluded that "students who do not
perform well on traditional tests" (p. 13) were better suited to group work and
long-term projects (Ganter, 1997).
The Classroom Setting
Another component of Lees class that affected student learning
was the layout of the classroom. The room contained six round tables that each sat three
students. The instructor did not assign seats. During the first few weeks, some students
moved around until they found a permanent seat. One student in sixth period moved again in
the winter because of a discipline problem. When Lee gave problems to work in class, the
students frequently asked their neighbors for help. There was no group grading or group
accountability. If they chose to, the setup of the classroom enabled them to work together
at any time during regular class periods.
To determine the effect of group interactions on their learning, I
asked each of the 12 students if they liked sitting at the round tables. One student
expressed a neutral opinion and one student stated a negative attitude. Ten students
shared positive reactions, but 3 of these 10 also stated negative opinions.
Each student that expressed a favorable opinion suggested that the
round tables created a relaxed, more comfortable environment. "It wasnt like a
regular class where you have to sit in an uncomfortable desk," Gretchen stated.
"I guess it was just more relaxed and different. It wasnt the same old
thing" (GR, Interview). "In a way, it was like a sense of community," Fran
said (FE, Interview). "It was more comfortable," Lisa said (LB, Interview).
Beverly elaborated the same idea.
It was a little more informal atmosphere. To me there is something in any classroom
that is a bit stifling about desks, even in classrooms that have straight tables. The
structure of the desks is very rigid, very enclosing. Whereas at tables, its more
open, you have more room to spread out, to be more comfortable, and to be able to situate
yourself to be ready to learn a little more. (BH, Interview)
Since most of the students responded to the physical aspects of the classroom
environment, I prompted them further to pursue if the round tables had an effect on their
learning and preparation for the AP exam. Hanson was the only student who did not think
they engaged in group interaction and that the tables had no effect on his learning.
"We didnt do a whole lot of group work together with the people at your table
during class," he said. "Like he didnt give us sets of problems to do or
anything" (HF, Interview). Ethan expressed a negative reaction to the group dynamics
without seeing any learning benefits. "In sixth period I think the round tables added
to the confusion and lack of math concentration," he said. "It seemed to make
the whole class more relaxed, but I dont think they were a very good thing"
(EB, Interview). Three other students, Adam, Carter and Ingrid, saw advantages and
disadvantages to the round tables. All three said "distracting" but also
referred to the advantages of being able to discuss ideas with classmates.
The remaining seven students believed the round tables contributed to
their learning experiences. In general, they expressed the idea that having a peer to
consult was beneficial. "I learn better than when everyone is in their own desk just
staring at the teacher at the board," Adam said. David also directly referred to
Lees effect.
It was a different atmosphere than just sitting at desks facing the teacher and
listening to him. When we were at our round tables, we could talk to each other and listen
to him at the same time. It felt like we were socializing while we were learning at the
same time. It helped a lot. (DW, Interview)
Gretchen expressed a similar idea. "When he was doing something on the board and
you got lost," she said, "it was easier to look over at Rachel and see what I
was doing wrong" (GR, Interview). Frans response referred to Lees
technique of not directly answering their questions and linked it to the advantages of
being at tables.
He just has a different teaching technique. He is a lot more lax and the tables just
allow a sense of creativity and at the same time we are working toward the same goal. Also
I think he wants us to talk amongst ourselves to figure things out and maybe talk to our
peers to try and work things out. A lot of times he just says, solve this
problem. Doing it by ourselves, sometimes I didnt know what to do. But when
you have other people, you can ask what they are doing. (FE, Interview)
A unique dialogue occurred with Sam. He expressed a deeper understanding of learning
dynamics and connected his idea to the round tables environment.
KR: Did you like sitting at the round tables?
SD: Yes, because you can talk to the people instead of just sitting there. Most of the
time we were talking about statistics but you could talk about something else. I guess
thats not good but when we were talking about statistics then it was useful because
somebody could help you or you could help somebody else. I guess thats more useful
than sitting at desks because sometimes, Lee might not explain it the same way.
KR: If you were the one explaining, did you benefit from that?
SR: I guess a little. I guess I understood it a little bit after I explained it. If you
dont explain it to somebody then you just think you already know it and you
dont really think through all of it. But when you explain it to somebody you really
have to understand every single point about it before you can really explain it to
somebody. (SD, Interview)
When asked if they like sitting at round tables, overall only one student expressed a
completely disfavorable opinion. One student failed to notice the group interactions that
the other ten students saw as advantageous. While three students mentioned the classes
were loud and other students were distracting, these same three students agreed with the
other seven that the round tables provided an environment that was beneficial to their
learning. Three of the best five academic students commented on the positive and negative
elements of the round tables. All five girls responded that sitting at tables provided a
more relaxed, comfortable environment that had a positive impact on learning.
Ganters (1997) study on calculus reform indicated similar results. She concluded
that "reform efforts using cooperative learning and group activities yield especially
positive results for women and minorities" (p. 14). No patterns for minorities
emerged from my study.
Technology
In recent years, pedagogy associated with teaching statistics has
been impacted by the increased availability of technology in the classroom (Dunham &
Dick, 1994; Gordon & Gordon, 1992; Moore, 1990; Shaughnessy, 1992; Watkins et al.,
1997). According to the AP Statistics Course Description, "The AP Stat course depends
heavily on the availability of technology suitable for the interactive investigative
aspects of data analysis" (College Entrance Examination Board, 1997, p. 10). The AP
Statistics Test Development Committee recommended the use of a computer when it is
available. Since they cannot require students to have computers during the exam, the AP
exam questions provide computer output and students are expected to interpret it (College
Entrance Examination Board, 1997). The committee also stated that students "will be
expected to bring a graphing calculator with statistics capabilities to the examination
and to be familiar with its use" (College Entrance Examination Board, 1997, p. 10).
The research site had computer laboratories available during class
time. The instructor scheduled several classes in the "mathematics bay" during
fall quarter. Students were instructed on the use of one statistical analysis package.
They were expected to navigate through descriptive statistics, graphing techniques, and
some forms of interactive analysis. Also, on project days, they had access to the computer
lab when needed. Most of the groups conducted their project analysis using the computer
software. However, the instructor relied primarily on the TI-83 graphing calculator even
though the AP Statistics Test Development Committee recommends use of a computer. His
reasons for this included availability for all students at any time, his students had
prior experience with this calculator, inconvenience of the computer laboratory, and a
strong belief that the TI-83 provides complete statistical analysis for data sets up to
999 observations. In both classes I observed, the TI-83 was utilized every day. Since the
students had extensive experience with this calculator, the instructor easily led them
through complicated transformations, residual analysis using the spreadsheet, and
simulations.
The Computer
To determine the effect of technology on students learning, I questioned the
students about the calculator and the computer lab. When asked if the computer lab helped
them learn, three students indicated they did not use it much and the other nine said it
did not help. Most of those who said the computer lab was not helpful suggested it did the
same things as the calculator. "I dont think theres anything the computer
can do that the calculator cant do except for printing out stuff," Ethan said
(EB, Interview). "It was just a blown up version of the calculator," Sam said.
"It didnt really help that much because the calculator did everything the
computer does" (SD, Interview). David expressed the same idea. "We werent
doing anything that was different than what we can do on our calculator," he said
(DW, Interview). Adam explained his preference of the calculator. "The calculator was
much more useful and user friendly," Adam said (AD, Interview). Hanson indicated the
computer software was difficult. "Minitab was very confusing to me," he said
(HF, Interview). Gretchen explained a unique impression. "All I felt like I was doing
when we did Minitab was just like clicking here and clicking there [sic]," she said.
Even though most students believed the computer was not helpful in
class, 8 of the 12 mentioned that the computer did help them on their projects. "It
was a great help with our project in coming up with visual aids and graphs and stuff like
that," Hanson said (HF, Interview). Josh expressed a similar opinion. "On the
project, Minitab was very useful," he said. "We used it to run the statistics
and print good graphs" (JK, Interview). Lisa also referred to the graphing advantages
of the computer. "I guess it did help for the project," she said, "because
we had to have it all displayed" (LB, Interview). Sam referred to the ability to
analyze large data sets. "It did help on the project when we had lots of data and we
had to analyze it," he said (SD, Interview). Overall, students saw the advantages of
using the computer to generate reports and graphical displays for project presentations.
Otherwise, these students preferred the TI-83 to the computer. There were no gender, race,
or mathematical patterns. Of those who said the computer lab helped on the project, there
were three girls and five boys, five Caucasian, two Indian, one African American, and an
even spread over mathematical abilities.
The Graphing Calculator
To examine the effect of the TI-83 calculator on students learning, I asked
questions regarding the calculator. When asked if the calculator helped them learn
statistics, three said no and nine said yes. Of the three that said no, one indicated an
overall confusion about the use of the calculators statistical functions. "But
it is just as hard for me to learn how to use the calculator than to learn the real
math," Gretchen said (GR, Interview). This student indicated difficulty understanding
how to use Minitab also. Carter suggested that they would have learned the concepts with
or without the calculator.
I think the concepts were stressed pretty well, but I think all the things we needed to
understand about the way curves looked and the theory behind using certain values to
determine things about sets of data, I think that was all pretty well taught. But I
dont think that thats because of or in spite of the calculator. I think that
was something, I think when they showed us the charts, when we would see a normal
distribution curve and would talk about the 99-95-68 thing and how the distributions had
different percentages, I think that is something you could see visually and that would
have been pretty well understood by almost everyone even if we had had to do a couple more
calculations. And it might have, doing all the calculations might have taken away the from
the focus being that broad and general of learning about things like that, but I still
think most of the people in our class would have got a firm grasp on both. (CF, Interview)
Frans opinion was unique. She initially thought the calculator helped, but then
discovered another effective studying technique.
At first I thought it was better to use the calculator. But when I was studying for the
exam, I went back and reread the book. It made a lot more sense to me. When I was doing
the problems, I found myself doing things out manually more. So if I had to go back and do
it, I might do it more by hand first. I probably would not use my calculator as much. (FE,
Interview).
Although these three students indicated the calculator did not help them understand
concepts, their reasons were different. One student was inhibited by technology in
general, one student needed the textbook readings, and the third student believed the
concepts were taught well enough that the calculator neither helped nor hurt. The two that
were not inhibited by technology, Fran and Carter, were the two strongest mathematical
students.
Students who thought the calculators were beneficial emphasized being
able to concentrate on the concepts. Seven students indicated the calculator directly
enabled them to focus on the ideas. I asked Lisa if the calculator helped her learn.
Yes, because I would have been really overwhelmed with all the equations and stuff.
Just plugging them in and doing them [sic]. There was nothing in them that was really
complicated, they were all just adding and subtracting, but to have the calculator do it
for you, you understood more of the big picture instead of getting caught up in having to
compute the standard deviation. (LB, Interview)
Ethan stated a similar idea. "But usually if you had a sense of the large
concepts," he said, "then the calculator cleared up the fog of the details for
you." Josh also expressed this thought. "It did because you could focus more on
what you were learning rather than how to calculate it because the calculator just did it
for you," he said. "And thats, I didnt feel [sic] that was what was
important, was to know how to calculate it but rather what it meant" (JK, Interview).
Three students stated that even though the calculator helped them learn
the concepts, they knew how to work the formulas also. "I wouldnt have been
able to do the course without the calculator," David stated. "But now that I
look back on it, I know how to do everything by hand. But as far as knocking out the real
boring tedious work, the calculator helped a lot" (DW, Interview). Hanson responded a
similar impression. "But on the basic problems you wouldnt have to do all the
drudge work and spend the whole time doing equations by hand. So, it was good," he
said. "And he asked questions that made sure we knew the formulas anyway" (HF,
Interview).
Overall, nine students thought the calculator enabled them to focus on
conceptual development. The two lowest mathematically able students referred directly to
the benefit of being able to concentrate on the concepts. Of the three who indicated the
calculator was not beneficial, one student was challenged with the computer also. The
other two were the top mathematical students and they integrated the calculator with other
learning techniques. No gender or race patterns emerged.
Impact of the Constructivist Teacher
Research suggests teaching practices directly effect student
learning. Cobb states that "teachers actions do influence the problems that
students attempt to solve and thus the knowledge they construct" (Cobb, 1988, p. 92).
The AP Statistics Test Development Committee made recommendations regarding preparation
for the AP exam. In one publication, they encouraged teachers to familiarize their
students with the form and notation of these given formulas (see Appendix K) by making
them accessible to their students at the appropriate time during the course (College
Entrance Examination Board, 1997). In the free response section of the AP stat exam,
students were asked to answer open-ended questions and to complete an investigative task.
The open-ended questions required students to relate different content areas as they
formulated a complete solution to a statistics or probability problem. (College Entrance
Examination Board, 1997).
To probe the effect of Lees teaching on their preparation for the
AP exam, I asked the students several different questions. From this data, two techniques
he utilized emerged. First, throughout the year he challenged students with difficult
questions in class and on the tests. In addition, he completed the AP syllabus material
approximately a month before the AP exam. They spent this time reviewing in general and
emphasizing specific areas where the students needed help. The instructor provided
numerous multiple-choice questions he obtained from various resources. Since most of his
test questions had been in the Free Response format, Lee recognized the students needed
practice with Multiple Choice questions. When asked, "What did the instructor do that
helped you prepare for the AP exam?" eight students mentioned the year end review,
five referred to his tests, and four gave miscellaneous responses. In addition to these
comments, I was able to relate specific pedagogical techniques that had a direct effect on
how they answered one free response question and the investigative task.
Year End Review
Several students indicated the review time before the AP exam was
helpful. "I like how he got the course done early," Josh said. "That left a
good month in the middle between the exam time and when we actually finished the syllabus
to go over everything that we had problems with" (JK, Interview). Sam expressed a
similar opinion. "After we covered everything we went through," he said,
"we did those multiple choice questions and those practice tests. That probably
helped the most" (SD, Interview). Gretchen pointed out that Lee provided them with
multiple choice questions like those on the AP exam. "He gave us a lot of tests to
do, what he thought the exam would be like," she said, "and they were pretty
dead on" (GR, Interview). Two students referred to a reiterative practice process.
Beverly explained.
The last weeks ever since the projects were over, he just ran us through a gamut of
multiple choice questions. In the end, we all thought the multiple choice section on the
AP exam was much easier than we ever expected. I think that has in part to do with that
preparation he provided us with and in part to do with the fact that he just, it was
practice, practice, practice toward the end. (BH, Interview)
David said the same pedagogy was helpful. "Probably hurrying through the year so
we could practice and giving us as many more tests, giving us tests over and over
again," he said (DW, Interview). Overall, 8 of the 12 students interviewed referred
to the review period as helpful in preparation for the AP exam.
Routine Testing
Students also indicated Lees tests were helpful in preparing for
the AP exam. Adam said, "His exams were much harder than the AP exam. That way we
knew we needed to study all year." Ingrid reiterated this impression. "The tests
were really thorough," she said. "I think that really helped because when we got
to the AP exam, it was a breeze. It was so easy compared to his tests" (IS,
Interview). Ethan felt Lees test questions were similar to those on the AP exam.
"I think a lot of his test questions were really helpful," he said. "If you
just went over his tests, that helped" (EB, Interview). Sam stated that "the
multiple choice wasnt as difficult as the questions as we had done in class"
(SD, Interview).
Miscellaneous
While many students referred directly to the review process or Lees
thorough tests, some students mentioned other aspects of Lees teaching. Gretchen
mentioned the project as helpful. "It really tied everything together and that helped
on the exam," she said (GR, Interview). Two students referred to his pedagogy and
implied he taught on a more difficult, challenging level the entire academic year. "I
think he taught on a level that was harder than the exam," Lisa said. "We went
into more detail, especially with probability" (LB, Interview). Carter was able to
articulate the pedagogy that directly helped him.
He basically just told us, not what would be on there, but how to do whatever they
asked us to do. There was nothing on the test that we hadnt seen in class. He
prepared us by giving us examples to work within almost every area. On the exams he gave
us things like the investigative task so we were prepared for that. I think we were
prepared for basically anything they could have thrown at us. I think he taught us
everything we needed to know. He assigned the reading to reinforce it if no one understood
but I think basically just teaching us and giving us worksheets and things like that. And
that was mostly during the end of the year. He taught for most of the first half of the
year and then the last half was worksheets and spot checking what he had taught earlier. I
think that was really helpful. (CF, Interview)
Hanson contributed his success partly to Lees ability to follow the recommended
AP Course Description. He also recognized the importance of the AP syllabus.
He followed a lot of the outline that the AP people gave him and he gave us a copy of
that and made sure that we were very familiar with everything on the outline. We knew all
the terminology and used that as a guide to what he was going to do but he also added a
lot of his own stuff. We had the basics and a little more. (HF, Interview)
In general, the students stated the instructor covered all the material thoroughly,
gave challenging tests, created test problems similar to the free response questions,
followed the AP syllabus, and spent a lot of time reviewing. No patterns of race, gender
or mathematical abilities emerged from this question.
Free Response Problem 3
Attempting to discover the direct effect of Lees pedagogy on
students performance on the AP exam, I probed the students regarding one Free
Response (FR) question and the Investigative Task (IT). In FR question 3, students were
given a scenario and asked to calculate both a probability and a conditional probability
(Appendix C). I chose this question to probe in student interviews because the instructor
consistently used tree diagrams to illustrate a variety of probability concepts (Field
Notes). Each student interviewed was asked how they solved this problem. All 12 students
responded that they used a tree diagram. When asked why they used this specific technique,
each student answered that is what they did in class.
The Investigative Task
Students responses about the IT question (see Appendix C) did not
yield the same consistency. Several students offered a solution to this problem based on a
similar problem the instructor had given them on a test. Ethan was the first to reveal
this prior knowledge.
KR: What did you do to solve this investigative task?
EB: When I did my own model, I ran a piecewise. So I ran the regression and a linear test.
KR: How did you know to try a piecewise function?
EB: One on the questions on our second quarter exam was a piecewise fit. So I just ran
from that. (EB, Interview)
Carter also recalled the similar problem from an in class test. "On the exams he
gave us things like the investigative task," he said, "so were prepared for
that" (CF, Interview). I asked Gretchen how she solved the investigative task.
"If Lee hadnt given us that exam question where we transformed something into
two separate lines, I dont know what I would have done," she said (GR,
Interview).
Eight other students indicated they used the TI-83 to fit an
appropriate model. They all remembered using r and r2 to analyze
their models. Two students transformed the data and three students used residual analysis
to decide which model best fit the data. Two students input the data into their TI-83 and
regenerated all the information that had been supplied as generic computer output. Ingrid
explained how she regenerated the information and then used what the exam provided.
IS: I went ahead and put all this in my calculator, put these lists in. Its nice
looking at this stuff (indicating the computer output) but I really like to be able to
manipulate it myself. I just redid everything.
KR: So even though you had all this generic computer output, you went and regenerated it
and looked at it again?
IS: Yes, and I played with it. Some of the equations were slightly different from the
equations on here so I checked to make sure I had the data exactly right to see where the
difference was there. I couldnt find any reason for a difference, so I went with
their equations. I didnt use mine. (IS, Interview)
Hanson said he was more familiar with the information provided by calculator and had
"a lot of extra time" (HF, Interview) to regenerate the same output that was
provided. Overall, students used different techniques to solve the investigative task
based on what they learned from Lees teaching. Several recalled a similar question
from the second quarter exam and others relied on familiarity with the calculator to find
an appropriate model. No patterns of race, gender or mathematical abilities emerged.
Writing
Student writing ability should be an important component of the
assessment process (College Entrance Examination Board, 1997). Research questions included
investigation of this pedagogical technique. However, the instructor did not require
extensive open-ended writing on tests. Therefore, writing was not probed during the
interviews.
Students Learning in a Concept-Oriented Course
The AP Statistics Test Development Committee described
concept-oriented instruction as an approach that actively involves students in the
learning process (College Entrance Examination Board, 1997). This approach included
"the use of technology, projects and laboratories, cooperative group problem solving
and writing" (College Entrance Examination Board, 1997, p. 10). They suggested that
concept-oriented instruction allows students to construct their own knowledge. They
recommended that teachers structure their course so students can focus on developing their
understanding of statistical concepts, rather than manipulations and formulas. A learning
environment with this structure provided opportunities for students to experience and make
connections with other academic subjects and realistic life examples. In addition, this
type of learning was more important to statistical thinking and resembles what practicing
statisticians experience (Watkins et al., 1997).
Concept-oriented instruction can be regarded as one pedagogical
application of the constructivist learning theory. As previously stated in chapter 2,
constructivism refers to a variety of theories that attempted to explain how students
construct, reconstruct, connect and apply mathematical knowledge. According to Ernest
(1996), constructivist learning theories were currently dominating mathematics education
research.
Borasi (1996) described vignettes that illustrated classroom activities
and experiences that addressed the NCTM Standards and the constructivist learning theory.
Borasis vignettes emphasized components of constructivist-based pedagogy that were
also present in this study. These classroom activities and experiences included an inquiry
approach to teaching, a requirement that students justify their methods, presentation of
problems in realistic contexts, and instructional support provided within flexible
guidelines. Her findings revealed that these strategies empower students to pose and solve
problems, learn to see and appreciate mathematics in their lives, and make
interdisciplinary connections.
Consistent with Borasis (1996) results, students at this research
site were actively involved in a variety of ways. Gathering data in class was common.
Informally structured as groups, they engaged in group problem solving. Use of graphing
calculators, including simulations, was the norm rather than the exception. Discussions
focused on overall understanding of the question and application of the calculators
numerical results. Assigned problems involved interactive, investigative data analysis.
Several components recommended by the AP Statistics Test Development
Committee (College Entrance Examination Board, 1997) and Borasi (1996) emerged from this
study that were relevant to students learning and affected their preparation for the
AP exam. Students at this research site indicated that use of technology, a project, and
group problem solving contributed to the learning process. In addition, students indicated
that specific elements affected their learning. These techniques included a relaxed,
discussion focused class, an emphasis on explaining their answers, and the freedom to
explore their ideas with peers and Lee.
Summary
Student learning in a constructivist, concept-oriented course was
the focus for this study. Students in a private, urban high school were the data source
for this constructivist study on the initial offering of AP Statistics. Data gathered
represented year long observations through field notes, student artifacts, and in depth
interviews. Interview data were collected as quickly as possible following the AP
Statistics exam in May 1997. Other data represented a variety of resources and components
I felt were relevant to a holistic description of the AP Statistics course. Two questions
emerged from the study as parts of the holistic description of the course. Data that
addressed the two emergent questions came from the College Board, ETS, the Chief Faculty
Consultant, the instructor, and the AP Statistics listserv.
Students participated in a group project. Each group formulated a
research question, gathered data, conducted statistical analysis, and presented their
results orally and in a written report. Some groups gathered data using survey instruments
they created. Other groups accessed information from the Internet, the library, or
government agencies. All projects followed the format for and were submitted to the
American Statistical Associations annual national project and poster competition.
Two of Lees groups won Honorable Mention, but only one of the four groups selected
to research won this honor. Four groups were selected to observe in detail. One student
from each of these four groups was selected to interview about the project. Other data
were gathered to investigate the effects of concept-oriented instruction. Twelve students
were interviewed about the components recommended by the AP Statistics Test Development
Committee. Interview questions pertained to gathering data, in class group work, the use
of technology, and the AP Statistics class in general. Interviews were audio taped and
transcribed.
Qualitative analysis software, QSR NUD*IST (Qualitative Solutions &
Research Pty Ltd, 1995), assisted in data management. Data were imported into QSR NUD*IST
(1995) and coded. The AP Statistics Test Development Committees recommended pedagogy
provided the framework for coding data (see Appendix D). Data were analyzed by comparison
and reevaluation. I looked for patterns that described learning processes and exceptions
to these patterns. When necessary, clarification was obtained from students and Lee in
follow up interviews. Field notes, interviews, and student artifacts revealed similar
ideas that satisfied triangulation. To satisfy member checking (Creswell, 1994; Guba &
Lincoln, 1994), Lee reviewed all writings and analysis for accuracy.
Question 1 addressed the initial offering of the AP Statistics course
and described the course in a holistic manner. Included in the description were factors
relevant to the courses creation and implementation, the AP Statistics listserv,
resources for teachers, and overall impressions from the AP Statistics Test Development
Committees members.
The second research question led to investigation of the
instructors role in effectively teaching a concept-oriented AP Statistics course.
Several significant characteristics emerged. Lee stressed concepts, allowed students to
discover and construct their own understandings, introduced topics using activities,
utilized technology extensively, encouraged group problem solving, and assigned a
comprehensive project. For professional development, he attended conferences, contributed
and read the listserv, conducted workshops, and collaborated with other teachers.
With respect to Question 3, no patterns emerged relating the effect of
a group project on learning specific statistical concepts. All projects were unique and
learning outcomes varied. However, students from all groups expressed that conducting the
analysis did help solidify their overall statistical understandings. Students expressed a
variety of advantages related to their active involvement with data. No patterns of race,
gender or mathematical ability emerged.
Question 4 addressed the effect of data gathering. Students who
gathered data using survey instruments and sampling techniques reported several types of
complications. Five indicated that writing survey questions were difficult, two said the
sampling procedure was harder then expected, and six indicated problems gaining assistance
from those surveyed. When asked what they learned from gathering data, all 12 students
mentioned at least one aspect of the overall process. No patterns of race, gender, or
mathematical abilities emerged.
Question 5 asked what components of concept-oriented instruction
affected students preparation for the AP exam. Each component was addressed and
analyzed individually.
When students were asked if the project helped prepare them for the AP
exam, two said no, two stated an indirect effect, three suggested on overall effect, and
the other six pinpointed the exact effect of the project. The two students, Carter and
Fran, who stated the project had no effect were the top mathematical student from each
class. The three students who perceived an overall effect were three of the weakest four
mathematically.
When asked if they like sitting at round tables, only one student
expressed a completely unfavorable opinion. One student failed to notice the group
interactions that the other ten students saw as advantageous. While three students
mentioned that class was loud and other students were distracting, these same three
students agreed with the other seven that the round tables provided an environment that
was beneficial to their learning. All five girls responded that sitting at tables provided
a more relaxed, comfortable environment that had a positive impact on learning. Three of
the best five academic students commented on the positive and negative elements of the
round tables. No race patterns emerged.
Students saw the advantages of using the computer to generate reports
and graphical displays for project presentations. Except for use on the project, these
students preferred the TI-83 to the computer. Nine students thought the calculator enabled
them to focus on conceptual development. The two lowest mathematically able students
referred directly to the benefit of being able to concentrate on the concepts. Of the
three who indicated the calculator was not beneficial, the computer also challenged one of
these students. The other two were the top mathematical students and they integrated the
calculator with other learning techniques. No gender or race patterns emerged.
Examining the teachers impact, students stated the instructor
covered all the material thoroughly, gave challenging tests, created test problems similar
to the free response questions, followed the AP syllabus, and spent a lot of time
reviewing. On two specific free response questions, all 12 indicated utilizing a
pedagogical technique the instructor used repeatedly in class. On the other hand, students
used different techniques to solve the investigative task based on what they learned from
Lees teaching. Several recalled a similar question from the second quarter exam
while others relied on familiarity with the calculator to find an appropriate model. No
patterns of race, gender or mathematical abilities emerged.
Overall, students suggested the group project provided an opportunity
to view statistics holistically. Data gathering was more difficult than any had
anticipated. The project helped the weaker students prepare for the AP exam more than the
mathematically strong students. Almost all enjoyed sitting at round tables and many
indicated the tables provided an environment that made it easy to ask questions. They
preferred the graphing calculator to the computer labs. Lees teaching techniques
encouraged students to develop sound statistical concepts in a relaxed atmosphere. The
next chapter presents discussion, conclusions, and recommendations. |