BOE Packet
Transcript of BOE Packet
-
8/9/2019 BOE Packet
1/27
REGENTS PHYSICS
Wi ll the rigor of the course be compromised?
No. Studies show that students need time to move from their nave conceptions aboutscience to more expert-like views. In addition, students who study fewer topics in greater
depth in high school have higher success in college science than their peers who had a
greater breadth of coverage. Instead of being asked to demonstrate their knowledge abouta wide-range of topics at a superficial level (like the Regents exam), students must show
they have a deep understanding of the essentials.[BLUE Attached: Depth vs. Breadth study]
What is essential to prepare students for college?
The College Board recently identified the knowledge and skills students need to besuccessful in college science. These standards adhere to the more depth, less breadth
approach. I can attest that the physics standards are pedagogically sound they draw fromlarge volume of research on how students learn physics.
[PINK Attached: College Board Standards for College Success]
How w ill students learn physics to obtain a deep understanding of the essentials?
We currently teach physics using Modeling Instruction whenever possible. Frank was trained
in Modeling Instruction at a 2.5 week summer institute at Buffalo State in 2004. Jimattended 2.5 weeks of summer training at Arizona State in 2005. Modeling instruction has
embraced Tony Wagners 7 essential skills long before he wrote the book! Instead of relyingon lectures and textbooks, Modeling Instruction has students design experiments to
determine physics concepts and relationships themselves. Students must reconcile theresults of their experiments with their own (often nave views) of how the world works. They
then present their results to the class so we can come to a consensus. This entire process
takes much more time than a traditional-lecture based approach, but the depth of studentunderstanding and retention is much greater.
[GREEN Attached: Modeling Instruction article]
What types of alternate assessments might students do?
There are a variety of ways students can be assessed besides a paper-and-pencil exam. Ive
included a list of possible projects/assessments that can be used as a culminating activity ina modeling cycle or even given at the start of a unit as motivation to drive instruction
forward. Again, implementing experiences like these for students takes more time thantraditional instruction.
[YELLOW Attached: Sample assessments]
How will you know students are performing at the same level without the exam?I am implementing a criterion-based grading system. Learning goals for teach topic are
clearly laid out and students are graded using a 1-4 rubric for each goal. Every HW, classdiscussion, quiz, project, etc. can be used as evidence to see how well students are
reaching these learning goals. Students are evaluated on eventual mastery and any initialmissteps while exploring the content are not considered. This system ensures I know (and
students know) whether students have the essential skills and knowledge needed for
success in college science.[WHITE Attached: Samples criterion-based grading and rubrics used by students]
-
8/9/2019 BOE Packet
2/27
Depth Versus Breadth: HowContent Coverage in High SchoolScience Courses Relates to LaterSuccess in College ScienceCoursework
MARC S. SCHWARTZ
University of Texas, Arlington, TX 76019, USA
PHILIP M. SADLER, GERHARD SONNERT
Science Education Department, Harvard-Smithsonian Center for Astrophysics,
Cambridge, MA 02138, USA
ROBERT H. TAI
Curriculum, Instruction, and Special Education Department, Curry School of Education,
University of Virginia, Charlottesville, VA 22904, USA
Received 5 March 2008; revised 1 September 2008, 10 October 2008;
accepted 17 October 2008
DOI 10.1002/sce.20328
Published online in Wiley InterScience (www.interscience.wiley.com).
ABSTRACT:Thisstudyrelatesthe performance of collegestudents in introductory science
courses to the amount of content covered in their high school science courses. The sample
includes 8310 students in introductory biology, chemistry, or physics coursesin 55 randomly
chosen U.S. colleges and universities. Students who reported covering at least 1 major topic
in depth, for a month or longer, in high school were found to earn higher grades in college
science than did students who reported no coverage in depth. Students reporting breadth in
their high school course, covering all major topics, did not appear to have any advantage in
chemistry or physics and a significant disadvantage in biology. Care was taken to account
for significant covariates: socioeconomic variables, English and mathematics proficiency,
and rigor of their preparatory high science course. Alternative operationalizations of depth
and breadth variables result in very similar findings. We conclude that teachers should
use their judgment to reduce coverage in high school science courses and aim for mastery
by extending at least 1 topic in depth over an extended period of time. C 2008 Wiley
Periodicals, Inc. Sci Ed 1 29, 2008
Correspondence to: Marc S. Schwartz; e-mail: [email protected] grant sponsor: Interagency Eductional Research Initiative.Contract grant number: NSF-REC 0115649.
C 2008 Wiley Periodicals, Inc.
-
8/9/2019 BOE Packet
3/27
DEPTH VERSUS BREADTH 21
academically weaker students? We systematically investigated the interactions be-
tween performance variables and the depth and breadth variables and found onlytwo interactions significant below the .05 level. Contrary to the main effects analysis
results, the significance of the interactions was not consistent and did not provide
a clear picture of the connections between the outcome and predictors. The results
suggest that the associations for high- and low-achieving students are similar with
respect to depth and breadth of content coverage.4
Students of highly rated teachers. Our survey asked students to rate several teacher
characteristics. If depth and breadth were to a considerable extent correlated with
those teacher characteristics, this would make the results harder to interpret because
of the conundrum of colinearity: that particular teacher characteristics (rather than
depth or breadth of coverage) might be the actual determinants of student outcomes,
and that depth or breadth themselves might merely reflect those teacher charac-
teristics by association. Teacher characteristics, however, were found to be only
minimally correlated with breadth and depth. Among the teacher characteristics,only very weak correlations are found between breadth and the teachers rated abil-
ity to explain problems in several different ways (r = .04). Depth correlated weakly
with the ratings of the teachers subject knowledge (r= .05). It appears that highly
rated teachers are no more likely than others to teach with depth or breadth.
DISCUSSION
The baseline model (Table 2) shows the association between breadth and depth of high
school science curricula and first-course introductory-level college science performance.
The most striking analytical characteristic is the consistency of the results across the three
baseline models, revealing the same trends across the disciplines of biology, chemistry,
and physics. In addition, the contrast of positive associations between depth and perfor-
mance and negative associations between breadth and performance is striking, though notsignificant in all cases. This replication of results across differing disciplines suggests a
consistency to the findings. However, we caution that the baseline model offers only out-
comes apart from the consideration of additional factors that may have some influence on
these associations. The robustness of these associations was put to the test, as additional
factors were included in an extended model with additional analyses.
The extended model, shown in Table 3, included variables that control for variations
in student achievement as measured by tests scores, high school course level (regular,
honors, AP), and high school grades as well as background variables such as parents
educational level, community socioeconomic level, public high school attendance, and
year in college. With the addition of these variables in the extended model, we find that
the magnitude of the coefficients decreased in the majority of instances, but the trends
and their significance remained. Keeping in mind the generalized nature of the analyses
we have undertaken, the most notable feature of these results stems not simply from themagnitude of the coefficients, but rather from the trends and their significance. Here, the
positive associations between depth of study and performance remain significant whereas
the negative association between breadth of study and performance retains its significance
in the biology analysis. Although this association is not significant in the chemistry and
physics analyses, the negative trend is consistent with our result for biology.
4 A significant interaction (p= .03) was found between the math SAT score and depth. In addition, a
second significant interaction (p= .02) was found between breadth and most advanced mathematics grade.
Apart from these two significant interactions, all others were nonsignificant.
Science Education
-
8/9/2019 BOE Packet
4/27
22 SCHWARTZ ET AL.
What these outcomes reveal is that although the choice to pursue depth of study has
a significant and positive association with performance, the choice to pursue breadth ofstudy appears to have implications as well. These appear to be that students whose teachers
choose broad coverage of content, on the average, experience no benefit. In the extended
model, we arrive at these results while accounting for important differences in students
backgrounds and academic performance, which attests to the robustness of these findings.
The findings run counter to philosophical positions that favor breadth or those that advocate
a balance between depth and breadth (Murtagh, 2001; Wright, 2000).
Finally, a particularly surprising and intriguing finding from our analysis indicated that
the depth and breadth variables as defined in this analysis appear to be uncorrelated;
additionally, the interactions between both variables are not significant in either model.
Figure 6 offers an analysis of the outcomes treating breadth and depth as independent
characteristics of high school science curriculum. The first panel reveals that over 40%
of the students in our survey fall within the depth presentbreadth absent grouping,
whereas the other three varied between 14% and 23%. The distribution across these fourgroupings shows that the teachers of students in our survey are making choices about which
topics to leave out and which to emphasize. These choices have consequences. The second
panel indicates that those students reporting high school science experiences associated
with the group depth presentbreadth absent have an advantage equal to two thirds of a
year of instruction over their peers who had the opposite high school experience (Depth
AbsentBreadth Present). This outcome is particularly important given that high school
science teachers are often faced with choices that require balancing available class time
and course content. It appears that even teachers who attempt to follow the best of both
worlds approach by mixing depth and breadth of content coverage do not, on average,
provide an advantage to their students who continue to study science in college over their
peers whose teachers focused on depth of content coverage.
Ratherthan relying solelyon onedefinition of depth andbreadth, we examinedalternative
operationalizations of the breadth and depth variables and replicated the analysis. Thefindings remained robust when these alternative operationalizations were applied.
However, a limitation in our definition of depth and breadth stems from the smallest unit
of time we used in the study to define depth of study, which was on the order of weeks.
Our analysis cannot discern a grain size smaller than weeks. Teachers may opt to study
a single concept in a class period or many within that period. Likewise, teachers might
decide that a single laboratory experiment should go through several iterations in as many
days, while others will cover three different, unrelated laboratories in the same time span.
These differences are beyond the capacity of our analysis to resolve. In the end, our work
is but one approach to the analysis of the concepts of depth and breadth generated from
students self-reports of their high school science classroom experiences.
Findings in Light of Research From Cognitive ScienceMost students hold conceptions that are at odds with those of their teachers or those
of scientists. In general, students cling tenaciously to these ideas, even in the face of
concerted efforts (Sadler, 1998). These misconceptions or alternative conceptions have
been uncovered using several research techniques, but qualitative interviews, traceable to
Piaget, have proven highly productive (Duckworth, 1987; Osborne & Gilbert, 1980). A
vast number of papers have been published revealing student misconceptions in a variety
of domains (Pfunt & Duit, 1994).
Students do not quickly or easily change their nave scientific conceptions, even when
confronted with physical phenomena. However, given enough time and the proper impetus,
Science Education
-
8/9/2019 BOE Packet
5/27
DEPTH VERSUS BREADTH 23
students can revisit and rethink their ideas. This change can often be painstakingly slow,
taking much longer than many teachers allow in the rapid conveyance of content that isthe hallmark of a curriculum that focuses on broad coverage. In the view of Eylon and
Linn (1988), in-depth coverage can elaborate incomplete ideas, provide enough cues to
encourage selection of different views of a phenomenon, or establish a well-understood
alternative (p. 263). Focused class time is required for teachers to probe for the levels of
understanding attained by students and for students to elucidate their preconceptions. It
takes focused time for students to test their ideas and find them wanting, motivating them to
reconstruct their knowledge. Eylon and Linn note, Furthermore, students may hold onto
these ideas because they are well established and reasonably effective, not because they are
concrete. For example, nave notions of mechanics are generally appropriate for dealing
with a friction-filled world. In addition, students appear quite able to think abstractly as
long as they have appropriate science topic knowledge, even if they are young, and even
if their ideas are incomplete. Thus, deep coverage of a topic may elicit abstract reasoning
(p. 290).The difficulty of promoting conceptual growth is well documented in neo-Piagetian
models (Case, 1998; Fischer & Bidell, 2006; Parziale & Fischer, 1998; Schwartz & Sadler,
2007; Siegler, 1998). These researchers argue that more complex representations, such as
those prized in the sciences, require multiple opportunities for construction in addition to
multiple experiences in which those ideas and observations may be coordinated into richer,
more complex understandings of their world. This process is necessarily intensive and time
consuming because the growth of understanding is a nonlinear process that is sensitive to
changes in context, emotions, and degree of practice. The experience of developing richer
understandings is similar to learning to juggle (Schwartz & Fischer, 2004). Learning to
juggle three balls at home does not guarantee you can juggle the same three balls in front of
an audience. Alternatively, learning to juggle three balls does not mean that you can juggle
three raw eggs. Changes in context and variables lead to differences in the relationships
that students have with ideas (both new and old) and their ability to maintain them overtime (Fischer & Pipp, 1984; Fischer, Bullock, Rotenberg, & Raya, 1993). The process
of integrating many variables that scientists consider in scientific models is a foreign and
difficult assignment for anyone outside the immediate field of research.
As just noted, the realization in the cognitive sciences that the learning process is not
linear is an important pedagogical insight. Because learning is a dynamic operation that
depends on numerous variables, leaving a topic too soon deprives students and teachers
the time to experience situations that allow students to confront personal understandings
and connections and to evaluate the usefulness of scientific models within their personal
models.
Implications in Light of High-Stakes Testing
We are currently in the Age of Accountability in U.S. education. The hallmark of thisera is high-stakes standardized testing. The nature and consequences of these examinations
influence the pedagogy that teachers use in the classroom. As Li et al. (2006) observed:
Academic and policy debates seem somewhat remote to practitioners on the frontline of
science education. Science teachers, department heads, and instructional specialists need to
survive and thrive in a teaching environment increasingly driven by standards and measured
by accountability tests. They are the ones who must, here and now, find solutions to the
pressing problems of standards-based reform (p. 5).
Our concern stems from the connection between the extent that high-stakes state ex-
aminations focus on the facts of science, secondary school science teachers will focus
Science Education
-
8/9/2019 BOE Packet
6/27
24 SCHWARTZ ET AL.
their pedagogy on ensuring that students can recite these facts. Clearly, high-stakes ex-
aminations that require recall of unrelated bits of scientific knowledge in the form of factsand isolated constructs will increase the likelihood that teachers will adjust their teaching
methodologies to address these objectives. The more often discrete facts appear on high-
stakes examinations, the more often we imagine that teachers will feel pressured to focus
on breadth of knowledge. Conversely, we feel that the adoption of a different approach in
high-stakes testing that is less focused on the recall of wide-ranging facts but is, instead,
focused on a few widely accepted key conceptual understandings will result in a shift of
pedagogy. In such situations, we envision teachers instructional practice and curricula
designed to offer students greater opportunity to explore the various contexts from which
conceptual understandings emerge. We suspect that the additional focused time will allow
students to recognize (and teachers to challenge) students nave conceptions of nature.
These concerns fall in line with Andersons (2004, p. 1) three conclusions about
standards-based reform in the United States:
The reform agenda is more ambitious than our current resources and infrastructure
will support.
The standards advocate strategies that may not reduce achievement gaps among
different groups of students.
There are too many standards, more than students can learn with understanding in
the time we have to teach science.
Andersons (2004) final conclusion strongly resonates with that of the NRC (2007)
and more specifically with findings, at the international level, by Schmidt et al. (1997,
2005). In a comparison of 46 countries, Schmidt et al. (2005) noted that in top-achieving
countries, the science frameworks cover far fewer topics than in the United States, and
that students from these countries perform significantly better than students in the United
States. They conclude that U.S. standards are not likely to create a framework that developsand supports understanding or coherence, a strategy that encourages the development of
a deeper understanding of the structure of the discipline. By international standards, the
U.S. science framework is unfocused, repetitive, and undemanding (p. 532).
From the perspective of our study, both Schmidt et al. (2005) and Andersons (2004)
conclusions are particularly relevant. Clearly, increasing the quantity of information re-
quired for examination preparation will lead to an increased focus on broader coverage
of course content, an approach that our findings indicate is negatively (or certainly not
positively) associated with performance in subsequent science courses. If teachers know
that they and their students are accountable for more material, then the pressure to focus
on breadth would seem like the natural pedagogical choice to make. Hence, teachers must
decide whether they choose to maximize students test scores or maximize preparation
for success in future study. Although they have considerable feedback concerning the test
scores of their students (from state tests, SATs, ACTs, and AP examinations), they have
almost no knowledge of how the bulk of their students do in college science, save the few
who keep in touch. Moreover, the rare college student who reports back to their high school
science teacher is often the most successful and simply reinforces a teachers confidence in
his or her current methods.
Caveats
There are several concerns we wish to clearly elucidate. A potential criticism of this
study stems from a central element of this analysis, the length of time spent on a topic
Science Education
-
8/9/2019 BOE Packet
7/27
DEPTH VERSUS BREADTH 25
and how this variable might be influenced by the ability level of students to grasp the
material. One might imagine classrooms containing many struggling students actuallyspending more time on particular topics and classes with generally high achieving students
requiring less time to grasp the concepts and quickly moving on to other topics. In this
scenario, depth of content coverage would be an indicator for remedial assistance by the
teacher at the classroom level. However, we assume that students in our samplethose
who went on to take introductory science coursesare typically well above average in
their science abilities. Thus we would expect our depth measure, if it really signified a
remedial scenario, to have a negative impact, if any, on student performance in introductory
college science courses. As it was, we observed the opposite (i.e., depth was associated
with higher performance, even when controlled for student achievement in high school).
This argument suggests that the remedial depth scenario is unlikely.
Another issue in this analysis is the degree to which we might expect other variables in
the FICSS survey to correlate with depth and breadth as defined. We identified one such
item in our survey: How would you best describe learning the material required in your[high school science] course? The respondents were provided with a 5-point rating scale
ranging from A lot of memorization of facts to A full understanding of topics. This
question is constructed in a manner that clearly alludes (at one end of the scale) to a type
of memorization that presumes a cursory or superficial level of understanding. This was
certainly our intention when we wrote this question. However, Ramsden (2003) notes that
the act of memorization may help learners deconstruct the structure and connections in the
body of information they are attempting to commit to memory. Thus, is memorization a
feature of both depth and breadth in learning? On the basis of this more carefully considered
characterization of memorization and taking into account the tone and clear intention of
this questionnaire item, we hypothesized that the responses to this item would have a
weak positive correlation, if any, with depth, and a weak negative correlation, if any, with
breadth. In the analysis, we found the correlation with depth was r = .15 (very weak) and
the correlation with breadth was r =.09, a result commonly considered not correlated.The results in this case suggest that memorization (as a new variable) is orthogonal with
our definition of breadth and depth and is not subsumed by depth or breadth. However, it
remains to be seen how well our definitions hold up as new variables are identified.
Further Research: Looking at Individual Subject Areas
A key issue for further research in the analysis of the constructs of breadth versus depth is
whether there are specific topics that high school teachers should focus on or whether high
school teachers might choose to focus on any topic and still potentially reap an advantage
in terms of students enhanced future performance. In other words, do students perform
better in introductory college science courses if they were exposed to at least one science
topic in depth, regardless of what it was, or does it help them if they specifically studied
topic A in depth, but not if they studied topic B in depth? An analogous argument canbe made regarding breadth. It therefore appears useful to examine the potential effects of
depth in individual subject areas, and of the omission of individual subject areas, in future
research.
CONCLUSION
The baseline model reveals a direct and compelling outcome: teaching for depth is
associated with improvements in later performance. Of course, there is much to consider
in evaluating the implications of such an analysis. There are a number of questions about
Science Education
-
8/9/2019 BOE Packet
8/27
26 SCHWARTZ ET AL.
this simple conclusion that naturally emerge. For example, how much depth works best?
What is the optimal manner to operationalize the impact of depth-based learning? Dospecific contexts (such as type of student, teacher, or school) moderate the impact of depth?
The answers to these questions certainly suggest that a more nuanced view should be
sought. Nonetheless, this analysis appears to indicate that a robust positive association
exists between high school science teaching that provides depth in at least one topic and
better performances in introductory postsecondary science courses.
Our results also clearly suggest that breadth-based learning, as commonly applied in
high school classrooms, does not appear to offer students any advantage when they enroll
in introductory college science courses, although it may contribute to higher scores on
standardized tests. However, the intuitive appeal of broadly surveying a discipline in an
introductory high school course cannot be overlooked. There might be benefits to such a
pedagogy that become apparent when using measures that we did not explore. The results
regarding breadth were less compelling because in only one of the three disciplines were
the results significant in our full model. On the other hand, we observed no positive effectsat all. As it stands, our findings at least suggest that aiming for breadth in content coverage
should be avoided, as we found no evidence to support such an approach.
The authors thank the people who made this large research project possible: Janice M. Earle, Finbarr
C. Sloane, and Larry E. Suter of the National Science Foundation for their insight and support; James
H. Wandersee, Joel J. Mintzes, Lillian C. McDermott, Eric Mazur, Dudley R. Herschbach, Brian
Alters, and Jason Wiles of the FICCS Advisory Board for their guidance; and Nancy Cianchetta,
Susan Matthews, Dan Record, and Tim Reed of our High School Advisory Board for their time
and wisdom. This research has resulted from the tireless efforts of many on our research team:
Michael Filisky, Hal Coyle, Cynthia Crockett, Bruce Ward, Judith Peritz, Annette Trenga, Freeman
Deutsch, Nancy Cook, Zahra Hazari, and Jamie Miller. Matthew H. Schneps, Nancy Finkelstein,
Alex Griswold, Tobias McElheny, Yael Bowman, and Alexia Prichard of our Science Media Group
constructed of our dissemination website (www.ficss.org). We also appreciate advice and interestfrom several colleagues in the field: Michael Neuschatz of the American Institute of Physics, William
Lichten of Yale University, Trevor Packer of the College Board, Saul Geiser of the University of
California, Paul Hickman of Northeastern University, William Fitzsimmons, Marlyn McGrath Lewis,
Georgene Herschbach, and Rory Browne of Harvard University, and Kristen Klopfenstein of Texas
Christian University. We are indebted to the professors at universities and colleges nationwide who
felt that this project was worth contributing a piece of their valuable class to administer our surveys
and their students willingness to answer our questions. Any opinions, findings, and conclusions or
recommendations expressed in this material are those of the authors and do not necessarily reflect
the views of the National Science Foundation, the U.S. Department of Education, or the National
Institutes of Health.
REFERENCES
American Association for the Advancement of Science. (1989). Project 2061: Science for all Americans.
Washington, DC: Author.
American Association for the Advancement of Science. (1993). Benchmarks for science literacy. New York:
Oxford University Press.
Anaya, G. (1999). Accuracy of self-reported test scores. College and University, 75(2), 13 19.
Anderson, C. W. (2004). Science education research, environmental literacy, and our collective future. National
Association for Research in Science Teaching. NARST News, 47(2), 1 5.
Anderson, R. D. (1995). Curriculum reform. Phi Delta Kappan, 77(1), 33 36.
Baird, L. (1976). Using self-reports to predict student performance. Research Monograph No. 7. New York:
College Entrance Examination Board.
Science Education
-
8/9/2019 BOE Packet
9/27
Print Page Educators - Information & Tools For Teachers, Counselors, Higher Education Faculty andAdministrators Home > K12 Services > College Board Standards for College Success
Close x
College Board Standards for College SuccessAbout the College Board Standards for College Success (CBSCS)
The College Board Standards for College Success (CBSCS) define the knowledge and skills students need to
develop and master in English language arts, mathematics and statistics, and science in order to be college and
career ready. The CBSCS outline a clear and coherent pathway to Advanced Placement (AP) and college
readiness with the goal of increasing the number and diversity of students who are prepared not only to enroll in
college, but to succeed in college and 21st-century careers. The College Board has published these standards freely
to provide a national model of rigorous academic content standards that states, districts, schools and teachers may
use to vertically align curriculum, instruction, assessment and professional development to AP and college
readiness. These rigorous standards:
provide a model set of comprehensive standards for middle school and high school courses that lead to
college and workplace readiness;
reflect 21st-century skills such as problem solving, critical and creative thinking, collaboration, and media and
technological literacy;
articulate clear standards and objectives with supporting, in-depth performance expectations to guide
instruction and curriculum development;
provide teachers, districts and states with tools for increasing the rigor and alignment of courses across
grades 6-12 to college and workplace readiness; and
assist teachers in designing lessons and classroom assessments.
Standards Development Process
To guide the standards development process, the College Board convened national committees of middle school
and high school teachers, college faculty, subject matter experts, assessment specialists, teacher education facultyand curriculum experts who had experience in developing content standards for states and national professional
organizations.
The standards advisory committees relied on college-readiness evidence gathered from a wide array of sources to
design and develop the CBSCS. These sources include national and international frameworks such as National
Assessment of Educational Progress (NAEP), Programme for International Student Assessment (PISA), and Trends
in International Mathematics and Science Study (TIMSS); results of surveys and course content analyses from
college faculty regarding what is most important for college readiness; assessment frameworks from relevant AP
exams, the SAT, the PSAT/NMSQT, and College Level Examination Program (CLEP) exams, and selected
university placement programs.
Beginning with the end goal in mind, the committees first defined the academic demands students will face in AP or
first-year college courses in English, mathematics and statistics, and science. After identifying these demands, thecommittees then backmapped to the start of middle school to outline a vertical progression, or road map, of critical
thinking skills and knowledge students need to be prepared for college-level work.
Standards and Curriculum Alignment Services
States and districts are encouraged to use the CBSCS as a guiding framework to strengthen the alignment of their
standards, curriculum and assessments to college readiness. The College Board offers standards and curriculum
alignment services to states and districts, providing independent reviews of standards, curriculum and assessments.
College Board content specialists use established alignment methods and review criteria to analyze the alignment
and offer meaningful findings and recommendations tailored to a states or district's needs.
Page 1 of 2College Board Standards for College Success
10/21/2009http://professionals.collegeboard.com/portal/site/Professionals/menuitem.b6b1a9bc0c561 ...
-
8/9/2019 BOE Packet
10/27
The College Board also uses the CBSCS to align our own curriculum and assessment programs, including
SpringBoard, to college readiness.
Learn More
Please contact Standards and Curriculum Alignment Services at [email protected] or your
regional College Board representative for more information on the CBSCS and our alignment services.
Science (.pdf/4.4M)English Language Arts (.pdf/1.9M)
Mathematics & Statistics (.pdf/535K)
Mathematics & StatisticsAdapted for Integrated Curricula(.pdf/368K)
Mathematics & Statistics Three-Year Alternative for Middle School(.pdf/121K)
Page 2 of 2College Board Standards for College Success
10/21/2009http://professionals.collegeboard.com/portal/site/Professionals/menuitem.b6b1a9bc0c561 ...
-
8/9/2019 BOE Packet
11/27
0 Science educator
Modeling Instruction: An Effective
Model for Science EducationThe authors describe a Modeling Instruction program that places an emphasis
on the construction and application of conceptual models of physical
phenomena as a central aspect of learning and doing science.
Jane Jackson, Larry Dukerich, David Hestenes
IntroductionModeling Instruction is an evolving,
research-based program for high
school science education reform
that was supported by the National
Science Foundation (NSF) from
989 to 2005. The name Modeling
Instruction expresses an emphasis
on the construction and application
of conceptual models of physical
phenomena as a central aspect of
learning and doing science (Hestenes,
987; Wells et al, 995; Hestenes,
997). Both the National Science Education Standards (NRC, 996)
and National Council of Teachers
of Mathematics Standards (NCTM),
as well as Benchmarks for Science
Literacy (AAAS, 993) recommend
models and modeling as a unifying
theme for science and mathematics
education. To our knowledge, no other
program has implemented this theme
so thoroughly.
From 995 to 999, 200 high
school physics teachers participated intwo four-week Leadership Modeling
Workshops with NSF support. Since
that time, 2500 additional teachers from
48 states and a few other nations have
taken summer Modeling Workshops at
universities in many states, supported
largely by state funds. Participants
include teachers from public and
private schools in urban, suburban,
and rural areas. Modeling Workshops
at Arizona State University (ASU) are
the cornerstone of a graduate programfor teachers of the physical sciences.
Recently, Modeling has expanded to
embrace the entire middle/high school
physical science curriculum. The
program has an extensive web site at
http://modeling.asu.edu.
Product: Students Who Can
Think
Modeling Instruction meets or
exceeds NSES teaching standards,
professional development standards,
assessment standards, and content and
inquiry standards.
Modeling Instruction produces
students who engage intelligently in
public discourse and debate about
matters of scientic and technical
concern. Betsy Barnard, a modeler
in Madison, Wisconsin, noticed
a significant change in this area
after Modeling was implemented
in her school: I teach a course inbiotechnology, mostly to seniors,
nearly all of whom had physics the
previous year. When asked to formally
present information to the class aboutcontroversial topics such as cloning
or genetically modied organisms, it
is delightfully clear how much more
articulate and condent they are.
Students in modeling classrooms
experience rst-hand the richness and
excitement of learning about the natural
world. One example comes from
Phoenix modeler Robert McDowell.
He wrote that, under traditional
instruction, when asked a questionabout some science application in a
movie, I might get a few students who
would cite -2 errors, but usually with
uncertainty. Since I started Modeling,
the students now bring up their own
topics not just from movies, but
their everyday experiences. One of
his students wrote, Mr. McDowell, I
was at a Diamondback baseball game
recently, and all I could think of was
all the physics problems involved.
A former student of another modeler,Gail Seemueller of Rhode Island,
described it as follows: She wanted us
to truly LEARN and more importantly
UNDERSTAND the material. I was
engaged. We did many hands-on
experiments of which I can still vividly
remember, three years later.
Kelli Gamez Warble of rural
Arizona, who has taught physics and
Students in modelingclassrooms experiencefrst-hand the richness andexcitement of learning aboutthe natural world.
-
8/9/2019 BOE Packet
12/27
Spring 2008 Vol. 17, no. 1
calculus for a decade using Modeling
Instruction, has had numerous students
whose career choices were inuenced
by Modeling Instruction. She wroteabout discovering several former
students when visiting an ASU
Engineering Day, and all but one were
females. She wrote, As a former
female engineering student myself,
I was gratied but not surprised.
Modeling encourages cooperation
and discourse about complicated
ideas in a non-threatening, supportive
environment. Females who view
science, engineering, and technology
as elds encouraging cooperation
and supportiveness will, I believe,
become much more attracted to these
non-traditional areas.
Excellence
Many modeling teachers have
been recognized nationally. For
example, three users of Modeling
Instruction have received the National
Science Teachers Association (NSTA)
Shell Science Teaching Award.
Numerous modelers have received
the Presidential Award for Excellence
in Math and Science Teaching
(PAEMST). At Modeling Workshops
and related graduate courses for
science teachers at ASU, as well as
at Modeling Workshops across the
United States, teachers learn to impact
students of various backgrounds and
learning styles. Modeling Workshops
and classrooms are thriving centers of
interactive engagement.
The Essence of Modeling
Instruction
The Modeling method of instruction
corrects many weaknesses of the
traditional lecture-demonstration
method, including the fragmentation
of knowledge, student passivity, and
the persistence of nave beliefs about
the physical world. From its inception,
the Modeling Instruction program has
been concerned with reforming highschool physics teaching to make it
more coherent and student-centered,
and to incorporate the computer as an
essential scientic tool.
In a series of intensive workshops
over two years, high school teachers
learn to be leaders in science teaching
reform and technology infusion in
their schools. They are equipped
with a robust teaching methodology
for developing student abilities to
make sense of physical experience,to understand scientic claims, to
articulate coherent opinions of their
own and defend them with cogent
arguments, and to evaluate evidence
in support of justied belief.
More specically, teachers learn
to ground their teaching in a well-
defined pedagogical framework
(modeling theory; Hestenes, 987),
rather than following rules of thumb;
to organize course content aroundscientifc models as coherent units
of structured knowledge; to engage
students collaboratively in making
and using models to describe, explain,
predict, design, and control physical
phenomena; to involve students in
using computers as scientifc tools
for collecting, organizing, analyzing,
visualizing, and modeling real data; to
assess student understanding in more
meaningful ways and experiment with
more authentic means of assessment;
to continuously improve and updateinstruction with new software,
curriculum materials, and insights
from educational research; and
to work collaboratively in action
research teams to mutually improve
their teaching practice. Altogether,
Modeling Workshops provide detailed
implementation of the National
Science Education Standards.
The modeling cycle, student
conceptions, discourseInstruction is organized into
modeling cycles rather than traditional
content units. This promotes an
integrated understanding of modeling
processes and the acquisition of
coordinated modeling skills. The
two main stages of this process
are model development and model
deployment.
T h e f i r s t s t a g e m o d e l
developmenttypically begins
with a demonstration and classdiscussion. This establishes a common
understanding of a question to be
asked of nature. Then, in small groups,
students collaborate in planning and
conducting experiments to answer or
clarify the question. Students present
and justify their conclusions in oral and
written form, including the formulation
of a model for the phenomena in
question and an evaluation of the
model by comparison with data.
Technical terms and representational
tools are introduced by the teacher as
they are needed to sharpen models,
facilitate modeling activities, and
improve the quality of discourse. The
teacher is prepared with a denite
agenda for student progress and guides
student inquiry and discussion in that
direction with Socratic questioning
Students present and justify
their conclusions in oral andwritten form, including theformulation of a model forthe phenomena in questionand an evaluation of themodel by comparison withdata.
-
8/9/2019 BOE Packet
13/27
2 Science educator
and remarks. The teacher is equipped
with a taxonomy of typical student
misconceptions to be addressed as
students are induced to articulate,analyze, and justify their personal
beliefs (Halloun and Hestenes, 985b,
Hestenes et al., 992).
During the second stagemodel
deploymentstudents apply their
newly-discovered model to new
situations to rene and deepen their
understanding. Students work on
challenging worksheet problems in
small groups, and then present anddefend their results to the class. This
stage also includes quizzes, tests, and
lab practicums. An example of the
entire modeling cycle is outlined in
Table .
The teacher is equipped
with a taxonomy of typicalstudent misconceptions tobe addressed as studentsare induced to articulate,analyze, and justify theirpersonal beliefs.
I. Model Development (Paradigm
Lab)A.Pre-lab discussion
Students observe battery-
powered vehicles moving
across the oor and describe
their observations. The
teacher guides them toward
a laboratory investigation to
determine whether the vehicle
moves at constant speed, and
to determine a mathematical
model of the vehiclesmotion.
B. Lab investigation
Students collect position and
time data for the vehicles and
analyze the data to develop a
mathematical model. (In this
case, the graph of position
vs. time is linear, so they do a
linear regression to determine
the model.) Students then
display their results on small
whiteboards and preparepresentations.
C. Post-lab discussion
Students present the results of
their lab investigations to the
rest of the class and interpret
what their model means in
terms of the motion of the
vehicle. After all lab groups
Table 1. Modeling Cycle Example: The Constant VelocityModel
have presented, the teacher
leads a discussion of themodels to develop a general
mathematical model that
describes constant-velocity
motion.
II. Model Deployment
A. Worksheets
Working in small groups,
students complete worksheets
that ask them to apply the
constant-velocity model
to various new situations.They are asked to prepare
whiteboard presentations of
their problem solutions and
present them to the class. The
teachers role at this stage is
continual questioning of the
students to encourage them to
articulate what they know and
how they know it, thereby
correcting any lingering
misconceptions.B. Quizzes
In order to do mid-course
progress checks for student
understanding, the modeling
materials include several
short quizzes. Students
are asked to complete
these quizzes individually
to demonstrate their
understanding of the modeland its application. Students
are asked not only to solve
problems, but also to provide
brief explanations of their
problem-solving strategies.
C. Lab Practicum
To further check for
understanding, students
are asked to complete a lab
practicum in which they need
to use the constant-velocitymodel to solve a real-world
problem. Working in groups,
they come to agreement on
a solution and then test their
solution with the battery-
powered vehicles.
D. Unit Test
As a f i na l check fo r
understanding, students take
a unit test. (The constant-
velocity unit is the rst unitof the curriculum. In later unit
tests, students are required to
incorporate models developed
earlier in the course into their
problem solving; this is an
example of the spiral nature of
the modeling curriculum.)
-
8/9/2019 BOE Packet
14/27
Spring 2008 Vol. 17, no. 1 3
That models and modeling should
be central to an inquiry-based approach
to the study of physics is no surprise.
The NSES state, Student inquiriesshould culminate in formulating
an explanation or model In the
process of answering the questions, the
students should engage in discussions
and arguments that result in the
revision of their explanations.
Traditional instruction often
overlooks the crucial inuence of
students personal beliefs on what
they learn. Force Concept Inventory
(FCI) data (Hestenes et al., 992) show
that students are not easily induced
to discard their misconceptions in
favor of Newtonian concepts. Some
educational researchers have expended
considerable effort in designing and
testing teaching methods to deal with
specic misconceptions. Although
their outcomes have been decidedly
human thought; we use metaphors so
frequently and automatically that we
seldom notice them unless they are
called to our attention. Metaphors areused to structure our experience and
thereby make it meaningful. A major
objective of teaching should therefore
be to help students straighten out
their metaphors. In Modeling, instead
of designing the course to address
specific nave conceptions, the
instructor focuses on helping students
construct appropriate models to
account for the phenomena they study.
When students learn to correctly
identify a physical system, represent
it diagrammatically, and then apply
the model to the situation they are
studying, their misconceptions tend
to fall away (Wells et al., 995).
A key component of this approach is
that it moves the teacher from the role
of authority gure who provides the
knowledge to that of a coach/facilitator
who helps the students construct their
own understanding. Since students
systematically misunderstand mostof what we tell them (due to the fact
that what they hear is ltered through
their existing mental structures),
the emphasis is placed on student
articulation of the concepts.
Laboratory experiences are centered
on experiments that isolate one
concept, with equipment that enables
students to generate good data reliably.
Students are given no pre-printed
list of instructions for doing these
experiments. Rather, the instructorintroduces the class to the physical
system to be investigated and engages
students in describing the system until
a consensus is achieved. The instructor
elicits from students the appropriate
dependent and independent variables
to characterize the system. After
obtaining reasoned defenses from
the students for selection of these
variables, the instructor asks the
students to help design the experiment.
A general procedure is negotiated sothat students have a sense of why
they are doing a particular procedure.
Frequently, multiple procedures arise
as students have access to equipment
that allows them to explore the
relationship in different ways. Lab
teams are then allowed to begin
collecting data.
Students have to make sense of the
experiment themselves. The instructor
must be prepared to allow them to fail.The apparatus should be available
for several days, should they need it.
Students use spreadsheet and graphing
software to help them organize and
analyze their data. After allowing time
to prepare whiteboards to summarize
their ndings, the instructor selects
certain groups to present an oral
account of the groups experimental
procedure and interpretation. Students
use multiple representations to present
their findings, including conciseEnglish sentences, graphs, diagrams,
and algebraic expressions.
After some initial discomfort with
making these oral presentations,
students generally become more at
ease and gradually develop the skills
of making an effective presentation.
They learn how to defend their
views clearly and concisely. These
In Modeling, instead ofdesigning the course toaddress specifc naveconceptions, the instructorfocuses on helping studentsconstruct appropriatemodels to account for thephenomena they study.
The Modeling method
stresses developinga sound conceptualunderstanding throughgraphical and diagrammaticrepresentations beforemoving on to an algebraictreatment of problemsolving.
better than the traditional ones,
success has been limited. Many have
concluded that student beliefs are so
deep-seated that heavy instructional
costs to unseat them are unavoidable.
However, documented success with
the Modeling method suggests that an
indirect treatment of misconceptions is
likely to be most efcient and effective.
(Wells et al., 995)
Cognitive scientists have identied
metaphors as a fundamental tool of
-
8/9/2019 BOE Packet
15/27
4 Science educator
communication skills are valuable
beyond their immediate application
in the physics classroom.
Assessment
Clearly, one role of assessment
is to ascertain student mastery of
the skills and understanding of the
concepts in the unit. An equally
important role is the feedback it
provides the instructor about his or her
curriculum and teaching methods. The
Modeling method stresses developing
a sound conceptual understanding
through graphical and diagrammatic
representations beforemoving on toan algebraic treatment of problem
solving. To be consistent with this
end, the assessment instruments test
students ability to interpret graphs and
draw conclusions, as well as to solve
quantitative problems.
In addition to lab write-ups, in which
students report their ndings using a
format outlined in the curriculum
materials, the lab practicum is used as a
means to check student understanding.
In the practicum, an application
problem is posed to the class as a
whole. The class has a xed period
of time to gure out what model is
appropriate to describe the situation,
decide what measurements to make,
collect and analyze the data, and then
prepare a solution to the problem. This
is used as the culminating activity in
the unit and usually helps the students
review key principles for the unit
test.Whiteboarding is another major
component of assessment. In
whiteboarding, small groups of
students write up their results from
a lab or solutions to a worksheet
problem on a small whiteboard. One
student from the group presents the
whiteboard to the class, responding
to questions from the class and the
instructor. Other group members
are allowed to help if needed. This
is an important assessment tool that
helps the instructor determine how
well students have mastered theconcepts. When one hears fuzzy or
incoherent explanations, one has the
opportunity to help students deal with
their incomplete conceptions before
moving on to the next topic. The two
questions teachers ask most frequently
are, Why do you say that? and
How do you know that? Students
have to account for everything they
do in solving a problem, ultimately
appealing to models developed on the
basis of experiments done in class.Instructors trained in the Modeling
method do not take correct statements
for granted; they always press for
explicit articulation of understanding.
This probing by the teacher often
reveals that the student presenter does
not fully understand the concept (even
when answers are correct). The teacher
then has the opportunity to help the
student correct his or her conceptions
through Socratic questioning.Whiteboarding has other valuable
uses as well. First, it gives students a
chance to reinforce their understanding
of concepts; students often dont know
exactly what they think until theyve
heard themselves express the idea.
Second, students are highly motivated
to understand the question they are
assigned to present. No one enjoys
getting up before a group of peers
with nothing to say. Additionally,
during preparation, the instructor has
the opportunity to help students if noone in the group knows how to do the
problem.
Professional Development
Modeling Instruction places a strong
emphasis on professional development,
both during the workshops and
afterward. The workshops are the
beginning of a process of lifetime
learning. Teachers are encouraged
to network amongst themselves and
to become leaders of reform in theirschools and districts. The ASU web
site and list-serve provide a forum
for communication among Modelers
across the nation and the world.
Since teachers teach as they have
been taught, the workshops include
extensive practice in implementing the
curriculum as intended for high school
classes. Participants rotate through
roles of student and instructor as they
practice techniques of guided inquiry
and cooperative learning. Plans andtechniques for raising the level of
discourse in classroom discussions and
student presentations are emphasized.
The workshops immerse teachers
in the physics content of the entire
semester, thereby providing in-depth
remediation for under-prepared
teachers.
The great success and popularity
of the Modeling Workshops has
generated an overwhelming demand
for additional courses. In response to
this demand, in 200 ASU approved
a new graduate program to support
sustained professional development of
high school physics teachers. Modeling
Workshops are the foundation of the
program, which can lead to aMaster
of Natural Science (MNS) degree.
The National Science Education
Students have to account
for everything they do insolving a problem, ultimatelyappealing to modelsdeveloped on the basis ofexperiments done in class.
-
8/9/2019 BOE Packet
16/27
Spring 2008 Vol. 17, no. 1 5
Standards (NSES) emphasize that
coherent and integrated programs
supporting lifelong professional
development of science teachers areessential for signicant reform. They
state that The conventional view of
professional development for teachers
needs to shift from technical training
for specic skills to opportunities for
intellectual professional growth. The
MNS program at ASU is designed to
meet that need.
Evidence of Effectiveness
Evaluation of Physics Instruction.The Force Concept Inventory (FCI)
was developed to compare the
effectiveness of alternative methods
of physics instruction (Halloun et al.,
985a, Hestenes et al., 992). It has
become the most widely used and
inuential instrument for assessing
the effectiveness of introductory
physics instruction, and has been cited
as producing the most convincing
hard evidence of the need to reform
traditional physics instruction (Hake,998).
The FCI assesses students
conceptual understanding of the
force concept, the key concept in
mechanics. It consists of 30 multiple
choice questions, but there is one
crucial difference between the FCI
questions and traditional multiple-
choice items: distracters are designed
to elicit misconceptions known from
the research base. A student must havea clear understanding of one of six
fundamental aspects of the Newtonian
force concept in order to select the
correct response. The FCI reveals
misconceptions that students bring
as prior knowledge to a class, and it
measures the conceptual gains of a
class as a whole. The FCI is research-
grounded, normed with thousands
of students at diverse institutions.
It is the product of many hours of
interviews that validated distracters,
and it has been subjected to intensepeer review.
Including the survey by Hake
(998), we have FCI data on some
30,000 students of 000 physics
teachers in high schools, colleges
and universities, throughout the
world. This large data base presents
a highly consistent picture, showing
that the FCI provides statistically
reliable measures of student concept
understanding in mechanics. Results
strongly support the following general
conclusions:
Before physics instruction, students
hold naive beliefs about motion and
force that are incompatible with
Newtonian concepts.
Such beliefs are a major determi-
nant of student performance in
introductory physics.
Traditional(lecture-demonstration)
physics instruction induces only a
small change in student beliefs. This
result is largely independent of the
instructors knowledge, experience
and teaching style.
Much greater changes in student
beliefs can be induced with
instructional methods derived
from educational research in, for
example, cognition, alternative
conceptions, classroom discourse,
and cooperative learning.
These conclusions can be quantied.
The FCI is best used as a pre/post
diagnostic. One way to quantify
pre/post gains is to calculate the
normalized gain (Hake, 998). This is
the actual gain (in percentage) divided
by the total possible gain (also in
percentage). Thus, normalized gain =
(%post - %pre)/(00 - %pre). Hence,
the normalized gain can range from
zero (no gain) to (greatest possible
gain). This method of calculating the
gains normalizes the index, so thatgains of courses at different levels
can be compared, even if their pretest
scores differ widely.
A challenge in physicseducation research for morethan a decade has been toidentify essential conditions
for learning Newtonianphysics and thereby devisemore effective teachingmethods.
From pre/post course FCI scores of
4 traditional courses in high schools
and colleges, Hake found a mean
normalized gain of 23%. In contrast,
for 48 courses using interactive
engagement teaching methods (minds-
on always, and hands-on usually),
he found a mean normalized gain of
48%. The difference is much greater
than a standard deviationa highly
signicant result. This would indicate
that traditional instruction fails badly,
and moreover, that this failure cannot
be attributed to inadequacies of the
students because some alternative
methods of instruction can do
much better. A challenge in physicseducation research for more than a
decade has been to identify essential
conditions for learning Newtonian
physics and thereby devise more
effective teaching methods. Modeling
Instruction resulted from pursuing this
challenge. Results from using the FCI
to assess Modeling Instruction are
given below.
-
8/9/2019 BOE Packet
17/27
6 Science educator
How effective is modeling instruction?
Figure summarizes data from a
nationwide sample of 7500 high school
physics students who participated inLeadership Modeling Workshops from
995 to 998. Teachers gave the FCI
to their classes as a baseline posttest
when they were teaching traditionally
(before their rst Modeling
Workshop), and as a pretest
and posttest thereafter.
The average FCI pretest
score was about 26%, slightly
above the random guessing
level of 20%. Figure
shows that traditional high
school instruction (lecture,
demonstration, and standard
laboratory activities) has little
impact on student beliefs,
with an average FCI posttest
score of 42%, well below the 60%
score which, for empirical reasons,
can be regarded as a threshold in
understanding Newtonian mechanics.
This corresponds to a normalized gain
of 22%, in agreement with Hakesresults.
After their rst year of teaching
with the Modeling method, posttest
scores for 3394 students of 66 novice
modelers were about 0 percentage
points higher, as shown in Fig. .
Students ofexpert modelers do much
better. For teachers identified
as expert modelers after two years
in the program, posttest scores for
647 students averaged 69%. This
corresponds to a normalized gain of56%, considerably more than double
the gain under traditional instruction.
After two years in the program, gains
for under-prepared teachers were
comparable to gains in one year for
well-prepared teachers. Subsequent
data have conrmed all these results
for 20,000 students (Hestenes, 2000).
Thus, student gains in understanding
under expert modeling instruction
are more than doubled compared to
traditional instruction.
Student FCI gains for 00 Arizonateachers who took Modeling
Workshops were almost as high as
those for leading teachers nationwide,
even though three-fourths of the
participating Arizona teachers do not
have a degree in physics. Teachers who
implement the Modeling method most
fully have the highest student posttest
FCI mean scores and gains.
External evaluation of ModelingInstruction.The Modeling Instruction
Program was assessed by Prof. Frances
Lawrenz, an independent external
evaluator for the National Science
Foundation. We quote at length from
the four page report on her July 22,
998 site visit, because it describes
the character of the workshops very
well.
This site visit was one of several
over the past four years to sitesin the modeling project I had
the opportunity to observe the
participants working in their concept
groups and presenting to the full
group. I also interviewed most of
the participants, either as part of
a small group or individually, and
interviewed two coordinators of the
workshop The workshop appears
to me to be a resounding success.
My observations revealed a very
conscientious, dedicated, and well-
informed group of teachers activelyinvolved in discussions about the
most effective ways to present physics
concepts to students. They were doing
a marvelous job of combining what
they knew about how children learn
with what they knew about physics
and the modeling approach. The
discussions were very rich.
The interviews confirmed my
observations about the nature of
the group. All the participants were
articulate about physics instruction
and the modeling approach. The
participants reported being pleased
with everything that was happening
at the workshop and spoke in glowing
terms about the facilitators. The
participants felt that the workshop
was well run and that the facilitators
were extremely knowledgeable about
how best to teach physics. They also
commented that the group itself was
an excellent resource. They all couldhelp each other.
I have almost never seen such
overwhelming and consistent
support for a teaching approach. It
is especially surprising within the
physics community, which is known
for its critical analysis and slow
acceptance of innovation. In short,
the modeling approach presented by
the project is sound and deserves to
be spread nationally.
Recognition by U.S. Department of
Education. In September 2000, the
U.S. Department of Education
announced that the Modeling
Instruction Program at Arizona State
University is one of seven K-2
educational technology programs
designated as exemplary or promising,
out of 34 programs submitted to the
42
26
52
26
69
2920
40
60
80
Traditional Novice
Modelers
Expert
Modelers
Pre-test
Post test
FCImeansscores(%)
-
8/9/2019 BOE Packet
18/27
Spring 2008 Vol. 17, no. 1 7
agencys Expert Panel. Selections
were based on the following criteria:
(l) Quality of Program, (2) Educational
Significance, (3) Evidence of
Effectiveness, and (4) Usefulness
to Others. In January 200, a U.S.
Department of Education Expert Panel
in Science recognized the Modeling
Instruction Program as one of onlytwo exemplary K-2 science programs
out of 27 programs evaluated (U.S.
Department of Education, 200).
Long-term implementation. In a
follow-up survey of Leadership
Modeling Workshop graduates,
between one and three years after
they had completed the program,
75% of them responded immediately
and enthusiastically. More than 90%
reported that the Workshops had ahighly signicant inuence on the
way they teach. 45% reported that
their use of Modeling Instruction has
continued at the same level, while
another 50% reported an increase.
(Hestenes, 2000).
Final Thoughts
Instead of relying on lectures and
textbooks, the Modeling Instruction
program emphasizes active student
construction of conceptual andmathematical models in an interactive
learning community. Students are
engaged with simple scenarios to
learn to model the physical world.
Modeling cultivates physics teachers
as school experts on the use of
technology in science teaching, and
encourages teacher-to-teacher training
in science teaching methods, thereby
providing schools and school districts
with a valuable resource for broader
reform.
Data on some 20,000 students showthat those who have been through the
Modeling program typically achieve
twice the gains on a standard test of
conceptual understanding as students
who are taught conventionally.
Further, the Modeling method is
successful with students who have
not traditionally done well in physics.
Experienced modelers report increased
enrollments in physics classes,
parental satisfaction, and enhanced
achievement in college courses across
the curriculum.
Carmela Minaya of Honolulu,
NSTA Shell Science Teaching
Awardee, wrote: The beauty of
Modeling Instruction is that it creates
an effective framework for teachers
to incorporate many of the national
standards into their teaching without
having to consciously do so, because
the method innately addresses many
of the various standards. In a certaincourse, different students may learn
the same material, except they never
learn it in exactly the same way. This
method appeals to all learning styles.
Students cling to whatever works for
them. Although the content is identical
yearly, no two students ever are. The
classroom becomes a dynamic center
for student owned learning.
References
[All references by David Hestenes are
online in pdf format at http://modeling.
asu.edu/R&E/Research.html]
U.S. Department of Education (200).
200 Exemplary and Promising Sci-
ence Programs. Retrieved Dec. 0,
2007 at http://www.ed.gov/ofces/
OERI/ORAD/KAD/expert_panel/
math-science.html
Hake, R. (998). Interactive-engage-
ment vs. traditional methods: A six
thousand-student survey of mechan-
ics test data for introductory physicscourses.American Journal of Physics
66, 64-74.
Halloun, I., & Hestenes, D. (985a). Initial
knowledge state of college physics
students,American Journal of Physics
53, 043-055.
Halloun, I., & Hestenes, D. (985b).
Common sense concepts about mo-
tion,American Journal of Physics 53,
056-065.
Hestenes, D. (987). Toward a modeling
theory of physics instruction,American
Journal of Physics 55, 440-454.Hestenes, D., Wells, M., & Swackhamer,
G. (992). Force concept inventory,The
Physics Teacher 30, 4-58.
Hestenes, D. (997). Modeling methodol-
ogy for physics teachers. In E. Redish
& J. Rigden (Eds.) The changing role
of the physics department in modern
universities. American Institute of
Physics. Part II, 935-957.
Hestenes, D. (2000). Findings of the mod-
eling workshop project, 994 - 2000.
One section of an NSF nal report.
Online in pdf format at http://modeling.asu.edu/R&E/Research.html.
Wells, M., Hestenes, D., & Swackhamer,
G. (995). A modeling method for high
school physics instruction, American
Journal of Physics 63, 606-69.
Jane Jackson is co-director, Modeling
Instruction Program, Department of Physics,
Arizona State University, PO Box 87504,
Tempe, AZ 85287. Correspondence pertaining
to this article may be sent to Jane.Jackson@
asu.edu.
Larry Dukerich is director of Professional
Development in Science, Center for Research
in Education in Science, Mathematics,
Engineering, and Technology (CRESMET),
Arizona State University, Tempe, AZ.
David Hestenes is distinguished research
professor, Department of Physics, Arizona
State University, Tempe, AZ
The Modeling method has
a proven track record ofimproving student learning.
-
8/9/2019 BOE Packet
19/27
ALTERNATE ASSESSMENTS
Students become sports broadcasters for PBS. They must compose a voice-over dubfor a sports video of their choice. Their video must convey the excitement of the
sport and the physics principles observed. To gain knowledge and understanding ofphysics principles necessary to meet this challenge, students work collaboratively on
activities in which they apply concepts of Newton's laws, forces, friction, andmomentum to sporting events.
Students consider themselves members of an engineering team that is developing asystem that will communicate from one room in the school to another. The challenge
is to send and receive, then measure the speed of the transmission. The final reportmust describe both the design and the physics of the system and a discussion of how
the system is better than the methods explored in the chapter. To gain
understanding of science principles necessary to meet this challenge, students workcollaboratively on activities with codes, electricity and magnetism, sound waves, and
light rays. They also use the iterative process of engineering design; refining designs
based on effectiveness and physics concepts.
Students are challenged to design or build a safety device, or system, for protecting
automobile, airplane, bicycle, motorcycle, or train passengers. New laws, increased
awareness, and improved safety systems are explored as students work on thischallenge. They are also encouraged to design improvements to existing systems
and to find ways to minimize harm caused by accidents. To meet this challenge,students engage in collaborative activities that explore motions and forces and the
principles of design technology.
Students are presented with a myth or story about some physical situation (For
example, The winner of a Tug-of-war is the strongest team.) They will work inteams to design, build, run, and analyze experiments that will test the physical ideas
central to the myth. Students will then extend their experiments, exploring thephysical limits of the experiment and applying it to real-world situations. Teams will
then present their findings to the class (and to the world!) in the form of a
Mythbusters video and make conclusions as to whether the situation described bythe myth is physically plausible or even possible.
Students will design and build their own musical instrument from available householditems. Students must analyze the tonal quality for the notes played and make acomparison to the tonal quality of several musical instruments. To gain
understanding of science principles necessary to meet this challenge, students work
collaboratively on activities to learn about wave motion, standing waves, soundwaves, resonance, timbre, and hearing. They also learn to use the iterative process
of engineering design, refining designs based on the physics they learn.
-
8/9/2019 BOE Packet
20/27
Dear Physics Students and Parents,
During this year, you will be learning information related to many topics in physics. In this course,
a non-traditional criterion-based assessment system is used. Rather than using a point system torecord scores on various assignments, quizzes and tests, you must demonstrate your level of
proficiency on various learning goals. For example, instead of getting one grade for a worksheetthat may cover many topics, you will be scored on individual learning goals such as, I can
interpret/draw position vs. time graphs for an object moving with constant velocity. Rubrics thatlist the learning goals and define achievement levels of each will be provided to you and used for
assessment.
Grades will be assigned based on descriptors of achievement only. Grades will not be affected by
issues such as lateness of work, effort, attitude, participation, and attendance. Those factors will bereported separately. Even though there will be many opportunities for cooperative learning, you
will never be assigned group grades.
New information showing additional learning will replace old information. Grades will reflect the
trend in most recent learning. You may re-attempt assessments provided that you havedocumented an effort to engage in additional learning (e.g., tutoring, additional practice, test
corrections, etc.). In addition, an alternative assessment may be accepted if the work is pre-contracted between you (the student) and me (the teacher). There is no deadline for
reassessments. Any grade changes due to reassessments made after the quarter ends will bereflected in the final year-end grade.
For each learning goal and unit of study, you will be scored using the following scale:
4 = Advanced. Indicators include:
I understand the content/skills completely and can explain them in detail. I can explain/teach the skills to another student. I have high confidence on how to do the skills. I can have a conversation about the skills. I can independently demonstrate extensions of my knowledge. I can create analogies and/or find connections between different areas within the sciences or
between science and other areas of study.
My responses demonstrate in-depth understanding of main ideas and of related details.3 = Proficient. Indicators include:
I understand the important things about the content/skills. I have confidence on how to do the skills on my own most of the time, but I need to continue
practicing some parts that still give me problems.
I need my handouts and notes once in a while. I am proficient at describing terms and independently connecting them with concepts. I understand not just the what, but can correctly explain the how and why of scientific
processes.
My responses demonstrate in-depth understanding of main ideas.2 = Developing. Indicators include:
I have a general understanding of the content/skills, but Im also confused about some importantparts.
I need some help from my teacher (one-on-one or small group) to do the skills correctly I do not feel confident enough to do the skills on my own I need my handouts and notebook most of the time. I can correctly identify concepts and/or define vocabulary; however I cannot not make
connections among ideas and/or independently extend my own learning.
My responses demonstrate basic understanding of some main ideas, but significant information ismissing.
-
8/9/2019 BOE Packet
21/27
-
8/9/2019 BOE Packet
22/27
THE BUGGY LAB
I. PROBLEM
Design an experiment to detposition of a toy buggy and t
You have access to rulers, mete
stopwatches.
II . DESIGN
___ Describe your experimenta
and a verbal description.___ State what the independen___ Include how will you vary a
II I. DATA
___ Perform the experiment and
appropriate table.
IV. ANALYSIS___ Graph and determine the n
V. CONCLUSION
___ What pattern did you find fand mathematical descript
___ What is the physical signific
___ What is the physical signific___ Turn your numerical model
You w ill be assessed using
-
8/9/2019 BOE Packet
23/27
-
8/9/2019 BOE Packet
24/27
1ST QUARTER LAB SKILLS
LEARNING GOALS
ASSIGNMENT/ ASSESSMENT & DATE:
INTERIMP
ROGRESS
QUARTERF
INAL
LAB.1 Ican identify the hypothesis to be
tested, phenomenon to be investigated, orthe problem to be solved.
LAB.2 I can design a reliable experimentthat tests the hypothesis, investigates the
phenomenon, or solves the problem.
LAB.3 I can communicate the details of an
experimental procedure clearly andcompletely.
LAB.4 I can revise the hypothesis whennecessary.
LAB.5 I can decide what parameters are to
be measured and can identify independentand dependent variables.
LAB.6 I can record and represent data in ameaningful way.
LAB.7 I can analyze data appropriately.
LAB.8 I can represent data graphically and
use the graph to make predictions.
LAB.9 I can identify a pattern in the data.
LAB.10 I can represent a patternmathematically and provide physical meaning
to the slope and y-intercept.
UNIT SCORE
-
8/9/2019 BOE Packet
25/27
MOMENTUM CONSERVATION AND TRANSFER
LEARNING GOALS
ASSIGNMENT/ ASSESSMENT & DATE:
INTERIMP
ROGRESS
QUARTERF
INAL
MOM.1 I can determine whether
interactions are present for a given situationby considering the motion of objects.
MOM.2 I can calculate the momentum ofan object/system with direction and proper
units.
MOM.3 I can draw an interaction diagramand specify the system and the surroundings.
MOM.4 I can draw and analyze momentumbar charts.
MOM.5 I can use momentum conservation
to solve different problems.
MOM.6 I can apply the property of
reciprocity to the interactions betweenobjects.
MOM.7 I can compute the momentum
transfer into/out of an object/system(impulse) with direction and proper units.
MOM.8 I know the relationship betweenaverage force and the rate of momentum
transfer.
MOM.9 I know the relationship betweenaverage force and time for a given
momentum transfer (impulse).
MOM.10 I can use momentum transfer
(impulse) to solve different problems.
UNIT SCORE
-
8/9/2019 BOE Packet
26/27
1ST 2ND 3RD 4TH INTERIM PROGRESS
LEARNING GOALS
UNIT SCORE
INTERIM GRADE: %
The learning goals I need to improve most are: _________________________________
______________________________________________________________________
What I can do to improve: _________________________________________________
______________________________________________________________________
The learning goals I excel in are: ____________________________________________
______________________________________________________________________
Reasons why I excel in these areas: _________________________________________
______________________________________________________________________
Student Name:
Student Signature:
Parent Signature:
_________________________________
_________________________________
_________________________________
Date: ___________
Date: ___________
Questions/ Comments:
-
8/9/2019 BOE Packet
27/27
1ST 2ND 3RD 4TH QUARTER FINAL
LEARNING GOALS
UNIT SCORE
QUARTER GRADE: %
The learning goals I need to improve most are: _________________________________
______________________________________________________________________
What I can do to improve: _________________________________________________
______________________________________________________________________
The learning goals I excel in are: ____________________________________________
______________________________________________________________________
Reasons why I excel in these areas: _________________________________________
______________________________________________________________________
Student Name:
Student Signature:
Parent Signature:
_________________________________
_________________________________
_________________________________
Date: ___________
Date: ___________
Questions/ Comments: