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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]

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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: schwarma@uta.eduContract grant sponsor: Interagency Eductional Research Initiative.Contract grant number: NSF-REC 0115649.

C 2008 Wiley Periodicals, Inc.

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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.

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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,

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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

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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

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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

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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.

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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.

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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 Standards_Requests@collegeboard.org 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)

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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.

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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.

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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.)

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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

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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.

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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.

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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(%)

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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.

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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.

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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.

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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

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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

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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

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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:

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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: