Peer Instruction: Ten years of experience and...

Peer Instruction: Ten years of experience and resultsCatherine H. Crouch and Eric Mazura)

Department of Physics, Harvard University, Cambridge, Massachusetts 02138

~Received 21 April 2000; accepted 15 March 2001!

We report data from ten years of teaching with Peer Instruction~PI! in the calculus- andalgebra-based introductory physics courses for nonmajors; our results indicate increased studentmastery of both conceptual reasoning and quantitative problem solving upon implementing PI. Wealso discuss ways we have improved our implementation of PI since introducing it in 1991. Mostnotably, we have replaced in-class reading quizzes with pre-class written responses to the reading,introduced a research-based mechanics textbook for portions of the course, and incorporatedcooperative learning into the discussion sections as well as the lectures. These improvements areintended to help students learn more from pre-class reading and to increase student engagement inthe discussion sections, and are accompanied by further increases in student understanding. ©2001

American Association of Physics Teachers.

@DOI: 10.1119/1.1374249#

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I. INTRODUCTION

In recent years, physicists and physics educators havealized that many students learn very little physics from tditional lectures. Several investigators have carefully domented college physics students’ understanding of a varof topics, and have concluded that traditionally taugcourses do little to improve students’ understanding ofcentral concepts of physics, even if the students successlearn problem-solving algorithms.1 Simultaneously, authorsstudying learning in higher education have establishedstudents develop complex reasoning skills most effectivwhen actively engaged with the material they are studyiand have found that cooperative activities are an excelway to engage students effectively.2 In response to thesfindings, many pedagogies have been devised to imprstudent understanding of physics, ranging from modificatiof traditionally taught courses to complete redesigncourses.3

Here we present the results of ten years of teachingtwo introductory physics courses for nonmajors at HarvUniversity with one such method, Peer Instruction~PI!. PeerInstruction modifies the traditional lecture format to incluquestions designed to engage students and uncover diffities with the material.4,5 Peer Instruction has also been ussuccessfully at many other institutions and in upper-lecourses; those results are described elsewhere.6

This paper is structured as follows. Peer Instruction isscribed in Sec. II. In Sec. III, we present data showinggoing improvement of student understanding as we havefined both implementation and materials. We describe threfinements in detail in Sec. IV. Most notably, to help sdents learn more from pre-class reading, we have replareading quizzes with a modified form of the Warm-up excises of the Just-in-Time-Teaching strategy7 and we haveused sections of a research-based mechanics text;8 to in-crease student engagement in the discussion sectionshave incorporated theTutorials in Introductory Physics~Mc-Dermottet al.3! and group problem-solving activities similato those developed by Helleret al.3 One of the strengths oPI is its adaptability to a wide range of contexts and instrtor styles. In Sec. IV we also provide recommendationssuch adaptation, and describe resources available for immenting PI.

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II. METHOD OVERVIEW

Peer Instruction engages students during class throughtivities that require each student to apply the core concebeing presented, and then to explain those concepts tofellow students. Unlike the common practice of asking infomal questions during a lecture, which typically engages oa few highly motivated students, the more structured qutioning process of PI involves every student in the claAlthough one of us~EM! developed PI for use in large lectures, many instructors have found it to be an effectiveproach for engaging students in small classes as well.6

A class taught with PI is divided into a series of shopresentations, each focused on a central point and folloby a related conceptual question, called a ConcepTest~Fig.1!, which probes students’ understanding of the ideaspresented. Students are given one or two minutes to forlate individual answers and report9 their answers to the in-structor. Students then discuss their answers with othersting around them; the instructor urges students to tryconvince each other of the correctness of their own ansby explaining the underlying reasoning. During the discusion, which typically lasts two to four minutes, the instructmoves around the room listening. Finally, the instructor caan end to the discussion, polls students for their answagain ~which may have changed based on the discussi!,explains the answer, and moves on to the next topic.~A moredetailed description of PI appears in Ref. 4.! Students are nograded on their answers to the ConcepTests, but do recesmall amount of credit for participating consistently over tsemester. They also have a strong incentive to participbecause the midterm and final exams include a significnumber of ConcepTest-like questions.10

To free up class time for ConcepTests, and to prepstudents better to apply the material during class, studare required to complete the reading on the topics to be ceredbefore class. Learning from reading is a skill well worthdeveloping, particularly because after college a great deaongoing learning takes place through reading. To help sdents identify and grasp the key points of the reading, as was to provide an incentive for students to actually complthe reading, we give students credit for answering a fquestions designed to help them think about the mate~This will be discussed further in Sec. IV A.!

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III. RESULTS: IMPROVED STUDENT LEARNING

We find in both the algebra- and the calculus-based inductory physics courses11 that our students’ grasp of thcourse material improves according to a number of differmeasures: two standard tests, the Force Concept Invent12

and the Mechanics Baseline Test;13 traditional examinationquestions; and ConcepTest performance, both during cand when tested for retention at the end of the semeAlthough we see the most dramatic differences in studachievement between courses taught with traditional insttion and those taught with PI, we also observe continuimprovement as we refine both pedagogy and ConcepTe

We have improved our implementation of PI as followIn 1993 and 1994, we refined the set of ConcepTests andin-class questioning/discussion strategy. We began usinresearch-based text for one-dimensional mechanics in 198

In 1996, we introduced free-response reading assignm~described in Sec. IV A!, and introduced cooperative learnininto the discussion sections~Sec. IV B!. Further improve-ment of the reading assignments took place in 1998. Becastudents learn from a wide range of activities in the coursis plausible that student learning would continue to improas more components of the course are modified to engstudents more actively.

Over the seven years of results reported from the calcubased course, five different instructors were involved, eusing Peer Instruction with his or her own style; all but oof the instructors had extensive previous experience withditional lecturing.14 Thus the results reported here do ndepend on a single particular instructor.

A. Conceptual mastery

Since 1990, we have given the Force Concept Invent~FCI!12 in our course at the beginning and at the end ofterm. As shown in Table I, we find that the average prescore^Spre& ~before instruction! for the calculus-based coursstays essentially constant over the period tes~1990–1997!.15 Likewise, the difference between the averapretest scores for the algebra-based course in 1998 andis not statistically significant.16

The average posttest score^Spost& ~after instruction! in thecalculus-based course increases dramatically on chanfrom traditional instruction~1990! to PI ~1991!; as shown inFig. 2 and Table I, the average normalized gain

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doubles from 1990 to 1991, consistent with what has bobserved at other institutions upon introducing interacti

Fig. 1. An example of a ConcepTest, taken from Ref. 4.~Answer: 3.!

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engagement instruction~Hake—Ref. 1!. With continued useof PI ~1993–1997!, along with additional improvements tthe course, the normalized gain continues to rise. In 1and 2000 we see high normalized gains teaching the algebased course with PI, while the same course taught traditally in 1999 by a different instructor produced a much lowthough still respectable, average normalized gain.

B. Quantitative problem solving

With PI, quantitative problem solving is de-emphasizedlecture; students learn these skills primarily through discsion sections and homework assignments. One way wesess our students’ quantitative problem-solving skills is wthe Mechanics Baseline Test~MBT!.13 Figure 3 and Table Ishow that the average score on this test in the calculus-bcourse increased from 66% in 1990 with traditional instrution to 72% in 1991 with the introduction of PI, and continued to rise in subsequent years, reaching 79% in 1997.thermore, student performance on the subset of Mquestions that require algebraic calculation also improfrom 62% to 66% on changing from traditional lecturingPI ~also shown in Fig. 3 and Table I!; for both traditionalinstruction and PI, the average score on those questionabout 5% lower than on the MBT overall.17 In the algebra-based course taught with PI, the MBT scores are 68% in1998 and 66% in Fall 2000, consistent with Hake’s findinthat average scores on the MBT are typically about 1lower than the FCI posttest score. The scores on the quatative questions are 59% in Fall 1998 and 69% in Fall 20~No MBT data are available from the traditionally taugalgebra-based course.!

For further comparison of conventional problem-solviskills with and without PI, in the calculus-based course,administered the 1985 final examination, consisting entirof quantitative problems, again in 1991~the first year ofinstruction with PI!. The mean score increased from 63%69%, a statistically significant increase~effect size 0.34!,18

and there are fewer extremely low scores. We also repe

Fig. 2. Average Force Concept Inventory~Ref. 12! normalized gaing& @Eq.~1!# for introductory calculus-based physics, Harvard University, Fall 199Fall 1997~no data available for 1992!, and for introductory algebra-basephysics, Harvard University, Fall 1998–Fall 2000. Open bars indicateditionally taught courses and filled bars indicate courses taught withDotted lines correspond tog&50.23, the typical gain for a traditionallytaught course, andg&50.48, the typical gain for an interactive cours~Hake–Ref. 1!. The average pretest and posttest scores are provideTable I.

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Table I. Force Concept Inventory~FCI! and Mechanics Baseline Test~MBT! results.a

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Calculus-based1990 Traditional ~70%! 78% 8% 0.25 66% 62% 1211991 PI 71% 85% 14% 0.49 72% 66% 171993 PI 70% 86% 16% 0.55 71% 68% 151994 PI 70% 88% 18% 0.59 76% 73% 211995 PI 67% 88% 21% 0.64 76% 71% 181996 PI 67% 89% 22% 0.68 74% 66% 151997 PI 67% 92% 25% 0.74 79% 73% 11

Algebra-based1998 PI 50% 83% 33% 0.65 68% 59% 241999 Traditional ~48%! 69% 21% 0.40 ¯ ¯ 1292000 PI 47% 80% 33% 0.63 66% 69% 12

aThe FCI pretest was administered on the first day of class; in 1990 no pretest was given, so the averag1991–1994 pretest is listed. In 1995 the 30-question revised version was introduced~Ref. 15!. In 1999 nopretest was given so the average of the 1998 and 2000 pretest is listed. The FCI posttest was administetwo months of instruction, except in 1998 and 1999, when it was administered the first week of the follsemester to all students enrolled in the second-semester course~electricity and magnetism!. The MBT wasadministered during the last week of the semester after all mechanics instruction had been completed. Fother than 1990 and 1999, scores are reported for matched samples for FCI pre- and posttest and MBT.are available for 1992~EM was on sabbatical! and no MBT data are available for 1999.

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individual problems from traditional exams on the midtermin the calculus-based course in 1991~results reported in Ref4!. Finally, in the second semester of the algebra-bacourse in Spring 2000~electricity and magnetism!, we in-cluded on the final exam one quantitative problem fromprevious year, when a different instructor had taughtcourse traditionally. We found that the students taught wPI ~Spring 2000,N5155! significantly outperformed the students taught traditionally~Spring 1999,N5178!, averaging7.4 out of 10 compared to 5.5 out of 10~standard deviations2.9 and 3.7, respectively!. The improvement of the PI students over the traditional students corresponds to an esize of 0.57. All measures indicate that our students’ quatative problem-solving skills are comparable to or better ththose achieved with traditional instruction, consistent wthe findings of Thackeret al.19

Fig. 3. Mechanics Baseline Test~Ref. 13! scores for introductory calculusbased physics, Harvard University, Fall 1990–Fall 1997. Average scorentire test~circles! and on quantitative questions~Ref. 17! only ~squares! vsyear are shown. Open symbols indicate traditionally taught coursesfilled symbols indicate courses taught with PI. The dotted line indicaperformance on quantitative questions with traditional pedagogy~1990!.

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C. ConcepTest performance

Students’ responses to the ConcepTests themselvesvide further insight into student learning. We analyzed sdent responses to all of the ConcepTests over an entiremester, and find that after discussion, the number of studwho give the correct answer to a ConcepTest increasesstantially, as long as the initial percentage of correct answto a ConcepTest is between 35% and 70%.~We find that theimprovement is largest when the initial percentage of corranswers is around 50%.4! In addition, the vast majority ofstudents who revise their answers during discussion chafrom an incorrect answer to the correct answer. Figureshows how students change their answers upon discusfor all of the ConcepTests used during the Fall 1997 semter. The answers are categorized as correct both beforeafter discussion~‘‘correct twice’’!, incorrect before and correct after discussion~‘‘incorrect to correct’’!, correct beforeand incorrect after discussion~‘‘correct to incorrect’’!, orincorrect both before and after discussion~‘‘incorrecttwice’’ !. Nearly half of the correct answers given were arived at after discussion, and students changed from cor

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ndsFig. 4. Answers given to all ConcepTests discussed in Fall 1997, catrized as described in the text.


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to incorrect answers during discussion only 6% of the timWe also examined the rate at which individual students gthe correct answer prior to discussion,5 and find that no stu-dent gave the correct answer to the ConcepTests priodiscussion more than 80% of the time, indicating that evthe strongest students are challenged by the ConcepTestlearn from them.

In the algebra-based course, we examined student maof the ideas behind the ConcepTests by testing studenthe end of the semester with free-response conceptual qtions based on ConcepTests but with a new physical conThese questions thus required students to generalizeideas they learned. We find that the number of studentssuccessfully answer these questions~explaining their answercorrectly as well as giving the correct answer! is comparableto the number who answer the ConcepTest correctly adiscussion, and significantly greater than the number wanswer the ConcepTest correctly before discussion, indiing that over the semester, students learn these ideas~Ofcourse, other elements of the course also help studentsthese ideas; this study primarily indicates that studentsvelop and retain real understanding of these concepts, wthey lacked prior to discussion.! These results are presentein more detail elsewhere.20

IV. IMPLEMENTATION

As summarized in Sec. III, we have refined our implemetation of Peer Instruction in three notable ways over theseveral years. We have replaced reading quizzes withclass Web-based assignments designed to help studentsabout the reading; we use a research-based mechanicsthat is written to be read before class, rather than to seprimarily as a reference after lecture; and we have introducooperative activities in the discussion sections. SectiIV A and IV B elaborate on these improvements. SectIV C describes opportunities provided for learning quantitive problem-solving skills, and Sec. IV D describes stragies for motivating students.

Peer Instruction has been successfully adopted by hdreds of instructors at other institutions worldwide, and ocommunication with them indicates that one of the reasfor this widespread adoption is the ease of adapting PI tolocal context.6 An instructor can use ConcepTests developelsewhere, write new questions, or use some of each.choice of questions, the amount of time devoted to equestion, the amount of lecturing, and the number of qutions per class can and should be adapted to best suit aticular context and teaching style. Guidelines for such adtations are given in Secs. IV E and IV F. For coursinvolving teaching assistants~TAs!, strategies for TA train-ing are given in Sec. IV G. Finally, Sec. IV H describes pulicly available resources available for teaching with PI.

A. Reading incentives

In traditional introductory science courses, students geally read the textbook only after the lecturer has coveredtopic ~if ever!. In a course taught with PI, students are epected to prepare for class by reading. This initial informtion transfer through reading allows the lectures to focusthe most important and difficult elements of the reading, phaps from a different perspective or with new examples,provide students with opportunities~in the form of Con-cepTests! to think through and assimilate the ideas. To p


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pare themselves effectively for a PI class, students needan incentive to complete the reading and guidelinesthinking about it before class.

Reading quizzes, which we used early on,4 act as an in-centive to complete the reading but do not help studethink about it. In place of quizzes, in 1996 and 1997, wrequired students to write short summaries of what they reWe found, however, that most students did not write efftive summaries.

The reading incentives we introduced in 1998, and hafound most effective, are an adaptation of the Warmups frthe Just-in-Time Teaching approach.7 A three-question Web-based assignment is due before each class. All three qtions are free response; the first two probe difficult aspectthe assigned reading, and the third asks, ‘‘What did you fidifficult or confusing about the reading? If nothing was dficult or confusing, tell us what you found most interestinPlease be as specific as possible.’’ Students receive cbased on effort rather than correctness of their answwhich allows us to ask challenging questions, and vastlyduces the effort needed to grade the assignments.21 Totalcredit for all of the reading assignments is worth 5% of tstudent’s overall course grade~homework accounts for anadditional 20% and exams for the remaining 75%!.

Access to the students’ responses to these questions athe instructor to prepare for class more effectively; readand thinking about students’ questions gives the instrucinsight into what students find difficult, complementing thinstructor’s ideas about what material needs most emphin class. Time spent preparing is comparable, becauseinstructor can spend less time reviewing other textbooksnotes for ideas on what should be covered, and this sorpreparation produces a class better suited to the studeidentified needs. Student response to these reading asments is particularly positive when their questions areswered~in class or by answers to FAQs posted on the couWeb site!.

B. Cooperative activities in discussion sections

Since 1996, to reinforce the interactive pedagogy oflectures, we have structured discussion sections aroundoperative activities as well. In the mechanics semester,dents attend a weekly two-hour workshop~there is no sepa-rate laboratory period!. Half of the workshop is devoted toconceptual reasoning and hands-on activities through theTu-torials in Introductory Physics3 and half to quantitative problem solving. Cooperative problem-solving activities are dscribed further in the next section.

C. Quantitative problem solving

As discussed in Sec. III, we find our students’ problesolving skills to be at least as good as before implemenPI. To achieve this, some direct instruction in quantitatproblem-solving skills is necessary, and such instructshould help students connect qualitative to quantitatreasoning.22 Students need opportunities to learn not only tideas of physics but also the strategies employed by exproblem solvers; otherwise their main strategy oftencomes finding a worked example similar to the problemhand.

Two components of our course are designed to helpdents learn problem solving: discussion sections~‘‘work-shops’’! and homework. The second half of the worksh


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begins with the instructor solving a problem to illustrate treasoning that goes into successful problem solving;problem is chosen to be challenging without being tedioStudents spend the remainder of the hour working in groon selected problems from the homework.23 The instructorcirculates around the classroom, asking students to exptheir work and helping students through difficulties~by ask-ing questions to lead them to the right answer, rather thangiving answers!. At the end of the week, each student muturn in their own written solutions to the problems, and thhomework solutions are graded individually on correctne

The weekly homework assignments consist of ten prlems, most of which are quantitative rather than conceptWe provide the students at the beginning of the year withandout on problem-solving strategies taken from Heet al.3 and encourage instructors to explicitly use the stfrom the handout in solving the example problems. We aencourage students to attempt the homework beforeworkshop so that they can benefit most from group work

D. Student motivation

It has been established24 that students often require a priod of adjustment to new methods of instruction before thlearning improves. In the same fashion, when learning a nway to grip a tennis racquet, a tennis player is likely to pworse at first, and improve only after becoming comfortawith the new~and presumably better! grip. At such times, itis the coach’s responsibility to encourage the player thatdecline is a normal part of the learning process. Likewisethe classroom, the instructor must not be discouragedcomplaints such as, ‘‘When are we going to do somerealphysics?’’ and must continue to explain to students the rsons that the course is taught this way.25

Peer Instruction requires students to be significantly mactively involved and independent in learning than doeconventional lecture class. It is common for some or mastudents to be initially skeptical about this forminstruction.26 Consequently, proper motivation of the stdents is essential. Motivation takes two forms: grading sdents on conceptual understanding, not just traditional prlem solving, and setting the right tone in class from the s~including explaining the reasons for teaching this way!. In-cluding conceptual questions on exams makes it clearthe instructor is serious about the importance of concepunderstanding; providing equation sheets or making theams open-book so that students do not need to memoequations is also important. Giving an examination earlythe semester is useful to communicate this from the sdistributing copies of past exams with the syllabus can abe helpful. Strategies for setting the right tone are givenPeer Instruction: A User’s Manual.4

Student attitudes to a course taught with PI, as measby student evaluations and by our interactions with studehave differed. In the calculus-based course, EM’s averevaluation score—4.5 on a scale of 1–527—did not changeon introducing PI, and written comments on evaluationsdicated that the majority of students appreciated the intetive approach of the course. For the algebra-based couwhile still good, EM’s average evaluation score dropped snificantly, to 3.4;28 although most students are satisfied wthe course, there are more dissatisfied students than incalculus-based course. Some of this dissatisfaction is nolated to PI; the most frequent complaint about the algebbased course is that it meets at 8:30 a.m.~the calculus-based


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course meets at 11 a.m.!. We also surmise that studentsthe algebra-based course are on average less interestedcourse and more intimidated by the material, since thesedents are primarily nonscience majors; the students incalculus-based course are mostly honors biology or chemtry majors.

We also examined student attitudes by giving the concand reality link clusters from the MPEX29 to the algebra-based course in 1998. For both clusters, we found thatpercentage of favorable responses remained exactly the sfrom the precourse to the postcourse survey~68% for con-cepts and 67% for reality link!, and the percentage of unfavorable responses increased slightly~from 11% to 14% forconcepts and from 12% to 15% for reality link; the remaing responses were neutral!. Thus we find very little changein class attitudes over the semester. In their six-institutstudy, the MPEX authors found a small increase in favoraresponses on the concept cluster and a small to modedecrease in favorable responses on the reality link cluste29

It is important to note that student evaluations and attituare not a measure of student learning; as discussed in Sewe saw high learning gains for the students in the algebbased course in spite of lower perceived satisfaction oveOther instructors report similar experiences.30 Furthermore,research indicates that student evaluations are based heon instructor personality31 rather than course effectivenesWe are nevertheless continuing to try to find strategieswill help motivate more of the students in the algebra-bacourse.

E. ConcepTest selection

Appropriate ConcepTests are essential for success. Tshould be designed to give students a chance to exploreportant concepts, rather than testing cleverness or memand to expose common difficulties with the material. For treason, incorrect answer choices should be plausible,when possible, based on typical student misunderstandiA good way to write questions is by looking at studenexam or homework solutions from previous years to idencommon misunderstandings, or by examining the literaton student difficulties. ConcepTests should be challengbut not excessively difficult; as mentioned previously~Sec.III C and Ref. 4!, 35%–70% of the students should answcorrectly prior to discussion. If fewer than 35% of the stdents are initially correct, the ConcepTest may be ambious, or too few students may understand the relevant ccepts to have a fruitful discussion~at least without somefurther guidance from the instructor!. If more than 70% ofthe students can answer the question correctly alone, thelittle benefit from discussion.

In a course with a large enrollment, it is often easiestthe instructor to poll for answers to multiple-choice quetions. However, open-ended questions can also be poseing a variety of strategies. For example, the instructor cpose a question and ask students to write their answertheir notebooks. After giving students time to answer,instructor lists several answer choices and asks studenselect the choice that most closely corresponds to their oAnswer choices can be prepared ahead of time, or thestructor can identify common student answers by walkaround the room while students are recording their answand prepare a list in real time. This tactic works especiawell when the answer is a diagram or graph.


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It is possible to pose quantitative problems in a simimanner. Students need more than two minutes to worksuch problems individually before discussion. One approis to have students outline the strategy for solving a compmulti-step problem; the instructor then shows a list of psible first steps and asks students which step to choose.~Thiscan lead to interesting discussions, because for many plems, more than one strategy is possible.! The primary chal-lenge in such problems should be to identify the underlyphysics and develop a strategy for solving the probleEquations should be readily available to the students eion the blackboard or in the textbook~if students bring theirbooks to class!.32 If mathematical answer choices are prvided, incorrect choices should be results obtained frmaking likely errors.

F. Time management

We typically devote one-third to one-half of class timeConcepTests and spend the remainder lecturing.~Theamount of time varies from class to class depending ontopic and the difficulty of the material.! Other instructorsmay use only one ConcepTest per class, or may spend nall class time on ConcepTests; regardless of the numbering ConcepTests leaves less time for traditional lecture psentation of material. The instructor therefore has tchoices:~a! discuss in lecture only part of the material tocovered over the semester~and expect the students to leathe remainder from reading, problem sets, and discussections! or ~b! reduce the number of topics covered durithe semester. In the calculus-based course, we opted fofirst strategy. In the algebra-based course, we followedsecond, reducing the number of topics covered10%–15%33 and covering those topics in more depth. Tbest approach depends on the abilities of the students angoals of the course.

To make the most of class time, we streamline the lecing component of class in several ways. Lectures incluvery few derivations; the instructor instead explains the stegy used to obtain a result from its starting point, highliging the strategy and the conceptual significance. Studentsexpected to study derivations outside of class, when theygo at their own pace. If the derivation is not explained win the text, the instructor provides a handout with moretailed comments. Because students are expected to reafore class, less time is spent repeating definitions thatprinted in the textbook. The instructor chooses quantitaexamples for maximum physical insight and minimal algbra, and often works such examples in the process ofplaining a related ConcepTest. Examples that are primamathematical can be presented in small discussion sec~where the instructor can tailor the presentation to the invidual students present and answer their questions!, or stud-ied by students from the text or handouts.

G. Teaching assistant training

In courses involving teaching assistants~TAs!, the TAshave a significant impact on students’ experience. Whmany TAs are excited by the opportunity to engage thstudents more actively, some resist innovation and may cmunicate a negative attitude to the students. To avoidproblem as much as possible, it is vital to motivate TAswell as students.34 Before the course begins, we explainour TAs the reasons for teaching with PI and give them


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data on improved student learning. We also require our Tto attend lecture, both so that they will be best able to hstudents and so that they see PI in action~which often con-vinces skeptical TAs!.

One way to help TAs see the value of PI is to have ththink about and discuss challenging ConcepTests, sothey experience the benefits of discussion. If such CcepTests are related to the course material, this also mthem realize that they don’t know everything already!~Ques-tions on introductory fluid statics and dynamics are usuachallenging for our TAs.! We hold a weekly meeting for outeaching staff, during which we go through the material tocovered the following week in section, emphasizing tpedagogy we wish them to use.

H. Resources

There are a number of resources available for implemeing PI in introductory physics courses~as well as in chemis-try and astronomy courses!. Peer Instruction: A User’sManual4 includes 243 ConcepTests developed for our intductory calculus-based physics for nonmajors, covering mchanics, electricity, magnetism, fluid statics and dynamoscillations and waves, geometrical and physical optics,modern physics. A searchable database of ConcepTestthe Project Galileo Web site~http://galileo.harvard.edu; freeregistration required for access! includes over 800 physicsConcepTests, many developed at other institutions for eialgebra- or calculus-based introductory physics, and sodeveloped for nonintroductory courses. Utilities for this dtabase allow the user to generate class-ready materials,as pages for a course Web site, directly from the databLinks to separate databases of ConcepTests for astronand chemistry are also available. A resource Web site, htgalileo.harvard.edu/galileo/course/index.html, provides aarchive of our course materials, organized in the same mner as our course Web site.

V. CONCLUSIONS

We find that, upon first implementing Peer Instruction, ostudents’ scores on the Force Concept Inventory and thechanics Baseline Test improved dramatically, and their pformance on traditional quantitative problems improvedwell. Subsequent improvements to our implementation,signed to help students learn more from pre-class readand to increase student engagement in the discussiontions, are accompanied by further increases in student unstanding. These results are not dependent on a particulastructor and are seen in both the algebra-based and calcbased courses. Finally, with significant effort investedmotivate students, student reactions to PI are generally ptive, though there are always some students resistant to btaught in a nontraditional manner, and we find more studeare resistant in the algebra-based course than the calcbased course.

ACKNOWLEDGMENTS

The authors would like to thank Professor Michael J. Azand other members of the Physics 1 and 11 teaching stafongoing partnership in developing Peer Instruction and CcepTests; Emily Fair Oster and Cinthia Guzman for h


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with data analysis; and Dr. Paul Callan, Adam Fagen, Pfessor Richard Hake, and Chris Schaffer for helpful discsions.

a!Electronic mail: [email protected] example, see I. Halloun and D. Hestenes, ‘‘The initial knowledge sof college physics students,’’ Am. J. Phys.53 ~11!, 1043–1055~1985!; L.C. McDermott, ‘‘Millikan Lecture 1990: What we teach and whatlearned—Closing the gap,’’ibid. 59, 301–315 ~1991!; R. R. Hake,‘‘Interactive-engagement vs. traditional methods: A six-thousand-studsurvey of mechanics test data for introductory physics courses,’’ibid. 66~1!, 64–74~1998!.

2D. W. Johnson, R. T. Johnson, and K. A. Smith,Active Learning: Coop-eration in the College Classroom~Interaction Book Company, Edina, MN1991!; R. T. Johnson and D. W. Johnson, ‘‘Cooperative learning andAchievement and Socialization Crises in Science and Mathematics Crooms,’’ from Students and Science Learning: Papers from the 1987tional Forum for School Science~AAAS, Washington, DC, 1987!, andreferences therein.

3Examples include L. C. McDermott, P. S. Schaffer, and the UniversityWashington PERG,Tutorials in Introductory Physics~Prentice–Hall, Up-per Saddle River, NJ, 1998!; Workshop Physics~developed by P. W.Laws, R. Thornton, D. Sokoloff, and co-workers, and published by JWiley!; Active Learning Problem Solving Sheets~developed by A. vanHeuvelen, Ohio State University!; and numerous forms of Socratic dialogue, as in R. R. Hake, ‘‘Socratic Pedagogy in the Introductory PhyLab,’’ Phys. Teach.30, 546–552~1992!, or group problem solving, as inPatricia Heller, Ronald Keith, and Scott Anderson, ‘‘Teaching problsolving through cooperative grouping. Group versus individual probsolving,’’ Am. J. Phys.60 ~7!, 627–636~1992!, and Patricia Heller andMark Hollabaugh, ‘‘Teaching problem solving through cooperative groing. 2. Designing problems and structuring groups,’’ibid. 60 ~7!, 637–644~1992!. Materials for these innovations are available by contactingpublishers or the developers; information on several innovations isavailable at http://galileo.harvard.edu.

4Eric Mazur, Peer Instruction: A User’s Manual~Prentice–Hall, UpperSaddle River, NJ, 1997!. Additional information and resources for PI cabe found at http://galileo.harvard.edu.

5Catherine H. Crouch, ‘‘Peer Instruction: An Interactive ApproachLarge Classes,’’ Opt. Photonics News9 ~9!, 37–41~September 1998!.

6Adam P. Fagen, Catherine H. Crouch, Tun-Kai Yang, and Eric Ma‘‘Factors That Make Peer Instruction Work: A 700-User Survey,’’ tagiven at the 2000 AAPT Winter Meeting, Kissimmee, FL, January 20and ‘‘Peer Instruction: Results From a Range of Classrooms’’~unpub-lished!.

7Gregor Novak, Evelyn Patterson, Andrew Gavrin, and Wolfgang Chtian, Just-in-Time Teaching: Blending Active Learning and Web Techogy ~Prentice–Hall, Upper Saddle River, NJ, 1999!, and http://webphysics.iupui.edu/jitt/jitt.html.

8Since 1995, we have replaced textbook readings on one-dimensionachanics with a draft text written by Eric Mazur, in which concepts aintroduced prior to the mathematical formalism, and many research fiings of typical student difficulties are directly addressed in the text.1998 and 2000 this text was used for all topics in mechanics inalgebra-based course.

9Methods for polling for student answers include a show of hands or flacards, classroom network systems, and scanning forms. A discussiothe pros and cons of each of these methods is given in Ref. 4; wescanning forms combined with a show of hands in 1991 and classrnetwork systems thereafter. We did not see any significant changestudent learning on introducing the classroom network system, andthe main advantages of the network are anonymity of student respoand data collection; our experience indicates that the success of Pestruction does not depend on a particular feedback method.

10Exam questions are free-response and graded primarily on the qualithe student’s explanation of the answer. In class, we typicallymultiple-choice ConcepTests, for ease of polling students for theirswers.

11The ‘‘algebra-based’’ course involves a very small amount of singvariable calculus, primarily derivatives and an occasional integral, insecond semester~electricity & magnetism!. The students in this courshave less facility with mathematical problem solving than in the calcubased course.

12The FCI is a test of conceptual understanding of mechanics, writte


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ordinary language so that it can be given before as well as after mechainstruction. The original version is published in D. Hestenes, M. Weand G. Swackhammer, ‘‘Force Concept Inventory,’’ Phys. Teach.30 ~3!,141–151~1992!. The test was revised in 1995 by I. Halloun, R. R. HakE. Mosca, and D. Hestenes; the revised version is printed inPeer Instruc-tion: A User’s Manualand can also be obtained from Professor Hesteat Arizona State University. For nationwide data that have been gathon student performance on the test, see Hake~Ref. 1!. To maintain thevalidity of the tests, we do not use materials in class that duplicatequestions.

13D. Hestenes and M. Wells, ‘‘A Mechanics Baseline Test,’’ Phys. Tea30 ~3!, 159–166~1992!. This test is available from the same sources asFCI ~Ref. 12!.

14In 1990, 1993, and 1994, the calculus-based course was co-taught byMazur and William Paul; in 1995, the course was taught by Eric Mazur1991 and 1996, the course was co-taught by Michael J. Aziz andMazur; and in 1997, the year in which the highest FCI gains weretained, the course was co-taught by Michael J. Aziz, Catherine H. Croand Costas Papaliolios. Leadership of class periods was divided eqamong co-instructors, with each instructor taking charge of the same nber of classes. All instructors used Peer Instruction beginning in 1991

15In 1994 we changed from the original~29-question! version of the FCI tothe revised~30-question! version. An informal e-mail survey on the listserv PhysLrnR found that at institutions which have given the FCI fonumber of years, instructors typically see both pretest and posttest sdrop by roughly 3% on changing to the revised version. We saw this din our pretest but not in our posttest scores. We thank Professor LMcCullough of the University of Wisconsin-Stout for telling us about thsurvey.

16A t-test ~two-tailed! was performed to determine the likelihood that thdifference in average pretest scores is due to real differences betweepopulations of students rather than simply variation within the populatof students. Thep value was 0.26; ap value of 0.05 or less is generallyagreed to indicate a statistically significant difference.

17The questions we identified as significantly quantitative are numbers 912, 17, 18, 23, 24, and 25~eight in all!.

18The exam distributions are published in Fig. 2.8 of Mazur~Ref. 4, p. 17!.A t-test was performed to determine the likelihood that this increasemean score was simply due to variation within the population of studerather than genuine improvement in understanding. Thep value was 0.001,well below the threshold of 0.05 for statistical significance, indicatingstatistically significant increase in mean score.

19B. Thacker, E. Kim, K. Trefz, and S. M. Lent, ‘‘Comparing problemsolving performance of physics students in inquiry-based and traditiointroductory physics courses,’’ Am. J. Phys.62, 627–633~1994!.

20Catherine H. Crouch, John Paul Callan, Nan Shen, and Eric Mazur, ‘‘CcepTests in Introductory Physics: What Do Students Get Out of ThemAmerican Association of Physics Teachers Winter 2000 Meeting, Kissmee, FL, January 2000; ‘‘Student Retention of ConceptTests’’~unpub-lished!; for transparencies and preprints consult http://mazwww.harvard.edu.

21To minimize grading work, the Web utility we have developed automacally assigns full credit to every completed answer, and a grader schecks answers via a Web interface, which takes relatively little time.

22Stephen Kanim, ‘‘An investigation of student difficulties in qualitative aquantitative problem solving: Examples from electric circuits and elecstatics,’’ Ph.D. thesis, University of Washington, 1999, and referentherein.

23Guidelines for effective group work are found in Heller and Hollabauand Heller, Keith, and Anderson~Ref. 3!, as well as Johnson, Johnson, anSmith ~Ref. 2!.

24Philip M. Sadler, ‘‘Psychometric Models of Student Conceptions in Sence: Reconciling Qualitative Studies and Distractor-Driven AssessmInstruments,’’ J. Res. Sci. Teach.35 ~3!, 265–296~1998!; ‘‘How studentsrespond to innovation,’’ seminar at the 1998 NSF Faculty EnhancemConference ‘‘Teaching Physics, Conservation Laws First’’~audio avail-able at http://galileo.harvard.edu/conference/program.html!. The tennis in-structor illustration is also courtesy of Professor Sadler~private communi-cation!.

25Richard M. Felder and Rebecca Brent, ‘‘Navigating the Bumpy RoadStudent-Centered Instruction,’’ College Teaching44, 43–47~1996!.

26D. R. Woods,Problem-Based Learning: How to Gain the Most from PB~self-published, 1994!; R. J. Kloss, ‘‘A nudge is best: Helping studen


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through the Perry scheme of intellectual development,’’ College Teach42 ~4!, 151–158~1994!; Felder and Brent~Ref. 25!.

27Students were asked to give their opinion of the statement ‘‘The profewas an effective instructor overall’’ on a five-point scale~15stronglydisagree; 25disagree; 35neutral; 45agree; 55strongly agree!. EM’saverage score in the calculus-based course for both traditional lectu~one semester! and teaching with PI~six semesters! was 4.5, with standarddeviations of 0.6~traditional,N5125! and 0.8~PI, N5789!.

28Over three semesters in the algebra-based course~Fall 1998, Spring 2000,and Fall 2000; Spring 2000 was the electricity and magnetism semestthe course!, which was taught only with PI, EM’s average score was 3standard deviation 1.2 (N5229).

29Edward F. Redish, Jeffery M. Saul, and Richard N. Steinberg, ‘‘StudExpectations in Introductory Physics,’’ Am. J. Phys.66 ~3!, 212–224~1998!.


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30Linda R. Jones, J. Fred Watts, and Andrew G. Miller, ‘‘Case Study of PInstruction in Introductory Physics Classes at the College of CharlestoProceedings of Charleston Connections: Innovations in Higher Educa2000 ~submitted!.

31Nalini Ambady and Robert Rosenthal, ‘‘Half a Minute: Predicting TeachEvaluations From Thin Slices of Nonverbal Behavior and Physical Attrtiveness,’’ J. Personality Soc. Psych.64 ~3!, 431–441~1993!.

32Students do not necessarily remember equations in class, especially ifare not required to memorize equations.~Examinations in our course areopen-book.!

33Lecture schedules for our courses are available online at htgalileo.harvard.edu/galileo/course/ in the ‘‘Lectures’’ area.

34Wendell Potter and collaborators at the University of California, Dahave developed an entire program of training teaching assistants in iactive teaching strategies, as reported at the AAPT Winter 2000 mee


THE PHYSICS TEACHER ◆ Vol. 40, April 2002206

Adam P. Fagen, Program in Molecular Biology and Education, Harvard University, Cambridge, MA 02138

Catherine H. Crouch, Division of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138

Eric Mazur, Department of Physics, Division of Engineering and Applied Sciences, Harvard University,Cambridge, MA 02138; [email protected]

Peer Instruction (PI) is a widely used ped-agogy in which lectures are interspersedwith short conceptual questions (Con-

cepTests) designed to reveal common misunder-standings and to actively engage students in lec-ture courses.1–3 Correspondence and informaldiscussions indicate a user base of hundreds ofinstructors around the world who teach with PI,yet to date there has been no systematic study ofPI implementation and effectiveness in the vari-ety of settings in which it is used.

As a first step toward such a systematic study,we polled current and former PI users via a web-based survey to learn about their implementa-tion of and experience with PI.4 The survey col-lected data about how instructors learned aboutPI, courses in which PI was used, implementa-tion details, course assessment, effectiveness, in-structor evaluation, and the community of PIusers.

In addition to posting the survey on the Pro-

Peer Instruction: Results from a Range

of Classrooms

ject Galileo website,4 we directly invited morethan 2700 instructors by e-mail to complete thesurvey. More than 700 instructors completedthe survey, 384 of whom we identify as usingPeer Instruction.1,2 The language of the surveywas purposely broad in order to include instruc-tors who had used a strategy similar to PI with-out being aware of our work; we therefore re-ceived responses from many instructors usingother collaborative learning strategies. Respon-dents represent a broad array of institution typesacross the United States and around the world(Fig. 1). Most use PI to teach physics, althoughchemistry, life sciences, engineering, and astron-omy courses are also represented.5

Our survey probed two different measures ofthe success of PI in a course: data on studentmastery of material, and instructors’ evaluationof the success of PI use. More than 108 PI usersresponding to the survey reported collectingquantitative data on the effectiveness of PI, ofwhom 81% administered the Force Concept In-ventory (FCI) in their courses.1,6 Instructors at11 colleges and universities provided us withmatched sets of pre- and post-test FCI data, toassess the gain for individual students. Fromthese data we determined the average normalizedgain for each course7

g = �S

1f

–

–

S

S

i

i� ,

where Si, Sf = initial, final score of students onthe FCI in 30 courses taught with PI; the aver-age for a given course is denoted g. These PIcourses have a class average gain of 0.39 � 0.09

Fig. 1. Demographic breakdown of survey respondents usingPI based upon institution type (n = 384).

207THE PHYSICS TEACHER ◆ Vol. 40, April 2002

(Fig. 2). In his survey of FCI data, Hake7

defines a “medium-g” range from g = 0.3 to 0.7and finds that 85% of the interactive engage-ment courses included in his survey and noneof the traditionally taught courses show gains inthis range. We find that 27 of 30 (90%) PIcourses in our survey fall in the medium-grange, with only three below g = 0.3 (Fig. 2).Data from Harvard courses are not included, asthey have been reported separately elsewhere,1,2

and the aim of this study is to investigateimplementations of PI by instructors other thanthe developers.

To determine whether instructors considerthe use of PI in their classes to be successful, weasked them if they were likely to use PI again inthe future. Of the 384 identified PI users re-sponding to the survey, 303 definitely plannedto use PI again and 29 probably would. Onlyseven respondents expressed no plans to use PIagain. Thus, the vast majority of instructorscompleting our survey consider their experienceswith PI to be successful. These responses maynot accurately represent the relative incidence ofpositive and negative experiences, as there maybe a selection bias in who chose to complete the

survey;8 however, the responses do indicate thatPI has been successfully implemented in a largenumber of classrooms.

Peer Instruction Challenges andSolutions

Many successful users of Peer Instruction in-dicate that they had to overcome a number ofchallenges, which we describe here along withsolutions suggested by the respondents. Thir-teen percent of instructors cite the time and en-ergy required to develop ConcepTests as an im-pediment to using PI. Developing good Con-cepTests certainly takes a great deal of effort; tominimize duplication of this effort, and to makePI easier to implement, we and other developersof ConcepTests have made online databases ofConcepTests for introductory physics, chem-istry, and astronomy freely available.9 Conse-quently, for courses in these areas, ConcepTestdevelopment need not be a major obstacle.

Ten percent of respondents report that theircolleagues are skeptical of the benefit of studentdiscussions that take away lecture time. A thirdof these instructors report addressing this skepti-cism by collecting data on student learninggains. One particularly effective approach is tocompare achievement of students taught withand without PI on identical exams.10 Otherssuggest inviting skeptical colleagues to sit in on aclass, sharing positive student feedback withthem, or even giving the assessment tests to oth-er faculty.

About 9% of respondents report that thequantity of material to cover in a semester oftenmakes it difficult to devote class time to Con-cepTests. One-tenth of these instructors reducethe amount of material covered by the course,but the majority do not have the freedom to doso. One option for those bound by a lengthy syl-labus is to require students to learn some of thematerial on their own, especially by assigningreading of the text before class. Instructors reportsuccess with a number of strategies for providingthe incentive for students to read ahead of time,including Just-in-Time Teaching.11

Fig. 2. Class-averaged normalized gain of introduc-tory physics students in college courses taughtusing Peer Instruction. Symbols denote institutiontype according to the 2000 Carnegie Classificationof Institutes of Higher Education. Data fromHarvard courses is not included and has beenreported separately.1,2

THE PHYSICS TEACHER ◆ Vol. 40, April 2002208

Another challenge is students’ resistance tothe method (7% of respondents). Because moststudents are unaccustomed to active participa-tion in science classes, some feel uncomfortableparticipating in discussions, or initially considerthe discussions a waste of time. Thus, respon-dents report that it is essential to thoroughly ex-plain the use of PI to their students. Persistencein using Peer Instruction in the face of initialstudent resistance is important; 15 (4%) usersreport that, while their students were initiallyskeptical of PI, the students warmed up to it asthey found the method helped them learn thematerial. Regularly presenting class-averageddata on student performance also shows studentsthat the method is helping them and thus mayalso motivate students.

A related challenge is the difficulty in fullyengaging students in class discussions (7% of re-spondents). In the words of one instructor,“some students were too cool, too alienated, orperhaps too lost to participate.” Nearly half ofthose citing this challenge say it is important forthe instructor to circulate through the classroomduring the group discussion of the ConcepTest,helping to guide and encourage students in dis-cussion. Other students may be motivated byreceiving credit for participation and by the pres-ence of ConcepTest-like conceptual questions onexams.12

Comments

In summary, the PI survey results indicatethat most of the assessed PI courses producelearning gains commensurate with interactiveengagement pedagogies, and more than 300 in-structors (greater than 80%) consider their im-plementation of Peer Instruction to be success-ful. Over 90% of those using the method planto continue or expand their use of PI.

Acknowledgments

We would like to thank all of the instructorswho generously shared their experiences anddata with us, and Richard R. Hake for com-ments on the manuscript. Tun-Kai Yang and

Katy Gladysheva assisted with analysis and datacollection. This work was funded by theDivision of Undergraduate Education of theNational Science Foundation (grants #DUE-9554870 and -9980802).

References1. Eric Mazur, Peer Instruction: A User’s Manual

(Prentice Hall, Upper Saddle River, NJ, 1997).

2. Catherine Crouch, “Peer Instruction: An inter-active approach for large classes,” Optics and Pho-tonics News 9 (9), 37–41 (1998); Catherine H.Crouch and Eric Mazur, “Peer Instruction: Tenyears of experience and results,” Am. J. Phys. 69,970–977 (Sept. 2001).

3. Sheila Tobias, Revitalizing Undergraduate Science:Why Some Things Work and Most Don’t (ResearchCorporation, Tucson, AZ, 1992); Clark R. Lan-dis et al. Chemistry ConcepTests: A Pathway to In-teractive Classrooms (Prentice Hall, Upper SaddleRiver, NJ, 2001); David E. Meltzer and KandiahManivannan, “Promoting interactivity in physicslecture courses,” Phys. Teach. 34 (2), 72–76 (Feb.1996); David E. Meltzer and Kandiah Manivan-nan, “Transforming the lecture-hall environment:The fully interactive physics lecture,” preprint;Antti Savinainen and Philip Scott, “Using theForce Concept Inventory to monitor studentlearning and to plan teaching,” Phys. Educ. 37(1), 53–58 (Jan. 2002); Jeffrey Kovac, “Studentactive learning methods in general chemistry,” J.Chem. Educ. 76 (1), 120–124 (1999); SumangalaP. Rao and Stephen E. DiCarlo, “Peer Instructionimproves performance on quizzes,” Adv. Physiol.Educ. 24 (1), 51–55 (2000).

4. Adam P. Fagen, Tun-Kai Yang, Catherine H.Crouch, and Eric Mazur, “Factors That MakePeer Instruction Work: A 700-User Survey,” pre-sented at AAPT Winter Meeting, Kissimmee, FL,2000. The “Peer Instruction ImplementationSurvey” is available on the web athttp://galileo.harvard.edu/PIsurvey.html.

5. Eighty-two percent of instructors responding tothe survey teach physics, 4% chemistry, 4% lifesciences, 3% engineering, 2% astronomy, 2%mathematics, and 3% other.

6. Ibrahim Abou Halloun and David Hestenes,“The initial knowledge state of college physicsstudents,” Am. J. Phys. 53, 1043–1055 (Nov.1985).

209THE PHYSICS TEACHER ◆ Vol. 40, April 2002

7. Richard R. Hake, “Interactive-engagement ver-sus traditional methods: A six-thousand-studentsurvey of mechanics test data for introductoryphysics courses,” Am. J. Phys. 66, 64–74 (Jan.1998).

8. While the survey was designed to encourage in-structors to provide feedback regardless of the ef-fectiveness of their experience, we have no inde-pendent accounting of PI users to know whethersatisfied users responded at the same rate as dis-satisfied users. We encouraged instructors to re-port their experiences, positive and negative, andespecially encouraged those with disappointingexperiences to respond.

9. Project Galileo, http://galileo.harvard.edu/, con-tains an extensive database of ConcepTests in in-troductory physics and links to sites with chem-istry ConcepTests (http://www.chem.wisc.edu/~concept/ and http://www.unet.brandeis.edu/~herzfeld/conceptests.html) and astronomyConcepTests (http://hea-www.harvard.edu/~pgreen/educ/ConcepTests.html).

10. Such comparative data are reported in Linda R.Jones, Andrew G. Miller, and J. Fred Watts,“Conceptual teaching and quantitative problemsolving: Friends or foes?” J. Coop. Collabor. Coll.Teach., in press.

11. Gregor M. Novak, Evelyn T. Patterson, AndrewD. Gavrin, and Wolfgang Christian, Just-in-TimeTeaching: Blending Active Learning with Web Tech-nology (Prentice Hall, Upper Saddle River, NJ,1999).

12. Sheila Tobias and Jacqueline Raphael, The Hid-den Curriculum: Faculty-Made Tests for Science.Part I: Lower Division Courses (Plenum Press,New York, 1997); Sheila Tobias, “In-class Exami-nations in College-level Science: What do yourtests tell your students about themselves andabout your subject?” presented at Teaching Intro-ductory Physics, Conservation Laws First: AnNSF Faculty Enhancement Conference, HarvardUniversity, Cambridge, MA, 1998; http://galileo.harvard.edu/conference/tobias_abs.html.

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