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Innovations in TeachingUndergraduate Biologyand Why We Need ThemWilliam B. WoodDepartment of Molecular, Cellular, and Developmental Biology, University of Colorado,Boulder, Colorado 80309-0347; email: [email protected]

Annu. Rev. Cell Dev. Biol. 2009. 25:5.1–5.20

The Annual Review of Cell and DevelopmentalBiology is online at cellbio.annualreviews.org

This article’s doi:10.1146/annurev.cellbio.24.110707.175306

Copyright c© 2009 by Annual Reviews.All rights reserved

1081-0706/09/1110-0001$20.00

Key Words

active learning, concept inventories, course transformation,discipline-based educational research, formative assessment, pedagogy

AbstractA growing revolution is under way in the teaching of introductory sci-ence to undergraduates. It is driven by concerns about American com-petitiveness as well as results from recent educational research, whichexplains why traditional teaching approaches in large classes fail to reachmany students and provides a basis for designing improved methods ofinstruction. Discipline-based educational research in the life sciencesand other areas has identified several innovative promising practicesand demonstrated their effectiveness for increasing student learning.Their widespread adoption could have a major impact on the introduc-tory training of biology students.

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Review in Advance first posted online on July 7, 2009. (Minor changes may still occur before final publication online and in print.)

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Contents

DEFINING THE CHALLENGE . . . . 5.2HISTORY AND CURRENT STATE

OF DISCIPLINE-BASEDEDUCATIONAL RESEARCH . . . . 5.3

HOW STUDENTS LEARN . . . . . . . . . 5.3APPLICATION TO THE COLLEGE

CLASSROOM . . . . . . . . . . . . . . . . . . . . 5.5EVIDENCE THAT

RESEARCH-BASED TEACHINGAT THE COLLEGE LEVELINCREASES STUDENTLEARNING . . . . . . . . . . . . . . . . . . . . . . 5.6

PROMISING PRACTICES FORINCREASING STUDENTLEARNING . . . . . . . . . . . . . . . . . . . . . . 5.6Content Organization: The Syllabus

versus Specific Learning Goals . . 5.8Student Organization: Individual

versus Group Work . . . . . . . . . . . . . 5.10Feedback: Summative versus

Formative Assessment . . . . . . . . . . . 5.10

In-Class Learning Activities:Listening and Note-Takingversus Active Engagement . . . . . . . 5.11

Out-of-Class Learning Activities:Instructor versus StudentResponsibility for Learning. . . . . . 5.13

Student-Faculty Interaction in Class:Making Pedagogy Explicit . . . . . . . 5.14

Student-Faculty Contact Out ofClass: Office Hours versusEnhanced Communication . . . . . . 5.15

Use of Teaching Assistants: Gradingand Recitation versus Facilitationof Student Learning. . . . . . . . . . . . . 5.15

Student Laboratories: CookbookExercises versus Inquiry . . . . . . . . . 5.15

CONCLUSION: THE DUALFUNCTIONS OF BIOLOGYEDUCATION . . . . . . . . . . . . . . . . . . . . 5.16

STEM: science,technology,engineering, andmathematics

DBER: discipline-based educationalresearch

DEFINING THE CHALLENGE

Two principal forces are generating momen-tum for a revolution in the way biology andother sciences are taught in high schools, col-leges, and universities (DeHaan 2005). First,there are deep concerns about American inter-national competitiveness, amid indications thatthe U.S. is doing a relatively poor job at retain-ing and training students in the science, tech-nology, engineering, and mathematics (STEM)disciplines (Glenn 2000, NAS 2004). Too manytalented students get the impression from intro-ductory courses that science is simply a collec-tion of facts to be memorized and consequentlydrop out of STEM majors, with little under-standing or appreciation of what science is allabout (Seymour & Hewitt 1997). For studentswho do major in life sciences, there is concernthat future research biologists are being inad-equately trained (NRC 2003, AAMC-HHMI2009).

The second driving force for reform is re-cent research from educators and cognitive sci-entists into how students learn. This research,discussed further below, provides strong ev-idence that the traditional teaching methodsemployed in most secondary-school and under-graduate introductory courses are far from opti-mal for promoting student learning. Alternativeresearch-based teaching methods have been de-veloped and shown to be more effective, and asmall but growing number of informed STEMfaculty and administrators are pushing for theiradoption.

Beyond the general findings about how stu-dents learn, there is now a substantial body ofdiscipline-based educational research (DBER),dealing with teaching and learning of specificSTEM disciplines. This review refers to someof the more important general findings on howstudents learn, but it primarily highlights re-sults and applications from recent DBER and,

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more specifically, life sciences education re-search. It focuses on teaching and learning forundergraduates, particularly in large courses,where innovation is most needed.

HISTORY AND CURRENT STATEOF DISCIPLINE-BASEDEDUCATIONAL RESEARCH

DBER grew out of the efforts of physicists in themid-1980s, who discovered that most under-graduate students in their introductory courseswere gaining only very superficial knowl-edge from traditional methods of instruction(Halloun & Hestenes 1985, Hestenes et al.1992). Rather than integrated conceptual un-derstanding and creative problem solving,students were learning fragmented factual in-formation and rote problem solving methods,while retaining many misconceptions aboutphysical phenomena. To gain some measureof student understanding, physicists developedthe Force Concept Inventory (FCI), a simplemultiple-choice test of basic concepts and com-mon misconceptions about Newtonian physicsof everyday events, written in simple languageand requiring no sophisticated mathematics(Hestenes et al. 1992). By administering theFCI at the beginning and the end of an in-troductory course, instructors could obtain ameasure of gains in student conceptual learn-ing. They could then experiment with differentinstructional approaches and test them for ef-ficacy. These physicists showed that adopting asmall number of nontraditional promising prac-tices in course design and implementation couldsubstantially increase student learning gains.These practices, and their basis in more gen-eral educational research on how people learn,are described in the following sections.

After a lag of several years, instructors inother STEM disciplines began to make simi-lar observations about their students and to ini-tiate similar efforts at improving instruction.The empirical approach of varying instruc-tional methods and measuring effects on stu-dent learning has been called “scientific teach-ing” (Handelsman et al. 2004, Wieman 2007).

FCI: force conceptinventory

Many DBE researchers doing this work arepracticing scientists trained in their disciplines,who have also learned educational researchmethods and taken up DBER as a sideline.Some schools of education have added DBERpractitioners trained as educators to their fac-ulties. In addition, some university science de-partments, particularly in physics but increas-ingly in other STEM disciplines, now includestaff or tenure-track DBE researchers (NAS2005) and are beginning to offer graduate train-ing and degrees in DBER.

DBER is published in a variety of edu-cation journals, some general and some thatare discipline-specific, sponsored by STEMprofessional societies. A few scientific jour-nals, including Nature, Science, PLoS Biology,and Genetics, have also begun publishingDBER articles, generally in an educationsection. Table 1 lists some of the morewidely read general and discipline-specificeducational journals that publish DBER in lifesciences.

HOW STUDENTS LEARN

New ideas about teaching and learning beganto receive public attention in the 1960s. Populariconoclasts such as Holt (1964, 1967) and Kozol(1967), building on earlier ideas (Dewey 1916,Ausubel 1963), pointed out the shortcomingsof passive learning environments for learnersof all ages, and advocated instead more student-centered, open classrooms that promoted activelearning through hands-on experience, by do-ing rather than by simply listening, reading, andwatching. These writers, considered radicals intheir time, articulated ideas about optimal con-ditions for meaningful learning that have sincebeen tested and validated by a large body of ed-ucational research. Also during the past threedecades, advances in cognitive science have be-gun to elucidate the neural activities and synap-tic changes that accompany learning. Resultsof research in both education and cognitionwere reviewed in the seminal National ResearchCouncil (NRC) report How People Learn: Brain,Mind, Experience, and School (NRC 1999). The

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Table 1 A partial list of journals that publish life sciences education researcha

General scientific journalsGeneticsNatureSciencePLoS Biologyb

Education journals (sponsored by professional societies)Advances in Physiology Education, 2001- (Amer. Physiol. Soc.)

∗†

Biochemistry and Molecular Biology Education, 2006- (Amer. Soc. Biochem. and Mol. Biol.)†

CBE-Life Sciences Education, 2002- (Am. Soc. Cell Biol.)b,c

Journal of Biological Education, 1990- (Brit. Inst. Biol.)b

Microbiology Education Journal (Amer. Soc. Microbiol.)c

Frontiers in Ecology and the Environment (Ecol. Soc. Am.)

General education journalsAmerican Biology Teacher (Natl. Assoc. Biol. Teach.)b.c

Bioscene: Journal of College Biology Teachingb

BioScience (Am. Inst. Biol. Sci.)International Journal of the Scholarship of Teaching and Learningb,c

Journal of College Science Teaching (Natl. Sci. Teach. Assoc.)

aFor additional journal listings, see Dolan (2007).bOpen access.cHigher standards: research articles require assessment and outcome evidence for efficacy of a new courseor intervention, rather than simple descriptions of practice.

Constructivist: theview that individuallearners must buildtheir own knowledgestructures, fromexperience andinstruction, on afoundation of priorknowledge

Formativeassessment: frequent,ongoing testing,usually during class,with the goal ofmonitoringunderstanding andproviding feedbackrather than judgingperformance

Summativeassessment: high-stakes testing at theend of an instructionalunit or course to judgestudent performance,e.g., mid-term andfinal exams

major conclusions from this research can besummarized as follows:

� Learning involves the elaboration ofknowledge structures in long-term mem-ory. According to this constructivist viewof education (Dewey 1916; Ausubel 1963,2000), effective instruction must beginat the level of a student’s prior knowl-edge (which may include misconcep-tions). New information unrelated toprior knowledge is difficult to learn andremember.

� No two learners are the same: Learn-ers differ in previous experience, previousinstruction, preferred styles of learning,family background, cultural background,and so on. Diversity is an asset for col-laborative work because different mem-bers of a group bring different perspec-tives and skills to bear, but it can hamperlearning for some students unless the leveland mode of instruction are appropriatefor all.

� Learning is promoted by frequentfeedback, that is, ongoing testing ofnew knowledge as students are acquir-ing it. Educators call this formativeassessment, as opposed to summativeassessment, which refers to high-stakesexams given after an extended periodof instruction. Formative assessmentprovides valuable feedback to bothinstructor and students: Do studentsunderstand the concept just presented ordiscussed? Can they transfer this under-standing to apply the concept in a newsituation?

� Effective learning requires awareness andquestioning of one’s own learning pro-cess: How well do I understand this?What information do I need to under-stand it better? What do I not under-stand yet? Do I understand it well enoughto transfer it, that is, apply it to a newsituation? Educators call this awarenessmetacognition.

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� Learning is enhanced in a community oflearners who value the knowledge thatis being learned. In early childhood thiscommunity is the family; at the universityit could be a group of students workingtogether to solve a problem or completea research project.

� Learning changes the structure of thebrain, and the extent of change increaseswith the degree of complexity, stimula-tion, and emotional involvement in thelearning environment (Zull 2002). Ac-tive learning, in which a student’s lev-els of motivation, curiosity, and attentionare high, for example during a group ef-fort to solve an intriguing problem, willbe better retained than learning fromrelatively passive activities such as read-ing a text or listening to a lecture.

� Learning in a particular area of knowl-edge such as life sciences can be viewedas a continuum from novice to expert sta-tus, along which we would like to helpour students progress. The knowledge ofan expert constitutes a coherent struc-ture into which new concepts can easily fitand from which relevant information canbe efficiently retrieved. In contrast, newknowledge for the novice often appears tobe a collection of unrelated facts, whichare difficult to memorize and retain. Inother words, experts see and make useof meaningful patterns and relationshipsin the information they possess, whereasnovices cannot.

APPLICATION TO THE COLLEGECLASSROOM

These general conclusions apply to teachingand learning of STEM disciplines at the un-dergraduate level:

� Effective instruction must build on stu-dents’ prior knowledge (which mayinclude misconceptions that requirecorrection).

� Instructors should be aware of the stu-dent diversity in their classrooms and use

Transfer: applicationof knowledge learnedin one context to aproblem in a differentcontext

Metacognition: theprocess of monitoringone’s own learningprocess and level ofunderstanding

a variety of teaching modes to optimizelearning for all students.

� Classes should include frequent forma-tive assessment to provide feedback toboth instructors and students.

� Students should be encouraged to exam-ine and monitor their own understandingof new concepts, for example, by explain-ing these concepts to their peers.

� Students should be encouraged to workcooperatively and collaboratively in smallgroups.

� In order to bring about the neurologi-cal changes that constitute learning, stu-dents should spend time actively engagedwith the subject matter, for example, dis-cussing, diagramming, solving problems,working on a research project, etc., in ad-dition to or in place of listening passivelyto a lecture, reading the textbook, or con-sulting Web sites.

Most undergraduate college STEM classes,particularly in large introductory courses, arenot designed around these principles, and it canbe argued that this is one reason for the highattrition rates and generally superficial learn-ing among introductory students in STEM dis-ciplines. Educators have shown that effectiveinstruction requires not only disciplinary con-tent knowledge, for example, expertise in lifesciences, but also pedagogical content knowl-edge, that is, understanding of and ability toapply known educational principles. Becausegraduate and postdoctoral training in STEMdisciplines seldom includes any instruction inpedagogical practice, most university facultyare unaware of new knowledge about learn-ing that could make their teaching more effec-tive. Therefore, they simply teach the way theywere taught in large classes, by traditional lec-turing. We need to improve the way we teachundergraduates. The remainder of this articlediscusses evidence that applying the above prin-ciples to college classrooms can make a differ-ence in how much and how well our studentslearn.

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EVIDENCE THATRESEARCH-BASED TEACHINGAT THE COLLEGE LEVELINCREASES STUDENTLEARNINGOur best undergraduates, sometimes with littlehelp from faculty, develop learning skills thatincorporate the above principles, allowing themto progress toward expert knowledge regard-less of how we teach them. However, many stu-dents, for whom studying means highlightingphrases in their textbooks and memorizing dis-connected facts, fail to develop effective learn-ing skills, and consequently learn very little. Isthere evidence that changes in teaching prac-tices at the college level can significantly en-hance student learning?

Physicists were the first to obtain such ev-idence, using the Force Concept Inventory(FCI; Hestenes et al. 1992) described above.The FCI became nationally accepted amongphysics instructors during the 1990s as a wayto gauge student learning of Newtonian me-chanics. Administering the FCI as a pre-test atthe start of a course and then again as a post-test at the end yielded a raw learning gain foreach student. For comparison of students withdifferent levels of incoming knowledge, eachraw gain was divided by the maximum possiblegain for that student, to arrive at a percentagenormalized gain: <g> = 100(post-test score –pre-test score)/(100 – pre-test score).

In attempts to increase the generally lownormalized gains seen in traditional intro-ductory courses, physics education researcherstransformed their courses with new teachingapproaches following the principles describedabove: more class time devoted to active learn-ing, more group problem solving, frequent for-mative assessment, and so on. They carriedout controlled studies, for example, the sameinstructor teaching the same syllabus throughtraditional lectures in one semester and thenusing the new approaches in the followingsemester (e.g., Beichner 2008). Study afterstudy indicated that students in the transformedcourses substantially outperformed those intraditional courses. In a compelling landmark

meta-analysis combining data from many suchstudies, Hake (1998) showed that for a sam-ple of over 6000 students in 55 introductoryphysics courses nationwide, the average learn-ing gains were nearly twice as high in trans-formed courses as in traditional courses.

Other STEM disciplines have lacked widelyaccepted assessment instruments comparableto the FCI until recently (see below). Nev-ertheless, several studies using some form ofpre- and post-testing have also yielded resultsshowing the greater efficacy of transformedcourses. In the life sciences, an early study fromthe University of Oregon showed that studentsin the traditional introductory course learnedsubstantially less than students in a workshopbiology course, in which lecturing was almostentirely replaced by student group problemsolving and other projects during class time(Udovic et al. 2002). Knight & Wood (2005)showed in a quasi-controlled study that evenan incremental change, substituting 30–40% oflecturing during class time with more engagingstudent-centered activities (described below),led to increases in normalized learning gainsaveraging about 30% in a large upper-divisiondevelopmental biology course. Similar resultshave been reported in large introductory biol-ogy courses (e.g., Smith et al. 2005, Armstronget al. 2007, Freeman et al. 2007).

Clearly, concept inventories in life scienceswould be valuable for continuation of this re-search (Garvin-Doxas et al. 2007), and sev-eral have recently been published for vari-ous subdisciplines, including general biology(Klymkowsky et al. 2003), genetics (Bowlinget al. 2008, Smith et al. 2008), and natural selec-tion (Anderson et al. 2002). Libarkin (2008) hascompiled a comprehensive current listing andcomparison of concept inventories in STEMdisciplines.

PROMISING PRACTICES FORINCREASING STUDENTLEARNING

Many college faculty use Socratic dialog andstudent-centered group work in small classes

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and seminars, but they believe there is no alter-native to lecturing when confronted with hun-dreds of students in an auditorium with fixedseats. However, innovative instructors pursuingDBER have developed and tested alternativeteaching approaches that prove to be substan-tially more effective than traditional lectures.This research has identified several promisingpractices for transforming large classes in waysthat enhance student learning and conceptualunderstanding (reviewed in Handelsman et al.2007).

Froyd (2008) has introduced a useful rat-ing of promising practices based on two crite-ria: (a) practicality of implementation (breadthof applicability to STEM courses, freedomfrom resource constraints, ease of transitionfor instructors), and (b) evidence for efficacyin promoting increased student learning (fromstrongest evidence, i.e., multiple high-qualitycomparison studies, to weakest evidence, i.e.,descriptive application studies only). The fol-lowing paragraphs, summarized in Table 2,compare these practices with their counterparts

Table 2 Comparison of traditional practices with corresponding research-based promising practices for nine aspects oflarge course design and implementation in STEM disciplines

Course aspect Traditional practice Research-based promising practice1. Content organization Prepare a syllabus, describing the topics that

the instructor will present in class.Formulate specific student learning objectives, in theform of “after this course, students will be able to. . .”

2. Student organization Most student work is done individually andcompetitively.

Most student work is done cooperatively, in smallgroups.

3. Feedback Grading based primarily or entirely onsummative assessments, i.e., midterm andfinal exams.

Feedback to instructor and students providedcontinually through in-class formative assessments.

4. In-class learningactivities

Instructor transmits information by lecturing.Some questions may be posed to students, butonly a small subset of the class is likely toparticipate in discussion.

All students spend most or all class time engaged invarious active-learning activities (see text), facilitatedby instructors and TAs. These activities also provideformative assessment.

5. Out-of-class learningactivities

Students read the text and may do assignedhomework to practice application of conceptspreviously presented in class.

Students read and do assigned homework on newtopics and post results online for the instructor toreview before the class on those topics.

6. Student-facultyinteraction in class

Students are expected to accept the teachingmode chosen by the instructor, and to inferhow they should study and what they shouldlearn from the instructor’s lectures andassignments.

Instructor explains the pedagogical reasons for thestructure of course activities to encourage studentbuy-in, and explicitly and frequently communicatesthe course learning goals to students.

7. Student-facultyinteraction out of class

Students must initiate out-of-class interactionwith each other and with the instructor, e.g.,by coming to office hours.

Instructor facilitates interaction with and amongstudents by setting up online chat rooms,encouraging group work on homework assignments,and communicating with students electronically.

8. Use of teachingassistants (TAs)

TAs grade assignments and exams, and mayconduct recitation sessions to demonstrateproblem solving methods or further explainlecture material.

TAs receive some initial instruction in basic pedagogyand serve as facilitators for in-class group work andtutorial sessions for small student groups to work outproblems on their own.

9. Student laboratories Students carry out exercises that demonstratewidely used techniques or verify importantprinciples by following a prescribed protocol(“cookbook labs”).

Students are required to solve a research problem,either defined (e.g., identify an unknown) or moreopen-ended (e.g., determine whether commonly usedcosmetic products are mutagenic), and learnnecessary experimental techniques and concepts inthe process (inquiry-based labs).

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Instructor-centered:designed around theknowledge theinstructor wishes totransmit to students;focused on theinstructor’s teachingprocess

Student-centered:designed around theneeds, abilities, priorknowledge anddiversity of students;focused on thestudent’s learningprocess

MCAT: medicalcollege admission test

in traditional instruction and rate them onFroyd’s two criteria. The practices are orga-nized under nine aspects of course organization.

Content Organization: The Syllabusversus Specific Learning Goals

The difference between preparing a course syl-labus and formulating learning objectives ismore profound than it may appear (Allen &Tanner 2007). The typical syllabus is instructor-centered; it lists the topics on which the instruc-tor will lecture and assign out-of-class work,but it gives students little information about thelevel of understanding they should strive for orthe skills they are to learn. In molecular biology,for example, the process of transcription canbe understood at many levels, which are gen-erally not distinguished in a syllabus. In con-trast, learning objectives are student-centeredand more explicit; they describe what a success-ful student should be able to do at the end ofthe course or unit. For example, students shouldbe able to: “name the principal enzyme that cat-alyzes transcription,” or “explain the nucleotidesequence relationships between the two strandsof the template DNA and the RNA transcrip-tion product,” or “diagram a step in the elon-gation of an RNA transcript, showing the localnucleotide sequences and strand polarities ofboth DNA strands and the RNA,” or “predictthe consequences for the transcription processif one of the four nucleoside triphosphates isunavailable.”

The learning objectives above demand dif-ferent levels of understanding. A half centuryago, the American educator Benjamin Bloomdeveloped a convenient scheme for classifyingthese levels (Bloom & Krathwohl 1956), whichbecame known as Bloom’s taxonomy of the cog-nitive domain (Figure 1). Each of Bloom’s sixlevels of understanding can be associated withverbs appropriate for a learning goal at thatlevel. For example, the ability to name an en-zyme or describe a process requires only mem-orization of the relevant information (level 1),whereas ability to predict an outcome (level 3)or defend a principle based on evidence (level 6)

require deeper conceptual understanding. Theverbs employed (Figure 1) describe an actionor ability that can be assessed by asking studentsto carry it out. Importantly, statements suchas “students should understand,” “appreciate,”or “be aware of” are inappropriate learningobjectives because their achievement cannotbe tested without more explicit performance-based criteria. Because lower Bloom’s levelsare easier to assess with multiple-choice andshort-answer exams, many instructors in largeSTEM courses neither demand nor test forhigher levels of understanding. In a survey ofover 500 final exams from a variety of introduc-tory undergraduate and medical school biologycourses, most questions were rated at Bloom’slevels 1 and 2, and questions on the MedicalCollege Admissions Test (MCAT) and Grad-uate Record Examination (GRE) ranked onlyslightly higher (Zheng et al. 2008). Anotherongoing research study on assessment in in-troductory biology courses indicates that theoverwhelming majority of test items on finalexams are Bloom’s level 1 (D. Ebert-May, per-sonal communication). Because most studentslearn at the level assessed on summative ex-ams, it is small wonder that they derive onlysuperficial knowledge from such courses. In-structors can remedy this situation by aimingfor higher Bloom’s levels in formulating courselearning goals and assessing student knowledgewith appropriately challenging questions on ex-ams (Crowe et al. 2008).

Course design around learning goals followsthe principle of backward design (Wiggins &McTighe 1998). The instructor first formulatesbroad learning goals for students in the course,and then more specific learning objectives.Once these are defined, she designs assessments(both formative and summative) to test for theirachievement. Only then does she choose themost appropriate text or other reference ma-terials and plan the learning activities in andoutside of class that will most effectively leadto fulfillment of the objectives. At the start ofthe course, she will explicitly apprise studentsof the learning objectives, which may includerubrics (Allen & Tanner 2006) demonstrating

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6Evaluation:

think criticallyabout and defend

a position

5Synthesis:

transform and combine ideas tocreate something new

4Analysis:

break down concepts into parts

3Application:

apply comprehension to unfamiliar situations

2Comprehension:

demonstrate understanding of ideas and concepts

1Factual knowledge:

remember and recall factual information

JudgeJustifyDefendCriticizeEvaluate

DevelopCreate

ProposeDesignInvent

ApplyUse

DiagramCompute

SolvePredict

DefineList

StateNameCite

CompareContrastDistinguish

RestateExplainSummarizeInterpretDescribe

Figure 1Bloom’s levels of understanding. Originally termed Bloom’s taxonomy of the cognitive domain, this schema defines six levels ofconceptual understanding, according to the intellectual operations that students at each level are capable of (Bloom & Krathwohl1956). The italicized verbs have been added to the original hierarchy; they indicate performance tasks that test achievement of learninggoals at each level. Fine distinctions in the hierarchy are difficult, and some educators prefer to classify goals on only three levels: low(1, 2), medium (3, 4) and high (5, 6). (Based on Allen & Tanner 2002.)

what achievement of the objectives would looklike. Figure 2 compares traditional and back-ward design of STEM courses.

Froyd’s (2008) implementation rating forthe practice of course design around learningobjectives is high (applicable to any STEMcourse, no significant resource constraints, noneed for radical change in instructor’s teachingmethods). As for efficacy rating, there are noempirical studies (known to this author) thatcompare student learning in courses taughtfrom syllabi and those built around learningobjectives. However, it seems self-evident thatmore learning will occur in courses that ex-plicitly set goals for higher levels of conceptual

Standard course planning

Choose textbook

Create syllabus

Write/revise lectures, notes,prepare PowerPoint presentations

Write homework, exam questions

Instructor-centered

versus Backward design

Formulate broad learning goals

Set specific learning objectives

Design assignments (formativeand summative)

Prepare learning activities

Student-centered

Figure 2Schematic comparison of standard and backward course design.

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understanding and require that studentsdemonstrate achievement of these goals on ex-ams and other course work.

Student Organization: Individualversus Group Work

Organizing students into small groups for in-class and out-of-class work can transform thecourse experience from competitive to collabo-rative, allow students to learn from each otheras well as from instructors, and help to involvestudents who might not otherwise become ac-tively engaged with the course content (Tanneret al. 2003). Groups can collaborate on regularhomework assignments, longer-term projectssuch as researching a topic and developing aposter presentation, and in-class work if thecourse includes problem solving and other ac-tive learning activities during class time.

The implementation rating for group orga-nization is lower than for learning objectives,because it involves additional instructor effortand decision making, regarding for example,how to form effective groups, facilitate theirfunction, and help students develop collabo-rative skills (for specific references, see Froyd2008). With regard to efficacy, much researchin social science has shown that groups in gen-eral are more effective at complex problem solv-ing than individuals (e.g., Brophy 2006), andthat a group’s effectiveness increases with thediversity of its members (Cox 1993, McLeodet al. 1996, Guimera et al. 2005). Compara-tive studies and meta-analyses provide strongevidence that group work in STEM coursescontributes to increased student learning (e.g.,Johnson et al. 1998, Springer et al. 1999). Thereis additional evidence in connection with in-class active learning in groups, discussed in thecontext of practice 4 below.

There are also other arguments for encour-aging group work. With the increasing popular-ity of distance learning, the opportunity for stu-dent collaborative intellectual endeavor is oneof the major advantages that resident universi-ties can provide, and these universities shouldexploit it. As Astin (1993) concluded in his book

of the same name, What Matters in College arethe relationships students build with each otherand with their instructors. Moreover, the de-velopment of group-work skills is important inpreparing students for the real world. Whenstudents who are comfortable with the tra-ditional individual and generally competitivelearning mode object to group work, the in-structor can point out that when they join theworkforce, they will probably be part of a team,whose members they did not choose, and thatthey need to learn how to work effectively witha group as an important part of their education.

Feedback: Summative versusFormative Assessment

One of the key aspects of effective instructionidentified in How People Learn (NRC 1999) isfeedback to students during the learning pro-cess. Traditional courses provide feedback byreturning graded homework and exams to stu-dents, often too late to be of optimal use be-cause the class has moved on to other topics.In contrast, in-class formative assessment pro-vides immediate feedback to both students andinstructors on how well a concept under dis-cussion is being understood. The results can beeye-opening, particularly for instructors whoare considered engaging and effective lectur-ers, when they find that only a fraction of theirstudents have understood a seemingly lucid ex-planation (see Hrepic et al. 2007). Students maybe surprised as well because the concept as pre-sented may have seemed clear, until they wereasked to explain or apply it. But most impor-tant, awareness of a problem in understandingallows the class to address it immediately and incontext, when it is most meaningful to students.

In the 1990s, the physicist Eric Mazurbegan to obtain this kind of feedback byposing to his class multiple-choice questions(“ConcepTests”) that required application ofthe concept under discussion (Mazur 1997,Crouch & Mazur 2001). Initially, students in-dicated their choices by a show of hands orby holding up different colored cards. Morerecently the audience response devices known

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as clickers, developed originally for TV gameshows, have made this kind of formative as-sessment more convenient and powerful (Wood2004, Caldwell 2007, Bruff 2009). Each stu-dent has a clicker, generally with five buttonslabeled A–E, and a receiver is connected to theinstructor’s computer. When students answera multiple-choice question using the clickers,their answers are recorded electronically, anda histogram of the results is displayed to theinstructor and, eventually, to the class. Howthe instructor can respond to this informationis discussed in the following section on activelearning, but the benefits for formative assess-ment are clear: Student responses are indepen-dent and anonymous, responses are recordedfor later analysis by the instructor if desired,problems with understanding are immediatelyapparent, and the class can address these prob-lems on the spot.

Frequent quizzes can also serve as forma-tive assessment, and research has shown thattaking tests after studying leads to significantlymore learning than studying alone (Karpicke &Roediger 2008, Klionsky 2008). Moreover, theresults of quizzes (and in-class concept ques-tions) are valuable to the instructor in design-ing appropriate exam questions for future sum-mative assessments. Another kind of formativeassessment is the “one-minute-paper” (Angelo& Cross 1993, Stead 2005). in which studentsare asked to write down and hand in anony-mously a brief statement of what they foundmost difficult and what they found most in-teresting during the preceding class. This ex-ercise encourages immediate reflection on thepart of students and informs the instructor ofpossible problems. Students can also be asked tocomment, positively or negatively, about gen-eral aspects of the course. Additional types offormative assessment are considered in the fol-lowing section on in-class active-engagementactivities. Any activity that requires students toapply concepts just discussed can provide use-ful feedback about conceptual understanding toboth students and instructors.

The ease of implementing formative as-sessment is high; instructors do not need to

change the way they teach to obtain occasionalfeedback during class, although the results ofsuch feedback may well change their teachingapproaches as discussed further below. Clickersare an added expense for students, who gener-ally purchase a clicker at the bookstore and canresell it if they wish at the end of the course(Barber & Njus 2007). With regard to evidencefor efficacy, formative assessment is generallycoupled with in-class activities and so cannotbe easily evaluated in isolation. Studies demon-strating the value of both these practices incombination are discussed in the followingsection.

In-Class Learning Activities: Listeningand Note-Taking versus ActiveEngagement

In large STEM classes, the traditional learningactivity is the lecture. Even students who arepaying close attention to the lecturer are en-gaged primarily in the passive recording of in-formation, with little time for reflection. Thereis compelling evidence from all STEM dis-ciplines that replacing some or all lecturingwith in-class activities that actively engage stu-dents can substantially increase their learn-ing gains. Of the promising practices reviewedhere, this one, especially when combined withpractice 2, students working in groups, andpractice 3, frequent formative assessment, hasproduced the most impressive improvementsin study after study. Many possible in-classactivities—brainstorming, reflection followedby discussion with a neighbor and reportingto the class (“think-pair-share”), concept map-ping, group problem solving, and more—arewell described in the excellent book ScientificTeaching (Handelsman et al. 2007) and in theseries of features titled “Approaches to Biol-ogy Teaching and Learning” by D. Allen &K. Tanner in the online journal CBE-Life Sci-ences Education (Allen & Tanner 2002, 2003a,b,2005). Table 3, adapted from Handelsman et al.(2007), compares the traditional lecture presen-tation of a few topics with corresponding active-learning alternatives.

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Table 3 Comparisons between presentation of topics in traditional lecture format and corresponding active learningactivities

Concept Passive lecture Active classDifferential geneexpression

Every cell in an organism has the same DNA, butdifferent genes are expressed at different timesand in different tissues. This is called differentialgene expression.

If every cell in an animal has the same DNA, then howcan cells of different tissues be so different? Discuss thisquestion with your neighbor and generate a hypothesis.

DNA structure andreplication

Complementary base pairing is the basis for themechanism of DNA replication.

What do you know about the structure of DNA thatsuggests a mechanism for replication? Think about thisfor a minute, and then discuss it with your neighbor.

Data analysis andinterpretation

Based on the data shown in this slide, researchersconcluded that Snarticus inferensis is the causalagent of the disease.

Consider these data from the experiment I just described.Which of the following conclusions can you draw fromthem? Think about it for a minute, and then we willtake a vote and discuss the results.

Biology and society Many people have concerns about geneticallymodified organisms (GMOs). Some of theseconcerns are well founded, and others are not.You have to decide for yourself.

I would like to split the class into two groups. One groupwill brainstorm about the potential benefits of GMOsand the other about possible harmful consequences.Then we will have a debate.

Distracters: theincorrect choices in amultiple-choicequestion

In-class concept questions, particularlywhen used with clickers, can be a power-ful active learning tool. When a challengingmultiple-choice concept question is presentedto the class, and the initial response is aboutevenly split between the correct choice and oneor more incorrect choices (distracters), a teach-able moment occurs: Students may be amusedor surprised, but they want to know who is rightand who is wrong, and they have become emo-tionally involved (Wood 2004). Rather than re-vealing the correct answer, or trying to explainthe concept again, the instructor, if interested inpromoting active learning, should ask the stu-dents to discuss their answers in small groups,trying to convince their neighbors of the cor-rect choice. Following a few minutes of discus-sion, the instructor calls for another vote, andalmost invariably, the majority of students willnow choose the correct answer, which is thenrevealed and discussed. Students are often bet-ter able than the instructor to identify flawedreasoning by their peers and convince themof the correct reasoning. Mazur named thisphenomenon peer instruction in his delightfulbook of the same name (Mazur 1997, Crouch& Mazur 2001). It could be argued that lessknowledgeable students are simply influencedduring discussion by peer pressure from neigh-bors they perceive to be more knowledgeable,

but a recent study indicates that, on the con-trary, students are actually learning during thediscussion, even when no one in a group initiallyknows the correct answer (Smith et al. 2009).

Clicker questions, to be effective, must beconceptual and challenging. Ideally they shouldinclude distracters based on known studentmisconceptions, and they should assess higherBloom’s levels of understanding (Modell et al.2005, Lord & Baviskar 2007, Crowe et al. 2008).Writing good questions is challenging but es-sential; questions that simply test factual recallof recently presented information do not en-gage students and are of little pedagogical use.Clicker questions are also not helpful if the in-structor, after the initial vote, simply indicatesthe correct answer and then moves on. Studentdiscussion before revealing the correct answeras well as after is key to learning. For addi-tional guidance on writing good clicker ques-tions and their effective use, see Beatty et al.(2006), Wieman et al. (2008), and Bruff (2009).

Clicker questions generally pose well-defined, discrete problems that are directly re-lated to the immediate class content. Othervaluable problem-based activities can be basedon larger, more open-ended questions thatgroups of students may work on for a largerfraction of the class period and continue out-side of class (see following section). But all

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are examples of building instruction aroundstudent engagement with a problem, ratherthan around a body of factual information.Prince & Felder (2007) have contrasted de-ductive teaching—transmitting facts, abstractconcepts, and, finally, (maybe) discussing theirapplication to real-world problems—with in-ductive teaching—posing a real-world problemto students at the start, and letting them un-cover the relevant concepts and facts in the pro-cess of solving it. When teaching is deductive,student motivation to learn facts and concepts isoften primarily extrinsic, driven by desire to ob-tain a good grade, and the instructor must tryto keep students engaged with assertions thatthis knowledge will be important in their futurestudies or careers. By contrast, when teaching isinductive, the students are presented with a realworld scenario (relevant to the particular groupof students being taught) that they are likely tofind interesting, and their motivation is intrin-sic, based on desire to find a solution. Induc-tive approaches have been given a variety of la-bels, including inquiry-based, problem-based,project-based, case-based, question-driven, anddiscovery learning (reviewed in Prince & Felder2007). Their scope can range from a series ofrelated clicker questions in a single class period(Beatty et al. 2006) to a complex problem re-quiring several weeks of work, in which new in-formation is provided in response to requestsfrom students for data or results of specificexperimental tests. Disease-related, problem-based, and case-based activities, in which stu-dents are presented with a set of symptomsand asked to arrive at a diagnosis, are usedextensively in medical education (Albanese &Mitchell 1993).

Instructors who wish to introduce more ac-tive learning into their classes may confrontseveral problems. Implementing this modeof teaching can involve more up-front effortthan the promising practices discussed above.Although designing a new course around the ac-tive learning model may require no more effortthan preparing the lectures for a new traditionalcourse, transforming a traditional course re-quires the additional work of creating effective

Transmissionist: theview that learning canor must occur bytransmission ofknowledge from aninstructor to thelearner

in-class activities and formative assessments.Another problem is that traditional auditorium-style classrooms with fixed seating are poorlysuited for interactive group work. A few institu-tions have installed large classrooms with cafe-style seating, which greatly facilitates student-centered teaching (see Beichner 2008), andmore such classrooms are needed to encouragecourse transformation. A final problem, per-haps most difficult for some instructors, is thatteaching effectively in the new mode requiresboth a willingness to let go of some controlin the classroom and a change in perspective,from instructor-centered teaching to student-centered learning. Instructors must give up thewidely held transmissionist view that studentsmust be told everything they need to know, andinstead realize that not only are students in astimulating and supportive environment capa-ble of learning a great deal on their own (theconstructivist viewpoint), but that they mustdevelop this ability in order to become eithersuccessful scientists or well-informed citizens.

Balanced against the above potential diffi-culties is the clear evidence from DBER thatmoving toward more active learning in a morestudent-centered classroom can substantiallyincrease student learning gains. And completerestructuring is not necessary; even incremen-tal changes can have a significant effect (e.g.Knight & Wood 2005). Other evidence fromthe life sciences has been mentioned (Udovicet al. 2002, Armstrong et al. 2007, Freemanet al. 2007), and additional references can befound in Froyd (2008).

Out-of-Class Learning Activities:Instructor versus StudentResponsibility for Learning

A frequent concern of instructors contemplat-ing introduction of clickers and other active-learning activities into their classrooms is thatthey will no longer be able to cover all the nec-essary content. First of all, this may not be abad thing. More coverage does not necessarilymean more learning, and it can be argued thatdeep student understanding of a few important

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MCAT: medicalcollege admission test

concepts is more valuable than superficial expo-sure to many concepts. Nevertheless, the con-tent issue is real because it can affect studentpreparation for subsequent courses and stan-dardized tests such as the MCAT. A solution tothis dilemma lies in placing more of the respon-sibility on the students themselves for learningbasic concepts, and again, recent technologymakes this solution more practical. Using an ap-proach that physicists have called Just-in-TimeTeaching ( JiTT) (Novak et al. 1999), studentsare assigned reading and required to submithomework online to a course Web site before atopic is considered in class. The instructor canthen scan the results (sampling randomly if theclass is large), determine which concepts stu-dents seem to have grasped on their own, andthen focus activities in the upcoming class onconcepts they found difficult. Students may re-sist taking this responsibility, but again, learn-ing to do so is essential preparation for later ad-vanced study as well as for the real world, whereone cannot expect to receive a lecture whenevera new concept must be learned. An extension ofJiTT, which may be more palatable to students,is the inverted classroom approach (Lage et al.2000). Students are provided in advance of classwith access to podcasts of a PowerPoint lectureby the instructor, or some other multimediapresentation that serves the information trans-mission function of the traditional in-class lec-ture. Class time can then be devoted to clickerquestions, solving problems, interpreting data,or other active learning activities, without con-cerns about decreased content coverage.

The implementation of these approachesis quite simple using the Internet and one ofthe Web-based course management programsthat are now available at most universitiesto instructors of large classes. Many facultyhave reported not only increased student learn-ing with these methods but also strong en-dorsement by students once they realized howmuch they were learning (e.g., Klionsky 2004,Silverthorn 2006).

In general, the practice of assigning home-work is underutilized in teaching biology.Homework may not be of much help for

assimilating factual information, but in trans-formed courses designed to help studentsachieve higher Bloom’s levels of understanding,homework assignments that require students topractice applying concepts, solving problems,predicting outcomes, analyzing data, and de-signing experiments can be an invaluable sup-plement to similar in-class exercises. In additionto more traditional forms of homework, inter-active simulations (e.g., http://phet.colorado.edu/index.php) and educational video games(Mayo 2009) seem likely to become increasinglyuseful as out-of-class learning activities.

Student-Faculty Interaction in Class:Making Pedagogy Explicit

Many students, who have become comfortablewith traditional instruction, may object to thenew teaching approaches and the demands thatare placed on them in transformed courses:more responsibility for learning outside of class,the need to attend class regularly, the emphasison group work, refusal of the instructor to tellthem all the things they need to know, and soon. The best way to confront these objections,in the author’s experience as well as in the lit-erature (e.g., Silverthorn 2006), is to encour-age buy-in by being open with students aboutthe pedagogical reasons for new approaches andthe benefits they bring. For example, the in-structor can spend a few minutes introducingthe concept of Bloom’s levels, and remind stu-dents that the skills likely to determine theirsuccess in graduate work and the job marketcorrespond to levels 3–6, not levels 1 and 2(Figure 1). Instructors can show students ev-idence from DBER that group work and ac-tive learning can substantially increase learninggains, and point out, as mentioned above, thatthese activities will better prepare them for lifein the real world. But instructors should also besympathetic and supportive of students strug-gling with these changes, because students, likeinstructors, must shift their perceptions aboutteaching and learning in order to succeed withthe new instructional approaches (Silverthorn2006).

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The active learning activities discussedabove greatly increase the amount of student-faculty interaction in comparison with tradi-tional lecture settings. Use of clickers with peerinstruction, in particular, is an easy way to moveclasses from one-way transmission of informa-tion to interactive dialogs between instructorand students, and between students, with in-structional benefits that have been documentedby research as described in the preceding para-graphs above.

Student-Faculty Contact Out of Class:Office Hours versus EnhancedCommunication

Umbach & Wawrzynski (2005) cite severalstudies showing that, in general, studentlearning is enhanced by increased student-faculty contact, suggesting that faculty, as timepermits, should provide more opportunities forinteraction than simply holding office hours forthose (often few) students who will make useof them. Additional interactions can includebrief get-acquainted visits by invitation to theinstructor’s office, or for larger courses, virtualcommunication through emails to the class,moderated discussion forums, or use of socialnetworking Web sites. Aside from requiringsome additional faculty time, this practice iseasy to implement, and its efficacy is supportedby the studies referenced above.

Use of Teaching Assistants: Gradingand Recitation versus Facilitation ofStudent Learning

Many instructors of large STEM courses havehelp from one or more teaching assistants(TAs), whose principal tasks are grading ofhomework and exams and perhaps conduct-ing recitation sessions to go over lecture ma-terial and solutions to homework problems.If TAs are made part of the course transfor-mation process and given minimal pedagogi-cal training (e.g., reading of Handelsman et al.2007), they can serve as valuable facilitatorsin class for discussion of clicker questions orgroup work on problems. In addition, they will

have gained a new kind of teaching experi-ence that can serve them well in the future ifthey should go on to become faculty them-selves. Many institutions, for example thoseinvolved in the Center for the Integration ofResearch, Teaching, and Learning (CIRTL)Network (http://www.cirtl.net/), provide suchtraining to STEM graduate students in Prepar-ing Future Faculty programs (e.g., Miller et al.2008). This practice is quite easy to imple-ment, and research to evaluate its efficacy isin progress at the author’s institution and else-where (personal communications).

Student Laboratories: CookbookExercises versus Inquiry

As one solution to the problem of inade-quate STEM education for undergraduates, theCarnegie Foundation’s Boyer Commission Re-port (Boyer 1998) recommended that researchuniversities integrate their research and teach-ing missions by involving more students inthe process of research. In traditional “cook-book labs” associated with many large in-troductory lecture courses, students performprescribed exercises in which they may learnsome laboratory techniques but generally gainlittle understanding of scientific inquiry. At theother end of the lab experience spectrum (seeFigure 3), some undergraduates become ap-prentices in faculty laboratories, learning howscience is done by working alongside graduatestudents and postdocs on research projects thatoften result in publication. Although this expe-rience is highly desirable, most departments canprovide it to only a fraction of their majors. Be-tween these extremes, some departments havedeveloped a variety of inquiry-based laboratorycourses designed to introduce large numbers ofstudents to the process of research (reviewed inWeaver et al. 2008). These courses range fromguided inquiry labs to open-ended group re-search projects that may result in publicationsby undergraduates (e.g., Hanauer et al. 2006).Faculty who supervise these courses oftendesign them to yield results that can contributedirectly to their own research programs.

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More studentautonomy andresponsibility

Less studentautonomy andresponsibility

Traditionalverification(cookbook)lab courses

Open inquirylab courses

Guided inquirylab courses

Researchproject lab

courses

Apprenticeshipin a faculty lab

Figure 3The range of student laboratory experiences, from verification exercises (“cookbook labs”) to apprenticeshipin a faculty research laboratory. Levels of student responsibility and autonomy increase from left to right.(Adapted from Weaver et al. 2008.)

Implementation of inquiry-based courses inplace of traditional labs may require additionalresources, including more extensive training forTAs. Although Froyd (2008) rates this promis-ing practice low in terms of evidence for effi-cacy, several studies, in addition to the two citedabove, have shown that engagement of stu-dents with real research problems is one of themost effective ways to move students along thepath from novice to expert (Nagda et al. 1998,Lopatto 2004, Luckie et al. 2004, Seymouret al. 2004). Compared to students who ex-perience only traditional lab courses, reportedbenefits to students in inquiry-based curriculainclude deeper understanding of content, in-creased confidence in their ability to understandand perform science, more positive attitudesabout science, and lower attrition rates. Thesegains are particularly evident among under-represented minority students (Nagda et al.1998, Russell et al. 2007). Thus, the benefitsof this promising practice can include not onlyincreased student learning and higher retentionof students in the major (especially if inquiry-based labs are introduced early in the curricu-lum), but also contributions to faculty research.

CONCLUSION: THE DUALFUNCTIONS OF BIOLOGYEDUCATION

There are two important purposes for the in-troductory biology courses we teach. One is

to attract, motivate, and begin preparing thenext generation of biologists, including the re-search stars of the future. The other is to helpthe large majority of our students who will notbecome biologists or even scientists to achieveminimum biological literacy and to understandthe nature of science, the importance of empir-ical evidence, and the basic principles that un-derlie biological systems. They will need thisknowledge as twenty-first century citizens ofthe United States and the world to make in-telligent decisions about issues such as personalhealth, conflicting claims in the media, energypolicy, climate change, and conservation of nat-ural resources.

Traditional teaching methods do notprevent the progress of superior studentsfrom introductory courses to upper-levelcourses to graduate training, where they maybecome experts in their fields and developinto skilled researchers. But the traditionalmethods fail the majority of students, wholeave our introductory courses viewing biologyas a large collection of disconnected facts thathave little relevance to their daily lives andwill soon be forgotten. Part of the problem,as described in this review, lies not in whatwe teach these students (though this is alsoa concern; see NRC 2003, AAMC-HHMI2009), but in how we teach it. We must dobetter! Widespread adoption of the research-based promising practices described here willhelp.

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SUMMARY POINTS

1. We must improve the undergraduate teaching of biology and other STEM disciplinesto remain competitive in the global economy and educate American citizens adequately.

2. Recent research in educational psychology, cognitive science, and neurobiology hasyielded important new insights into how people learn and the optimal conditions forlearning.

3. Discipline-based educational research (DBER) has led to the development of teachingapproaches based on these insights (promising practices), and has provided extensive evi-dence that these approaches can be substantially more effective than traditional lecturing,even in large classes.

4. These promising practices vary in their ease of implementation, but even their partialadoption can lead to significant gains in student learning.

5. Applying these promising practices widely in STEM classes can have a major impact onbetter preparing our undergraduate biology students for their future endeavors.

DISCLOSURE STATEMENT

The author is Editor-in-Chief of CBE-Life Sciences Education.

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