Pedagogy

April 2006 Journal of Engineering Education 123

MICHAEL J. PRINCE Department of Chemical Engineering Bucknell University

RICHARD M. FELDER Department of Chemical Engineering North Carolina State University

To state a theorem and then to show examples of it is literally to teach backwards.

(E. Kim Nebeuts)

ABSTRACT

Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories. Alternative teaching approaches are more inductive. Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been estab- lished. This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem- based learning, project-based learning, case-based teaching, dis- covery learning, and just-in-time teaching. The paper defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness of the methods. While the strength of the evidence varies from one method to another, inductive methods are consistently found to be at least equal to, and in general more effective than, traditional deductive methods for achieving a broad range of learning outcomes.

Keywords: inductive, teaching, learning

I. INTRODUCTION

A. Two Approaches to Education Engineering and science are traditionally taught deductively.

The instructor introduces a topic by lecturing on general princi-

ples, then uses the principles to derive mathematical models,

shows illustrative applications of the models, gives students prac-

tice in similar derivations and applications in homework, and

finally tests their ability to do the same sorts of things on exams.

Little or no attention is initially paid to the question of why any of that is being done. What real-world phenomena can the models

explain? What practical problems can they be used to solve, and

why should the students care about any of it? The only motivation

that students get—if any—is that the material will be important

later in the curriculum or in their careers.

A well-established precept of educational psychology is that

people are most strongly motivated to learn things they clearly

perceive a need to know [1]. Simply telling students that they will

need certain knowledge and skills some day is not a particularly

effective motivator. A preferable alternative is inductive teaching and learning. Instead of beginning with general principles and eventually getting to applications, the instruction begins with

specifics—a set of observations or experimental data to interpret,

a case study to analyze, or a complex real-world problem to solve.

As the students attempt to analyze the data or scenario and solve

the problem, they generate a need for facts, rules, procedures, and

guiding principles, at which point they are either presented with

the needed information or helped to discover it for themselves.

Inductive teaching and learning is an umbrella term that en-

compasses a range of instructional methods, including inquiry

learning, problem-based learning, project-based learning, case-

based teaching, discovery learning, and just-in-time teaching.

These methods have many features in common, besides the fact

that they all qualify as inductive. They are all learner-centered (also known as student-centered), meaning that they impose more re- sponsibility on students for their own learning than the traditional

lecture-based deductive approach. They are all supported by re-

search findings that students learn by fitting new information into

existing cognitive structures and are unlikely to learn if the infor-

mation has few apparent connections to what they already know

and believe. They can all be characterized as constructivist meth- ods, building on the widely accepted principle that students con-

struct their own versions of reality rather than simply absorbing

versions presented by their teachers. The methods almost always

involve students discussing questions and solving problems in

class (active learning), with much of the work in and out of class being done by students working in groups (collaborative or cooper- ative learning). The defining characteristics of the methods and features that most of them share are summarized in Table 1.

There are also differences among the different inductive meth-

ods. The end product of a project-based assignment is typically a

formal written and/or oral report, while the end product of a

guided inquiry may simply be the answer to an interesting ques-

tion, such as why an egg takes longer to boil at a ski resort than at

the beach and how frost can form on a night when the tempera-

ture does not drop below freezing. Case-based instruction and

problem-based learning involve extensive analyses of real or hypo-

thetical scenarios while just-in-time teaching may simply call on

students to answer questions about readings prior to hearing

Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases

about the content of the readings in lectures. However, the

similarities trump the differences, and when variations in the im-

plementation of the methods are taken into account, many of the

differences disappear altogether.

Although we just claimed that inductive methods are essentially

variations on a theme, they do not appear that way in the litera-

ture. Each method has its own history, research base, guidebooks,

proponents, and detractors, and a great deal of confusion exists re-

garding what the methods are and how they are interrelated. Our

objective in this paper is to summarize the definitions, founda-

tions, similarities, and differences among inductive learning

methods and to review the existing research evidence regarding

their effectiveness.

Before we begin our review, we will attempt to clarify two

points of confusion that commonly arise in discussions of induc-

tive methods.

Is inductive learning really inductive? In practice, neither teach- ing nor learning is ever purely inductive or deductive. Like the sci-

entific method, learning invariably involves movement in both di-

rections, with the student using new observations to infer rules

and theories (induction) and then testing the theories by using

them to deduce consequences and applications that can be verified

experimentally (deduction). Good teaching helps students learn

to do both. When we speak of inductive methods, we therefore do

not mean total avoidance of lecturing and complete reliance on

self-discovery, but simply teaching in which induction precedes

deduction. Except in the most extreme forms of discovery learn-

ing (which we do not advocate for undergraduate instruction), the

instructor still has important roles to play in facilitating learning—

guiding, encouraging, clarifying, mediating, and sometimes even

lecturing. We agree with Bransford: “There are times, usually

after people have first grappled with issues on their own, that

‘teaching by telling’ can work extremely well” [2, p. 11].

Are we talking about inductive learning or inductive teaching? Is there a difference? A common point of semantic confusion associ- ated with inductive methods has to do with the distinction between

teaching and learning. Thus, for example, one hears about prob-

lem-based learning but just-in-time teaching, and both inquiry

learning and inquiry-based teaching are commonly encountered in

the literature. There is, of course, a difference between learning

(what students do) and teaching (what teachers do), but in this

paper we will never examine one without explicitly or implicitly

considering the other. The reader should therefore understand that

when we refer to “inductive learning” or to an inductive instruction-

al method with either teaching or learning in its name, we are talk-

ing about both strategies that an instructor might use (teaching) and

experiences the students might subsequently undergo (learning).

II. FOUNDATIONS OF INDUCTIVE TEACHING AND LEARNING

A. Constructivism According to the model that has dominated higher education

for centuries (positivism), absolute knowledge (“objective reality”) exists independently of human perception. The teacher’s job is to

transmit this knowledge to the students—lecturing being the nat-

ural method for doing so—and the students’ job is to absorb it. An

alternative model, constructivism, holds that whether or not there is an objective reality (different constructivist theories take opposing

views on that issue), individuals actively construct and reconstruct

their own reality in an effort to make sense of their experience.

New information is filtered through mental structures (schemata) that incorporate the student’s prior knowledge, beliefs, preconcep-

tions and misconceptions, prejudices, and fears. If the new infor-

mation is consistent with those structures it may be integrated into

124 Journal of Engineering Education April 2006

Table 1. Features of common inductive instructional methods.

them, but if it is contradictory, it may be memorized for the exam

but is unlikely to be truly incorporated into the individual’s belief

system—which is to say, it will not be learned.

Constructivism has its roots in the eighteenth-century philoso-

phies of Immanuel Kant and Giambattista Vico, although some

have traced it as far back as the fourth to sixth centuries B.C. in the

works of Lao Tzu, Buddha, and Heraclitus. The constructivist view

of learning is reflected in the developmental theories of

Piaget [3], Dewey [4], Bruner [5], and Vygotsky [6], among others.

In cognitive constructivism, which originated primarily in the work of Piaget, an individual’s reactions to experiences lead to (or fail to lead

to) learning. In social constructivism, whose principal proponent is Vygotsky, language and interactions with others—family, peers,

teachers—play a primary role in the construction of meaning from

experience. Meaning is not simply constructed, it is co-constructed.

Proponents of constructivism (e.g., Biggs [7]) offer variations

of the following principles for effective instruction:

● Instruction should begin with content and experiences likely

to be familiar to the students, so they can make connections

to their existing knowledge structures. New material should

be presented in the context of its intended real-world appli-

cations and its relationship to other areas of knowledge,

rather than being taught abstractly and out of context.

● Material should not be presented in a manner that requires

students to alter their cognitive models abruptly and drasti-

cally. In Vygotsky’s terminology, the students should not be

forced outside their “zone of proximal development,” the re-

gion between what they are capable of doing independently

and what they have the potential to do under adult guidance

or in collaboration with more capable peers [6]. They should

also be directed to continually revisit critical concepts, im-

proving their cognitive models with each visit. As Bruner [5]

puts it, instruction should be “spirally organized.”

● Instruction should require students to fill in gaps and ex-

trapolate material presented by the instructor. The goal

should be to wean the students away from dependence on

instructors as primary sources of required information,

helping them to become self-learners.

● Instruction should involve students working together in

small groups. This attribute—which is considered desirable

in all forms of constructivism and essential in social

constructivism—supports the use of collaborative and

cooperative learning.

The traditional lecture-based teaching approach is incompati-

ble with all of these principles. If the constructivist model of learn-

ing is accepted—and compelling research evidence supports it—

then to be effective instruction must set up experiences that

induce students to construct knowledge for themselves, when

necessary adjusting or rejecting their prior beliefs and misconcep-

tions in light of the evidence provided by the experiences. This

description might serve as a definition of inductive learning.

B. Cognition Research Bransford et al. [2] offer a comprehensive survey of neurologi-

cal and psychological research that provides strong support for

constructivism and inductive methods. Here are some of their

findings:

● “All new learning involves transfer of information based on previous learning” [2, p. 53].

Traditional instruction in engineering and science frequently

treats new courses and new topics within courses as self-contained

bodies of knowledge, presenting theories and formulas with mini-

mal grounding in students’ prior knowledge and little or no

grounding in their experience. Inductive instruction, on the other

hand, presents new information in the context of situations, is-

sues, and problems to which students can relate, so there is a much

greater chance that the information can be linked to their existing

cognitive structures.

Since learning is strongly influenced by prior knowledge, if new

information is fully consistent with prior knowledge it may be

learned with relative ease, but if it involves a contradiction several

things may happen. If the contradiction is perceived and understood,

it may initially cause confusion but the resolution of the contradic-

tion can lead to elimination of misconceptions and greater under-

standing. However, if learners fail to understand the contradiction or

if they can construct coherent (to them) representations of the new

material based on existing misconceptions, deeper misunderstand-

ing may follow [2, p. 70]. Traditional teaching generally does little to

force students to identify and challenge their misconceptions, lead-

ing to the latter situation. The most effective implementations of in-

ductive learning involve diagnostic teaching, with lessons being de- signed to “discover what students think in relation to the problems

on hand, discussing their misconceptions sensitively, and giving

them situations to go on thinking about which will enable them to

readjust their ideas” [2, p. 134]. The proper choice of focus questions

and problems in inquiry-based, problem-based, and discovery learn-

ing methods can serve this function.

● Motivation to learn affects the amount of time students are will- ing to devote to learning. Learners are more motivated when they can see the usefulness of what they are learning and when they can use it to do something that has an impact on others [2, p. 61].

This finding supports techniques that use authentic (real-

world, professionally relevant) situations and problems to provide

contexts for learning the content and skills a course is intended to

teach. Inductive methods such as problem-based learning and

case-based teaching do this.

● The likelihood that knowledge and skills acquired in one course will transfer to real work settings is a function of the similarity of the two environments [2, p. 73].

School often emphasizes abstract reasoning while work focuses

almost exclusively on contextualized reasoning. Organizing learning

around authentic problems, projects, and cases helps to overcome

these disparities and improves the likelihood of subsequent transfer,

in addition to increasing motivation to learn as noted in the previous

item. Moreover, traditional schools differ from most work environ-

ments in that school heavily emphasizes individual work while most

work involves extensive collaboration. Assigning teams to perform

most required tasks (as most inductive methods do) thus further pro-

motes transfer, provided that the students are helped to develop

teamwork skills and the work is organized in a way that assures indi-

vidual accountability for all of the learning that takes place [8–12].

● Helping students develop metacognition—knowledge of how they learn—improves the likelihood of their transferring infor- mation learned in one context to another one [2, p. 67].

Methods that train students in systematic problem-solving

methods (generating and evaluating alternative solutions, periodi-

cally assessing progress toward the solution, extracting general

principles from specific solutions, etc.) and call on them to make

April 2006 Journal of Engineering Education 125

sense of new information, to raise questions when they cannot,

and to regularly assess their own knowledge and skill levels pro-

mote the development of metacognitive skills. Most variants of

problem-based learning include such steps.

C. Intellectual Development and Approaches to Learning Most college students undergo a developmental progression from

a belief in the certainty of knowledge and the omniscience of author-

ities to an acknowledgment of the uncertainty and contextual nature

of knowledge, acceptance of personal responsibility for determining

truth, inclination and ability to gather supporting evidence for judg-

ments, and openness to change if new evidence is forthcoming [13,

14]. At the highest developmental level normally seen in college stu-

dents (termed “contextual relativism” by Perry [13]), individuals dis-

play thinking patterns resembling those of expert scientists and engi-

neers. A goal of science and engineering instruction should be to

advance students to that level by the time they graduate.

In their courses, students may be inclined to approach learning

in one of three ways [15]. Some take a surface approach, relying on rote memorization and mechanical formula substitution, making

little or no effort to understand the material being taught. Others

may adopt a deep approach, probing and questioning and exploring the limits of applicability of new material. Still others use a strate- gic approach, doing whatever is necessary to get the highest grade they can, taking a surface approach if that suffices and a deep ap-

proach when necessary. Another goal of instruction should be to

induce students to adopt a deep approach to subjects that are im-

portant for their professional or personal development.

Felder and Brent [16] observe that the characteristics of high

levels of intellectual development and of a deep approach to learn-

ing are essentially the same. Both contextual relativism and a deep

approach involve taking responsibility for one’s own learning,

questioning authorities rather than accepting their statements at

face value, and attempting to understand new knowledge in the

context of prior knowledge and experience. It is reasonable to as-

sume that instructional conditions that induce students to adopt a

deep approach should also promote intellectual growth.

Several conditions of instruction have been shown to promote

a deep approach, including interest and background knowledge of

the subject, use of teaching methods that foster active and long-

term engagement with learning tasks, and assessment that em-

phasizes conceptual understanding as opposed to recall or the ap-

plication of routine procedural knowledge [17]. Well

implemented inductive teaching methods serve all of these func-

tions. Authentic problems and case studies can motivate students

by helping to make the subject matter relevant, and they also tend

to keep the students interested and actively engaged in their learn-

ing tasks. Having to analyze complex situations also promotes the

students’ adoption of a deep approach to learning, as rote memo-

rization and simple algorithmic substitution are clearly inadequate

strategies for dealing with such situations. Moreover, open-ended

problems that do not have unique well-defined solutions pose se-

rious challenges to students’ low-level beliefs in the certainty of

knowledge and the role of instructors as providers of knowledge.

Such challenges serve as precursors to intellectual growth [14].

D. Learning Cycle-Based Instruction Several well-known instructional models involve learning cycles,

wherein students work through sequences of activities that involve

complementary thinking and problem-solving approaches. In

most of these cycles, the different activities are designed to appeal

to different learning style preferences (concrete and abstract, ac-

tive and reflective, etc.) [18]. When instructors teach around the cycle in this manner, all students are taught partly in a manner they prefer, which leads to an increased comfort level and willingness

to learn, and partly in a less preferred manner, which provides

practice and feedback in ways of thinking they might be inclined

to avoid but which they will have to use to be fully effective profes-

sionals. Teaching around the best known of such cycles—that

associated with Kolb’s experiential learning model [19]—involves:

(1) introducing a problem and providing motivation for solving it

by relating it to students’ interests and experience (the focal ques-

tion is why?); (2) presenting pertinent facts, experimental observa- tions, principles and theories, problem-solving methods, etc., and

opportunities for the students to reflect on them (what?); (3) pro- viding guided hands-on practice in the methods and types of

thinking the lessons are intended to teach (how?); and (4) allow- ing and encouraging exploration of consequences and applications

of the newly learned material (what if ?). A learning cycle developed at the Vanderbilt University Learn-

ing Technology Center is the STAR Legacy module (Software Technology for Action and Reflection) [20], which consists of the

following steps:

1. Students are presented with a challenge (problem, scenario, case, news event, or common misconception presenting the

targeted content in a realistic context) that establishes a

need to know the content and master the skills included in

the learning objectives for the module.

2. The students then formulate their initial thoughts, reflecting on what they already know and think about the context of

the challenge and generating ideas about how they might

address the challenge.

3. Perspectives and resources are provided next. Perspectives are statements by experts that offer insights into various dimen-

sions of the challenge without providing a direct solution to

it, and resources may include lectures, reading materials,

videos, simulations, homework problems, links to websites,

and other materials relevant to the challenge.

4. Assessment activities are then carried out in which the stu- dents apply what they know, and identify what they still

need to learn to address the challenge. The activities may

include engaging in self-assessments and discussions, com-

pleting homework assignments, writing essays or reports,

and taking on-line quizzes or exams. Multiple iterations be-

tween Steps 3 and 4 would normally be required to fully

meet the challenge.

5. In the final wrap-up, an expert may present a model solu- tion to the challenge, or the students may present a report

and/or complete an examination showing that they have

met the challenge and demonstrated their mastery of the

knowledge and skills specified in the learning objectives.

The Star Legacy module is a clear exemplar of an inductive ap-

proach to teaching and learning. Depending on the nature and

scope of the challenge, instruction based on such a module would

qualify as inquiry learning, project-based learning, or problem-

based learning. Similarly, learning cycles based on learning styles

that begin with the presentation of a realistic problem or a challenge

of some sort are inductive. Instruction based on learning cycles is

126 Journal of Engineering Education April 2006

consistent with accepted principles of cognitive science [2] and its

effectiveness has been repeatedly demonstrated empirically [21].

In summary, inductive approaches to teaching and learning

have much in their favor. They are supported by the best research

on learning currently available, compatible with the currently

most widely accepted theories of learning, and promote problem-

solving skills and attitudes to learning that most instructors would

say they desire for their students. Following a brief section on as-

sessment, we will examine the individual inductive methods—

what they are, what they have in common and how they differ,

and what is known about how well they succeed in achieving de-

sired educational outcomes.

III. ASSESSMENT AND EVALUATION OF INDUCTIVE METHODS

Rigorous comparisons of inductive methods with traditional

expository methods are not easy to design for several reasons [22].

● There are many varieties of inductive approaches, each of

which can be implemented in many ways—with greater or

lesser instructor involvement, with or without formal facili-

tation of teamwork, with most of the work being done in or

out of class, and so on. Two articles may claim to be studies

of, say, problem-based learning, but they could involve dra-

matically different forms of instruction and may well pro-

duce different learning outcomes.

● Instructors may have varying degrees of experience and skill

with whichever method they adopt. Two different instruc-

tors using the same method in the same class could get dif-

ferent results.

● Student populations also vary considerably in distributions of

gender and ethnicity, age, experience, motivation to learn,

learning styles, and levels of intellectual development (among

others) [21]. The same instructor could use the same method

in two different classes and get different outcomes.

● The conclusions drawn from a study may depend strongly

on the learning outcome investigated—acquisition of factual

knowledge, development of a problem-solving or interper-

sonal skill, retention in a curriculum, self-confidence level,

attitude, or any combination of these. An inductive method

may be superior with respect to one outcome and inferior

with respect to another. (We will shortly see an example of

this phenomenon in the case of problem-based learning,

which has frequently been found to lead to superior high-

level skills and attitudes but inferior short-term acquisition

of factual knowledge.) Moreover, reliable and valid assess-

ments of high-level skills such as critical or creative think-

ing or attributes such as lifelong learning skills are difficult

to obtain, and two studies that use different assessment

methods could arrive at different conclusions.

● Finally, as Prince [22] points out, implementations of in-

ductive approaches such as problem-based learning nor-

mally involve active and collaborative learning methods,

both of which are known to have positive effects on many

learning outcomes. If an inductive method is found to have

a positive effect, sorting out how much of it can be attrib-

uted to the method itself and how much to other methods

imbedded in it can be a formidable challenge.

Considering these difficulties, it is not surprising that pub-

lished studies report both positive and negative outcomes for in-

ductive learning relative to conventional instruction. Given the

difficulty (if not impossibility) of carrying out a clean and conclu-

sive comparative study, the best we can do is to look at results

from a number of studies with different instructors, implementa-

tions, learning outcomes, and student populations, to see if any

robust generalizations can be inferred. The sections that follow

summarize results of such meta-analyses.

IV. INQUIRY LEARNING

A. Definition and Applications Inquiry learning begins when students are presented with

questions to be answered, problems to be solved, or a set of obser-

vations to be explained [23]. If the method is implemented effec-

tively, the students should learn to “formulate good questions,

identify and collect appropriate evidence, present results systemat-

ically, analyze and interpret results, formulate conclusions, and

evaluate the worth and importance of those conclusions [24].”

The same statements could also be made about problem-based

learning, project-based learning, discovery learning, certain forms

of case-based instruction, and student research, so that inquiry

learning may be considered an umbrella category that encompasses

several other inductive teaching methods. Lee makes this point,

observing that inquiry is also consistent with interactive lecture,

discussion, simulation, service learning, and independent study,

and in fact “probably the only strategy that is not consistent with

inquiry-guided learning is the exclusive use of traditional lectur-

ing” [24, p. 10]. In this paper we will use the term inquiry learning to refer to instruction that uses questions and problems to provide

contexts for learning and does not fall into another more restric-

tive inductive learning category.

Besides overlapping with other inductive methods, inquiry

learning encompasses a variety of techniques that differ from one

another in significant ways. Staver and Bay [25] differentiate be-

tween structured inquiry (students are given a problem and an outline for how to solve it), guided inquiry (students must also fig- ure out the solution method) and open inquiry (students must for- mulate the problem for themselves). Smith [26] makes a similar

distinction between teacher inquiry, in which the teacher poses questions, and learner inquiry, in which questions are posed by the students. In process-oriented-guided-inquiry-learning (POGIL), students work in small groups in a class or laboratory

on instructional modules that present them with information or

data, followed by leading questions designed to guide them to-

ward formulation of their own conclusions. The instructor serves

as facilitator, working with student groups if they need help and

addressing class-wide problems when necessary. Some propo-

nents of inquiry suggest using a relatively structured form of in-

quiry in the first year, gradually shifting toward more self-directed

learning (including problem formulation) as the curriculum

progresses, while others advocate moving immediately to self-

direction [24].

Inquiry-based methods have been used extensively in the sci-

ences [27–32] and to a lesser extent in engineering [33, 34]. Guid-

ed inquiry has been particularly widely used in chemistry curricula.

The POGIL Web site contains reports of implementations on

April 2006 Journal of Engineering Education 127

several campuses, instructional materials for different branches of

chemistry, and a video showing an implementation of the method

in an introductory chemistry class.1

Lee et al.[24] report on a series of inquiry-based courses in dif- ferent disciplines at North Carolina State University that had four

desired student outcomes in common: (a) improved critical think-

ing skills, (b) greater capacity for independent inquiry, (c) taking

more responsibility for one’s own learning, (d) intellectual growth

(e.g., on the Perry scale of intellectual development). Following

are several examples.

● Introductory chemistry and physics courses are conducted

in a hands-on inquiry-based environment called SCALE-

UP (Student-Centered Activities for Large Enrollment

University Programs) [35]. Students read and take quizzes

about assigned material before coming to class (a charac-

teristic of Just-in-Time Teaching, another inductive tech- nique to be discussed), and work in teams on activities

designed to help them discover or investigate concepts for

themselves.

● In an introductory first-year microbiology course, the stu-

dents read articles, generate questions stimulated by the

readings, identify underlying hypotheses and assumptions

in the articles, discuss their findings in small groups, and

submit both their individual work and group assignments.

In honors sections of several third-year microbiology courses,

the students do extensive analysis and interpretation of

experimental data and case studies, with emphasis being

placed on collecting and interpreting scientific data and

testing hypotheses [36].

● In a first-year paper science and engineering course, the

students complete an open-ended design project, and in

another first-year course they spend most of their time

working in teams on advanced problems at a level previously

reserved for seniors, learning on their own a great deal of

the material that would traditionally have been delivered in

lectures [37].

● In an experimental College of Engineering program, instruc-

tors are given grants to develop innovative classroom applica-

tions of laptop computers with wireless Internet

access, which are made available to all students in their cours-

es. Courses in this program that made inquiry a significant

component of their instruction included the second and third

semesters of calculus, in which students used MAPLE® to

explore solutions to real-world problems, and a course on

JAVA programming, in which students worked in pairs at

the computer during class to develop and implement pro-

grams and to clarify their conceptual understanding of

programming principles [38].

B. Evaluation Several published meta-analyses conclude that inquiry-based

instruction is generally more effective than traditional instruction

for achieving a variety of learning outcomes [26, 39]. Shymansky

et al. [40] analyzed results from 81 experimental studies involving thousands of students and found that inquiry learning produced

significant positive gains for academic achievement, student per-

ceptions, process skills and analytic abilities. In a meta-analysis of

79 individual studies between 1965 and 1995 involving students

from seventh grade through college, Smith [26] found that in-

quiry learning improved academic achievement (effect size � 0.33), critical thinking skills (effect size � 0.77) and laboratory skills (effect size � 0.14). There was also a slight improvement in process skills (effect size � 0.05), which was not statistically sig- nificant. In a meta-study of laboratory instruction conducted over

roughly the same time period, Rubin [41] found that inquiry-

based instruction was superior to traditional instruction for cogni-

tive learning outcomes, which included conceptual and subject

learning, reasoning ability, and creativity (effect size � 0.18), as well as for non-cognitive outcomes, including manipulative skills

and attitudes (effect size � 0.39). Colburn’s review of the literature [42] concludes that inquiry-

based methods are likely to be more effective than deductive

methods in helping students gain understanding of concrete ob-

servable phenomena, and less so in helping them understand how

scientists explain or model phenomena (e.g., via kinetic and mole-

cular theories in chemistry and physics). He recommends focus-

ing activities around questions that students can answer directly

via investigation, which helps assure that the activities are oriented

toward concrete concepts. He also advises emphasizing activities

that use materials and situations familiar to students for which

they have the necessary prerequisite skills and knowledge to suc-

ceed, but pose a sufficient level of challenge to help them develop

better thinking skills.

V. PROBLEM-BASED LEARNING

A. Definition and Applications Problem-based learning (PBL) begins when students are con-

fronted with an open-ended, ill-structured, authentic (real-world)

problem and work in teams to identify learning needs and develop

a viable solution, with instructors acting as facilitators rather than

primary sources of information [43–50]. Class time may be devoted

to: (a) groups reporting out their progress on previous learning

issues and listing their current learning issues and plans of work,

(b) mini-lectures giving information on issues being dealt with by

all groups, clarifying common difficulties, and suggesting addi-

tional learning issues, and (c) whole class discussion [50]. A well-

designed problem guides students to use course content and

methods, illustrates fundamental principles, concepts, and proce-

dures, and perhaps induces the students to infer those things for

themselves instead of getting them directly from the instructor;

and engages the students in the types of reflection and activities

that lead to higher-order learning. Problems may vary significantly

in scope, from single-topic single-discipline problems that can be

solved in a matter of days to multidisciplinary problems that may

take an entire semester to solve. The formulation of problems is

discussed by Weiss [47], Tan [48, Ch. 6], and several authors in

the edited volume of Duch et al. [49]. PBL may be implemented in a variety of ways [50]. In the

medical school model, students work in groups of 7–10 under the supervision of a faculty member or another designated tutor (e.g. a

graduate student or advanced undergraduate). There is very little

formal class time, if any. In the floating facilitator model, students work on problems in groups of three to five during class. The in-

structor moves from group to group during class, asking questions

128 Journal of Engineering Education April 2006

1Web site: www.pogil.org; Video: www.pogil.org/resources/GI_video.php.

and probing for understanding. Different levels of external guid-

ance may be provided by a faculty member or a designated tutor,

or responsibility for the work may be taken by the groups them-

selves in what Woods [51] calls self-directed, interdependent, small group problem-based learning. Acar and Newman [52] describe a module in which students in their final year of a systems engineer-

ing program served as tutors to first and second year students

doing PBL-based project work. The experience was instructive

for both the tutors and the tutees, with the former noting its help-

fulness in interviews and as preparation for the workplace.

Modern problem-based learning originated in medical

schools, principally those at Case Western Reserve University in

the 1950s and McMaster University in the 1960s. It is now ex-

tensively practiced in medical education and other health-related

disciplines including veterinary medicine and nursing [53], and

in other fields including architecture, psychology, business and

management, and engineering [48, 54]. It has been used in a

number of curricula at the University of Delaware and Samford

University in the United States, McMaster University in Canada,

the University of Maastricht in the Netherlands, Linköping Uni-

versity in Sweden, and the University of Newcastle in Australia;

in chemical engineering at McMaster [51, 55], Bucknell Univer-

sity [56, 57] and the Universitat Rovira I Virgili in Spain [58]

and civil engineering at Monash University in Australia [59–61];

and in an integrated physics, mathematics, and computer science

course at the Instituto Tecnológico y de Estudios Superiores de

Monterrey, Mexico [62]. PBL problems in chemistry and

physics (and many other fields) and guidance on how to use them

are given in Duch et al. [49] and on Web sites maintained at the University of Delaware2 and Samford University3, both of which

provide links to many other resources. A 2003 issue of the Inter- national Journal of Engineering Education (Vol. 19, No. 5) is de- voted entirely to PBL implementations at universities around the

world.

Nelson [63] discusses using design projects as a basis for

problem-based learning, observing that the stages of design—

naming (identifying main issues in the problem), framing (estab- lishing the limits of the problem), moving (taking an experimental action), and reflecting (evaluating and criticizing the move and the frame) provides an ideal framework for the PBL process. He cites

examples in which he used PBL successfully to teach graduate

courses in instructional design, software development, and project

management. The previously described Star Legacy module

developed at Vanderbilt University [20] provides another excel-

lent framework for PBL.

B. Evaluation Dochy et al. [64] published a meta-analysis of the effectiveness

of problem-based learning. The authors identified 43 empirical

studies of the effects of PBL on knowledge acquisition and devel-

opment of problem-solving skills in college students. Only studies

that utilized natural classroom instruction (as opposed to controlled

laboratory studies) were included in the data base. The average

effect size was calculated both in an unweighted form and with each

effect size weighted by the inverse of the variance (which being

proportional to N gives greater weight to larger samples).

Seven of the studies analyzed found a positive effect of PBL on

knowledge acquisition and 15 found a negative effect, with a

weighted average effect size and 95 percent confidence interval of

–0.223 (�0.058). When only true randomized tests are included; however, the negative effect of PBL on knowledge acquisition al-

most disappears, and when the assessment of knowledge is carried

out some time after the instruction was given, the effect of PBL is

positive. The implication is that students may acquire more

knowledge in the short term when instruction is conventional but

students taught with PBL retain the knowledge they acquire for a

longer period of time. For skill development, the results are un-

equivocal: 14 studies found a positive effect and none found a neg-

ative effect, and the weighted average effect size was 0.460

(�0.058). The positive effect of PBL on skill development holds regardless of whether the assessment is concurrent with the in-

struction or delayed.

Prince [22] examined several meta-analyses of problem-based

learning, separately considering the effects of its constituent ap-

proaches: active learning (actively engaging students in the learn-

ing process in class, as opposed to merely presenting them with

information), collaborative learning (students work on problems

and projects collaboratively rather than doing everything individ-

ually), and cooperative learning (team-based learning in which

certain criteria must be met, most notably, individual account-

ability for all of the learning that is supposed to take place). He

concluded that the strongest positive effects of PBL related to the

student and faculty responses to the method and to a small but

robust improvement in students’ skill development. While a sta-

tistically significant effect was not found for improvement of

academic achievement as measured by exams, there was evidence

that PBL enhanced students’ retention and ability to apply

material.

Individual studies have found a robust positive effect of PBL

on skill development [1, 65, 66], understanding the interconnec-

tions among concepts [65], deep conceptual understanding [67],

ability to apply appropriate metacognitive and reasoning strategies

[68], teamwork skills [69], and even class attendance [70], but

have not reached any firm conclusion about the effect on content

knowledge. A longitudinal study of the effectiveness of the

McMaster PBL program in chemical engineering demonstrated

its superiority to traditional education in the development of key

process skills [55]. PBL has also been shown to promote self-

directed learning [71] and the adoption of a deep (meaning-

oriented) approach to learning, as opposed to a superficial (mem-

orization-based) approach [21, 46, 72].

Several papers discuss the possible tradeoff between knowledge

acquisition and skill development, or alternatively, between

breadth and depth of content coverage when PBL is used. de

Graaf and Kolmos [73] observe that students may be expected to

reach a level of analytical comprehension through problem-based

work that cannot be attained in conventionally-taught classes, but

they might experience subject area gaps in doing so and so should

be equipped to fill in such gaps when a need arises. Perrenet et al. [74] make a similar point specifically related to engineering

education. They observe that if PBL is implemented in a way that

permits considerable self direction by the students, the learning

that takes place may not necessarily attack and correct the

misconceptions that hinder understanding of critical engineering

concepts, which could in turn interfere with the students’ ability to

April 2006 Journal of Engineering Education 129

2www.udel.edu/pbl 3www.samford.edu/pbl

apply their learning to novel problems in a professional setting.

They also note that unlike medicine, which has an encyclopedic

structure, the knowledge structures of engineering and the sci-

ences tend to be hierarchical. Engineering students engaged in

self-guided PBL might easily overlook or bypass critical topics,

which could interfere with future learning of important content,

especially if the implementation of PBL is curriculum-wide rather

than being limited to a few specific courses. Instructors should be

aware of these potential pitfalls and design courses and problem

sets so that all essential concepts are addressed.

Problem-based learning is not an easy instructional method to

implement. It requires considerable subject expertise and flexibility

on the part of instructors, who may be forced out of their areas of

expertise when student teams set off in unpredictable and unfa-

miliar directions. PBL also makes students assume unaccustomed

levels of responsibility for their own learning, and all of the project

management problems and interpersonal conflicts that commonly

occur when students are required to work in teams crop up in

PBL. Many students are consequently hostile to PBL when they

first encounter it, which can be intimidating to instructors who

are unprepared for this reaction. Instructors—particularly rela-

tively new ones—are therefore not advised to jump into full-scale

problem-based learning until they familiarize themselves with

proven facilitation techniques, and they are also advised to use

scaffolding, providing a fairly high level of guidance to students who are new to PBL and gradually withdrawing it as the students

gain more experience with the approach [75]. Tan [48, Ch. 4]

provides an excellent guide to instructors on preparing students

for PBL and helping them adjust to this instructional method,

and good guidance is also provided by Duch et al. [49] and Woods [51].

The possibility of student resistance should not deter knowl-

edgeable instructors from adopting the method. A number of

studies offer evidence that most students who experience PBL even-

tually come to favor it over traditional methods [66, 67, 70, 76, 77].

VI. PROJECT-BASED LEARNING AND HYBRID (PROBLEM/PROJECT-BASED) APPROACHES

A. Definition and Applications Project-based learning begins with an assignment to carry out

one or more tasks that lead to the production of a final product—a

design, a model, a device or a computer simulation. The culmina-

tion of the project is normally a written and/or oral report summa-

rizing the procedure used to produce the product and presenting

the outcome. (Note: The acronym PBL is frequently used to de-

note project-based learning as well as problem-based learning.

We will not do so in this paper to avoid adding to the confusion

this labeling may cause.)

A trade-off exists between instructors being fairly directive in

choosing projects, which helps maintain a focus on course and

curriculum objectives, and allowing students the autonomy

to choose their own project formulations and strategies, which

increases their motivation. de Graaf and Kolmos [73] define three

types of projects that differ in the degree of student autonomy:

● Task project: Student teams work on projects that have been defined by the instructor, using largely instructor-

prescribed methods. This type of project provides minimal

student motivation and skill development, and is part of

traditional instruction in most engineering curricula.

● Discipline project: The instructor defines the subject area of the projects and specifies in general terms the approaches to

be used (which normally involve methods common in the

discipline of the subject area), but the students identify the

specific project and design the particular approach they will

take to complete it.

● Problem project: The students have nearly complete autonomy to choose their project and their approach to it.

de Graaf and Kolmos [73] note that a common difficulty faced

by students in a project-based environment is transferring meth-

ods and skills acquired in one project to another project in a differ-

ent subject or discipline. Instructors should include such transfer-

ence in their course objectives and should guide students to see

connections between their current project and what they have

learned previously, gradually withdrawing this support as the stu-

dents become more adept at seeing the connections themselves.

The instructors should also prepare students to fill in gaps in con-

tent knowledge when a need arises, taking into account the fact

that such gaps may be more likely to arise in project-based learn-

ing than in conventional lecture-based instruction.

Project-based learning at the individual course level is familiar

in engineering education, having been used almost universally in

capstone design and laboratory courses and with growing frequen-

cy in first-year engineering courses and courses that engage stu-

dents in consulting projects [78–80]. A few schools have made

project-based learning the focus of many or most of their engineer-

ing courses, including the Universities of Aalborg and Roskilde in

Denmark; Bremen, TU Berlin, Dortmund, and Oldenburg in

Germany, Delft and Wageningen in the Netherlands [81],

Monash University and Central Queensland University in

Australia [82], and Olin College in the United States [83].

Project-based learning is similar to problem-based learning in

several respects. Both normally involve teams of students in open-

ended assignments that resemble challenges the students are likely

to encounter as professionals, and both call for the students to for-

mulate solution strategies and to continually re-evaluate their ap-

proach in response to outcomes of their efforts. However, there are

differences in the two approaches as they have traditionally been

implemented. A project typically has a broader scope and may en-

compass several problems. Also, in project-based learning, the end

product is the central focus of the assignment and the completion

of the project primarily requires application of previously acquired

knowledge, while solving a problem requires the acquisition of new

knowledge and the solution may be less important than the knowl-

edge gained in obtaining it. In other words, the emphasis in pro-

ject-based learning is on applying or integrating knowledge while

that in problem-based learning is on acquiring it.

In practice, however, the distinction between the two methods is

not necessarily that clean, and programs have recently adopted

approaches that include features of both of them. The University of

Aalborg has the oldest and best known project-based engineering

curriculum in the world, which began with the formation of the

university in 1974. Project work accounts for roughly 50 percent of

the curriculum, with task and problem projects dominating the

first year of instruction, task and discipline projects dominating

the second and third years, and problem projects dominating the

fourth and fifth years [73]. The current approach at Aalborg is a

130 Journal of Engineering Education April 2006

hybrid of problem-based and project-based learning, with the

projects being more about acquiring knowledge than applying it

[84]. The main goal in the first year is to give students a general

competence in project work and an awareness of general problem

solving methods, while in the rest of the curriculum the focus

shifts to more specific technical and scientific learning objectives,

with the project work being mainly a mechanism for achieving

those goals.

Aalborg has recently adapted its project-based approach to dis-

tance education offerings, with virtual groups meeting once or

twice a week using Internet chat facilities [85]. Many of the posi-

tive features of project work have been observed in this format as

well, although the authors note that the experience seems to ac-

centuate the differences between strong and weak students, with

the latter being more likely to become less motivated and to make

less progress in the distance environment than they do in a con-

ventional classroom environment.

Another institutional implementation of problem/project-

based learning was initiated in 2000 by the engineering school of

the University of Louvain in Belgium, with both week-long prob-

lems and semester-long projects being routinely assigned to stu-

dent teams in the first two years of the engineering curriculum

[86]. The evaluation of this program summarized in the next sec-

tion provides some of the best available evidence for the effective-

ness of the hybrid approach.

B. Evaluation Thomas [87] carried out an extensive review of research on

project-based learning done primarily at the pre-college level,

considering only projects that (a) were central to the course, (b)

focused on central concepts and principles of the discipline, (c) re-

quired acquisition of some new knowledge rather than being

straightforward applications of existing knowledge, (d) were

student-driven to some degree (as opposed to being “cookbook”

exercises), and (e) were authentic, containing as many elements as

possible of the type of environment the students are likely to en-

counter as professionals. The findings resemble those found for

problem-based learning: comparable or somewhat better perfor-

mance in project-based environments on tests of content knowl-

edge, and significantly better performance on assessments of con-

ceptual understanding and ability to solve problems that require it,

metacognitive skills, and attitudes to learning. Thomas also cites

studies suggesting that project-based learning may effectively

reach students whose learning styles are poorly suited to a tradi-

tional lecture-based classroom environment.

More recently, Mills and Treagust [82] reviewed published

evaluations of project-based learning programs in engineering and

concluded that the findings are similar to those for problem-based

learning in medicine. Relative to traditionally-taught students,

students who participate in project-based learning are more moti-

vated, demonstrate better communication and teamwork skills,

and have a better understanding of issues of professional practice

and how to apply their learning to realistic problems; however,

they may have a less complete mastery of engineering fundamen-

tals, and some of them may be unhappy over the time and effort re-

quired by projects and the interpersonal conflicts they experience

in team work, particularly with teammates who fail to pull their

weight. In addition, if the project work is done entirely in groups,

the students may be less well equipped to work independently.

The hybrid (problem/project-based) curriculum at the Univer-

sity of Louvain was assessed by a multidisciplinary team of engi-

neers and educators, who compared three cohorts of students who

passed through the new curriculum with two cohorts from the

final years of the old (traditional) curriculum [86]. The assessment

measures included pretests and posttests of students’ basic knowl-

edge, understanding of concepts, and ability to apply them; stu-

dents’ self-efficacy, intrinsic vs. extrinsic goal orientation, satisfac-

tion with the curriculum, learning and self-regulating strategies,

and attitudes toward group work; and instructors’ teaching prac-

tices, satisfaction with teaching, and perceptions of the impact of

the PBL curriculum on the instructional environment. The stu-

dent tests and questionnaire responses were blind-rated after the

fourth year of the study, so that the raters did not know whether

the subjects had gone through the old or the new curriculum.

The results of the Louvain study are dramatic. Of 79 between-

group comparisons of knowledge, conceptual understanding, and

application, 23 favored the new curriculum, one favored the old

one, and the remainder showed no significant differences. Stu-

dents in the new curriculum felt that they received more support

from their instructors, saw more connections between theory and

practice, were more inclined to use autonomous learning strate-

gies (search for information, seek help when needed, verify com-

pleted work), and were less reliant on rote memorization relative

to students in the old curriculum. The superior outcomes for the

PBL-taught students could be attributed in part to their percep-

tion of greater support from their instructors, a factor known to

have a positive impact on both performance and attitudes. They

also felt that they had to work more and harder than students

taught traditionally, and they had problems with being tested in-

dividually after doing most of their work in groups (a common

complaint of students working in a heavily collaborative learning

environment). Teachers in the study saw a positive impact of the

PBL curriculum on student competencies in teamwork, model-

ing, transfer of knowledge, and analysis; the quality of student-

teacher interactions and teacher-teacher interactions; their satis-

faction with and pleasure in teaching; and their engagement in

teaching and willingness to change their teaching practices. The

last two outcomes were particularly strong among teachers who

perceived their administration to be supportive of teaching (en-

couraging discussion of teaching, valuing teaching improvement,

and offering training and collegial support). This result has im-

portant implications for the critical role of administrators in at-

tempts to reform education.

VII. CASE-BASED TEACHING

A. Definition and Applications In case-based teaching, students analyze case studies of histori-

cal or hypothetical situations that involve solving problems and/or

making decisions. Kardos and Smith [88] defined a case in the

context of engineering education as “an account of an engineering

activity, event or problem containing some of the background and

complexities actually encountered by an engineer.” The same defi-

nition (with the appropriate substitution being made for “engi-

neering”) applies to law, medicine, management, teacher educa-

tion, or any of the other fields that have made extensive use of

cases for professional training.

April 2006 Journal of Engineering Education 131

Cases in all fields typically involve one or more challenges of

various types, such as diagnosing technical problems and formu-

lating solution strategies, making business management decisions

taking into account technical, economic, and possibly social and

psychological considerations, and confronting ethical dilemmas.

The cases should be authentic—representative of situations likely

to be encountered in professional practice—and may be drawn

from stories in newspapers or magazines or built from interviews

with individuals involved in the situations in question. A case

might include descriptions of what happened and what led up to

it, the problems and challenges, the resources and constraints

under which solutions could be sought, the decisions that were

made, the actions that were taken, and the outcomes. The idea is

that in analyzing complex authentic cases, the students become

aware of the kinds of situations and dilemmas they might have to

face as professionals, gain both theoretical and practical under-

standing of their subjects, develop critical reasoning skills, explore

their existing preconceptions, beliefs, and patterns of thinking,

and make necessary modifications in those preconceptions, be-

liefs, and patterns to accommodate the realities of the cases [89].

These attributes of case-based teaching—particularly those relat-

ed to making students aware of their preconceptions and beliefs—

clearly fit comfortably in the framework of constructivism.

Whether or not case-based instruction qualifies as inductive

(and, one might suspect, whether and how well it succeeds) de-

pends on how it is implemented. In one variant (which Lynn [90]

terms a “research case”), the case is a complete narrative of a prob-

lematic situation, how people dealt with it, and what the out-

comes were. Students may be called on to study the case ahead of

time and be prepared to discuss it in class, but the same may be

said of any traditional lecture-based approach that incorporates

Socratic questioning. Lynn observes that research cases can be

useful for illustrating appropriate, typical, or exemplary decision

making but not for teaching critical thinking and decision-

making skills, since in those cases the thinking has already been

done, the decisions made, and the outcomes determined and

given to the students. Instruction based on the use of such cases

cannot be considered inductive.

Forms of case-based instruction that are inductive use what Lynn calls “teaching cases,” in which the circumstances of the case

are described but the decisions made by the protagonists are with-

held so that the students can do their own analysis and decision-

making. Analyses of teaching cases involve several steps [91]: (1)

review of the case content, (2) statement of the problem, (3) col-

lection of relevant information, (4) development of alternatives,

(5) evaluation of alternatives, (6) selection of a course of action,

and (7) evaluation of solutions, and possibly review of actual case

outcomes. The similarities of this method to problem-based

learning are evident; however, unlike the problems generally used

in PBL, cases tend to be relatively well-structured, rich contextual

details are provided, and students are called on to apply material

that is already somewhat familiar, whereas PBL tends to use

poorly structured problems to drive the acquisition of new content

knowledge [92].

The use of cases for teaching probably goes back to about 1870

at the Harvard Law School. The method was subsequently adopt-

ed by the Harvard Business School after World War I, and is now

used routinely in schools of law, medicine, public administration

and business management [90]. Cases are also used with increas-

ing frequency in science education [93] and engineering educa-

tion [94, 95]. Libraries of cases in science and engineering and re-

sources for teachers wishing to use them have been compiled by

the National Center for Case Study Teaching in Science,4 the

Penn State Center for Teaching and Learning with Technology,5

and the Center for Case Studies in Engineering.6 Most of the

cases in the latter database are decades old and might therefore in-

volve obsolete technology, but they should still be

useful vehicles for promoting the types of critical thinking and

problem-solving skills that are as vital today as they were when the

cases were developed. Engineering case studies are also regularly

published in the Journal of STEM Education (Science, Technology, Engineering and Math).7

B. Evaluation Case-based teaching has strong proponents among practi-

tioners; however, there is relatively little solid empirical support

for it, a fact noted by several authors [89, 96, 97]. Lundeberg

et al. [89] report that the use of case studies enhanced students’ ability to recognize multiple perspectives (a finding that is further

supported by Adams [98]), and they also note that the use of

cases developed students’ ability to identify relevant issues. Levin

[99] found that cases improved students’ reasoning and problem-

solving skills, and Gabel [100] claims that they increased the use

of higher-order thinking on Bloom’s taxonomy. Fasko [97]

found that most studies he examined showed little or no differ-

ence in knowledge acquisition between case studies, discussion,

and lecture-based methods, but both cases and discussions

were better than lectures for retention and application of material

as well as problem-solving skills. Katsikitis et al. [101] compared case studies to PBL and found no significant difference between

the two methods related to performance or knowledge

acquisition.

VIII. DISCOVERY LEARNING

A. Definition Discovery learning is an inquiry-based approach in which stu-

dents are given a question to answer, a problem to solve, or a set of

observations to explain, and then work in a largely self-directed

manner to complete their assigned tasks and draw appropriate in-

ferences from the outcomes, “discovering” the desired factual and

conceptual knowledge in the process [5]. In the purest form of

this method, teachers set the problems and provide feedback on

the students’ efforts but do not direct or guide those efforts. There

are many reasons why this method is rarely used in higher educa-

tion, among those being because instructors who hear about it

fear—probably with good cause—that they would only be able to

cover a small fraction of their prescribed content if students were

required to discover everything for themselves. The only way to

counter this fear would be to present solid evidence that discovery

learning produces improved learning outcomes without requiring

a major sacrifice of content, and as we will see in the next section,

132 Journal of Engineering Education April 2006

4/ublib.buffalo.edu/libraries/projects/cases/ubcase.htm 5tlt.its.psu.edu/suggestions/cases 6www.civeng.carleton.ca/ECL 7www.jstem.org

such evidence does not exist. What instructors are more likely to

do is apply a variant of discovery learning (sometimes called

“guided discovery”) that involves the instructor providing some

guidance throughout the learning process [102]. Once this is

done, the distinctions between discovery and guided inquiry or

problem-based learning tend to disappear.

B. Evaluation Leonard [103] studied the use of guided inquiry and discovery

learning in science laboratory courses and found no statistically

significant differences in student scores on tests and lab reports.

Some studies suggest that discovery learning can enhance stu-

dents’ retention of material and others reach the opposite conclu-

sion [104–108]. The studies that show a positive effect also sug-

gest that retention is improved only when the learning task is

based on previously understood principles. Singer and Pease [109]

compared the effectiveness of guided inquiry and discovery learn-

ing on the acquisition, transfer and retention of motor skills. They

concluded that for learning new tasks, guided inquiry was more

efficient, and for transferring learned skills to tasks of similar or

greater difficulty there was no difference.

IX. JUST-IN-TIME TEACHING

A. Definition and Applications Just-in-Time Teaching (JiTT) combines Web-based technol-

ogy with active learning methods in the classroom [110–113].

Students individually complete Web-based assignments a few

hours before class in which they answer questions, and the in-

structor reads through their answers before class and adjusts the

lessons accordingly (“just in time”). This process is repeated several

times a week. The use of questions to drive learning makes the

method inductive. The technique was developed jointly by physics

faculty at IUPUI (Indiana University-Purdue University

Indianapolis), the U.S. Air Force Academy, and Davidson

College. It can be combined with almost any in-class active learn-

ing approach.

The preliminary Web-based exercises (termed “Warmups” at

IUPUI and Davidson and “Preflights” at the Air Force Academy)

normally require the student to preview the textbook material.

The exercises are conceptual in nature and are designed to help

students confront misconceptions they may have about the course

material. They serve the functions of encouraging students to pre-

pare for class regularly, helping teachers to identify students’ diffi-

culties in time to adjust their lesson plans, and setting the stage for

active engagement in the classroom. They are individualized to

minimize plagiarism and graded using an automated on-line sys-

tem, although the authors stress the importance of instructors

reading a representative selection of responses to monitor the stu-

dents’ qualitative understanding of the material. The students

may submit solutions any number of times with no penalty until

they get them correct.

JiTT resources also include enrichment materials of several

types [110]:

● course-related news stories that demonstrate the real-world

relevance of the course material, historical anecdotes, and

descriptions of familiar phenomena or devices that illustrate

course concepts;

● on-line homework, extra-credit assignments that often deal

with the enrichment materials, and “puzzles,” additional

conceptual questions that force the students to think about

the material at a deeper level than the straightforward

preparatory assignments;

● various computer-based mechanisms for communication

between students and the instructor and among students,

including an electronic suggestion box that instructors

monitor regularly, a course bulletin board that students may

use to communicate among themselves (e.g. to set up study

sessions or team meetings, or to raise and answer ques-

tions), archives of previous materials, and a “credit check” in

which they can monitor their assignment grades and see

how they are doing with respect to the class as a whole.

Novak et al. [112], the physicists who developed JiTT, cast many of their Web-based materials in the form of Java applets

that they call physlets. The students are presented with a problem that presents a set of observations or experimental data in a visual

manner, and they have to analyze it qualitatively before they are

allowed to do any mathematical analysis, figuring out what they

know and what they need to find out and then planning a solution

strategy. The connection to inquiry learning and problem-based

learning is clear.

JITT classes are a combination of interactive lectures, in which the instructor does a fair amount of mini-lecturing between activi-

ties; collaborative recitations, which are not necessarily preceded by preparatory Web-based exercises, and laboratories. In the lec-

tures, the instructor might begin by summarizing student re-

sponses to the preparatory exercises and then discussing common

errors. The end of the lecture might involve a similar discussion of

a puzzle. The collaborative recitations are likely to begin with a re-

view of the homework, and then teams of students work on new

problems. Faculty members circulate, help teams that need help,

and if a common problem emerges, provide some instruction on

how to address it. Lectures and recitations may be held separately

or they may be integrated with each other and with laboratories.

Paper homework is assigned in addition to the preparatory web-

based exercises.

B. Evaluation Novak et al. [112] assess JiTT for its impact on cognitive out-

comes, student attrition and student attitudes in physics. Student

learning was assessed using the Force Concept Inventory, which

showed normalized student gains between 35 percent and 40 per-

cent. This gain is similar to that found for other interactive-

engagement teaching methods [114] and is significantly better

than the average normalized gains found in traditionally-taught

physics courses. The authors also report that JiTT reduced stu-

dent attrition by 40 percent compared to previous offerings taught

traditionally and that student responses to JiTT have been over-

whelmingly positive.

X. GETTING STARTED WITH INDUCTIVE TEACHING AND LEARNING

Once instructors are persuaded that inductive teaching methods

are worth attempting, they face the question of which method to

use. The answer, like the answer to all real questions, begins with “it

April 2006 Journal of Engineering Education 133

depends”; specifically, it depends on the instructor’s learning objec-

tives, the instructor’s and the students’ prior experience with learn-

er-centered teaching methods, the instructor’s confidence in his or

her content knowledge and teaching skill, and the availability of

local expertise and support for each of the various methods.

Before teaching a topic or series of lessons using any inductive

method, the instructor should write learning objectives that define what the student should be able to do (explain, calculate, derive, de-

sign, model, critique,…) when the instruction has been concluded.

The objectives should guide the choice of focus problems, learning

activities, and assessment methods. Mager [115] and Gronlund

[116] provide guidance on how to write effective learning objec-

tives, and Felder and Brent [117] discuss writing objectives to

address Outcomes 3a–3k of the ABET Engineering Criteria.

Once learning objectives have been defined, a suitable induc-

tive instructional method may be identified. We propose the fol-

lowing guidelines for making the choice:

● Inquiry learning. Inquiry is the simplest of the inductive ap- proaches and might be the best one for inexperienced or

previously traditional instructors to begin with. It requires

designing instruction so that as much learning as possible

takes place in the context of answering questions and solv-

ing problems. As the students gain more experience with

this approach, the instructor may increase the scope and

difficulty of the focus questions, use more open-ended and

ill-structured problems and simultaneously decrease the

amount of explicit guidance provided.

● Problem-based learning. Problem-based learning is the most complex and difficult to implement of the methods re-

viewed in this paper. It calls for a complex, open-ended,

authentic problem whose solution requires knowledge and

skills specified in the learning objectives. Such problems

take time to create. PBL also requires considerable teach-

ing skill for instructors to deal with unfamiliar technical

questions and problems, student resistance and possibe

hostility toward PBL, and the array of interpersonal prob-

lems that frequently arise when students work in teams.

Full-fledged PBL is therefore best undertaken by experi-

enced instructors with solid expertise in the subject matter

of the course and two or more semesters of experience with

cooperative learning in a more conventional instructional

environment. Smith et al. [118] offer suggestions for

implementing cooperative learning, and Felder and

Brent [8, 119] and Oakley et al. [10] suggest strategies for overcoming student resistance to learner-centered instruc-

tional methods and helping student groups become effec-

tive teams. Despite the challenges, PBL is a natural envi-

ronment in which to develop students’ professional skills

such as problem-solving, team work and self-directed or

lifelong learning, and it provides an excellent format to in-

tegrate material from across the curriculum. Instructors

wishing to focus specifically on these learning outcomes

should consider adopting PBL.

● Project-based learning and hybrid problem/project-based ap- proaches. Project-based learning is well suited to the cap- stone design course in engineering and to laboratory cours-

es that are more than collections of cookbook experiments,

and it may also be used in other courses that deal with

process or product design and development. Like the focus

problems in problem-based learning, projects should be au-

thentic and should address the instructor’s learning objec-

tives; moreover, if students work in teams, the instructor

should observe the principles of cooperative learning in-

cluding holding all team members individually accountable

for the entire project content and facilitating their acquisi-

tion of teamwork skills [8, 10, 118, 119]. As instructors and

students gain experience with project-based learning, the

projects may be made more open-ended with less guidance

being provided on how to complete them. In other words,

they may be increasingly structured as problem-based

learning exercises.

● Case-based teaching. Cases are effectively used when learn- ing objectives include decision-making in complex authen-

tic situations. With appropriate selection, case-based teach-

ing can also provide an excellent environment in which to

address specific ABET mandated outcomes such as acquir-

ing an understanding of professional and ethical responsi-

bility, knowledge of contemporary issues, or the ability to

understand engineering solutions in a global and societal

context. Scenarios suitable for cases might involve diagnos-

ing technical problems and formulating solution strategies,

making business management decisions taking into ac-

count technical, economic, and possibly social and psycho-

logical considerations, and confronting ethical dilemmas.

Formulating good cases can be a difficult and time-

consuming task; before trying to do it, instructors should

first check the libraries of cases in science and engineering

cited in Section VII to see if an existing case addresses their

learning objectives.

● Just-in-time teaching. JiTT is a natural method to use when (1) it is important to the instructor that the students keep

up with readings and assignments on a day-by-day basis,

and (2) course management software is available and conve-

nient to use for administering on-line assignments and as-

sessing the students’ responses. Instructors who plan to use

the method should have solid expertise in the course con-

tent and the flexibility needed to modify their lectures on

short notice after examining students’ responses to the pre-

liminary exercises. Also, a significant expenditure of time

and effort is sure to be required if the preliminary Web-

based exercises and Java applets must all be developed from

scratch. Before undertaking this task, instructors should see

if materials can be obtained from colleagues at their institu-

tion or elsewhere who have used JiTT for the same course.

We do not recommend using the pure form of discovery

learning—in which students work with little or no guidance from

instructors—in undergraduate engineering curricula.

Once the decision regarding adoption of a method is made, the

instructor should refer to texts, articles, and Web-based

resources on the chosen method and take full advantage of experi-

enced colleagues and teaching center consultants who can offer tips

on implementing it and dealing with problems that arise with its use.

XI. SUMMARY

The traditional approach to teaching science and engineering

is deductive, beginning with the presentation of basic principles

134 Journal of Engineering Education April 2006

in lectures and proceeding to the repetition and application of the

lecture content by the students. The teaching methods discussed

in this paper—inquiry learning, problem-based learning, project-

based learning, case-based teaching, discovery learning, and just-

in-time teaching—instead proceed inductively, beginning with

observations to be interpreted, questions to be answered, prob-

lems to be solved, or case studies to be analyzed. The content

knowledge, methods, and skills that the course is designed to

teach are acquired by the students, with varying degrees of

instructor guidance, in the context of those exercises. If and

when instructors present information, they do so only once the

need for that information to complete the exercises has been

established.

While the quality of research data supporting the different in-

ductive methods is variable, the collective evidence favoring the

inductive approach over traditional deductive pedagogy is conclu-

sive. Induction is supported by widely accepted educational theo-

ries such as cognitive and social constructivism, by brain research,

and by empirical studies of teaching and learning. Inductive

methods promote students’ adoption of a deep (meaning-orient-

ed) approach to learning, as opposed to a surface (memorization-

intensive) approach. It also promotes intellectual development,

challenging the dualistic type of thinking that characterizes many

entering college students (which holds that all knowledge is cer-

tain, professors have it, and the task of students is to absorb and

repeat it) and helping the students acquire the critical thinking

and self-directed learning skills that characterize expert scientists

and engineers.

This is not to say, however, that simply adopting an inductive

method will automatically lead to better learning and more satis-

fied students. As with any form of instruction, inductive teaching

can be done well or poorly, and the outcomes that result from it

are only as good as the skill and care with which it is implemented.

Many students are resistant to any type of instruction that makes

them more responsible for their own learning, and if the appropri-

ate amount of guidance and support is not provided when induc-

tive methods are used, the resistance can escalate to hostility, infe-

rior learning outcomes, poor evaluations, and a resolution by the

instructor never to try anything like that again.

Instructors who set out to implement an inductive method

should therefore first familiarize themselves with best practices

such as providing adequate scaffolding—extensive support and guidance when students are first introduced to the method, fol-

lowed by gradual withdrawal of the support as the students gain

more experience and confidence in its use. Instructors should also

anticipate some student resistance to inductive learning and

should be aware of effective strategies for defusing it, many of

which are outlined by Felder and Brent [8, 16, 119]. If these pre-

cautions are taken, both the students and the instructor should

soon start seeing the positive outcomes promised by the research.

ACKNOWLEDGMENTS

The authors are grateful to Rebecca Brent, Valri Hammonds,

Anette Kolmos, and Virginia Lee for reading a preliminary draft

of the paper and offering valuable comments and suggestions for

its improvement.

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AUTHORS’ BIOGRAPHIES

Michael Prince is a professor in the Department of Chemical

Engineering at Bucknell University, where he has been since re-

ceiving his Ph.D. from the University of California at Berkeley in

1989. He is the author of several education-related papers for en-

gineering faculty and gives faculty development workshops on ac-

tive learning. He is currently continuing the work of Project Cata-

lyst, an NSF-funded initiative to help faculty re-envision their

role in the learning process, and researching the use of inductive

teaching methods to correct common student misconceptions in

engineering.

Address: Department of Chemical Engineering, Bucknell Uni- versity, Lewisburg, Pennsylvania 17837; telephone: (�1) 570.577.1781; e-mail: prince@bucknell.edu.

Richard M. Felder is Hoechst Celanese Professor Emeritus of

Chemical Engineering at North Carolina State University. He re-

ceived his BChE from City College of New York and his PhD

from Princeton University. He is coauthor of the text Elementary Principles of Chemical Processes (Wiley, 2005) and co-director of the ASEE National Effective Teaching Institute.

Address: Department of Chemical Engineering, N.C. State University, Raleigh, North Carolina 27695-7905; e-mail:

rmfelder@mindspring.com.

138 Journal of Engineering Education April 2006