Review of Inductive Teaching & Learning Methods: Inquiry, Problem-Based, Project-Based, Ca, Lecture notes of Teaching method

Download Review of Inductive Teaching & Learning Methods: Inquiry, Problem-Based, Project-Based, Ca and more Lecture notes Teaching method in PDF only on Docsity! 1 INDUCTIVE TEACHING AND LEARNING METHODS: DEFINITIONS, COMPARISONS, AND RESEARCH BASES* Michael J. Prince Bucknell University Richard M. Felder 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 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 established. This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem-based learning, project-based learning, case-based teaching, discovery 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. I. INTRODUCTION A. Two Approaches to Education Engineering and science are traditionally taught deductively. The instructor introduces a topic by lecturing on general principles, then uses the principles to derive mathematical models, shows illustrative applications of the models, gives students practice 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 the students should care about any of it. The only motivation to learn that students get—if they get any at all—is suggestions 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 or solve the problem, * J. Engr. Education, 95(2), 123–138 (2006). 2 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 encompasses 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 (aka student-centered), meaning that they impose more responsibility on students for their own learning than the traditional lecture-based deductive approach does. They are all supported by research findings that students learn by fitting new information into existing cognitive structures and are unlikely to learn if the information has few apparent connections to what they already know and believe. They can all be characterized as constructivist methods, building on the widely accepted principle that students construct 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 cooperative learning). The defining characteristics of the methods and features that most of them share are summarized in Table 1. Table 1. Features of Common Inductive Instructional Methods Method à Feature ¯ In qu iry Pr ob le m - ba se d Pr oj ec t - ba se d C as e- ba se d D is co ve ry Ji TT Questions or problems provide context for learning 1 2 2 2 2 2 Complex, ill-structured, open-ended real-world problems provide context for learning 4 1 3 2 4 4 Major projects provide context for learning 4 4 1 3 4 4 Case studies provide context for learning 4 4 4 1 4 4 Students discover course content for themselves 2 2 2 3 1 2 Students complete & submit conceptual exercises electronically; instructor adjusts lessons according to their responses 4 4 4 4 4 1 Primarily self-directed learning 4 3 3 3 2 4 Active learning 2 2 2 2 2 2 Collaborative/cooperative (team-based) learning 4 3 3 4 4 4 1 – by definition, 2 – always, 3 – usually, 4 – possibly There are also differences among the different inductive methods. 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 question, 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 temperature does not drop below freezing. Case-based instruction and problem-based learning involve extensive analyses of real or hypothetical scenarios while just-in-time teaching may simply call on students to answer questions about readings prior to hearing about the content of 5 B. Cognition Research Bransford et al. [2] offer a comprehensive survey of neurological 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 minimal 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, issues, 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 contradiction can lead to elimination of misconceptions and greater understanding. 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 misunderstanding may follow [2, p. 70]. Traditional teaching generally does little to force students to identify and challenge their misconceptions, leading to the latter situation. The most effective implementations of inductive learning involve diagnostic teaching, with lessons being designed 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 learning methods can serve this function. • Motivation to learn affects the amount of time students are willing 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 so 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 environments 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 promotes transfer, provided that the students 6 are helped to develop teamwork skills and the work is organized in a way that assures individual 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 information learned in one context to another one [2, p. 67]. Methods that train students in systematic problem-solving methods (generating and evaluating alternative solutions, periodically assessing progress toward the solution, extracting general principles from specific solutions, etc.) and call on them to make sense of new information, to raise questions when they cannot, and to regularly assess their own knowledge and skill levels promote 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 authorities 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 judgments, and openness to change if new evidence is forthcoming [13,14]. At the highest developmental level normally seen in college students (termed “contextual relativism” by Perry [13]), individuals display thinking patterns resembling those of expert scientists and engineers. 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 and 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 strategic approach, doing whatever is necessary to get the highest grade they can, taking a surface approach if that suffices and a deep approach when necessary. Another goal of instruction should be to induce students to adopt a deep approach to subjects that are important for their professional or personal development. Felder & Brent [16] observe that the characteristics of high levels of intellectual development and of a deep approach to learning 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 assume 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 in and background knowledge of the subject, use of teaching methods that foster active and long-term engagement with learning tasks, and assessment that emphasizes conceptual understanding as opposed to recall or the application of routine procedural knowledge [17]. Well implemented inductive teaching methods serve all of these functions. 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 learning tasks. Having to 7 analyze complex situations also promotes the students’ adoption of a deep approach to learning, as rote memorization 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 serious 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, active 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 professionals. 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 question is why?); (2) presenting pertinent facts, experimental observations, principles and theories, problem-solving methods, etc., and opportunities for the students to reflect on them (what?); (3) providing guided hands-on practice in the methods and types of thinking the lessons are intended to teach (how?); and (4) allowing and encouraging exploration of consequences and applications of the newly learned material (what if?). A learning cycle developed at the Vanderbilt University Learning Technology Center is the STAR Legacy module [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 next provided. Perspectives are statements by experts that offer insights into various dimensions 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 students 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, completing homework assignments, writing essays or reports, and taking on-line quizzes or exams. Multiple iterations between 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 solution to the challenge, or the students may present a report and/or complete an examination showing that they have met the 10 Inquiry-based methods have been used extensively in the sciences [27–32] and to a lesser extent in engineering [33, 34]. Guided inquiry has been particularly widely used in chemistry curricula. The POGIL Web site (<http://www.pogil.org>) contains reports of implementations on several campuses, instructional materials for different branches of chemistry, and a video showing an implementation of the method in an introductory chemistry class (<http://www.pogil.org/resources/GI_video.php>). Lee et al.[24] report on a series of inquiry-based courses in different disciplines at North Carolina State University that had four desired student outcomes in common: (a) improved critical thinking 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 characteristic of Just-in-Time Teaching, another inductive technique 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 students 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, instructors are given grants to develop innovative classroom applications of laptop computers with wireless Internet access, which are made available to all students in their courses. 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 programs 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 perceptions, process skills and analytic abilities. In a meta-analysis of 79 individual studies between 1965 and 1995 involving students from 7th grade through college, 11 Smith [26] found that inquiry 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 significant. 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 cognitive 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 observable phenomena, and less so in helping them understand how scientists explain or model phenomena (e.g., via kinetic and molecular theories in chemistry and physics). He recommends focusing 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 succeed, 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 confronted 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 (i) groups reporting out their progress on previous learning issues and listing their current learning issues and plans of work, (ii) minilectures giving information on issues being dealt with by all groups, clarifying common difficulties, and suggesting additional learning issues, and (iii) whole class discussion [50]. A well-designed problem guides students to use course content and methods, illustrates fundamental principles, concepts, and procedures, 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 3–5 during class. The instructor moves from group to group during class, asking questions and probing for understanding. Different levels of external guidance may be provided by a faculty member or a designated tutor, or responsibility for the work may be taken by the groups themselves in what Woods [51] calls self-directed, interdependent, small group problem-based learning. Acar & Newman [52] describe a module in which students in their final year of a systems engineering 12 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 helpfulness 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 extensively 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 University in Sweden, and the University of Newcastle in Australia; in chemical engineering at McMaster [51, 55], Bucknell University [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 & 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 Delaware (<http://www.udel.edu/pbl/>) and Samford University (<http://www.samford.edu/pbl/>), both of which provide links to many other resources. A 2003 issue of the International Journal of Engineering Education (Vol. 19, No. 5) is devoted 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 (establishing 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 excellent 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 development 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% confidence interval of –0.223 (±0.058). When only true randomized tests are included, however, the negative effect of PBL on knowledge acquisition almost 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 15 objectives and should guide students to see connections between their current project and what they have learned previously, gradually withdrawing this support as the students become more adept at seeing the connections themselves. The instructors should also prepare students to fill in gaps in content knowledge when a need arises, taking into account the fact that such gaps may be more likely to arise in project-based learning 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 frequency in first-year engineering courses and courses that engage students in consulting projects [78–80]. A few schools have made project-based learning the focus of many or most of their engineering 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 formulate solution strategies and to continually re-evaluate their approach in response to outcomes of their efforts. There are differences in the two approaches as they have traditionally been implemented, however. A project typically has a broader scope and may encompass several problems. In addition, in project-based learning the end product is the central focus of the assignment and the completion of the project requires primarily application of previously acquired knowledge, while solving a problem requires the acquisition of new knowledge and the solution may be less important than the knowledge gained in obtaining it. In other words, the emphasis in project- 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% 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 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 distance education offerings, with virtual groups meeting once or twice a week using Internet chat facilities [85]. Many of the positive features of project work have been observed in this format as well, although the authors note that the experience seems to accentuate the differences between strong and weak students, with the latter being more likely to become demotivated and to make less progress in the distance environment than they do in a conventional classroom environment. 16 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 problems and semester-long projects being routinely assigned to student teams in the first two years of the engineering curriculum [86]. The evaluation of this program summarized in the next section provides some of the best available evidence for the effectiveness of the hybrid approach. B. Evaluation Thomas [87] carried out an extensive review of research on project-based learning done primarily at the precollege level, considering only projects that (a) were central to the course, (b) focused on central concepts and principles of the discipline, (c) required 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 encounter as professionals. The findings resemble those found for problem-based learning: comparable or somewhat better performance in project-based environments on tests of content knowledge, and significantly better performance on assessments of conceptual 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 traditional 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 motivated, 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 fundamentals, and some of them may be unhappy over the time and effort required 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 University of Louvain was assessed by a multidisciplinary team of engineers 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 knowledge, understanding of concepts, and ability to apply them; students’ self- efficacy, intrinsic vs. extrinsic goal orientation, satisfaction with the curriculum, learning and self-regulating strategies, and attitudes toward group work; and instructors’ teaching practices, satisfaction with teaching, and perceptions of the impact of the PBL curriculum on the instructional environment. The student 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. Relative to students in 17 the old curriculum, students in the new one felt that they received more support from their instructors, saw more connections between theory and practice, were more inclined to use autonomous learning strategies (search for information, seek help when needed, verify completed work), and were less reliant on rote memorization. The superior outcomes for the PBL-taught students could be attributed in part to their perception 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 individually 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, modeling, transfer of knowledge, and analysis; the quality of student-teacher interactions and teacher-teacher interactions; their satisfaction 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 (encouraging discussion of teaching, valuing teaching improvement, and offering training and collegial support). This result has important implications for the critical role of administrators in attempts to reform education. VII. CASE-BASED TEACHING A. Definition and Applications In case-based teaching, students analyze case studies of historical or hypothetical situations that involve solving problems and/or making decisions. Kardos & 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 definition (with the appropriate substitution being made for “engineering”) applies to law, medicine, management, teacher education, or any of the other fields that have made extensive use of cases for professional training. Cases in all fields typically involve one or more challenges of various types, such as diagnosing technical problems and formulating 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 understanding of their subjects, develop critical reasoning skills, explore their existing preconceptions, beliefs, and patterns of thinking, and make necessary modifications in those preconceptions, beliefs, and patterns to accommodate the realities of the cases [89]. These attributes of case-based teaching—particularly those related to making students aware of their preconceptions and beliefs—clearly fit comfortably in the framework of constructivism. 20 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 prepare for class regularly, helping teachers to identify students’ difficulties 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 system, although the authors stress the importance of instructors reading a representative selection of responses to monitor the students’ 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 questions), 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 activities; collaborative recitations, which are not necessarily preceded by preparatory Web-based exercises, and laboratories. In the lectures, the instructor might begin by summarizing student responses 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 review 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. 21 B. Evaluation Novak et al. [112] assess JiTT for its impact on cognitive outcomes, student attrition and student attitudes in physics. Student learning was assessed using the Force Concept Inventory, which showed normalized student gains between 35% and 40%. 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 student attrition by 40% compared to previous offerings taught traditionally and that student responses to JiTT have been overwhelmingly 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 depends”: specifically, it depends on the instructor’s learning objectives, the instructor’s and the students’ prior experience with learner-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, design, 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 objectives, 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 inductive instructional method may be identified. We propose the following guidelines for making the choice: • Inquiry learning. Inquiry is the simplest of the inductive approaches 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 solving 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 reviewed 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 teaching skill for instructors to deal with unfamiliar technical questions and problems, student resistance and possibly hostility toward PBL, and the array of interpersonal problems that frequently arise when students work in teams. Full-fledged PBL is therefore best undertaken by experienced 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 22 resistance to learner-centered instructional methods and helping student groups become effective teams. Despite the challenges, PBL is a natural environment 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 integrate 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 approaches. Project-based learning is well suited to the capstone design course in engineering and to laboratory courses 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 authentic and should address the instructor’s learning objectives; moreover, if students work in teams, the instructor should observe the principles of cooperative learning including holding all team members individually accountable for the entire project content and facilitating their acquisition 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 learning objectives include decision- making in complex authentic situations. With appropriate selection, case-based teaching can also provide an excellent environment in which to address specific ABET mandated outcomes such acquiring an understanding professional and ethical responsibility, knowledge of contemporary issues or the ability to understand engineering solutions in a global and societal context. Scenarios suitable for cases might involve diagnosing technical problems and formulating solution strategies, making business management decisions taking into account technical, economic, and possibly social and psychological 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 convenient to use for administering on-line assignments and assessing the students’ responses. Instructors who plan to use the method should have solid expertise in the course content and the flexibility needed to modify their lectures on short notice after examining students’ responses to the preliminary 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. 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