The success of an intervention depends not only upon its theoretical soundness, but also on proper implementation that reflects the guidelines derived from its theoretical conception. Debates surrounding the effectiveness of problem-based learning (PBL) have focused on its theoretical conception and students' learning outcomes, but implementation is seemingly absent from the picture. This paper attempts to describe what research evidence is needed to fill in this missing information and provide a clearer picture of PBL. The author examines current PBL implementation practices and identifies potentially confounding variables that may play a role in inconsistent or conflicting research results in PBL. For example, various models of PBL have been developed and implemented to afford the specific instructional needs of the institution or learner population. These PBL models are in fact quite different in terms of the nature of problem solving and the degrees of selfdirected learning, which theoretically, should result in different types of learning outcomes. Without distinguishing the models used, the results of comparative PBL research could have been confounded. Furthermore, human factors are another set of confounding variables that could influence the students' learning processes and consequently affect PBL implementations and research results. To remedy these problems and reach PBL's full potential, as well as obtain a more accurate picture of PBL as an instructional method and its effects on students' learning, some fundamental changes are needed.Keywords Problem-based learning Á Implementation Á Problem solving Á Self-directed learning Á Student learning Despite its popularity in educational settings, problem-based learning (PBL) generates a great deal of skepticism and speculation among theorists. More than half a dozen metaanalyses and systematic reviews of PBL studies have been conducted to answer the question, These meta-analyses examined the effect of PBL on various aspects of students' learning outcomes, such as domain knowledge acquisition, problem solving skills, self-directed learning, group processing, and social and psychological soft skills. However, the results from the meta-analyses were not conclusive, even yet, conflicting.More recently, Kirschner et al. (2006) brought this issue back to the surface by openly criticizing PBL as an ineffective instructional method because it ignores or contradicts human cognitive architecture and cognitive load principles. Hmelo-Silver et al. (2007) and Schmidt et al. (2007) countered the argument by presenting the related cognitive science principles and empirical evidence that support the soundness of PBLs theoretical foundation. Specifically, some researchers suggested that PBL may not be effective in all aspects of student learning, but is especially effective in certain aspects of student learning because of its instructional emphases and characteristics. For example, there has been a general agreement that PBL is effective in promoting students' problem sol...
Well-designed problems are crucial for the success of problem-based learning (PBL). Previous discussions about designing problems for PBL have been rather general and inadequate in guiding educators and practitioners to design effective PBL problems. This paper introduces the 3C3R PBL problem design model as a conceptual framework for systematically designing optimal PBL problems. The 3C3R model comprises two classes of components: core components and processing components. Core components-including content, context, and connection-support content and conceptual learning, while processing components-consisting of researching, reasoning, and reflecting-concern students' cognitive processes and problem-solving skills. This paper discusses the model in terms of its theoretical basis, component functions, and the techniques used in designing PBL problems.
Troubleshooting is a common form of problem solving. Technicians (e.g., automotive mechanics, electricians) and professionals (physician, therapists, ombudspersons) diagnose faulty systems and take direct, corrective action to eliminate any faults in order to return the systems to their normal states. Traditional approaches to troubleshooting instruction have emphasized either theoretical or domain knowledge about the system or specific troubleshooting procedures. These methods have failed to develop transferable troubleshooting skills in learners. In this article, we propose an architecture for designing learning environments for troubleshooting. The architecture integrates experiential, domain, and device knowledge in a learning system that enables learners to generate and test hypotheses for every action they take, relate every action to a conceptual model of the system, and query experienced troubleshooters about what they would do. The architecture includes three essential components: A multi-layered conceptual model of the system that includes topographic, function, strategic, and procedural representations; a simulator that requires the learner to generate hypotheses, reconcile the hypotheses to the system mode, test the hypotheses, and interpret the results from the test; and a case library that uses a case-based reasoning engine to access relevant stories of troubleshooting experiences as advice for the learner. This novel architecture can be used to develop learning environments for different kinds of troubleshooting. 78 Jonassen and Hung WHAT IS TROUBLESHOOTING?Troubleshooting is among the most common types of problem solving. Whether troubleshooting a faulty modem, a multiplexed refrigeration system in a modern supermarket, or communication problems in an advertising agency, troubleshooting attempts to isolate fault states in a system and repair or replace the faulty components in order to reinstate the system to normal functioning. Troubleshooting is normally associated with the repair of physical, mechanical, or electronic systems. However, organizational ombudsmen, such as employee relations managers, customer relation specialists, consumer advocates, public relations specialists, and human resource directors are also troubleshooters. These people are responsible for handling complaints that represent fault states that must be repaired in customer relations systems. Individuals in their everyday lives engage in personal troubleshooting associated with self-change, especially when related to addictive behaviors (Prochaska et al., 1992). Medical and psychological diagnoses also involve troubleshooting.On the continuum of problems from well-structured (algorithms, story problems) to ill-structured (systems analysis, design), troubleshooting problems are in the middle (Jonassen, 2000). Troubleshooting problems:• appear ill-defined because the troubleshooter must determine what information is needed for problem diagnosis (which data about the electrical and fuel systems are needed in troubleshooting...
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