Cindy E. Hmelo-Silver

Scaffolding and Achievement in Problem-Based and Inquiry Learning: A Response to Kirschner, Sweller, and Clark (2006)

Many innovative approaches to education such as problem-based learning (PBL) and inquiry learning (IL) situate learning in problem-solving or investigations of complex phenomena. Kirschner, Sweller, and Clark (2006) grouped these approaches together with unguided discovery learning. However, the problem with their line of argument is that IL and PBL approaches are highly scaffolded. In this article, we first demonstrate that Kirschner et al. have mistakenly conflated PBL and IL with discovery learning. We then present evidence demonstrating that PBL and IL are powerful and effective models of learning. Far from being contrary to many of the principles of guided learning that Kirschner et al. discussed, both PBL and IL employ scaffolding extensively thereby reducing the cognitive load and allowing students to learn in complex domains. Moreover, these approaches to learning address important goals of education that include content knowledge, epistemic practices, and soft skills such as collaboration and self-directed learning.

Goals and Strategies of a Problem-based Learning Facilitator

This paper describes an analysis of facilitation of a student-centered problem-based learning group. The focus of this analysis was to understand the goals and strategies of an expert facilitator in support of collaborative learning. This was accomplished through interaction analysis using video data and stimulated recall to examine two PBL group meetings. In this paper, we examine how specific strategies were used to support the PBL goals of help ing students construct causal explanations, reason effectively, and become self-directed learners while maintaining a student-centered learning process. Being able to articulate these strategies is an important step in helping others learn the art of PBL facilitation.

Comparing expert and novice understanding of a complex system from the perspective of structures, behaviors, and functions

Complex systems are pervasive in the world around us. Making sense of a complex system should require that a person construct a network of concepts and principles about some domain that represents key (often dynamic) phenomena and their interrelationships. This raises the question of how expert understanding of complex systems differs from novice understanding. In this study we examined individuals’ representations of an aquatic system from the perspective of structural (elements of a system), behavioral (mechanisms), and functional aspects of a system. Structure–Behavior–Function (SBF) theory was used as a framework for analysis. The study included participants from middle school children to preservice teachers to aquarium experts. Individual interviews were conducted to elicit participants’ mental models of aquaria. Their verbal responses and pictorial representations were analyzed using an SBF-based coding scheme. The results indicated that representations ranged from focusing on structures with minimal understanding of behaviors and functions to representations that included behaviors and functions. Novices’ representations focused on perceptually available, static components of the system, whereas experts integrated structural, functional, and behavioral elements. This study suggests that the SBF framework can be one useful formalism for understanding complex systems.

Problem-based learning : a research perspective on learning interactions

Contents: H. Barrows, Foreword. Preface. C.E. Hmelo, D.H. Evensen, Introduction. Part I:The Group Meeting. H.G. Schmidt, J.H.C. Moust, Factors Affecting Small-Group Tutorial Learning: A Review of Research. T. Koschmann, P. Glenn, M. Conlee, When Is a Problem-Based Tutorial Not a Tutorial? Analyzing the Tutors Role in the Emergence of a Learning Issue. J.E. Duek, Whose Group Is It, Anyway? Equity of Student Discourse in Problem-Based Learning (PBL). J. Faidley, D.H. Evensen, J. Salisbury-Glennon, J. Glenn, C.E. Hmelo, How Are We Doing? Methods of Assessing Group Processing in a Problem-Based Learning Context. T. Koschmann, D.H. Evensen, Five Readings of a Single Text: Transcript of a Videoanalysis Session. A.C. Meyers Kelson, L.H. Distlehorst, Groups in Problem-Based Learning (PBL): Essential Elements in Theory and Practice. C. Bereiter, M. Scardamalia, Commentary on Part I: Process and Product in Problem-Based Learning (PBL) Research. Part II:Self-Directed Learning. P. Blumberg, Evaluating the Evidence That Problem-Based Learners Are Self-Directed Learners: A Review of the Literature. C.E. Hmelo, X. Lin, Becoming Self-Directed Learners: Strategy Development in Problem-Based Learning. D.H.J.M. Dolmans, H.G. Schmidt, What Directs Sef-Directed Learning in a Problem-Based Curriculum? D.H. Evensen, Observing Self-Directed Leraners in a Problem-Based Learning Context: Two Case Studies. B. Zimmerman, R.B. Lebeau, A Commentary on Self-Directed Learning. A.C. Myers Kelson, Epilogue: Assessment of Students for Proactive Life-Long Learning.

Facilitating Collaborative Knowledge Building

This article describes a detailed analysis of knowledge building in a problem-based learning group. Knowledge building involves increasing the collective knowledge of a group through social discourse. For knowledge building to occur in the classroom, the teacher needs to create opportunities for constructive discourse in order to support student learning and collective knowledge building. In problem-based learning, students learn through collaborative problem solving and reflecting on their experiences. The setting for this study is a group of second-year medical students working with an expert facilitator. The analysis was designed to understand how the facilitator provided opportunities for knowledge-building discourse and how the learners accomplished collective knowledge building. We examined episodes of knowledge-building discourse, the questions and statements that the students and facilitator generated throughout the tutorial, the change in their understanding of the problem that they were solving, and the collective knowledge that was constructed. The results indicate that the group worked to progressively improve their ideas through engaging in knowledge-building discourse. The facilitator helped support knowledge building through asking open-ended metacognitive questions and catalyzing group progress. Students took responsibility for advancing the groups understanding as they asked many high-level questions and built on each others thinking to construct collaborative explanations. The results of this study provide suggestions for orchestrating knowledge-building discourse.

Fish Swim, Rocks Sit, and Lungs Breathe: Expert-Novice Understanding of Complex Systems.

Understanding complex systems is fundamental to understanding science. The complexity of such systems makes them very difficult to understand because they are composed of multiple interrelated levels that interact in dynamic ways. The goal of this study was to understand how experts and novices differed in their understanding of two complex systems, the human respiratory system and an aquarium ecosystem. In particular, we examined how a representation of complex systems, Structure-Behavior-Function theory (SBF), might account for these differences. SBF is particularly relevant in understanding biological systems because an important domain principle is the relation between form, function, and mechanism. Our results demonstrated that there were minimal differences between the expert and novice groups on structures, but that the locus of the difference was on understanding causal behaviors and functions, the least salient elements of the systems. Mental model analysis provided largely convergent results. We also found differences between the two different kinds of experts in each domain. These results suggest that SBF does capture expert-novice differences and may have implications for instruction. This research was funded by National Science Foundation CAREER Grant 0133533 to Cindy E. Hmelo-Silver. Conclusions or recommendations expressed in this material are our own and do not necessarily reflect the views of the National Science Foundation. We thank Vera Tuchapsky for her assistance with coding the data and Rebecca Jordan for providing feedback on an earlier draft. We thank Paul Feltovich and two anonymous reviewers for their helpful feedback. Portions of this research have been presented at the annual meeting of the European Association for Research on Learning and Instruction (2003), the annual convention of the American Psychological Association (2004), and International Conference of the Learning Sciences (2004).

Analyzing collaborative knowledge construction: multiple methods for integrated understanding

Documenting collaborative knowledge construction is critical for research in computer-supported collaborative learning. Because this is a multifaceted phenomenon, mixed methods are necessary to construct a good understanding of collaborative interactions, otherwise there is a risk of being overly reductionistic. In this paper I use quantitative methods of verbal data analysis, qualitative analysis, and techniques of data representation to characterize two successful knowledge building interactions from a sociocultural perspective. In the first study, a computer simulation helped mediate the interaction and in the second, a student-constructed representation was an important mediator. A fine-grained turn-by-turn analysis of the group discussions was supplemented with qualitative analysis of larger units of dialogue. In addition, chronological representations of discourse features and tool-related activity were used in study 2 to gain an integrated understanding of how a student-generated representation mediated collaborative knowledge construction. It is only by mixing methods that collaborative knowledge construction can be well characterized.

Understanding Complex Systems: Some Core Challenges

Complex systems have a hierarchical nature and have multiple interacting levels (Wilensky & Resnick, 1999). In complex systems, the aggregate nature of the system is not predictable from isolated components but occurs through the interaction of multiple components. For example, the human body is composed of multiple sub systems and may be understood anatomically and physiologically. Only with experi ence and expertise do we come to understand how different levels of a complex sys tem are related. There are some deep principles that underlie many complex systems, some of which Jacobson and Wilensky (this issue) discussed, such as structure behavior-function (SBF) and emergence (see Goldstone & Sakamoto, 2003, for oth ers). What differentiates these complex systems from complicated systems such as pulley systems is the heterogeneity of components and their multiple levels of orga nization. For example, a pulley system is made up of several pulleys, perhaps of dif ferent sizes and orientation, but they are fundamentally the same. Compare this to an artery, which is composed of at least three different kinds of cells and networks of fi bers, all different components that together form the blood vessel. Many complex systems can be viewed as emergent or causal depending on the point of view one is taking. The human circulatory system is a good example. It is a subsystem of the human body. Many different kinds of cells form the tissues of system. The blood is composed of several different kinds of cells suspended in

Design and Reflection Help Students Develop Scientific Abilities: Learning in Introductory Physics Laboratories

Design activities, when embedded in an inquiry cycle and appropriately scaffolded and supplemented with reflection, can promote the development of the habits of mind (scientific abilities) that are an important part of scientific practice. Through the Investigative Science Learning Environment (ISLE), students construct physics knowledge by engaging in inquiry cycles that replicate the approach used by physicists to construct knowledge. A significant portion of student learning occurs in ISLE instructional labs where students design their own experiments. The labs provide an environment for cognitive apprenticeship enhanced by formative assessment. As a result, students develop interpretive knowing that helps them approach new problems as scientists. This article describes a classroom study in which the students in the ISLE design lab performed equally well on traditional exams as ISLE students who did not engage in design activities. However, the design group significantly outperformed the non-design group while working on novel experimental tasks (in physics and biology), demonstrating the application of scientific abilities to an inquiry task in a novel content domain. This research shows that a learning environment that integrates cognitive apprenticeship and formative assessment in a series of conceptual design tasks provides a rich context for helping students build scientific habits of mind.

Cognitive Apprenticeship in Science through Immersion in Laboratory Practices

This study investigates how high school students respond to an environment of authentic science inquiry while participating in an intensive summer institute, the Waksman Student Scholars Programme at Rutgers University. We examined how students apprenticed with expert scientists in a study of contemporary questions in molecular genetics. Students engaged in both laboratory practices and seminars as part of their experience in this program. We assessed student learning about conceptual knowledge of molecular genetics as well as their beliefs about the nature of science. Student conceptual knowledge increased and their beliefs about the nature of science changed to a more tentative perspective. We examined student learning qualitatively through their journals, which showed that some students were developing more sophisticated ways of thinking about the issues that were raised in their seminars and laboratory research. These ways included an increased ability to generate hypotheses, consider alternative hypotheses, implement models and logical argumentation in explanations, connect ideas, extend concepts, and ask questions. These results suggest that meaningfully engaging pre‐college students in the practice of real science can make a difference in their understanding and beliefs.