CATO is an intelligent learning environment designed to help beginning law students learn basic skills of making arguments with cases. Using CATO, students practice tasks of induction and analogical argumentation. They practice testing theories against a body of cases and making written arguments about a problem, comparing and contrasting it to past cases. CATO’s model addresses arguments in which two opponents analogize a problem to favorable cases, distinguish unfavorable cases, assess the significance of similarities and differences between cases in light of normative knowledge about the domain, and use that knowledge to organize multi-case arguments. CATO communicates the model to students by presenting dynamically-generated argumentation examples and by reifying argument structure based on the model. CATO also provides a case database and tools based on the model that help make students ’ tasks more manageable. CATO was evaluated in the context of an actual legal writing course, in a study involving 30 first-year law students. We found that instruction with CATO leads to statistically significant improvement in students ’ basic argumentation skills, comparable

Case studies of professional software development practices describe how real (or realistic) projects are planned and executed. Cases provide engaging models of the activities and materials of software development to students and other novice practitioners. They vividly remind learners of the possibilities for meaningfully applying knowledge and skills in the world beyond the classroom. During the past six years, we have developed and used a collection of usability engineering case studies for teaching human-computer interaction, primarily to upper-level undergraduates in computer science and in information sciences and technology. In this article we describe the rationale for this approach, the structural schema and browser that we developed for case studies, the case-based activities we employ in courses, and the experiences of instructors and students who have used the cases.

An antidote for reproductive learning is to engage learners in active manipulative), constructive, intentional, complex, authentic, cooperative (collaborative and conversational), and reflective learning activities. Those characteristics are the goal of constructivist learning environments (CLEs). This paper presents a model for designing CLEs, which surround a problem/project/issue/question (including problem context, problem representation space, and problem, manipulation space) with related cases (to supplant learners ’ lack of experiences and convey complexity), information resources that support knowledge construction, cognitive tools, conversation and collaboration tools, and social-contextual support for implementation. These components are supported by instructional supports, including modeling, coaching, and scaffolding. This model is directly applicable to web-based learning. Examples of web-CLEs will be demonstrated in the presentation. Model for Designing Constructivist Learning Environments Constructivist conceptions of learning assume that knowledge is individually constructed and socially co-constructed by learners based on their interactions in the world. The meaning that learners construct depends on their needs, beliefs, and prior knowledge. This paper presents a model for designing constructivist learning environments (CLEs) that engage learners in meaning making based on constructivist assumptions(Duffy & Jonassen,

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This paper proposes a design framework for constructing a groupware-based learning environment (GBLE) that enables electronic cognitive apprenticeship. The central theme of this framework is that any design of a GBLE must have learning theories as foundations to substantiate the learning effectiveness of this environment. The proposed framework applies the principles of cognitive apprenticeship and casebased learning in designing a learning environment using groupware technology. In this framework, the practice of case-based learning is grounded in cognitive apprenticeship. The theory base of cognitive apprenticeship provides not only more coherent guidance but also opportunities to fine-tune the pedagogy of case-based learning. Groupware tools provide needed functions to enable instructional methods of cognitive apprenticeship. This technological support also facilitates the learning process of learners and thus enhances the effectiveness of case-based learning. Based on this framework, a system titled “Using Notes for a Case-based Learning Environment ” (UNCLE) was created to demonstrate the framework's utility.

Modem science has been built on a Cartesian or Newtonian (mechanical) world view giving rise to an artifactual view of mind and suggesting that particles (learners) are continuously working to destroy order (are recalcitrant), which can only be main-tained by an external artificer (the teacher). At the core of the Cartesian worldview is the absolute separation of mind and matter. Beginning with the separation of mind and body, Cartesianism is grounded in a set of dualisms that separate individual from environment and leads to the belief that knowledge refers to a self-sumcient immate-rial substance that can be understood independently from the individual, environ-Corres~ondence and reauests for reorints should be sent to Sasha A. Barab, School of Education, In-

Cases are evocative narrative descriptions of a specific, real-world activity, event or problem. We are investigating cases as a minimalist information design technique, that is, as a design technique that (1) orients information to facilitate user action, (2) anchors information in activity, (3) prevents, mitigates and leverages error, and (4) develops user autonomy. We describe recent experiences employing case-based learning in an undergraduate usability engineering class. We discuss the next steps in a research programme on case-based learning, and speculate on other applications of cases as minimalist information design.

Abstract: Research has shown the potential of a problem-based approach to enhance students’ learning. The interactive nature of hypermedia technology and its ability to deliver information in different media formats can provide unique capabilities for implementing problem-based learning (PBL) environments. Yet, we know little about the types of tools that are effective in supporting students ’ learning in a hypermedia supported PBL environment. The purpose of this study was to investigate both the use of tools and design features in a piece of PBL software and their effectiveness on middle school students ’ learning. The findings of this study show that students who were exposed to the PBL environment increased their achievement scores from pre to posttest more than those students who learned the same content in the traditional classroom. Students ’ reading ability was found to be a better predictor for their achievement in PBL than their math ability. However, the brief treatment of the study had only limited impact on students ’ attitude toward learning science. The findings of the study and their implications are discussed in detail.

The objective of this paper is to describe a design method and rational for creating

Despite the progress made in the field of intelligent tutoring systems (ITS), it is still a major challenge to build systems that can teach about complex, ill-structured domains. A chief reason is that detailed, dynamic modeling of students ' knowledge is intractable in such areas, and complete, correct models of expert knowledge are inherently difficult to build. These difficulties have led some to argue that the goal of intelligent tutoring should be abandoned and that more benefit could be provided by systems without tutoring. We believe that there are many areas in which tutorial intervention is essential, particularly for the communication of expertise. In this paper we advocate basing tutorial intervention on an analysis of a student's likely points of interest within a learning environment, rather than on his or her state of knowledge. This interestfocused approach results in considerable simplification of the modeling task, and has other advantages as well. We describe an interest-tracing intelligent tutoring framework that we have been using to build learning environments for such ill-structured tasks as selling, managing, and other interpersonal skills using tutorial guidance. Our design is based on case-based reasoning as a model of human problem-solving. Expertise is modeled as an organized library of cases; student modeling is restricted to the considerations that enter into the decision to retrieve and present relevant cases. This paper describes the cognitive theory underlying our tutoring approach, and the implementation of the tutor. We show how it is possible to present useful tutorial intervention based on a student's state of interest, without an overwhelming burden of student modeling.