Janet L. Kolodner

What Is Case-Based Reasoning?

This chapter describes case-based reasoning. Case-based reasoning can mean adapting old solutions to meet new demands, using old cases to explain new situations, using old cases to critique new solutions, or reasoning from precedents to interpret a new situation or create an equitable solution to a new problem. Case-based reasoning is also used extensively in day-to-day commonsense reasoning. When one orders a meal in a restaurant, one often bases decisions about what might be good in other experiences in that restaurant and those like it. As one plans his or her household activities, he or she remembers what worked and did not work previously and use that to create new plans. A child care provider mediating an argument between two children remembers what worked and did not work previously in such situations and bases his or her suggestion on that. In general, the second time one solves some problem or does some task is easier than the first because he or she remembers and repeats the previous solution.

Problem-Based Learning Meets Case-Based Reasoning in the Middle-School Science Classroom: Putting Learning by Design(tm) Into Practice

This article tells the story of the design of Learning by Design(tm) (LBD), a project-based inquiry approach to science learning with roots in case-based reasoning and problem-based learning, pointing out the theoretical contributions of both, classroom issues that arose upon piloting a first attempt, ways we addressed those challenges, lessons learned about promoting learning taking a project-based inquiry approach, and lessons learned about taking a theory-based approach to designing learning environments. LBD uses what we know about cognition to fashion a learning environment appropriate to deeply learning science concepts and skills and their applicability, in parallel with learning cognitive, social, learning, and communication skills. Our goal, in designing LBD, was to lay the foundation in middle school for students to be successful thinkers, learners, and decisionmakers throughout their lives and especially to help them begin to learn the science they need to know to thrive in the modern world. LBD has students learn science in the context of achieving design-and-build challenges. Included in LBDs framework is a set of ritualized and sequenced activities that help teachers and students acclimate to the culture of a highly collaborative, learner-centered, inquiry-oriented, and design-based classroom. Those ritualized activities help teachers and students learn the practices of scientists, engineers, and group members in ways that they can use outside the classroom. LBD is carefully crafted to promote deep and lasting learning, but we have learned that careful crafting is not enough for success in putting a collaborative inquiry approach into practice. Also essential are fostering a collaborative classroom culture in which students want to be engaged in deep learning and where the teacher sees herself as both a learner and a facilitator of learning, trusts that with her help the students can learn, and enthusiastically assumes the roles she needs to take on.

An Introduction to Case-Based Reasoning*

Case-based reasoning means using old experiences to understand and solve new problems. In case-based reasoning, a reasoner remembers a previous situation similar to the current one and uses that to solve the new problem. Case-based reasoning can mean adapting old solutions to meet new demands; using old cases to explain new situations; using old cases to critique new solutions; or reasoning from precedents to interpret a new situation (much like lawyers do) or create an equitable solution to a new problem (much like labor mediators do). This paper discusses the processes involved in case-based reasoning and the tasks for which case-based reasoning is useful.

Designing to Learn About Complex Systems

Complex systems are commonly found in natural and physical science. Understanding such systems is often difficult because they may be viewed from multiple perspectives and their analysis may conflict with or extend beyond the range of everyday experience. There are many complex structural, behavioral, and functional relations to understand as well. Design activities, which allow explorations of how systems work, can be an excellent way to help children acquire a deeper, more systemic understanding of such complex domains. We report on a design experiment in which 6th grade children learned about the human respiratory system by designing artificial lungs and building partial working models. Structure-behavior-function models are used as a framework for the cognitive analysis of the domain. The design activities helped students learn about the respiratory system. The design students indeed learned more than students receiving direct instruction. They learned to view the respiratory system more systemically. As expected, because of the short time they spent on the exercise, they understood more about structure than function and more about the functions of different parts of the respiratory system than its causal behaviors. This early Learning by Design experiment makes several important suggestions about successful learning from design activities: (a) the need to define design challenges functionally; (b) the importance of dynamic feedback; (c) the need for multiple iterations toward a solution; and most important; (d) thinking about design as a system of activities and allocating time so that the full system can be carried out, allowing its full set of affordances to be realized.

Improving human decision making through case-based decision aiding

Case-based reasoning provides both a methodology for building systems and a cognitive model of people. It is consistent with much that psychologists have observed in the natural problem solving people do. Psychologists have also observed, however, that people have several problems in doing analogical or case-based reasoning. Although they are good at using analogs to solve new problems, they are not always good at remembering the right ones. However, computers are good at remembering. I present case-based decision aiding as a methodology for building systems in which people and machines work together to solve problems. The case-based decision-aiding system augments the persons memory by providing cases (analogs) for a person to use in solving a problem. The person does the actual decision making using these cases as guidelines. I present an overview of case-based decision aiding, some technical details about how to implement such systems, and several examples of case-based systems.

Maintaining organization in a dynamic long-term memory *

As new unanticipated items are added to a memory, it must be able to reorganize itself, integrating the new items into its structure. The reorganization process must maintain the memorys structure and also build up the knowledge retrieval strategies need to search that structure. This study will present an algorithm for knowledge-based memory reorganization. Included in that algorithm are processes for directed generalization and generalization refinement. A fact retrieval system called CYRUS which uses the algorithm is also presented. Conclusions are drawn about maintaining accessibility in a conceptual memory, organizing generalized knowledge with respect to specific knowledge, and expected retrieval failures due to change over time in the memorys organization.

Retrieval and organizational strategies in conceptual memory: a computer model

Abstract : People effortlessly recall past events and episodes in their lives many times in the course of a normal day. A reasonable goal in the design of computer programs is to construct a memory with that same capability. To facilitate human-like retrieval of events from a computer memory, we must first specify a reasonable memory organization. We must then design updating and retrieval processes to build up and access that information. This thesis will present such a theory, and will describe a computer program called CYRUS which implements that theory. CYRUS (Computerized Yale Retrieval and Updating System) stores and retrieves episodes in the lives of Secretaries of State Cyrus Vance and Edmund Muskie. When new events are added to its memory, CYRUS integrates them into memory along with the events it already knows about. CYRUS can then answer questions posed to it in English about the events it stores. The algorithms and memory organization used in CYRUS have been developed by examining the way people answer questions requiring extensive memory search. Its reconstructive processes include instantiation strategies, which construct and elaborate on contexts for search, and search strategies, which direct construction.

Educational Implications of Analogy: A View from Case-Based Reasoning.

Case-based reasoning (CBR) focuses on analogy in the context of solving real-world problems. Its research methodology of computational modeling is aimed at deriving hypotheses about cognition. CBRs computational models show the roles of encoding, retrieval, and adaptation in analogical reasoning processes. In addition, its algorithms provide insight into what it might take to enhance human cognition. CBR as a plausible cognitive model can thus advise on educational philosophy, educational practice, and design of educational software.

The MEDIATOR: Analysis of an early case-based problem solver☆

Case-based reasoning is a reasoning method that capitalizes on previous experience. In case-based reasoning, a new problem is solved in a way that is analogous to a previous similar problem. Case-based reasoning can improve problem-solving behavior in several ways: by providing reasoning shortcuts, by warning of the potential for error, and by suggesting a focus for reasoning. The MEDIATOR was one of the earliest case-based, problem-solving programs. Its domain is dispute resolution, and it uses case-based reasoning for 10 different tasks involved in its problem solving. While some of the MEDIATORs processes have been elaborated and improved on in later case-based problem solvers, there remain many lessons that can be learned about case-based reasoning by analyzing the MEDIATORs behavior. This article provides a short description of the MEDIATOR and its domain, presents its successes and shortcomings, and analyzes the reasons why it behaves the way it does. As part of the analysis, the differences and similarities between the MEDIATOR and later case-based reasoners are also described, as well as the implications of those differences.

A Case-Based Design Aid for Architecture

This paper summarizes the current status of a project to construct a design aiding system for architects. The Archie-II system is an application of case-based reasoning techniques to the task of assisting human designers. The focus on design aiding, the choice of case-based techniques, and the resulting specification of a case browsing system are reviewed and justified in the first section. The balance of the paper then focuses on the ways in which design cases can be carved up for presentation to designers and how the resulting pieces can be indexed and organized so as to make them available at appropriate times in the design process.