Intelligent Learning Environments And Knowledge Acquisition In Physics

The NATO workshop ''Knowledge acquisition in the domain of physics and intelligent learning environments" was held in Lyon, France, July 8-12, 1990. A total of 31 researchers from Europe (France, Germany, Greece, Italy, Portugal, and the U. K. ), the U. S. A. , and Japan worked together. This proceedings volume contains most of the contributions to the workshop. The papers show clearly the main directions of research in intelligent learning environments. They display a variety of points of view depending on the researcher's own background even when a single domain of teaching, namely physics, is considered. We acknowledge the assistance of Michael Baker, who was responsible for reviewing the English of the contributions. February 1992 Andree TIberghien Heinz Mandl Table of Contents Introduction 1 1. Teaching Situations and Physics Knowledge Introductory University Courses and Open Environment Approaches: The Computer as a Multi-role Mediator in Teaching/Learning Physics 5 E. Balzano, P. Guidoni, M. Moretti, E. Sassi, G. Sgueglia Practical Work Aid: Knowledge Representation in a Model Based AI System 21 J. Courtois Simultaneous Processing of Different Problem Aspects in Expert Problem Solving: An Analysis in the Domain of Physics on the Basis of Formal Theories of Commonsense Knowledge 35 A. Hron Modelis: An Artificial Intelligence System Which Models Thermodynamics Textbook Problems 47 G. Tisseau 2. Different Approaches to Student Modelling Steps Towards the Formalisation of a Psycho-logic of Motion 65 J. Bliss, J.

Biology education, like science education in general, is in the midst of a revolution that is worldwide in scope. The changes in the ways science education researchers think about learning and understanding represent a major paradigm shift. In this book, international leaders in the field of biology education research give summaries of problems and solutions in biology learning and teaching at various grade levels. Based on a NATO workshop in the Special Programme on Advanced Educational Technology, it provides practical information for teachers, especially in using new interactive, constructivist teaching methods. For science education researchers, it offers a concise summary of a number of research issues in biology education.

This book is a thoroughly revised result, updated to mid-1995, of the NATO Advanced Research Workshop on "Intelligent Learning Environments: the case of geometry", held in Grenoble, France, November 13-16, 1989. The main aim of the workshop was to foster exchanges among researchers who were concerned with the design of intelligent learning environments for geometry. The problem of student modelling was chosen as a central theme of the workshop, insofar as geometry cannot be reduced to procedural knowledge and because the significance of its complexity makes it of interest for intelligent tutoring system (ITS) development. The workshop centred around the following themes: modelling the knowledge domain, modelling student knowledge, design ing "didactic interaction", and learner control. This book contains revised versions of the papers presented at the workshop. All of the chapters that follow have been written by participants at the workshop. Each formed the basis for a scheduled presentation and discussion. Many are suggestive of research directions that will be carried out in the future. There are four main issues running through the papers presented in this book: • knowledge about geometry is not knowledge about the real world, and materialization of geometrical objects implies a reification of geometry which is amplified in the case of its implementation in a computer, since objects can be manipulated directly and relations are the results of actions (Laborde, Schumann). This aspect is well exemplified by research projects focusing on the design of geometric microworlds (Guin, Laborde).

The present volume contains a large number of the papers contributed to the Advanced Study Institute on the Psychological and Educational Foundations of Technology-Based Learning Environments, which took place in Crete in the summer of 1992. The purpose of the Advanced Study Institute was to bring together a small number of senior lecturers and advanced graduate students to investigate and discuss the psychological and educational foundations of technology-based learning environments and to draw the implications of recent research findings in the area of cognitive science for the development of educational technology. As is apparent from the diverse nature of the contributions included in this volume, the participants at the ASI came from different backgrounds and looked at the construction of technology -based learning environments from rather diverse points of view. Despite the diversity, a surprising degree of overlap and agreement was achieved. Most of the contributors agreed that the kinds of technology-supported learning environments we should construct should stimulate students to be active and constructive in their knowledge-building efforts, embed learning in meaningful and authentic activities, encourage collaboration and social interaction, and take into consideration students' prior knowledge and beliefs.

As we approach the 21st century, the need to better link research findings and practical applications of advanced educational technologies (AET) continues to be a priority. During the five-year NATO Special Programme on AET, many advanced study institutes and research workshops focused on building bridges between researchers in and users of educational technology. The organizing committee of the final capstone workshop which took place in September 1993 also chose to focus on this theme. Three position papers, written by members of the AET advisory committee, provided the background and platform for the two-day workshop that was designed to provide guidelines for future AET research and implementation projects. Nicolas Balacheff kicked off the workshop with a philosophical review of the research issues and future research agendas. Herman Bouma and his colleagues at the Institute for Perception Research discussed implementation issues and problems of technology transfer from research laboratories to educational product development.

Not long ago, projections of how office technologies would revolutionize the production of documents in a high-tech future carriedmany promises. The paper less office and the seamless and problem-free sharing of texts and other work materials among co-workers werejust around the corner, we were told. To anyone who has been involved in putting together a volume of the present kind, such forecasts will be met with considerable skepticism, if not outright distrust. The diskette, the email, the fax, the net, and all the other forms of communication that are now around are powerful assets, but they do not in any way reduce the flow of paper or the complexity of coordinating activities involved in producing an artifact such as a book. Instead, the reverse seems to be true. Obviously, the use of such tools requires considerable skill at the center of coordination, to borrow an expression from a chapter in this volume. As editors, we have been fortunate to have Ms. Lotta Strand, Linkoping University, at the center of the distributed activity that producing this volume has required over the last few years. With her considerable skill and patience, Ms. Strand and her work provide a powerful illustration of the main thrust of most of the chapters in this volume: Practice is a coordination of thinking and action, and many things had to be kept in mind during the production of this volume.

This book is the result of a NATO sponsored workshop entitled "Student Modelling: The Key to Individualized Knowledge-Based Instruction" which was held May 4-8, 1991 at Ste. Adele, Quebec, Canada. The workshop was co-directed by Gordon McCalla and Jim Greer of the ARIES Laboratory at the University of Saskatchewan. The workshop focused on the problem of student modelling in intelligent tutoring systems. An intelligent tutoring system (ITS) is a computer program that is aimed at providing knowledgeable, individualized instruction in a one-on-one interaction with a learner. In order to individualize this interaction, the ITS must keep track of many aspects of the leamer: how much and what he or she has leamed to date; what leaming styles seem to be successful for the student and what seem to be less successful; what deeper mental models the student may have; motivational and affective dimensions impacting the leamer; and so ono Student modelling is the problem of keeping track of alI of these aspects of a leamer's leaming.