Screen LibraryComputer assisted learning : selected contributions from the CAL91 Symposium, 8-11 April 1991, Lancaster University /
This volume contains a selection of the best papers from the Computer Assisted Learning '91 Symposium. It includes research on a wide range of topics related to computers and learning with an emphasis on hard research evidence and innovative explorations.
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| Corporate Authors: | ; |
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| Group Author: | ; |
| Published: |
Pergamon Press,
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| Publisher Address: | Oxford : |
| Publication Dates: | 1992. |
| Literature type: | eBook |
| Language: | English |
| Edition: | First edition. |
| Subjects: | |
| Online Access: |
http://www.sciencedirect.com/science/book/9780080413952 |
| Summary: |
This volume contains a selection of the best papers from the Computer Assisted Learning '91 Symposium. It includes research on a wide range of topics related to computers and learning with an emphasis on hard research evidence and innovative explorations. |
| Item Description: | "Published as volume 18, number 1-3 of the journal Computers & education"--title page verso. |
| Carrier Form: | 1 online resource (1 volume (various pagings)) : illustrations |
| Bibliography: | Includes bibliographical references and indexes. |
| ISBN: |
9781483298726 1483298728 |
| Index Number: | LB1028 |
| CLC: | G434-532 |
| Contents: |
Front Cover; Computer Assisted Learning; Copyright Page; Table of Contents; PREFACE; INTERNATIONAL PROGRAMME COMMITTEE; CHAPTER 1. REASONING SUPPORTED BY COMPUTATIONAL TOOLS; INTRODUCTION; LEARNING AND REASONING; CHOICE OF TOOLS; RESEARCH STRATEGY; TOPICS AND TASKS; DATA COLLECTION; DATA ANALYSIS; CONCLUSIONS; REFERENCES; APPENDIX; CHAPTER 2. OBJECT-LESSONS FROM SELF-EXPLANATORY OBJECTS; INTRODUCTION; SEO AIMS; INTERFACES AND HELP SYSTEMS; OBJECTS, EXPLANATION AND SELF-EXPLANATION; SELF-EXPLANATORY OBJECTS; THE EMPIRICAL STUDIES; DISCUSSION; REFERENCES. Chapter 3. how can intelligent cal better adapt to learners?introduction; systemic student modelling for ical; empirically important learner attributes six key components of a student model for tutoring; questioning and diagnostic techniques needed to build learner models; articulation-how human tutors use their models of their students, including the student's models of the tutor; conclusion; references; chapter 4. modelling domain knowledge for intelligent simulation learning environments*; 1. introduction; 2. knowledge related to computer simulations; 3. formalisation of domain knowledge. 4. the conceptual domain model5. discussion; references; chapter 5. pedagogical decisions within an its-shell; 1. introduction; 2. architecture; 3. representing domain-dependent pedagogical knowledge; 4. a teacher-managed pedagogical component; 5. conclusions; references; chapter 6. a differential diagnostic skills assessment and tutorial tool; introduction; computational models of information processing under uncertainty; the tendency towards a deterministic approach to decision making; classification and pattern recognition; assessment issues. Knowledge base extraction and ddx skills assessmentcorrelations between skills and constructs; advantages of an explicit cognitive and integrated paradigm for assessment and instruction in ddx; current and proposed instructional features; conclusion; references; chapter 7. educational and research utilization of a dynamic knowledge base; 1. introduction; 2. knowledge representation and knowledge acquisition; 3. memory structures and textual information processing; 4. educational basis of our approach; 5. an overview of the system; 6. dynamic knowledge base (dkb) implementation; 7. conclusion |