Learning in humans and machines: towards an interdisciplinary learning science
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Oxford [u.a.]
Pergamon
1996
|
| Ausgabe: | 1. ed. |
| Schriftenreihe: | Journals of related interest
|
| Schlagworte: | |
| Online-Zugang: | Klappentext Inhaltsverzeichnis |
| Beschreibung: | XII, 241 S. Ill., graph. Darst. |
| ISBN: | 0080425690 |
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| 245 | 1 | 0 | |a Learning in humans and machines |b towards an interdisciplinary learning science |c ed. by Peter Reimann ... |
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Datensatz im Suchindex
| _version_ | 1804117123914530816 |
|---|---|
| adam_text | Recent
developments provide interdisciplinary research
on learning with some challenges all of which are
addressed in this book. The book is one of the outcomes
of the European Science Foundation s Scientific
Programme on Learning in Humans and Machines . The
contributing authors are all considered as leading experts
in their field and come from the fields of cognitive,
computer and educational science.
For researchers working in the fields of cognitive, science
artificial intelligence and educational technology. In
addition individuals interested in learning and instruction
and the social context of learning.
Table
of Contents
1.
Towards an Interdisciplinary Learning Science
Peter
Reimann
and
Hans Spada
....................................... 1
Interdisciplinary Learning Research: Success Stories
........................ 2
The Research Program Learning in Humans and Machines
................. 4
Scope and Limitations
.............................................. 5
Research Themes in the LHM Program
................................... 6
Task Force
1 :
Representation Changes in Learning
....................... 7
Task Force
2:
Multiobjective Learning with Multiple Representations
........ 9
Task Force
3:
Learning Strategies to Cope with Sequencing Effects
......... 11
Task Force
4:
Situated Learning and Transfer
.......................... 13
Task Force
5:
Collaborative Learning
................................. 15
Chapter Overview
.................................................. 17
References
........................................................ 21
2.
A Cognitive Psychological Approach to Learning
Stella Vosniadou
................................................... 23
Introduction
....................................................... 23
Learning as Change in the Way Information is Represented and Processed
...... 24
Strategies for Processing Information
................................. 24
Knowledge Representation
......................................... 26
Challenging Cognitivism
............................................. 30
Is a Unitary Theory of Learning Possible?
............................. 30
Learning Without Rules
........................................... 31
Learning Without Symbols
......................................... 32
Conclusions
....................................................... 33
References
........................................................ 34
3.
Learning to Do and Learning to Understand:
A Lesson and a Challenge for Cognitive Modeling
Stellan Ohlsson....................................................
37
On Routes and Maps
................................................ 37
Learning to Do
..................................................... 40
A Model of Agency
............................................... 41
Learning from Errors
.............................................. 43
A Broader View
.................................................. 45
Lesson Learned
.................................................. 47
Learning to Understand
.............................................. 48
The Dissociation Between Understanding and Action
.................... 49
Epistemic
Activities
.............................................. 51
Towards Models of
Epistemic
Activities
.............................. 52
Summary
....................................................... 55
Final Words
....................................................... 56
Acknowledgments
.................................................. 57
References
........................................................ 58
4.
Machine
Learning: Case Studies of an Interdisciplinary Approach
Werner Emde
......................................................63
Introduction
........................................................63
Taxonomy of Basic Learning Mechanisms
...............................64
Heuristic Approaches to Concept Learning and Concept Formation
............66
FOIL
...........................................................67
KBG
...........................................................71
Final Remarks on FOIL and KBG
....................................76
Theoretical Approaches
..............................................76
Computational Models of Human Learning
...............................77
Final Remarks and Conclusions
........................................79
Acknowledgments
...................................................80
References
.........................................................80
5.
Mental and Physical Artifacts in Cognitive Practices
Roger
Säljö
.......................................................83
Introduction
........................................................83
Cognition And Human Practices:
A Sociocultural
Approach
.................84
Thinking and the Use of Tools
.......................................84
Psychological Tools and Learning
...................................87
Artifacts and Cognition
............................................88
Situating Thinking in Human Practices
................................91
Conclusions
........................................................92
References
.........................................................93
6.
Learning Theory and Instructional Science
Erik
De Corte .....................................................
97
Introduction
........................................................97
Aptitudes Involved in Skilled Learning and Thinking
.......................97
Major Features of Effective Learning
....................................98
Transfer: A Holy Grail?
............................................. 100
Learning Theory and the Design of Powerful Learning Environments
......... 102
References
....................................................... 105
7.
Knowledge Representation Changes in Humans and Machines
Lorenza
Saitta and Task Force
1..................................... 109
Introduction
....................................................... 109
Representation Changes in Humans
....................................
Ill
Concepts and Conceptual Structures
.................................
Ill
Theories
....................................................... 112
Mental Representations
........................................... 112
Procedural Knowledge
............................................ 113
Computational Models
............................................ 113
An Educational Perspective
........................................ 114
Representation Changes in Machines
................................... 116
Constructive Learning
............................................ 117
Abstraction
..................................................... 118
Research Directions
................................................ 120
Computational-Cognitive Modelling
of Representational Change
in Elementary Dynamics
.......................................... 120
Formation and Evolution of Mental Models of Physical Phenomena
in a Restricted Set of Situations
.................................... 120
Conclusions
...................................................... 121
References
....................................................... 121
8.
Multi-objective Learning With Multiple Representations
Maarten
van Someren and Peter
Reimann............................. 130
Introduction
...................................................... 130
Multiple Representations
............................................ 132
Psychological Research
........................................... 133
Machine Learning
................................................ 137
Issues in Learning with Multiple Representations
...................... 138
Learning Goals
.................................................... 139
Psychological Research
........................................... 141
Machine Learning
............................................... 142
Issues in Goal-Directed Learning
................................... 143
Learning Strategies
................................................. 144
Psychology
.................................................... 144
Machine Learning
............................................... 146
Issues
......................................................... 147
Conclusions
...................................................... 147
Research Issues
................................................. 148
A Methodological Note
........................................... 149
References
....................................................... 149
9.
Order Effects in Incremental Learning
Pat Langley
...................................................... 154
Introduction
...................................................... 154
The Nature of Incremental Learning
................................... 154
Definitions of Incremental Learning
................................. 154
Definitions of Order Effects
....................................... 156
Levels of Order Effects
........................................... 157
The Effects of Instance Order
........................................ 158
Mitigating the Effects of Instance Order
.............................. 158
Instance Order in Instructional Design
............................... 160
Instance Order and Human Behavior
................................ 162
The Effects of Concept Order
........................................ 163
From Simple to Complex Concepts
................................. 163
From Complex to Simple Concepts
................................. 163
Directions for Research on Incremental Learning
......................... 164
Acknowledgments
................................................. 165
References
....................................................... 165
10.
Situated Learning and Transfer
Hans
Gruber, Lai-Chong
Law, Heinz
Mandl,
and Alexander Renkl
........ 168
Recognition of the Problem: Lack of Transfer in Learning
................. 168
Situated Cognition And Learning: Review of Theoretical Frameworks
....... 170
Lave s Theory of Cognition in Practice
.............................. 170
Rogoff
s
Theory of Apprenticeship in Thinking and Transfer of Learning
... 171
Situated Cognition as Perceiving Affordances:
Greeno s
Theory
.......... 173
Situated Cognition as Socially Shared Cognition: Resnick s Theory
........ 174
Situated Cognition as Coordinating Without Deliberation: Clancey s Theory.
176
Communalities and Differences in Situated Cognition Perspectives
........ 177
Situated Cognition and Instruction: Technology-Based Approaches
.......... 178
The Instructional Model of Cognitive Apprenticeship
................... 178
Anchored Instruction
............................................. 179
Spiro s Instructional Theory of Cognitive Flexibility
.................... 180
Potentials and Pitfalls of Educational Technology
for Implementing Situated Learning
................................... 181
Questions for Further Research
....................................... 182
References
....................................................... 184
11.
The Evolution of Research on Collaborative Learning
Pierre Dillenbourg, Michael Baker, Agnes Blaye, and Claire O Malley
..... 189
Introduction
....................................................... 189
Theoretical Issues: The Individual or the Group as the Unit
................. 190
The Socio-Constructivist Approach
.................................. 190
The Socio-Cultural Approach
...................................... 192
The Shared Cognition Approach
.................................... 193
Empirical Issues: Effects, Conditions and Interactions
..................... 194
The Effect Paradigm
............................................ 194
The Conditions Paradigm
........................................ 195
The Interactions Paradigm
....................................... 198
Tools for Observing Interactions
...................................... 199
Two Human Users Collaborate on a Computer-Based Task
............... 199
Computer-Mediated Collaboration
.................................. 200
Human-Computer Collaborative Learning
............................. 200
Tools for Analyzing Interactions
...................................... 201
Analysis Categories
.............................................. 202
Conversation Models
............................................. 203
Synthesis
......................................................... 205
References
........................................................ 205
12.
A Developmental Case Study on Sequential Learning:
The Day-Night Cycle
Katharina
Могік
and Stella Vosniadou
............................... 212
Previous Research on Sequencing Effects
............................... 212
The Development of Knowledge about the Day-Night Cycle: A Case Study
.... 215
Psychological Observations
........................................ 215
Layout of a Computational Model
................................... 219
Why an Interdisciplinary Approach?
................................... 225
References
........................................................ 226
Subject Index
.......................................................228
Author Index
.......................................................234
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| indexdate | 2024-07-09T15:49:24Z |
| institution | BVB |
| isbn | 0080425690 |
| language | English |
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| record_format | marc |
| series2 | Journals of related interest |
| spelling | Learning in humans and machines towards an interdisciplinary learning science ed. by Peter Reimann ... 1. ed. Oxford [u.a.] Pergamon 1996 XII, 241 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Journals of related interest Cognitieve processen gtt Leren gtt Machine-learning gtt Transfer van training gtt Cognition Cognitive learning Computer-Assisted Instruction Concept Formation Learning Machine learning Transfer (Psychology) Transfer of training Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Maschine (DE-588)4037786-6 gnd rswk-swf Mensch (DE-588)4038639-9 gnd rswk-swf Lernen (DE-588)4035408-8 gnd rswk-swf Kognitives Lernen (DE-588)4164479-7 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Lernen (DE-588)4035408-8 s Maschinelles Lernen (DE-588)4193754-5 s DE-604 Mensch (DE-588)4038639-9 s Maschine (DE-588)4037786-6 s Kognitives Lernen (DE-588)4164479-7 s DE-188 Reimann, Peter Sonstige oth Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=001771434&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Klappentext Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=001771434&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Learning in humans and machines towards an interdisciplinary learning science Cognitieve processen gtt Leren gtt Machine-learning gtt Transfer van training gtt Cognition Cognitive learning Computer-Assisted Instruction Concept Formation Learning Machine learning Transfer (Psychology) Transfer of training Maschinelles Lernen (DE-588)4193754-5 gnd Maschine (DE-588)4037786-6 gnd Mensch (DE-588)4038639-9 gnd Lernen (DE-588)4035408-8 gnd Kognitives Lernen (DE-588)4164479-7 gnd |
| subject_GND | (DE-588)4193754-5 (DE-588)4037786-6 (DE-588)4038639-9 (DE-588)4035408-8 (DE-588)4164479-7 (DE-588)4143413-4 |
| title | Learning in humans and machines towards an interdisciplinary learning science |
| title_auth | Learning in humans and machines towards an interdisciplinary learning science |
| title_exact_search | Learning in humans and machines towards an interdisciplinary learning science |
| title_full | Learning in humans and machines towards an interdisciplinary learning science ed. by Peter Reimann ... |
| title_fullStr | Learning in humans and machines towards an interdisciplinary learning science ed. by Peter Reimann ... |
| title_full_unstemmed | Learning in humans and machines towards an interdisciplinary learning science ed. by Peter Reimann ... |
| title_short | Learning in humans and machines |
| title_sort | learning in humans and machines towards an interdisciplinary learning science |
| title_sub | towards an interdisciplinary learning science |
| topic | Cognitieve processen gtt Leren gtt Machine-learning gtt Transfer van training gtt Cognition Cognitive learning Computer-Assisted Instruction Concept Formation Learning Machine learning Transfer (Psychology) Transfer of training Maschinelles Lernen (DE-588)4193754-5 gnd Maschine (DE-588)4037786-6 gnd Mensch (DE-588)4038639-9 gnd Lernen (DE-588)4035408-8 gnd Kognitives Lernen (DE-588)4164479-7 gnd |
| topic_facet | Cognitieve processen Leren Machine-learning Transfer van training Cognition Cognitive learning Computer-Assisted Instruction Concept Formation Learning Machine learning Transfer (Psychology) Transfer of training Maschinelles Lernen Maschine Mensch Lernen Kognitives Lernen Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=001771434&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=001771434&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT reimannpeter learninginhumansandmachinestowardsaninterdisciplinarylearningscience |