Puntambekar / Hmelo-Silver / Erkens Analyzing Interactions in CSCL

Methods, Approaches and Issues
1. Auflage 2011
ISBN: 978-1-4419-7710-6
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 12, 416 Seiten

Reihe: Computer-Supported Collaborative Learning Series

Analyzing Interactions in CSCL: Methodology, Approaches, and Issues deepens the understanding of ways to document and analyze interactions in CSCL and informs the design of the next generation of CSCL tools. It provides researchers with several alternative methodologies, theoretical underpinnings of the methods used, data indicating how the method worked, guidance for using the methods, implications for understanding collaborative processes and their effect on learning outcomes and implications for design.

CSCL research tends to span across several disciplines such as education, psychology, computer science and artificial intelligence. As a result, the methods for data collection and analysis are interdisciplinary, from fields such as sociology, anthropology, psychology, computer science, and artificial intelligence. This book brings perspectives together, and provides researchers with an array of methodologies to document and analyze collaborative interactions.

Autoren/Hrsg.

Hmelo-Silver, Cindy

Erkens, Gijsbert

Puntambekar, Sadhana

Inhaltsverzeichnis

1;Analyzing Interactions in CSCL;3
1.1;Acknowledgements;7
1.2;Introduction;9
1.3;Contents;15
1.4;Contributors;19
1.5;Part I: Understanding Group Processes;23
1.5.1;Chapter 1: A Complexity-Grounded Model for the Emergence of Convergence in CSCL Groups;24
1.5.1.1;1.1 Introduction;24
1.5.1.1.1;1.1.1 Unpacking Emergent Behavior: Emergent Simplicity Versus Emergent Complexity;26
1.5.1.1.2;1.1.2 Purpose;27
1.5.1.2;1.2 Methodology;27
1.5.1.2.1;1.2.1 Research Context and Data Collection;27
1.5.1.2.2;1.2.2 Procedure;28
1.5.1.2.3;1.2.3 Hypothesizing Simple Rules;28
1.5.1.2.4;1.2.4 Operationalizing Convergence;29
1.5.1.3;1.3 Results;29
1.5.1.3.1;1.3.1 Interpreting Fitness Curves;30
1.5.1.3.2;1.3.2 Relationship between Convergence and Group Performance;31
1.5.1.3.3;1.3.3 Comparing Convergence with Other Commonly-Used Interactional Predictors;34
1.5.1.4;1.4 Discussion;35
1.5.1.4.1;1.4.1 Implications for Scaffolding;35
1.5.1.4.2;1.4.2 Implications for Methodology: The Temporal Homogeneity Assumption;36
1.5.1.4.3;1.4.3 Implications for Theorizing CSCL Groups as Complex Systems;37
1.5.1.4.4;1.4.4 Some Caveats and Limitations;38
1.5.1.4.5;1.4.5 Future Directions;39
1.5.1.5;1.5 Conclusion;41
1.5.1.6;References;41
1.5.2;Chapter 2: Analyzing the Contextual Nature of Collaborative Activity;45
1.5.2.1;2.1 Taking into Account the Context of Activity in Research on Collaboration: Theoretical Considerations;45
1.5.2.2;2.2 Evaluating Collaborative Activity in Its Context;47
1.5.2.2.1;2.2.1 Discursive Approach to Studying Context in Students’ Collaborative Activity: The Case of Face-To-Face Activity;47
1.5.2.2.1.1;2.2.1.1 Different Contexts in Meaning-Making;48
1.5.2.2.2;2.2.2 Contextual Process of Collaborative Knowledge Construction: The Case of Asynchronous Web-Based Discussion;54
1.5.2.2.2.1;2.2.2.1 Analyzing Collaborative Knowledge Construction in Its Specific Context;56
1.5.2.2.2.2;2.2.2.2 Combining Quantitative and Qualitative Analysis;60
1.5.2.3;2.3 Discussion;63
1.5.2.4;References;64
1.5.3;Chapter 3: Understanding Learners’ Knowledge Building Trajectory Through Visualizations of Multiple Automated Analyses;67
1.5.3.1;3.1 Introduction;68
1.5.3.2;3.2 Indicators for Knowledge Building Advancement in the Literature;69
1.5.3.2.1;3.2.1 ATK Indices as Indicators for Knowledge Building;70
1.5.3.2.2;3.2.2 Questioning and Level of Inquiry;71
1.5.3.2.3;3.2.3 Argumentation as Indicative of Inquiry and Engagement in Discourse;73
1.5.3.3;3.3 A Study to Identify Features of More Productive Discourse Threads;74
1.5.3.4;3.4 Methods and Tools Used in this Study;76
1.5.3.4.1;3.4.1 Scaffold Supports Used;78
1.5.3.4.2;3.4.2 Discourse Acts Related to Argumentation and Questioning;78
1.5.3.4.3;3.4.3 Domain-Specific Topics and Associated Keywords and Text Patterns;79
1.5.3.4.4;3.4.4 Information Visualization;79
1.5.3.5;3.5 The Context and Basic Quantitative Informationof the Discourse Corpora Analyzed;83
1.5.3.6;3.6 Comparing Corpora Using Discourse Markers;85
1.5.3.7;3.7 Comparing Scaffolds Used in the Discourses;87
1.5.3.8;3.8 Comparing the Discussion Content of the Discourses;89
1.5.3.9;3.9 Integrating the Different Comparisons: Towards a Methodology for Understanding Learners’ Knowledge Building Trajectory;98
1.5.3.10;References;99
1.5.4;Chapter 4: Representational Tools for Understanding Complex Computer-Supported Collaborative Learning Environments*;103
1.5.4.1;4.1 Visual Representations for Understanding CSCL;105
1.5.4.2;4.2 CORDTRA Diagrams;106
1.5.4.3;4.3 Example I: CORDTRA Analysis for Asynchronous CSCL;107
1.5.4.3.1;4.3.1 Context for Study: The STELLAR Learning Environment;108
1.5.4.3.2;4.3.2 CORDTRA Analysis;108
1.5.4.4;4.4 Example II: CORDTRA for Synchronous CSCL;115
1.5.4.4.1;4.4.1 CORDTRA Analysis;117
1.5.4.5;4.5 Discussion;123
1.5.4.6;References;124
1.5.5;Chapter 5: How to Study Group Cognition;127
1.5.5.1;5.1 The Need for a New Science of Group Cognition;127
1.5.5.2;5.2 Designing a Testbed for Studying Group Cognition;131
1.5.5.3;5.3 Studying Group Cognition;133
1.5.5.3.1;5.3.1 Group Cognition in a Virtual Math Team (Research Question);133
1.5.5.3.2;5.3.2 Non-laboratory Experimental Design (External Validity);134
1.5.5.3.3;5.3.3 Data Collection at the Group Level of Description (Unit of Analysis);134
1.5.5.3.4;5.3.4 Instrumentation and Data Formats (Objectivity);135
1.5.5.3.5;5.3.5 Collaborative Data Sessions (Reliability);136
1.5.5.3.6;5.3.6 Describing Social Practices (Generalizability);139
1.5.5.4;5.4 Conceptualizing Group Cognition;141
1.5.5.4.1;5.4.1 Proposal-Driven Sustained Group Activity;142
1.5.5.4.2;5.4.2 The Social Order of Group Cognition;144
1.5.5.5;5.5 How We Study Group Cognition;146
1.5.5.6;References;147
1.5.6;Chapter 6: Thinking about Methods to Capture Effective Collaborations;151
1.5.6.1;6.1 Capturing the Influence of Context;152
1.5.6.2;6.2 Representing Timing;153
1.5.6.3;6.3 Calculating When Timing Matters;155
1.5.6.4;6.4 Capturing Community Knowledge Building;157
1.5.6.5;6.5 Designing to Support (and Capture) Collaboration;158
1.5.6.6;6.6 Where Do We Go from Here?;160
1.5.6.7;References;161
1.6;Part II: Understanding Learning Within Groups;163
1.6.1;Chapter 7: Analyzing Collaborative Processes and Learning from Hypertext Through Hierarchical Linear Modelling;164
1.6.1.1;7.1 Introduction;164
1.6.1.2;7.2 Purpose of the Study;165
1.6.1.3;7.3 Research Context: Integrating CoMPASS in the Science Classroom;166
1.6.1.3.1;7.3.1 Technological Affordances of CoMPASS;166
1.6.1.3.2;7.3.2 Participants;167
1.6.1.3.3;7.3.3 Procedures;168
1.6.1.4;7.4 Providing Metanavigation Support;168
1.6.1.5;7.5 Data Sources and Measures;169
1.6.1.5.1;7.5.1 Individual Measures;170
1.6.1.5.2;7.5.2 Group Measures;171
1.6.1.5.3;7.5.3 Investigations and Data Analyses;171
1.6.1.6;7.6 Results;173
1.6.1.6.1;7.6.1 Predicting Connection Ratio in the Concept Map Test;173
1.6.1.6.2;7.6.2 Predicting Concept Ratio in the Concept Map Test;174
1.6.1.7;7.7 Conclusions;176
1.6.1.8;References;177
1.6.2;Chapter 8: Analyzing Collaborative Interactions with Data Mining Methods for the Benefit of Learning;179
1.6.2.1;8.1 Introduction;179
1.6.2.2;8.2 Temporality in Groups: Development and Change;180
1.6.2.2.1;8.2.1 Phases of Group Development;181
1.6.2.2.2;8.2.2 Adaptation to Change;182
1.6.2.2.3;8.2.3 Groups as Activity Systems;183
1.6.2.2.4;8.2.4 Learning from Experience;184
1.6.2.2.5;8.2.5 Conclusions;185
1.6.2.3;8.3 Methods for Process Analysis;186
1.6.2.3.1;8.3.1 Conceptualizing Process in Terms of Event Sequences;187
1.6.2.3.2;8.3.2 Accounting for Event Sequences with Patterns and Models;188
1.6.2.4;8.4 Sequential Pattern Mining in Asynchronous Interaction Data;189
1.6.2.4.1;8.4.1 Top-Down, Theory Driven Data Mining on Traces of Group Interaction;189
1.6.2.4.2;8.4.2 Bottom-up Discovery of Patterns;190
1.6.2.4.3;8.4.3 Synergies from Modeling Groups and Individuals;192
1.6.2.4.4;8.4.4 Abstraction from Data Traces to Meaningful Sequences;193
1.6.2.5;8.5 Mining for Process Models Based on Chat Data;194
1.6.2.5.1;8.5.1 Discrete Event Models as a Model Class for Activity Systems;195
1.6.2.5.2;8.5.2 Discovering Discrete Event Models;196
1.6.2.5.2.1;8.5.2.1 Heuristic Process Mining;198
1.6.2.6;8.6 Discussion;199
1.6.2.7;References;201
1.6.3;Chapter 9: Multilevel Analysis in CSCL Research;204
1.6.3.1;9.1 Introduction;205
1.6.3.2;9.2 Multilevel Analysis: A ‘New’ Methodological Approach in CSCL Research;205
1.6.3.3;9.3 The Problems CSCL Researchers Encounter;207
1.6.3.3.1;9.3.1 Hierarchically Nested Datasets;207
1.6.3.3.2;9.3.2 Nonindependence of Dependent Variables;207
1.6.3.3.3;9.3.3 Differing Units of Analysis;209
1.6.3.4;9.4 Common Analysis Strategies;210
1.6.3.4.1;9.4.1 Ignoring Nonindependence;210
1.6.3.4.2;9.4.2 Aggregating or Disaggregating Data;211
1.6.3.4.3;9.4.3 Multilevel Analysis;212
1.6.3.5;9.5 Illustration of Problems and Analysis Strategies;213
1.6.3.5.1;9.5.1 Example 1: Impact of an Awareness Tool on Online Discussion;213
1.6.3.5.2;9.5.2 Example 2: Influence of Representational Guidance on Student Learning;215
1.6.3.5.3;9.5.3 Example 3: Influence of Representational Guidance on Essay Quality;218
1.6.3.6;9.6 Conclusion and Discussion;218
1.6.3.7;References;220
1.6.4;Chapter 10: Sequential Analysis of Scientific Argumentation in Asynchronous Online Discussion Environments*;223
1.6.4.1;10.1 Introduction;224
1.6.4.2;10.2 Steps, Tools, and Metrics Used in Each Approach;225
1.6.4.2.1;10.2.1 Core Coding: Examining the Nature of Comments Found within Discourse Episodes;226
1.6.4.2.1.1;10.2.1.1 Coding the Discourse Moves of Individual Postings;226
1.6.4.2.1.2;10.2.1.2 Coding the Grounds of a Comment;227
1.6.4.2.1.3;10.2.1.3 Coding the Conceptual Quality of a Comment;227
1.6.4.2.1.4;10.2.1.4 Coding the Level of Opposition within Discourse Episodes;229
1.6.4.2.2;10.2.2 Using Sequential Analysis to Identify Discourse Patterns in Argumentation;229
1.6.4.3;10.3 A Sample Study and Analysis;231
1.6.4.3.1;10.3.1 Data Sample;232
1.6.4.3.2;10.3.2 Instructional Context;232
1.6.4.3.3;10.3.3 Two Experimental Conditions;234
1.6.4.4;10.4 Discussion of Findings with Coding Scheme Only;235
1.6.4.4.1;10.4.1 Conceptual Quality;236
1.6.4.4.2;10.4.2 Grounds Quality and Frequency of Rebuttals;236
1.6.4.4.3;10.4.3 Discourse Moves;236
1.6.4.4.4;10.4.4 Level of Opposition;237
1.6.4.5;10.5 Discussion of Findings Using Sequential Analysis in Tandem with the Core Coding Scheme;238
1.6.4.5.1;10.5.1 Statistical Analysis;238
1.6.4.5.2;10.5.2 Differences in Transitional Probabilities;240
1.6.4.5.3;10.5.3 Differences in the Mean Number of Responses Elicited Per Message;242
1.6.4.5.3.1;10.5.3.1 Oppositional Exchanges;242
1.6.4.5.3.2;10.5.3.2 Supportive Exchanges;242
1.6.4.6;10.6 Affordances of Using Both Methods in Tandem;244
1.6.4.7;10.7 Directions for Future Research;245
1.6.4.8;References;248
1.6.5;Chapter 11: Is the Whole Greater than the Sum of Its Parts? Explaining the Role of Individual Learning and Group Processes in ;250
1.6.5.1;11.1 The Power of Multilevel Analysis (MLA) in CSCL Research: N Is the Answer;250
1.6.5.2;11.2 The Sum Is Better than Its Parts;252
1.6.5.3;11.3 Mirrors for Metacognition: Visual Aids to See Oneself and Others in the Context of Problem Solving;253
1.6.5.4;11.4 From Temporal Data Mining Techniques to Sequential Pattern Recognition;255
1.6.5.5;11.5 Where Do We Go from Here?;256
1.6.5.6;References;257
1.7;Part III: Frameworks for Analyzing Interaction in CSCL;259
1.7.1;Chapter 12: Quantifying Qualities in Collaborative Knowledge Construction: The Analysis of Online Discussions;260
1.7.1.1;12.1 Multidimensional Approach for the Qualitative Coding of Online Discussions (MAQCOD);261
1.7.1.1.1;12.1.1 The Initial Research Question;262
1.7.1.1.1.1;12.1.1.1 Illustrative Example;262
1.7.1.1.2;12.1.2 Definition of Data Structure and Rules for Coding;265
1.7.1.1.2.1;12.1.2.1 Categories and Scaling;266
1.7.1.1.2.2;12.1.2.2 Additional Dimensions Addressing Methodological Questions;268
1.7.1.1.3;12.1.3 Segmentation;269
1.7.1.1.3.1;12.1.3.1 Skipping Segmentation;272
1.7.1.1.4;12.1.4 Training of Coders;272
1.7.1.1.4.1;12.1.4.1 Training for High Objectivity (Without a Loss of Validity);273
1.7.1.1.4.2;12.1.4.2 Handling Biased Data;274
1.7.1.1.5;12.1.5 Aggregation and High-Level Analyses;275
1.7.1.1.5.1;12.1.5.1 Tracing Knowledge;276
1.7.1.1.5.2;12.1.5.2 Quantifying Mutual Influence;276
1.7.1.1.5.3;12.1.5.3 Visualising Mutual Inf.luence;277
1.7.1.2;12.2 Automated Analyses of Online Discussions Using MAQCOD with Natural Language Processing;277
1.7.1.3;12.3 Summary and Conclusion;278
1.7.1.4;References;279
1.7.2;Chapter 13: An Interaction-Aware Design Process for the Integration of Interaction Analysis into Mainstream CSCL Practices;282
1.7.2.1;13.1 Introduction;283
1.7.2.2;13.2 Overview and Model of the Interaction Analysis Process;284
1.7.2.3;13.3 Main Problems for the Integration of Interaction Analysis into Mainstream CSCL Practices;286
1.7.2.3.1;13.3.1 An Illustrating Example: The Mosaic Experience;286
1.7.2.3.2;13.3.2 A Data-Driven Analysis of Problems Regarding Integration of IA Tools and CSCL Environments;288
1.7.2.4;13.4 Towards an Integrated Perspective on Learning and Analysis Activities in CSCL;293
1.7.2.4.1;13.4.1 Design-Driven Solutions;293
1.7.2.4.2;13.4.2 Technology-Driven Solutions;297
1.7.2.5;13.5 Conclusions;300
1.7.2.6;References;302
1.7.3;Chapter 14: A Framework for Assessment of Student Project Groups On-Line and Off-Line;305
1.7.3.1;14.1 Introduction;306
1.7.3.2;14.2 Theoretical Framework on Group Processesin Project Teams;309
1.7.3.3;14.3 Study 1: Interviews with Instructors;310
1.7.3.3.1;14.3.1 Method: Data Collection and Analysis;311
1.7.3.3.2;14.3.2 Results;313
1.7.3.3.2.1;14.3.2.1 Personal Goal Setting and Group Goal Setting;315
1.7.3.3.2.2;14.3.2.2 Personal Progress and Group Progress;316
1.7.3.3.2.3;14.3.2.3 Knowledge Contribution and Group Knowledge Building;317
1.7.3.3.2.4;14.3.2.4 Participation and Division of Labor;318
1.7.3.3.2.5;14.3.2.5 Team Player and Interpersonal Dynamics;318
1.7.3.4;14.4 Study 2: Project Group Observations;319
1.7.3.4.1;14.4.1 Method;319
1.7.3.4.2;14.4.2 Results;320
1.7.3.5;14.5 Study 3: Developing Technology for Automatic Monitoring of Group Processes;321
1.7.3.5.1;14.5.1 Automatic Assessment from Message Board Data;322
1.7.3.5.2;14.5.2 Automatic Assessment from Speech;323
1.7.3.6;14.6 Discussion;325
1.7.3.7;14.7 Conclusions and Future Work;327
1.7.3.8;References;328
1.7.4;Chapter 15: Analyzing Productive Interactions in CSCL: Collaborations, Computers and Contradictions;330
1.7.4.1;15.1 Introduction;331
1.7.4.2;15.2 General Trends in Methods;331
1.7.4.3;15.3 Case Studies;333
1.7.4.4;15.4 Methods of Data Collection;334
1.7.4.5;15.5 Analysis;335
1.7.4.5.1;15.5.1 Case 1: Running in the Rain;336
1.7.4.5.2;15.5.2 Context;337
1.7.4.5.3;15.5.3 Case 2: Gameshow;338
1.7.4.5.4;15.5.4 Discussion: Dealing with Complex Learning Settings;340
1.7.4.5.5;15.5.5 Case 3: Mobile Collaborative Learning in Formal and Informal Learning Settings/Personal Inquiry;342
1.7.4.6;15.6 Conclusions;346
1.7.4.7;References;347
1.7.5;Chapter 16: Tracing Interaction in Distributed Collaborative Learning;351
1.7.5.1;16.1 Introduction;351
1.7.5.2;16.2 Theoretical Assumptions;353
1.7.5.3;16.3 Data Requirements;354
1.7.5.4;16.4 Analytic Challenges;355
1.7.5.4.1;16.4.1 The Distributed Nature of the Data;356
1.7.5.4.2;16.4.2 The Contingent Nature of Human Behavior;356
1.7.5.4.3;16.4.3 The Meaning of Nonverbal Behavior;357
1.7.5.4.4;16.4.4 Selective Attention to Large Data Sets;357
1.7.5.4.5;16.4.5 Multi-scale Phenomena;357
1.7.5.5;16.5 Analyzing Distributed Interaction with Contingency Graphs;358
1.7.5.5.1;16.5.1 Contingency Graphs;358
1.7.5.5.1.1;16.5.1.1 Vertices: Events;358
1.7.5.5.1.2;16.5.1.2 Arcs: Contingencies;358
1.7.5.5.1.3;16.5.1.3 Addressing the Challenges;359
1.7.5.5.2;16.5.2 Example Analysis;360
1.7.5.5.2.1;16.5.2.1 Source of Data;361
1.7.5.5.2.2;16.5.2.2 Log File Description;362
1.7.5.5.2.3;16.5.2.3 Contingency Graph Construction;362
1.7.5.5.2.4;16.5.2.4 Contingency Graph Analysis;363
1.7.5.5.2.4.1;Selective Attention: Identifying Convergent Conclusions;363
1.7.5.5.2.4.2;Tracing: Subgraph Building Reveals Non Verbal Interaction Pattern;363
1.7.5.5.2.4.3;Micro Analysis: Indexing Video to Correlate Individual and Social Phenomena;365
1.7.5.5.2.5;16.5.2.5 Analytic Rationale for Using the Contingency Graph;370
1.7.5.5.2.6;16.5.2.6 Scaling up;371
1.7.5.6;16.6 Remaining Challenges;371
1.7.5.6.1;16.6.1 The Distributed Nature of the Data;371
1.7.5.6.2;16.6.2 The Contingent Nature of Human Behavior;371
1.7.5.6.3;16.6.3 The Meaning of Nonverbal Behavior;372
1.7.5.6.4;16.6.4 Selective Attention to Large Data Sets;372
1.7.5.6.5;16.6.5 Multi-scale Phenomena;373
1.7.5.7;16.7 Broader Implications;373
1.7.5.8;References;374
1.7.6;Chapter 17: Analyzing Collaborative Interactions Across Domains and Settings: An Adaptable Rating Scheme.*;377
1.7.6.1;17.1 The Original Rating Scheme1;379
1.7.6.1.1;17.1.1 Aspects of Collaboration Quality;380
1.7.6.1.1.1;17.1.1.1 Communication;380
1.7.6.1.1.2;17.1.1.2 Joint Information Processing;381
1.7.6.1.1.3;17.1.1.3 Coordination;382
1.7.6.1.1.4;17.1.1.4 Interpersonal Relationship;382
1.7.6.1.1.5;17.1.1.5 Motivation;383
1.7.6.1.2;17.1.2 Applying the Original Rating Scheme;383
1.7.6.1.3;17.1.3 Empirical Evaluation of the Rating Scheme;384
1.7.6.2;17.2 Adaptation of the Rating Scheme;385
1.7.6.2.1;17.2.1 Adaptation Process;386
1.7.6.2.1.1;17.2.1.1 Redefining the Rating Dimensions;386
1.7.6.2.1.2;17.2.1.2 Adapting the Rating Handbook;388
1.7.6.2.2;17.2.2 Empirical Evaluation of the Adapted Rating Scheme;388
1.7.6.2.3;17.2.3 Giving Adaptive Feedback Based on Collaboration Quality Assessment;390
1.7.6.3;17.3 Implementing the Rating Scheme in ActivityLens;391
1.7.6.3.1;17.3.1 Adaptation of ActivityLens;391
1.7.6.3.2;17.3.2 Using ActivityLens to Analyze Process Datafrom Algebra Study;392
1.7.6.4;17.4 Implications for Practitioners;394
1.7.6.4.1;17.4.1 Adapting the Dimensions to Further Settings;395
1.7.6.4.2;17.4.2 Concluding Thoughts on When to Apply a Rating Scheme in the Assessment of Collaboration Quality;396
1.7.6.5;References;397
1.7.7;Chapter 18: Analytical Frameworks for Group Interactions in CSCL Systems;401
1.7.7.1;18.1 Introduction;401
1.7.7.2;18.2 Objectives of Analytical Frameworks for Group Interactions;401
1.7.7.2.1;18.2.1 Linking Process Quality and Knowledge Construction;401
1.7.7.2.2;18.2.2 Mediating and Transforming Learning and Teaching with Technology;402
1.7.7.2.3;18.2.3 Supporting Instructors;402
1.7.7.2.4;18.2.4 Measuring the Quality of Collaboration;402
1.7.7.2.5;18.2.5 Defining the Process of Interaction Analysis;403
1.7.7.2.6;18.2.6 Making Interaction Apparent;403
1.7.7.2.7;18.2.7 Summary of Objectives for Analytical Frameworks;403
1.7.7.3;18.3 A Selection of Theoretical Assumptions Made by Authors of Analytical Frameworks for Group Interactions;404
1.7.7.3.1;18.3.1 Positive Relations between Process Features and Knowledge Construction;404
1.7.7.3.2;18.3.2 Positive and Negative Relations between Process Features and Context;405
1.7.7.3.3;18.3.3 Predictive Relations between the Flow of Language Communication and Group Difficulties;405
1.7.7.3.4;18.3.4 Definitive Relations between Nine Different Dimensions of the Collaborative Process and the Quality of Collaboration;406
1.7.7.3.5;18.3.5 Interdependent Relations between the CSCL Environment, Its Context of Use and the Interaction Analysis Tools;407
1.7.7.3.6;18.3.6 Contingency Relations between the Trajectories of Intra- and Inter-subjective Meaning Making and the Media Participa;408
1.7.7.3.7;18.3.7 Summary of Selected Theoretical Assumptions;409
1.7.7.3.8;18.3.8 Unit of Analysis: Individual, Group or Both?;410
1.7.7.4;18.4 A Selection of Methodological Assumptions Made by Authors of Analytical Frameworks for Group Interactions;411
1.7.7.4.1;18.4.1 Origins of Research;412
1.7.7.4.2;18.4.2 Tensions between Methodological Constraints and Views on Interaction;413
1.7.7.4.3;18.4.3 Is Technology a Variable?;413
1.7.7.4.4;18.4.4 Top-down vs. Bottom Up?;414
1.7.7.4.5;18.4.5 Summary of Selected Methodological Assumptions;415
1.7.7.5;18.5 Remaining Challenges;416
1.7.7.5.1;18.5.1 Automating Assessing and/or Intervening;416
1.7.7.5.2;18.5.2 Assessing Quality of Processes;416
1.7.7.5.3;18.5.3 Research Questions, Data, Methods: Interdependencies;417
1.7.7.5.4;18.5.4 Interdependencies of CSCL Systems and Interaction Analysis Software;418
1.7.7.6;18.6 Conclusions;418
1.7.7.7;References;419
1.8;Index;422