Abductive reasoning is the process of finding the best explanation for a set of observations. The theory of abductive reasoning (TAR, Johnson & Krems, 2001) allows detailed process assumptions that were only partly tested in detail up until now. This thesis employs an artificial abductive reasoning task, the Black Box task, and eye tracking measures in order to gain insight into the process. The first part of this thesis aims at evaluating process measures based on eye tracking and using them in order to gain a better understanding of the processes postulated in TAR such as the construction of a situation model or retrieval of relevant information. The second part investigates the relationship between working memory and abductive reasoning by manipulating the amount of information stored in memory and examining the relationship between visual abductive reasoning and working memory skills. In a last part a perspective to the transferability of our results to everyday life tasks is given.
The first study focuses on differentiating between processes that take place during the encoding and the evaluation of observation information by comparing eye movement measures.
In the second study, we tested process assumptions such as the construction of a mental representation from TAR using memory indexing, an eye tracking method that makes it possible to trace the retrieval of explanations currently held in working memory. Gaze analysis revealed that participants encode the presented evidence (i.e., observations) together with possible explanations into memory. When new observations are presented, the previously presented evidence and explanations are retrieved. With the memory indexing method, we were able to assess the process of information retrieval in abductive reasoning, which was previously believed to be unobservable.
The theory of abductive reasoning (TAR; Johnson & Krems, 2001) assumes that when information is presented sequentially, new information is integrated into a mental representation called a situation model, the central data structure on which all reasoning processes are based. Since working memory capacity is limited, the question arises how reasoning might change with the amount of information that has to be processed in memory. To answer this question, we conducted a third experimental study, in which we manipulated whether previous observation information and previously found explanations had to be retrieved from memory or were still present in the visual array. We analyzed individual ratings of difficulty as well as behavioral data and reasoning outcomes. Our results provide evidence that people experience differences in task difficulty when more information has to be retrieved from memory. This is also evident in changes in the mental representation as reflected by eye tracking measures. However, these differences are not evident in the reasoning outcome. These findings suggest that individuals construct their situation model from both information in memory as well as external memory stores. The complexity of the model depends on the task at hand: when memory demands are high, only relevant information is included. With this compensation strategy, people are able to achieve similar reasoning outcomes even when faced with more difficult tasks.
The precise relationship between reasoning and working memory capacity remains largely opaque. Combining data of both studies from chapter 3 and 4, we firstly investigated if reasoning performance differs due to differences in working memory capacity. Secondly, using eye tracking, we explored the relationship between the facets of working memory and the process of visuospatial reasoning. Therefore both, a test for storage and processing, and content components (verbal-numerical/ spatial) of working memory as well as an intelligence measure, were engaged. Results show a clear relationship between reasoning accuracy, spatial storage and processing components as well as intelligence. Process measures suggest that high spatial working memory ability might lead to the use of strategies optimizing the content and complexity of the mental representation on which abductive reasoning is based.
In a fifth study, we aimed to investigate whether there are also indicators for the mechanisms postulated by TAR in a task that is closer to real life reasoning. Therefore, we asked participants to solve 12 jigsaw puzzles whereby the abductive task was the identification of the motive presented on the puzzles. Thereby, the pieces of the puzzles posed as observation and hypotheses to the motive of the puzzle as explanations. As a process tracing measure, we used thinking aloud. Verbal protocols were recorded, transcripted and carefully coded according to the operators and explanation types postulated in TAR. We found evidence that participants use most of the operators with a likeliness that significantly lies above chance level. We also found evidence of the existence of the different explanation types.
Eye movements were able to give insight in the interrelations between working memory, attention, and action. Therefore, this work contributes to understanding abductive reasoning, not only by testing the assumptions of TAR, but also by finding relations between memory, action and thought. The results do not only account for abductive reasoning in an artificial task but also in everyday life reasoning.:1 Introduction 1
1.1 Theories on Abductive Reasoning and Beyond 4
1.1.1 Theory of Abductive Reasoning 4
1.1.2 Other Theories 7
1.2 Reasoning, Working Memory, and Mental Representation 9
1.3 Process Tracing 11
1.4 An Artificial Abductive Task: The Black Box 12
1.5 Overview and Research Objectives 15
1.5.1 Differentiating between Encoding and Processing 15
1.5.2 Current Explanations in Memory 16
1.5.3 Information Stored in Memory 16
1.5.4 More than Storage of Information 17
1.5.5 In the Context of Everyday Life 18
1.5.6 Summary, Perspectives, and Conclusion 18
2 The Possibilities of Eye Tracking: Differentiating between Encoding and Processing 21
2.1 Abstract 22
2.2 Introduction 23
2.3 Method 26
2.3.1 Participants 26
2.3.2 Task and Apparatus 27
2.3.3 Procedure 28
2.3.4 Analysis 29
2.4 Results 30
2.5 Discussion 32
3 Tracing Current Explanations in Memory: A Process Analysis Based on Eye Tracking 37
3.1 Abstract 38
3.2 Introduction 39
3.2.1 Current Explanations of Abductive Reasoning 41
3.2.2 Tracing the Reasoning Process 44
3.2.3 Present Study 45
3.3 Method 48
3.3.1 Participants 49
3.3.2 Apparatus 49
3.3.3 Material 50
3.3.4 Procedure 53
3.4 Results 54
3.4.1 Performance 54
3.4.2 Gaze Analyses 55
3.4.3 Hypothesis 1: Information Stored in the Situation Model 57
3.4.4 Hypothesis 2: Different Types of Explanations—Concrete vs. Abstract 61
3.5 Discussion 67
3.5.1 Information Stored in the Situation Model 68
3.5.2 Concretely and Abstractly Explained Observations 68
3.5.3 TAR and Current Theories on Abductive Reasoning 70
3.5.4 Tracing Memory Processes 72
3.5.5 Conclusion 74
Appendix 3.1 75
Appendix 3.2 76
Appendix 3.3 77
Appendix 3.4 78
4 Information Stored in Memory Affects Abductive Reasoning 79
4.1 Abstract 80
4.2 Introduction 81
4.2.1 The Reasoning Process 82
4.2.2 Visual Attention 85
4.2.3 Research Objectives 86
4.2.4 This Study 87
4.2.5 Using Eye Movements as a Method to Assess Memory Retrieval 89
4.2.6 Hypotheses 89
4.3 Method 92
4.3.1 Participants 92
4.3.2 Apparatus 92
4.3.3 The Black Box Task 92
4.3.4 Procedure 95
4.3.5 Pairwise Comparisons 96
4.4 Results 96
4.4.1 Performance 96
4.4.2 Gaze Analysis 99
4.4.3 Hypothesis 1: Differences Experienced in Task Difficulty 101
4.4.4 Hypothesis 2: Elements of the Situation Model 102
4.4.5 Hypothesis 3: Integrative Solutions 105
4.5 Discussion 107
4.5.1 Differences Experienced in Task Difficulty 108
4.5.2 Elements of the Situation Model 108
4.5.3 Integrative Solutions 110
4.5.4 Summary 112
5 More than Storage of Information – What Working Memory Contributes to Visual Abductive Reasoning 113
5.1 Abstract 114
5.2 Introduction 115
5.2.1 Working memory 116
5.2.2 Relations between Abductive Reasoning Working Memory Capacity 118
5.2.3 Eye Movements as a Process Tracing Method 119
5.2.4 Abductive Reasoning Outcomes and Working Memory Ability. 120
5.2.5 Abductive Reasoning Processes and Working Memory Ability 121
5.3 Method 123
5.3.1 Participants 124
5.3.2 Apparatus 124
5.3.3 Material 125
5.3.4 Procedure 127
5.4 Results 128
5.4.1 Analysis 128
5.4.2 Abductive Reasoning Accuracy and Working Memory Ability 131
5.4.3 Abductive Reasoning Processes and Working Memory Ability 132
5.5 Discussion 135
5.5.1 The Interaction of Reasoning Accuracy and Memory Ability 135
5.5.2 The Interaction of the Process of Reasoning and Memory Ability 136
5.5.3 Conclusion 138
6 The Theory of Abductive Reasoning in the Context of Everyday Life 141
6.1 Abstract 142
6.2 Introduction 143
6.2.1 Abduction in “Real Life” 145
6.3 Method 146
6.3.1 Participants 146
6.3.2 Task 147
6.3.3 Material 148
6.3.4 Apparatus 148
6.3.5 Procedure 149
6.3.6 Coding system 150
6.4 Results 153
6.4.1 Analysis 153
6.4.2 Descriptive Data 153
6.3.3. Likeliness of Operator Use 155
6.5 Discussion 156
6.5.1 Operator Use 156
6.5.2 Explanation Types 157
6.5.3 Perspectives 158
7 Summary, Perspectives, and Conclusion 159
7.1 The Process of Abductive Reasoning 159
7.2 Contributions of other Theories 162
7.3 Eye Tracking and its Methodological Implications 164
7.4 Future Research and Applications 167
7.5 Conclusion 169
8 References 171
Curriculum Vitae 191
Publications 196
Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:74428 |
Date | 04 May 2021 |
Creators | Klichowicz, Anja |
Contributors | Krems, Josef F., Jahn, Georg, Technische Universität Chemnitz |
Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/updatedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
Rights | info:eu-repo/semantics/openAccess |
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