Investigation of effects of working memory capacity on rule discovery process using eye movement data

Investigation of effects of working memory capacity on rule discovery process using eye movement data Miki Matsumuro (muro@cog.human.nagoya-u.ac.jp) Kazuhisa Miwa (miwa@is.nagoya-u.ac.jp) Graduate School of Information Science, Nagoya University, Fro-cho, Chikusa-ku, Nagoya, Japan Abstract Many studies have investigated the process of rule discov- ery. However, the data utilized in these studies, such as per- formance and verbal protocol data, were course-grained. In this study, we designed a new experimental method using eye movement data to observe the detailed process of rule discov- ery. In the proposed method, we corresponded the task display and a rule space in the participants’ minds to understand how they consider the rules and observe instances by eye tracking. Then, we compared the process of rule discovery by people with high and low working memory capacities. The results of the experiment revealed that those with high working memory capacity tried to consider one or similar rules from multiple instances. On the other hand, those with low working memory capacity tended to consider various rules from one instance. Keywords: Rule discovery; eye tracking; working memory capacity; search strategy Introduction It is one of the most important activities to find regularities not only in science but also in many aspects of daily life. In this study, we tackle two goals in order to understand the pro- cess of rule discovery. Our first goal is to propose a new ex- perimental method so as to observe the detailed process of rule discovery. The second goal is to investigate the relation between working memory capacity (WMC) and strategies of rule discovery. The origin of this study is traced back to the dual space search theory proposed by Simon and Lea (1974). They sug- gested that the process of rule discovery develops through the interaction between two types of searches in two spaces, a rule space and an instance space. Problem solvers state rules by searching in a rule space while generating and observing instances in an instance space, and modify the rules or pro- pose new rules based on their observations. Although their theory can successfully explain the process of rule discovery, when conducting experiments based on this theory, there are limitations. One is that it is difficult to ob- serve the detailed process of search in a rule space because the thought process to state rules cannot be monitored directly. To investigate this process, the researchers have utilized the protocol analysis method (e.g., Haverty, Koedinger, Klahr, & Alibali, 2000). The participants’ think-aloud protocol data were used for this analysis. However, the data were coarse- grained on the time scale, and the participants mentioned only their conscious thoughts. Therefore, the analysis of the de- tailed patterns of search in the two spaces from protocol data often faced essential limitations. For these reasons, our first purpose is to propose a new experimental method to observe the detailed process of rule discovery. The second goal is to investigate the relation between WMC and strategies of rule discovery. Dougherty and Hunter (2003) showed that people with high WMC maintained more alternative hypotheses in their mind when they engaged in hypothesis generation. However, their task was a probability judgment task and their analysis was based on participants’ performance of the thought-listing task that was even more coarse-grained than the protocol data. Other studies also ana- lyzed the effects of WMC based on the score of the reasoning tasks (e.g., S¨us, Oberauer, Wittmann, Wilhelm, & Schulze, 2002). In the current study, we focus not on outputs as results but on the process of rule discovery by using eye movement data. In summary, the first purpose of our study is to propose a new experimental method by which we obtain detailed data about the process of rule discovery. The second purpose is to investigate how participants’ WMC affects such a process. Our method using eye tracking was established based on the SDDS (Scientific Discovery as Dual Search) model of Klahr and Dunbar (1988). The reason we use eye tracking is that eye movement data are more fine-grained than verbal reports and obtained directly without participants’ conscious effort (cf. Rehder & Hoffman, 2005). With this method, we exam- ine differences in search strategies affected by WMC, select- ing those who have high or low WMC based on screening test scores. Experimental Method Search in Each Space We designed an experimental method by means of eye track- ing. We utilize the idea of the structure of a hypothesis space in the SDDS model. It extends the dual space search theory for investigating scientific discovery. The hypothesis space in the SDDS model corresponds to a rule space in dual space search. The hypothesis space includes all available hypothe- ses, each of which is connected with others through search paths. The search path does not connect hypotheses that have different schema. Therefore, similar hypotheses with an iden- tical schema construct a subspace of the hypothesis space. Based on this idea, in our method, we manipulate the struc- ture of a rule space by giving a different function to each rule. Since a different function evokes a different schema, only rules that have the same function are connected, and they construct a subspace in a rule space. We obtain search patterns in the rule and instance spaces by means of eye tracking. First, we define search in each space as follows. The search in a rule space is the process where