Individual Difference in Reasoning about Broken Devices: An Eye Tracking Study

Individual Differences in Reasoning about Broken Devices: An Eye Tracking Study Shulan Lu (shulanlu@hotmail.com) Department of Psychology, University of Memphis, 3693 Norriswood Memphis, TN 38152 USA Brent Olde (baolde@memphis.edu) Department of Psychology, University of Memphis, 3693 Norriswood Memphis, TN 38152 USA Elisa Cooper (culdihavben@hotmail.com) Department of Psychology, University of Memphis, 3693 Norriswood Memphis, TN 38152 USA Arthur C. Graesser (a-graesser@memphis.edu) Department of Psychology, University of Memphis, 3693 Norriswood Memphis, TN 38152 USA Abstract We examined the questions college students ask when everyday devices malfunction. Our investigation of the explanatory reasoning processes is organized around the central theme of question asking. PREG, a model of human question asking, predicts when and what types of questions are asked by humans while comprehending expository texts. PREG has two salient predictions. First, deep comprehenders should ask questions that converge on plausible faults. Second, eye movements should converge on those likely faults. An eye tracking study supported these predictions. The present research supports the claim that question asking and eye tracking are two excellent indicators of device comprehension in the context of breakdown scenarios. Introduction Deep comprehension of everyday devices can be manifested in a number of tasks and measures. For example, most colleagues would agree that the deep comprehenders construct coherent representations of functioning devices, draw appropriate inferences, answers explanation-based questions correctly (e.g., why, how, what-if, what-if-not), and solve transfer problems that apply their understanding (Gentner & Stevens, 1983; Graesser, Singer, & Trabasso, 1994). This study investigates the manifestations of deep comprehension of devices that are not as widely recognized. We believe that deep comprehension is required when devices breakdown, when eyes fixate on likely faults, and when questions are asked about likely faults. (Graesser, Olde, & Lu, in press; Graesser, Olde, Pomeroy, Whitten, Lu, & Craig, in press). Question asking and its role in understanding texts and stories is well-documented (Graesser & McMahen, 1993; Kass, 1992; Schank, 1986, 1999; Ram, 1994). The literature has consistently suggested that the understanding of a story is achieved by identifying the questions raised by the story and then searching for the answers in the story. Question asking has many potential functions in reasoning and problem solving. For instance, question asking is often affiliated with searches, comparisons, explanations, predictions and several other cognitive processes. It is reasonable to say that comprehenders would have more questions as they reason through an expository text and that their questions would manifest comprehension depth. For example, it is very hard to imagine that a shallow comprehender could ask questions addressing the critical causal components of an event. In this article, we examine a model of question asking in the context of understanding technical texts. More specifically, we are interested in the model’s predictions about deep versus shallow comprehension of everyday devices as revealed by question asking. It is suggested that question asking opens a window for viewing the sub- processes involved in understanding (Ram, 1994), such as the retrieval of explanations in long term memory and the search of information from a display. However, there has been very little empirical research that documents the relationships among comprehension, question asking, and information search (as reflected in eye tracking). Therefore, we conducted a study in which eye tracking was measured while college students generated questions when confronted with a breakdown scenario.