• unlimited access with print and download
    $ 37 00
  • read full document, no print or download, expires after 72 hours
    $ 4 99
More info
Unlimited access including download and printing, plus availability for reading and annotating in your in your Udini library.
  • Access to this article in your Udini library for 72 hours from purchase.
  • The article will not be available for download or print.
  • Upgrade to the full version of this document at a reduced price.
  • Your trial access payment is credited when purchasing the full version.
Continue searching

The mediating role of mind wandering in the relationship between working memory capacity and reading comprehension

Author: Jennifer C. McVay
The primary goal of this study was to investigate the mediating role of mind wandering in the relationship between working memory capacity (WMC) and reading comprehension as predicted by the executive-attention theory of WMC (e.g., Kane & Engle, 2003). I used a latent-variable, structural-equation-model approach with three WMC span tasks, seven reading comprehension tasks, and three attention-restraint tasks. Mind wandering was assessed using experimenter-scheduled thought probes during four different tasks. The results support the executive-attention theory of WMC. Mind wandering is a significant mediator in the relationship between WMC and reading comprehension, suggesting that the relationship is driven, in part, by attention control over intruding thoughts. I discuss implications for theories of WMC, attention control, and reading comprehension.

TABLE OF CONTENTS Page LIST OF TABLES……………………………….………………………………….……vi LIST OF FIGURES….......................................................................................................vii CHAPTER I. INTRODUCTION……………………………………………….………..1 II. METHODS………………………………………………………………24 III. RESULTS………………………………………………………………..35 IV. DISCUSSION AND CONCLUSIONS………………………………….46 REFERENCES…………………………………………………………………………..59 APPENDIX. TABLES AND FIGURES………………………………………………...74


LIST OF TABLES Page Table 1. Order of tasks across sessions……………………………………………..……74 Table 2. Descriptive statistics for WMC and reading comprehension measures….……75 Table 3. Correlations and reliability for WMC, reading comprehension, attention tasks, and mind wandering measures……………………………....76

Table 4. Descriptive statistics for attention restraint tasks……………………………....77 Table 5. Descriptive statistics for mind wandering….......................................................78


LIST OF FIGURES Page Figure 1.Confirmatory factor analysis model for the latent variables working memory capacity, reading comprehension, mind wandering, and attention restraint………………………………...…….80

Figure 2. Structural equation model depicting the relationship between working memory capacity and reading comprehension with mind wandering as a partial mediator………………………………...…81

Figure 3. Structural equation model depicting the relationship between working memory capacity and reading comprehension with mind wandering as a full mediator…………………..………………….82

Figure 4. Structural equation model depicting the relationship between working memory capacity and reading comprehension with attention restraint as a mediator…………………...……………….........83

Figure 5. Structural equation model depicting the relationship between executive attention and reading comprehension with mind wandering as a mediator……………….…………………………..84



Mind wandering, a universal aspect of human experience, is defined as a shift of attention away from stimuli and mental representations associated with a person’s current-task goals to the consideration of task-unrelated thoughts (TUTs). Not all instances of attention to internal stimuli are considered mind wandering. For example, deliberate retrieval from long term memory, or generating imagery as a part of a task, are not mind wandering. In contrast, daydreaming during a class lecture, zoning out while reading, or contemplating evening plans while driving home are all examples of mind wandering, or task-unrelated thought. The prevalence and pervasiveness of mind wandering makes it important to psychologists attempting to understand the processes that govern human thought and behavior. Previous research indicates that, on average, people spend 30-40% of their time in this mind-wandering state (Kane, Brown, et al., 2007; Klinger & Cox, 1987; Singer, 1975). Furthermore, mind wandering has been implicated in current-task performance deficits (e.g., McVay & Kane, 2009), including deficits in reading comprehension (e.g., Schooler, Reichle, & Halpern, 2004). The main goal of the current study was to investigate mind wandering as a mediator in the relationship between working memory capacity (WMC) and reading


comprehension. WMC, an individual-differences variable reflecting executive aspects of attention, predicts performance on a number of cognitive tasks ranging from simple attention restraint tasks (e.g., antisaccade; Stroop) to complex tasks (e.g., fluid reasoning; reading comprehension). The executive-attention view of WMC posits the control of attention as one important mechanism underlying performance on both WMC tasks and reading comprehension. Furthermore, I predicted that lapses of control over attention (i.e., mind wandering experiences) would be partially responsible for reading- comprehension deficits. That is, individuals with lower WMC have greater deficits in reading comprehension in part because they are unable to keep their thoughts on-task. Task-unrelated thoughts displace the task goal of comprehending the reading material and disrupt a person’s ability to process the relevant details of the text for comprehension. I will discuss the relevant literature on mind wandering, WMC, and their connection to reading comprehension before addressing the specific aims and predictions for the current study. How is mind wandering studied? The systematic exploration of mind wandering necessitates an objective method for measuring subjective experience. Many studies (e.g., Giambra, 1993; Greenwald & Harder, 1995; Tang & Singer, 1997) have used scales to measure general tendencies to daydream or frequencies of cognitive failures, such as the Imaginal Processes Inventory (Singer & Antrobus, 1970). These global self-report measures are interesting as individual-difference variables but they are not sufficient to isolate cognitive, task, and contextual variables affecting mind wandering in a particular situation. Furthermore,


global reports are subject to bias and inaccuracies as a result of their retrospective nature. In-the-moment reports of mind wandering allow researchers to explore the ostensible relationship between TUTs and ongoing task performance. In their seminal paper, Antrobus, Singer, and Greenberg (1966) asked subjects to indicate, at the end of each trial block of a vigilance task, whether they had experienced any mind wandering. This trial-by-trial assessment of TUTs provided a new tool—the “thought probe”—to the field. When probing subjects for thought content, task interruptions should be minimized to maintain the integrity of both the task and thought content. Unfortunately, some researchers have asked subjects to report the contents of their thoughts out loud at the probe signal, to be transcribed and coded later for relatedness to the ongoing task (Parks, Klinger, & Perlmutter, 1988-89; Smallwood, Obonsawin, & Reid, 2003; Smallwood, Obonsawin, Reid, & Heim, 2002; Smallwood, O’Connor, Sudberry, & Ballantyre, 2004; Teasdale, Lloyd, Proctor, & Baddeley, 1993; Teasdale et al., 1995). This method is problematic in two ways: it interrupts the flow of the task for too long and it forces subjects to verbalize an experience that may not be easily to put into words (Nisbett & Wilson, 1977; see also Ericsson & Simon, 1980). A mind-wandering episode may only contain images or incomplete thoughts, making it necessary for the subject to fill in details for coherence or even to refrain from reporting the thought at all. This type of “verbalization” probe often results in particularly low frequencies of mind wandering. In contrast, binary responses to probes, which ask subjects some form of the question “Are you mind wandering?”’ with a yes or no response choice (Antrobus, 1968; Antrobus, Coleman, & Singer, 1967; Antrobus et al., 1966; Antrobus, Singer, Goldstein,


& Fortgang, 1970; Giambra, 1995; Mason et al., 2007; McKiernan, D’Angelo, Kaufman, & Binder, 2006; Schooler et al., 2004; Shaw & Giambra,1993), do not interrupt the task for more than a few seconds (e.g., M = 1555 ms in McKiernan et al., 2006). The cost of using such binary responses, however, is that they do not allow for assessment of other types of cognitive interference during tasks, such as self-evaluative thoughts about task performance (sometimes called “task-related interference”; Smallwood & Schooler, 2006). A simple way around these costs is to use probes that allow subjects to indicate a category for their thought, (e.g., “everyday stuff” or “personal worries”; Giambra, Belongie, & Rosenberg, 1994-95; Giambra, Rosenberg, Kasper, Yee, & Sack, 1988-89; McVay & Kane, 2009; Smallwood, McSpadden, & Schooler, 2007). Such categorical probes do not interrupt the task for very long (e.g., M = 2300 ms in McVay & Kane, 2009) and provide more information about the subjective experience. In the current study, subjects were asked to categorize their thoughts at the time of the probe based on both task-relatedness and the temporal nature of the thought (past, present, future; e.g., Mason et al., 2007). Validity of Thought Reports The use of introspective self-report methods may raise concerns about validity of the measures. First, subjects may not respond honestly to probes if their thoughts are too complex, incomplete, or of a sensitive nature. One way to deal with this problem is to simplify the responses necessary to the probes (i.e., providing multiple-choice questions rather than asking for free descriptions of thoughts) so subjects do not feel pressure to reveal personal details or to generate coherent content from their thoughts. Second,


subjects may not recall the contents of their thoughts with clarity. To deal with this issue, researchers should avoid probes that rely heavily on retrospective memory, such as global assessments and questionnaires at the end of a task. Brief interruptions to the task that ask subjects to assess the immediate contents of their thoughts allow for an in-the-moment record of TUTs. Systematic variations in mind wandering frequency that co-occur with variation in theoretically-motivated task variables indicate that there is validity to self-reports of mind wandering. The frequency of mind wandering decreases with increased task complexity (Grodsky & Giambra, 1990; Teasdale et al., 1995), task difficulty (Antrobus et al., 1970; Filler & Giambra, 1973; McGuire, Paulesu, Frackowiak, Frith, 1996; McKiernan et al., 2006; Smallwood et al., 2003; Teasdale et al., 1993), and motivation for high performance (Antrobus et al., 1966); the frequency of mind wandering increases with time on task (Antrobus et al., 1967; Antrobus et al., 1966; McVay & Kane, 2009; McVay & Kane, in prep; Smallwood et al., 2004; Smallwood, 2002, Smallwood, Heim, Riby, & Davies, 2005; Teasdale et al., 1995) and alcohol consumption (Finnigan, Schulze, & Smallwood, 2007; Sayette, Reichle, & Schooler, 2009). As well, individual differences in the propensity to mind wander in the laboratory appear to be stable over time and reliable across a variety of tasks (Giambra, 1995; Grodsky & Giambra, 1990; McVay, Kane, & Kwapil, 2009). The relationship between subjective reports of mind wandering and objective task performance measurements also validate the introspective measure. For example, intra- individual variation in task reaction times is an objective indicator of attention fluctuation


that can be used to validate self-report measures. McVay and Kane (2009) found a relationship between the frequency of TUTs and variation in reaction times (r = .40) in a go/no-go, sustained attention task (i.e., SART). It is unlikely that subjects are monitoring and manipulating their overall reaction time variability throughout the task to somehow map onto their probe responses or vice versa. McVay and Kane (in prep) demonstrated a relationship between individuals’ longest RTs and their propensity to mind wander. The authors generated an individualized ex-Gaussian distribution (the normal curve with an exponential component) for the RTs of each subjects and isolated the τ parameter (the tail) to represent the degree to which an individual produced exceptionally long RTs (within their own distribution). Individuals with larger estimates of τ mind wandered more often than individuals who did not produce many long RTs (McVay & Kane, in prep). The authors use this finding to help explain the worst performance rule, whereby an individual’s longest reaction times are more predictive of their performance than their fastest or overall RTs, in terms of lapses of attention. An individual’s longest RTs may represent those trials on which the subject’s mind has wandered and thereby represent another example of the negative relationship between mind wandering and performance. Researchers are searching for additional objective markers of mind wandering, using eye tracking and other physiological measures in addition to observed behavior (Schooler & Smallwood, 2006). For example, Reichle, Reineberg, and Schooler (in press) presented eye-tracking data from reading that suggests that although participants continue to move their eyes in a forward motion across the page when they are mind wandering, they cease to make the specific saccades necessary for comprehension (e.g., making more


saccades to infrequent or less-predictable words in a sentence). Moreover, researchers have connected TUTs to activity in certain areas of the brain using neuroimaging technology (e.g., Riby, Smallwood, & Gunn, 2008). Neuroimaging studies have identified several regions of the brain implicated directly in mind wandering experiences, reinforcing the validity of subjective reports. These areas, labeled the “default mode network” (Raichle et al., 2001), generally show deactivations in activity when subjects shift from a rest state, a time period with no task to complete, to an attention-demanding or goal-driven activity. These deactivations are interpreted to mean that “something” is going on in the brain even when there is no explicit task to complete and that this “something” decreases when attention to a particular task is required. During “rest,” the mind is free to wander, whereas during a task, thoughts must be more constrained. Subjective experience, however, indicates that people do not stay fully tuned in to the task at hand (i.e., their mind wanders) and therefore it is important to look at the activity in these same areas in relation to the subjective experience of mind wandering (Mason et al., 2007; Mason, Bar, & Macrae, 2008; McGuire et al., 1996; McKiernan et al., 2006). Indeed, several fMRI studies have demonstrated the relationship between rate of TUTs (measured during the task) and changes in activity in the default mode network (Christoff, Gordon, Smallwood, Smith, & Schooler, 2009; Mason et al., 2007; Mason et al., 2008; McKiernan et al., 2006). Most recently, Christoff and colleagues (2009) directly connected in-the-moment thought reports during a scanning session with the fMRI data. Participants performed a go/no-go task with periodic thought probes while in


the fMRI scanner. The researchers measured default network activity in the time interval just prior to each thought probe. They observed greater recruitment of the default network for off-task thought reports than on-task thought reports, confirming the role of the default network in mind-wandering episodes. Another potential criticism of thought probes is that social desirability and thought monitoring might reactively change the frequency of mind-wandering episodes (or the frequency of their reporting). For example, Filler and Giambra (1973) predicted that the expectation of thought probes would increase estimates of mind wandering during a vigilance task. In the study, Filler and Giambra varied when subjects were first asked about mind-wandering experiences (i.e., after the first, second, or third block of the ongoing task). Contrary to predictions, TUT reports decreased when subjects knew earlier about the thought probes. The findings suggested, perhaps, that subjects’ awareness of their mind wandering in the first block caused them to exert more executive control during the second block. Alternatively, awareness of their mind wandering in the first block may have caused subjects to monitor for it in the second block, thereby interrupting normal mind-wandering production. Mind-wandering researchers, therefore, should take note of a possible underestimation of TUTs using the probe technique. Mind Wandering and Performance Errors Mind wandering has the obvious potential to interfere with ongoing task performance to varying degrees, depending on the task requirements. For example, whereas task-unrelated thought during a lecture is likely to impair learning of the material, the same type of thoughts during a drive would not necessarily affect


performance because driving is a largely automatic process. Psychologists are primarily interested in mind wandering during tasks that require focused attention, because errors caused by those mental lapses can range from the bothersome (e.g., brushing one’s teeth twice) to the catastrophic (e.g., crashing an airplane). The study of why mind wandering occurs, when it occurs, may shed light on the task and individual-difference variables necessary for optimal task performance. The ability to accomplish a non-automatic task or to fulfill a complex goal fundamentally depends on maintaining attention to that task or goal. Even the most skilled athlete does not expect to perform well if she “can’t keep her head in the game.” In fact, mind wandering has been connected to errors on many attention- demanding tasks. The relationship between mind wandering and errors takes two forms: Some studies report a correlation between individual differences in mind wandering rates and performance (McVay & Kane, 2009; Smallwood et al., 2004; Smallwood et al., 2003), whereas others report a within-subjects comparison showing a greater in-the- moment likelihood of an error in conjunction with the report of a TUT than a report of on-task thinking (McVay & Kane, 2009; Schooler et al., 2004; Smallwood et al., 2007). For example, overall recall memory for words is negatively related to TUT rates at study (r = -.25; Ellis, Moore, Varner, Ottaway, & Becker,1997) and subjects who reported one or more TUTs while learning words performed worse than no-TUT subjects on the subsequent memory test (Smallwood et al., 2003). McVay and Kane (2009) found that mind wandering predicts in-the-moment errors on a Sustained Attention to Response Task (SART; Manly, Robertson, Galloway,


& Hawkins, 1999; Robertson, Manly, Andrade, Baddeley, & Yiend, 1997). The SART is a go/no-go task in which stimuli are presented rapidly (250 ms; 900 ms mask) and subject are instructed to respond to all stimuli except infrequent (11%) randomly-occurring target trials that differ on some dimension. Previous work demonstrated that SART performance is related to both global measures of Cognitive Failures (CFQ; Robertson et al., 1997) and end-of-trial thought reports (Smallwood et al., 2004). McVay and Kane (2009) used a version of the SART with word stimuli and thought probes following randomly occurring target trials. Subjects committed more errors on target trials where they reported off-task thinking (M = .58) than when they were on-task (M = .38). The deterioration in performance over time on the SART task paralleled the increase in mind wandering over the same period. Individual differences in subjects’ overall accuracy also correlated negatively with their TUT rate (r = -.37). Variation in reaction time to the frequent non-target trials, an index of general fluctuations in attention, shared a relationship with TUTs in this task (r = .40). McVay and Kane (in prep) replicated these findings in the standard SART condition (r = -.30 for TUTs and accuracy; r = .25 for TUTs and RT variability). McVay and Kane (2009) used evidence from mind wandering in the SART to argue that conscious thought affects performance by interrupting maintenance of the task goal. This claim, if true, should apply to all tasks that require executive control to stay “on-task.” Although SART is a useful tool for testing this hypothesis in the lab, it is not a task that people encounter in their daily lives. Reading, on the other hand, is fundamental to learning and communication throughout the lifespan. Starting in the early years of


elementary school, textbooks are used to convey information to children; by teenage years, students are required to learn class material almost entirely through reading. Reading is also a task during which most people have had mind wandering experiences, where their eyes continue to move across the page although they are no longer processing the written material (Schooler et al., 2004). Furthermore, reading is usually an integrative task. Whereas SART errors occur on a trial-by-trial basis and do not necessarily affect future trials, missing information during reading can affect overall comprehension of the material. For example, if while reading a scientific article, a reader zones out during the operational definition of one of the variables, she may find it difficult to interpret the results. Mind Wandering and Reading Although mind wandering during reading is an experience common to most people, little work has addressed how off-task thoughts affect comprehension of reading material. Giambra and Grodsky (1989, 1990) measured mind wandering during reading and demonstrated a stable propensity to mind wander over vigilance and reading tasks (r = .51). They did not, however, report comprehension measures for the reading tasks and thus, did not demonstrate the effect of mind wandering on reading comprehension. Reichle et al. (submitted; originally presented in Schooler et al., 2004) presented data from the only studies looking directly at the relationship between the performance aspect of reading (i.e., comprehension) and mind wandering. They reported three studies in which subjects read a portion of Tolstoy’s War and Peace and completed a reading comprehension test. While reading the excerpt on the computer screen, subjects were


asked to monitor their mind wandering and report any occurrences by pressing a key (i.e., self- caught mind wandering reports). Some subjects were also probed every 2-4 minutes following either a self-reported mind wandering experience or the last probe. The proportion of probes on which subjects reported mind wandering predicted overall reading comprehension accuracy (r = -.51 in E1; r = -.25 in E2) indicating that more mind wandering predicted of worse comprehension accuracy. In Experiment 2, comprehension questions followed directly after each self-report or probe-caught mind wandering episode. Subjects who reported mind wandering (either self-reported or probe caught) performed worse on comprehension questions directly following the report (M accuracy = .59) than did unprobed control subjects (M = .80). One major limitation of the Reichle et al. study is that the authors’ focus on meta- awareness (i.e., monitoring the contents of conscious experience) affected their design for thought probes. The probes were contingent on self-reports of mind wandering in that they occurred 2-4 minutes after either the last self-caught report or the last probe. There were, therefore, different numbers of each type of mind wandering report for each subject. This makes the essential comparison of reading comprehension following on- task reports versus following off-task reports difficult. The authors’ comparison of accuracy during off-task reports with accuracy of unprobed subjects assumes that the unprobed subjects were not mind wandering and is contrary to the argument that most people mind wander at some point (if not many points) during reading. The current study used only experimenter-scheduled probes, which occurred at certain points in the text or at specific time intervals.


In a third experiment from the same series, Reichle et al. (submitted) compared mind wandering in a vigilance task to mind wandering in a reading task. One potential criticism of their first two experiments is that poor readers mind wander just because they are poor readers and not because task-irrelevant thoughts are actually causal in disrupting reading comprehension. Rather, poor readers mind wander because they are already reading poorly. A relationship between mind wandering in a vigilance task and reading comprehension would strengthen the claim that individual differences in the ability to maintain on-task thinking contributes to comprehension performance. However, while Reichle et al. (submitted) replicated the finding of Grodsky and Giambra (1990), that mind wandering reports in a vigilance task are related to mind wandering reports in reading (r = .36, self-caught reports only), they did not report the crucial relationship between mind wandering in the vigilance task and comprehension performance. Therefore, the current study will provide a more conclusive study of mind wandering and reading comprehension by linking mind wandering during a variety of tasks to reading comprehension. Mind Wandering and Executive Control Mind wandering is connected to errors in a variety of tasks, but why? Several researchers have suggested that mind wandering is related to executive function, although there are different views on how TUTs and executive function are related. Smallwood and Schooler (2006) posit that mind wandering requires executive resources, primarily on the basis of two studies by Teasdale and colleagues. Teasdale et al. (1993, 1995) found that subjects reported fewer TUTs during a task than while sitting quietly, during tasks


with greater versus lesser memory load, during tasks with faster versus slower stimulus presentation rate, and during more versus less practiced tasks. Finally, subjects were worse at generating random patterns of numbers (an executive function task; Teasdale et al., 1995) when they reported mind wandering than when they reported on-task thoughts (Teasdale et al., 1995). Smallwood and Schooler (2006) view these findings as evidence for resource sharing between the tasks and mind wandering (i.e., fewer resources are available for mind wandering when completing tasks with executive control demands). An alternative explanation for the Teasdale findings, however, is that the engagement of executive control in the above situations prevented mind wandering in order to facilitate task performance. Mind wandering, by this view, can be conceptualized as reflecting a lapse of executive control, rather than a process that requires executive resources (“control failures × concerns” view; McVay & Kane, 2009; in press). In fact, mind wandering may be the subjective experience of allowing automatically generated thoughts from a continuous stream of thoughts to enter consciousness in an uncontrolled manner. The shared brain areas active during “rest,” arguably an unconstrained time period, and mind wandering support this view. Mind wandering that affects performance, therefore, reflects a break in the restraints imposed on the train of thought in order to focus on the task. Our view is that a failure to control attention underlies the relationship between mind wandering and performance errors (McVay & Kane, 2009; in press). Mind wandering is the subjective experience that accompanies a failure to properly maintain task goals when successful performance relies on goal maintenance. TUTs increase with


time on task, suggesting that maintaining on-task thoughts may be subject to fatigue. Other types of control failures, such as expression of stereotype biases (Richeson & Trawalter, 2005), are also subject to fatigue (see also Muraven & Baumeister, 2000; Schmeichel, 2007). More importantly, the propensity to mind wander varies with individual differences in working memory capacity (WMC), a measure of attention control (Engle & Kane, 2004; Kane & Engle, 2003). The executive-attention view of WMC explains the relationship between WMC span tests and complex cognition, such as language comprehension and reading, through a domain-general attentional-control mechanism – that is, individual differences in the control of attention underlie performance on both WMC span tests and complex cognitive tasks (Engle & Kane, 2004; Kane & Engle, 2003). WMC is measured using complex span tasks requiring subjects to maintain access to items in memory while processing new incoming information. For example, the operation span (Ospan) requires subjects to verify the solution to compound math equations as the processing task. Interpolated with the math problems, subjects see a sequence of letters to learn for an immediate memory test. The reading span (Rspan) shares the same memory task with Ospan (remembering individual letters) but requires subjects to verify whether sentences make sense for the processing task. In addition to complex cognitive tasks like general fluid intelligence, language learning, and scholastic achievement (Engle, Tuholski, Laughlin, & Conway, 1999; Kane et al., 2004; Kane, Hambrick, & Conway, 2005), WMC predicts performance on low-level attention tasks involving minimal memory demands, such as the antisaccade task (Kane, Bleckley, Conway, & Engle, 2001; Unsworth, Scrock, & Engle, 2004). This


task requires subjects to resist attentional capture from a flashed stimulus to accurately attend to a target presented in the opposite field of vision. People with high WMC better resist the automatic pull of the flashing distracter stimulus than people with low WMC. Evidence from tasks like these (for review, see Kane, Conway, et al., 2007) suggests that WMC is closely linked to attentional control. According to Engle and Kane (2004; Kane, Conway, Hambrick, & Engle, 2007) there are two components of executive attention that are related to WMC: goal maintenance and competition resolution. Goal maintenance is sustaining access to task- relevant information in the face of interference from habit, distracters, or competing thoughts (i.e., mind wandering). Competition resolution deals with the interference associated with the particular trial stimulus. That is, even if the goal of the task is sufficiently maintained, there may still be variation in overcoming a stimulus-driven response on a trial-by-trial basis. The dual components of executive attention can also be discussed in terms of “proactive” and “reactive” processes (Braver, Gray, & Burgess, 2007). Proactive processes are initiated prior to the need for control and are sustained until the completion of the task. Reactive processes are initiated on an as-needed basis in response to the conflict on a trial. These two processes are strategically allocated based on the expected demands of the task (Botvinick, Braver, Barch, Carter, & Cohen, 2001; Braver et al., 2007; Brown & Braver, 2005). If the subject anticipates the need for top- down control in the task, goal maintenance processes will be initiated at the onset of stimuli and maintained throughout the task. Successful performance on many attention-


demanding tasks relies on both components of executive attention (for exceptions, see Kane, Poole, Tuholski, & Engle, 2006). Kane and Engle (2003) provided crucial evidence for the dual-component nature of executive attention. Using a Stroop paradigm, they manipulated the proportion of color-word congruency, such that in some cases the color words and hues matched most of the time and in other they were mostly incongruent. In a mostly incongruent version of the task, the goal of naming the color is reinforced on most trials because reading the word would lead to an incorrect response. In contrast, in a mostly congruent condition, the color naming goal is not reinforced and therefore must be endogenously maintained throughout the task. Two important span differences in the ability to maintain the task goal emerged in the mostly congruent Stroop task. High spans were more accurate than low spans on the infrequent incongruent trials, suggesting they were better maintaining the color naming goal without reinforcement. Furthermore, the low spans responded more quickly than high spans to the congruent trials, suggesting that low spans were reading the words (a faster, more habitual task) rather than naming the color on congruent trials (i.e., they were not maintaining access to the color-naming goal throughout the task). Variation in competition resolution, the second component of executive attention, should produce reaction time differences even in conditions where the goal is easily maintained (mostly incongruent condition). In fact, low spans were slower than high spans to respond accurately on incongruent Stroop trials suggesting that even when they were maintaining the color naming goal, they were having more difficulty resolving the stimulus-based conflict than high spans.

Full document contains 94 pages
Abstract: The primary goal of this study was to investigate the mediating role of mind wandering in the relationship between working memory capacity (WMC) and reading comprehension as predicted by the executive-attention theory of WMC (e.g., Kane & Engle, 2003). I used a latent-variable, structural-equation-model approach with three WMC span tasks, seven reading comprehension tasks, and three attention-restraint tasks. Mind wandering was assessed using experimenter-scheduled thought probes during four different tasks. The results support the executive-attention theory of WMC. Mind wandering is a significant mediator in the relationship between WMC and reading comprehension, suggesting that the relationship is driven, in part, by attention control over intruding thoughts. I discuss implications for theories of WMC, attention control, and reading comprehension.