mind wandering in learning

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Mind wandering and education: from the classroom to online learning

Karl k. szpunar.

1 Department of Psychology, Harvard University, Cambridge, MA, USA

Samuel T. Moulton

2 Harvard Initiative for Learning and Teaching, Harvard University, Cambridge, MA, USA

Daniel L. Schacter

In recent years, cognitive and educational psychologists have become interested in applying principles of cognitive psychology to education. Here, we discuss the importance of understanding the nature and occurrence of mind wandering in the context of classroom and online lectures. In reviewing the relevant literature, we begin by considering early studies that provide important clues about student attentiveness via dependent measures such as physical markers of inattention, note taking, and retention. We then provide a broad overview of studies that have directly measured mind wandering in the classroom and online learning environments. Finally, we conclude by discussing interventions that might be effective at curbing the occurrence of mind wandering in educational settings, and consider various avenues of future research that we believe can shed light on this well-known but little studied phenomenon.

During the past decade, there has been impressive growth in research concerning the cognitive and neural bases of mind wandering, including a rapid expansion of experimental procedures that have rendered the phenomenon tractable for experimental studies, a growing body of reliable findings, and a number of theoretical proposals aimed to account for the phenomena of interest (for reviews, see Smallwood and Schooler, 2006 ; Smallwood, 2013 ). During the same time period, there has been a similarly impressive increase in the application of findings and ideas from cognitive psychology to understanding learning and retention in educational contexts (for recent reviews, see Roediger and Karpicke, 2006 ; Bjork et al., 2013 ; Dunlosky et al., 2013 ). It seems clear that these two domains of research should be highly relevant to one another, because mind wandering and related attention failures are widely recognized to be common in the traditional classroom setting (e.g., Johnstone and Percival, 1976 ; Bligh, 2000 ; Bunce et al., 2010 ) as well as in online education (e.g., Koller, 2011 ; Khan, 2012 ). Perhaps surprisingly, there has been relatively little research linking the two domains; indeed, only a few years ago, Smallwood et al. ( 2007 ) characterized mind wandering as an “underrecognized” influence in educational settings and provided a useful discussion of experimental results and conceptual/theoretical considerations relevant to linking the two domains.

In the past couple of years, systematic research has begun to emerge that focuses on the incidence and nature of mind wandering in both traditional classrooms as well as online learning environments. The primary purpose of the present article is to provide a focused review and discussion of recent research, as well as some lesser known older studies that examine the occurrence and consequences of mind wandering during both classroom and online lectures. In addition, we consider possible interventions for reducing the occurrence of mind wandering in educational settings and conclude by discussing potentially fruitful directions for future research.

Mind wandering during classroom instruction

Within educational settings, the occurrence of mind wandering is perhaps most readily observable within the context of classroom instruction. Indeed, educators have long been concerned about the possible negative impact of mind wandering on student learning (Brown, 1927 ; Lloyd, 1968 ). It is important to note, however, that few studies have directly measured mind wandering in the classroom. Instead, early research made use of measures such as physical markers of inattention, note taking, and retention. Data emerging from these early studies revealed important clues about the nature of student attentiveness over extended periods of study that have helped to guide more recent research on mind wandering in the classroom. In this section, we review and evaluate the basic findings emerging from these early studies, discuss the possible relation of these findings to mind wandering, and highlight direct attempts to measure mind wandering in the classroom. In addition, we assess the influence of possible interventions for reducing the occurrence of student mind wandering.

Observational approaches

In what is often cited as a classic example of student attentiveness in the classroom, Johnstone and Percival ( 1976 ) asked observers to make note of physical signs of inattention, such as diversions in gaze, as students sat through chemistry lectures. The authors found that initial breaks in attention occurred after approximately 10–18 min of class time, and that the frequency of breaks in attention rose to a level of every 3–4 min toward the end of lectures. Indeed, the notion that student attentiveness decreases as a function of time spent in the classroom has strongly influenced research in this area. Nonetheless, it is important to note that physical markers of inattention should be interpreted cautiously (Wilson and Korn, 2007 ). For instance, students who have momentarily directed their gaze away from the lecturer may still be listening to the lecturer, and not necessarily mind wandering; conversely, a focused gaze does not necessarily indicate a focused mind. Importantly, recent studies have drawn stronger links between physical markers of inattention and mind wandering. For example, Smilek et al. ( 2010 ) recently assessed the relation of blinking to mind wandering during a reading task. In that study, students were asked to indicate whether or not they were paying attention to the text in response to a series of auditory tones. The authors found that blinking was more likely to precede moments of inattention than attention, and suggested that blinking might facilitate the decoupling of attention from the immediate environment during instances of mind wandering. Moving forward, additional research is needed to demonstrate how physical markers of inattention relate to the occurrence of mind wandering in the classroom (for relevant discussion, see Bligh, 2000 ; Rosengrant et al., 2011 ).

Note taking and retention

Various attempts have been made to circumscribe the difficulties associated with inferring student attentiveness via direct observation. For instance, some researchers have focused on note taking. Although note-taking behavior does not necessarily correlate with comprehension (e.g., McClendon, 1958 ), reductions in note taking over time may indicate inattention on the part of students. Unfortunately, the conclusions that can be drawn on the basis of relevant data are equivocal. For instance, Maddox and Hoole ( 1975 ) and Scerbo et al. ( 1992 ) examined the percentage of ideal notes (notes deemed important by the experimenter) that students recorded during lectures (for further discussion on research approaches to note taking, see Aiken et al., 1975 ). Maddox and Hoole ( 1975 ) found no decline in note taking across five 10-min intervals of a geography lecture—44, 54, 50, 52, and 55% of ideal notes. Conversely, Scerbo et al. ( 1992 ) observed a steep decline in note taking across three 12-min intervals of a psychology lecture—97, 67, and 50% of ideal notes (see also Hartley and Cameron, 1967 ; Locke, 1977 ). One possibility for this discrepancy may be related to factors such as student interest. For instance, students in the geography class (51%) took significantly fewer notes across the entire lecture than students in the psychology class (71%), and high levels of initial note taking may be necessary to observe subsequent declines over time. Moreover, additional studies are needed to demonstrate the extent to which inattention and declines in note taking co-occur. Along these lines, Lindquist and McLean ( 2011 ) recently demonstrated that frequent bouts of mind wandering—as measured by direct probes of attention—were associated with lower subjective ratings of note taking. Whether this observation extends beyond subjective reports of note taking to actual note taking behavior remains to be tested.

Alternatively, various researchers have looked to measures of retention as proxies for student attentiveness in the classroom. Specifically, if students are less likely to pay attention to the latter portion of a lecture, then information presented toward the end of the lecture should not be retained as well as information presented in earlier portions of the lecture. Again, the evidence is somewhat mixed. While some studies have found reduced memory for information presented at the end of lectures (Burns, 1985 ), others have not (Thomas, 1972 ; Scerbo et al., 1992 for additional discussion, see McLeish, 1968 ). One possibility for this unreliable pattern of data is that the critical test is commonly presented immediately after the lecture. This design feature may allow students to rehearse information from the final portion of the lecture until the test is administered (Glanzer and Kunitz, 1966 ). In order to more accurately assess what information students have integrated into their knowledge base, additional studies ensuring that students express their understanding of lecture content on the sole basis of long-term memory are needed. In addition to possible primacy and recency effects (e.g., Jersild, 1929 ; Ehrensberger, 1945 ), future studies might also consider the possible influence of other factors that might moderate attention over extended periods of time, such as the distinctiveness or relation of materials to one another across an entire lecture.

Although little is known about the relation of the occurrence of mind wandering and retention of lecture content, Lindquist and McLean ( 2011 ) showed that the frequency of mind wandering in response to direct probes of attention during one lecture was negatively correlated with retention of course material on an exam taken several weeks later. Moving forward, it will be important to more closely investigate the extent to which mind wandering accounts for both the immediate and long-term retention of specific materials from lectures.

Direct probes of attention and mind wandering

We now discuss in more detail studies that have used direct probes of student attention and mind wandering. These studies are important because they provide a more accurate depiction of the extent to which students are actually mind wandering in educational contexts. In one of the initial studies of this sort, Cameron and Giuntoli ( 1972 ) randomly interrupted college lectures with a bell and asked students various questions about the content of their conscious mind, including whether or not they were listening to the speaker, and, if so, whether their listening was “a superficial kind of listening accompanied by frequent distractions,” “a close following of the speaker's train of thought,” or a kind of listening in which they felt that they were “actively meeting the speaker's mind.” Depending on how one classifies students' responses, the results revealed that only between 40 and 46% of students were paying “good attention” to the lecturer or lecture content at any given moment. Using a similar method of consciousness sampling in undergraduate and graduate classrooms, Schoen ( 1970 ) estimated attention during lectures at only 67%, whereas attention during discussion was estimated at 75% (see also Geerligs, 1995 ) and attention during problem solving was at 83%.

Stuart and Rutherford ( 1978 ) asked medical students in twelve 50-min hematology lectures to indicate the extent to which they were paying attention using a 9-point scale (1 = not concentrating at all; 9 = maximum concentration). A buzzer that was audible to students sounded the attention probes at 5-min intervals. The authors found that students, on the whole, never indicated more than an “average level of concentration” throughout the lecture. Interestingly, the authors also found that student attention peaked around 10–15 min into the lecture, but that their attention waned considerably thereafter (see also, Johnstone and Percival, 1976 ; for possible alternative interpretations, see Wilson and Korn, 2007 ).

In a more recent study, Lindquist and McLean ( 2011 ) more directly assessed the occurrence of mind wandering during lectures. Specifically, the authors asked students in three 50-min psychology lectures to report on the occurrence of task unrelated thoughts in response to auditory attention probes that were sounded on five separate occasions—8, 15, 25, 34, and 40 min. Across the entire lecture, task unrelated thoughts were reported in response to ~33% of the attention probes. Moreover, the authors found that task unrelated thoughts were more likely to be reported at the end of the lecture (44%) than the beginning of the lecture (25%). As discussed earlier, Lindquist and McLean also demonstrated a negative impact of mind wandering on note taking and retention. We will revisit this important feature of the authors' data in the context of learning from online lectures, where researchers have greater control over study materials.

Other researchers have used experience sampling paradigms to estimate student attention in everyday life, and such results help contextualize the findings from classroom environments. Unsworth et al. ( 2012 ) asked students to record in a diary their attentional failures during everyday life, and found that the most frequent failures were distraction while studying and mind wandering in class; moreover, 76% of the reported lapses of attention—distraction, mind wandering, or absent-mindedness—occurred in classroom or study situations. Kane et al. ( 2007 ) asked undergraduates to report whether their minds were wandering at random times during the day. On the average, students' minds were wandering 30% of the time (see also, Hurlburt, 1979 ). Furthermore, mind wandering increased when students reported they were tired, stressed, and in boring or unpleasant activities. McVay et al. ( 2009 ) measured mind wandering in the everyday lives of college students, who similarly reported mind wandering on 30% of the samples. Here again, mind wandering was more frequent when students reported feeling tired or anxious, or when they rated the current activity as stressful or boring. Interestingly, mind wandering was also less frequent when participants reported being happy (see also, Killingsworth and Gilbert, 2010 ), good at the current activity (see also Moneta and Csikszentmihalyi, 1996 ), liking the current activity, or rating it as important.

It is important to note that assessments of mind wandering in different contexts are complicated in several important ways. For instance, educational activities such as sitting through a lecture and studying for an exam typically require sustained attentional focus, whereas non-educational everyday activities such as eating breakfast or checking the mail do not necessarily require an individual's undivided attention. Moreover, the consequences of mind wandering also depend on context: The cost of attentional failures during the attention-demanding tasks of education are almost certainly greater than the cost of attentional failures during highly rehearsed, largely automatic tasks of everyday life. As a result, mental experiences such as thinking about a recent or upcoming personal experience may be classified as mind wandering in one context but not the other, and may impact performance in one context but not the other.

In sum, studies making use of direct measures of student attention in educational settings have demonstrated that students frequently report lapses of attention and mind wandering in the classroom, mind wandering appears to increase as a function of time spent in class, and mind wandering may be especially prevalent in educational, as compared to non-educational, settings. Taken together, studies of student mind wandering in the classroom highlight the need for evidence-based research that considers the manner in which classroom instruction is structured, and what interventions might be effective for holding student interest and attention.

Classroom interventions

Educational guidelines commonly urge teachers to intersperse their lectures with tasks that can help to re-focus student attention (e.g., Myers and Jones, 1993 ; Middendorf and Kalish, 1996 ; see also, Olmsted, 1999 ). Unfortunately, only a few attempts have been made to test the effectiveness of such techniques, and the data are often difficult to interpret.

For instance, Burke and Ray ( 2008 ) tested the efficacy of four active learning interventions (student-generated questions, guided reciprocal peer questioning, truth statements, and think-pair-share) across four instructional theory lectures. Each lecture was devoted to testing one of the four interventions, with the intervention occurring halfway through lecture. During each lecture, students were asked to rate their concentration levels on five separate occasions using a 4-point rating scale (1 = not concentrating at all; 4 = fully concentrating), including once at the start of class and once after the intervention. Although the authors demonstrated enhanced levels of concentration following some interventions (student-generated questions) and not others (truth statements), there was no baseline condition against which these effects could be evaluated. Additionally, the order in which students encountered the interventions was not counterbalanced (see also, Young et al., 2009 ). As a result, it is difficult to know for certain how effective the various interventions were in focusing the attention of students.

More recently, Bunce et al. ( 2010 ) asked students in three 50-min chemistry lectures to use clicker technology to indicate whenever their attention to lecture content had been drawn away by various distractions (e.g., texting, completing homework from other courses). In addition, the authors noted various pedagogical techniques used by the instructors of these lectures (e.g., lecturing, quizzing, demonstrations). Although the implementation of the pedagogical techniques was not experimentally manipulated, the authors found that bouts of distraction during lectures were reduced following quizzes and demonstrations. It is also important to note that attentiveness to lecture content was measured via self-reports of distraction that are potentially limited because students are often unaware that they are mind wandering (Smallwood and Schooler, 2006 ; but see recent neuroimaging data suggesting common neural correlates for subjective and objective reports of mind wandering; Smallwood et al., 2008 ). Nonetheless, the results of this study are informative, and additional studies that carefully manipulate that frequency and timing of active learning interventions in the classroom, and that assess distraction and mind wandering in a more direct or objective manner, will be of considerable importance.

Next, we delve into the world of online education, and consider the limitations that mind wandering places on effective learning of lecture videos. As discussed below, the advent of online learning is of great interest in its own right in light of its recent prominence on the educational scene. Moreover, using online lectures as target materials has made it possible to study the occurrence of mind wandering during lectures, and explore possible interventions for reducing mind wandering, with tighter experimental control than is typically available in the classroom.

Mind wandering during online lectures

The studies discussed in the preceding section indicate that mind wandering occurs frequently in the classroom and while studying. As noted earlier, in recent years there has been rapidly growing interest in online education. While online education has existed in some form for nearly as long as the Internet has been around, the emergence of such online platforms as Coursera and edX, which are composed of leading research universities, has led to a dramatic increase in the number of students participating in the entity known as a MOOC or massive open online course. The primary form of instruction in a MOOC is a videorecorded lecture delivered online. Given the frequent occurrence of mind wandering in the traditional classroom, an important question concerns whether mind wandering occurs to a similar, greater, or lesser extent in online settings. While there is very little systematic research on the topic, relevant data have been provided by two recent studies in which participants viewed videorecorded classroom lectures that to some degree resemble those used in online courses. Importantly, by mimicking the online experience in the laboratory, researchers have been able to bring the lecture learning experience, measures of the occurrence of mind wandering during lectures, and tests of possible interventions to ward off mind wandering during lectures under greater experimental control.

Risko et al. ( 2012 ) reported two experiments in which students watched videorecorded lectures—alone in Experiment 1, and with other students in a classroom setting in Experiment 2. Risko and colleagues showed participants one of three 1-h lectures on different topics (psychology, economics, or classics). In Experiment 1, 60 undergraduates watched the lectures and were probed at four different times into a lecture—5, 25, 40, and 55 min. During each probe, students were asked if they were mind wandering at that moment. Overall, participants indicated that they were wandering in response to 43% of the probes, with significantly more mind wandering observed in response to the two probes given during the second half of the lecture (52%) than to those given during the first half (35%). The increase in mind wandering across the lecture was associated with poorer performance on a test of lecture material given shortly after the lecture: students responded correctly to 57% of questions concerning the second half of the lecture, compared with 71% correct responses to questions concerning the first half of the lecture. Further, there was a significant negative correlation between test performance and mind wandering ( r = −0.32): individuals who performed more poorly on the test reported more mind wandering. Experiment 2 yielded a highly similar pattern of results: students reported mind wandering in response to 39% of probes, reports of mind wandering increased significantly from the first half of the lecture (30%) to the second (49%), and mind wandering during the second half of the lecture was associated with significantly poorer test performance compared with the first half of the lecture (for similar results, see Risko et al., 2013 ).

The incidence of mind wandering during videorecorded lectures was notably high—at least as high as the rate of mind wandering during classroom lectures reported by Lindquist and McLean ( 2011 ). One possible contributing factor is the 1-h length of the videorecorded lectures used by Risko et al. ( 2012 ). Some advocates of online education, such as Salman Khan, founder of the highly successful Khan Academy, and Daphne Koller, co-founder of Coursera at Stanford University, have argued that online lectures should be brief—as short as 10 min—in part because of concerns raised by earlier studies of classroom lectures, as discussed above, showing that individuals cannot sustain attention for longer periods of time (Koller, 2011 ; Khan, 2012 ; for possible limitations associated with this view, see Wilson and Korn, 2007 ). Thus, it is possible that mind wandering would occur much less often during videorecorded lectures that are considerably shorter than the 1-h lectures used in the Risko et al. ( 2012 ) study.

Szpunar et al. ( 2013 ) addressed this issue in a study that used a 21-min videorecorded lecture. This study also examined the critical and as yet unaddressed question of whether it is possible to reduce mind wandering during an online lecture. Szpunar et al. ( 2013 ) addressed the question by interpolating brief tests within the lecture. Previous research using materials such as word lists, face-name pairs, and prose passages has shown that interpolating brief tests at regular intervals between lists of stimuli can help to improve retention of materials from the end of extended study sequences (see Szpunar et al., 2008 ; Weinstein et al., 2011 ; Wissman et al., 2011 ).

Szpunar et al. ( 2013 ) reported two experiments in which participants watched a 21-min videorecorded statistics lecture (results of the two experiments were very similar; here we focus on Experiment 2). The lecture was divided into four segments of equal length. Prior to the lecture, all participants were instructed that they might or might not be tested after each segment, and that they would also receive a final test at the conclusion of the lecture. Participants were encouraged to take notes during the lecture. After each lecture segment, all participants completed arithmetic problems unrelated to the lecture for about a minute. However, there were three different groups, which were defined by what the participants did next: the tested group received brief tests on each segment that took about 2 min each; the non-tested group did not receive a test until after the final segment, and continued to work on arithmetic problems for an additional 2 min for each of the segments preceding the final segment; and the re-study group did not receive a test until after the final segment, and was shown, but not tested on, the same material as the tested group for 2 min for each of the segments preceding the final segment. At random times during the lectures, participants in all groups were probed about whether they were paying attention to the lecture or mind wandering off to other topics.

Participants in the non-tested and re-study groups indicated that they were mind wandering in response to about 40% of the probes, but the incidence of mind wandering was cut in to half, to about 20%, in the tested group. Moreover, participants in the tested group took significantly more notes during the lectures (three times as many), and retained significantly more information from the final segment of the lecture, than did than participants in the other two groups, who performed similarly. Participants in the tested group were also less anxious about a final test that followed the lecture and performed significantly better on that final test than those in the other groups. These results indicate that part of the value of testing comes from encouraging people to sustain attention to a lecture in a way that discourages task-irrelevant activities such as mind wandering and encourages task-relevant activities such as note taking.

Taken together, the results of the studies by Risko et al. ( 2012 , 2013 ) and Szpunar et al. ( 2013 ) suggest that mind wandering occurs frequently during the viewing of online lectures regardless of lecture length: both studies found evidence of mind wandering in response to about 40% of probes in non-tested conditions, even though the lectures used by Risko et al. were three times as long as those used by Szpunar et al. We think that these estimates of mind wandering are probably conservative when one considers the conditions that characterize online learning in everyday life: many students may view online lectures under conditions conducive to mind wandering and distraction, such as at home or in dorm rooms that are full of potentially attention-diverting material such as friends, television, Facebook, e-mail, and the like (for further discussion, see Risko et al., 2013 ).

It is encouraging that interpolated testing can dramatically reduce the incidence of mind wandering, and increase the incidence of task-relevant activities such as note taking. Such findings provide some confirmation for those practitioners of online learning who are already incorporating interpolated testing into their online lectures. Nonetheless, the results reported by Szpunar et al. ( 2013 ) must be treated with some caution, both because they were obtained only with a single lecture on a single topic (i.e., statistics), hence raising the question of whether the beneficial effects of testing can be observed across lectures on a variety of topics, and also because it is unclear whether the benefits of testing will persist across multiple lectures. For example, it is possible that students become less responsive to interpolated testing as an online course goes on (Dyson, 2008 ). Given the paucity of data available concerning processes and variables that affect learning from online lectures, these and related questions will be important to address in future studies.

Concluding comments

In sum, early research using proxies of student attention such as physical manifestations of inattentiveness, note taking, and retention, along with more recent studies that more directly probe for instances of mind wandering, highlight the prevalence of attentional lapses and mind wandering in the classroom and during online learning. To some extent, student mind wandering reflects a larger reality of human mental life: just as our minds wander frequently in everyday life, they also wander frequently in educational settings. But mind wandering is particularly relevant to education for two reasons. First, on theoretical and empirical grounds, there is good reason to think that mind wandering is particularly prevalent in educational settings. Online or in the classroom, instruction and studying demand unusually sustained periods of student attention in the presence of unusually salient distractors. In everyday life, one is not typically expected to listen attentively to an hour-long presentation twice a day in a large room full of one's peers, or read large amounts of challenging literature on one's own time instead of socializing or browsing the internet. The attentional demands of lecturing or studying differ from the attentional demands of commuting, cooking, or conversing with colleagues. And as the studies we have summarized (e.g., Unsworth et al., 2012 ) suggest, mind wandering does seem to occur more frequently during instruction and studying than other activities.

Secondly, mind wandering is particularly relevant to education because learning depends critically on attention in ways that other activities do not. Indeed, engaging student attention is often considered an essential feature of education. In a recent survey of nearly 200 Harvard faculty (Advancing the science, 2013), they were asked to complete the following sentence: “For me, an essential of good learning or teaching is _________.” By far, the most common response was “engagement,” and we suspect students, teachers, and educators of all stripes would agree about the central importance of student engagement. Learning experiences—whether they occur in the classroom, library, dining hall, or online—are intended to engage student attention. And for good reason: If a student does not attend consciously to instruction due to an episode of mind wandering, then that student's learning is surely diminished, both for the content not initially encoded and any subsequent content that depends on this initial learning. Thus, because learning is the goal of instruction and studying—and because learning depends on attention—mind wandering presents a particular challenge to education.

What can students or instructors do to reduce unwanted mind wandering during instruction? As we outlined above, there is some preliminary evidence that interspersing periods of instruction with low-stakes quizzing can promote student attention. We also noted earlier that instructors are commonly encouraged to mix up the content of their lectures (Middendorf and Kalish, 1996 ). In fact, cognitive psychologists have demonstrated that interleaving the presentation of various interrelated topics as opposed to dealing with each one in turn can help students to avoid confusing related concepts (e.g., Rohrer, 2012 ). Whether these approaches are effective because frequent changes of topic or brief exposures to any single topic—as compared to prolonged exposure to a single topic—help to sustain students' attention remains an open question for future research. Indeed, education researchers and psychologists have not satisfactorily explored how pedagogy affects mind wandering. To give another example, a considerable amount of research has demonstrated that spacing study over multiple learning sessions as opposed to massing (or cramming) study into a single learning session is a more effective means of ensuring long-term retention of classroom materials (Cepeda et al., 2006 ; Pashler et al., 2007 ; Dunlosky et al., 2013 ) One interesting question for future research may be to examine the extent to which spaced, as compared to massed, study sessions are resistant to bouts of mind wandering and inattention. Given the relative ease of thought sampling methodology and relative importance of student attentiveness, we encourage researchers to expand the empirical literature.

To better understand the causes of and countermeasures against student mind wandering, it is perhaps worthwhile to consider contrasting scenarios. First, how does the experience of attending a lecture differ from the experience of attending other events as an audience member? Indeed, students face attentional requirements during instruction very similar to those of other audiences who passively watch extended presentations. In attending a lecture instead of a movie screening, musical performance, or theatrical performance, however, many of the situational interventions designed to avoid distraction are absent: smartphones and laptop use is allowed (or even encouraged) not banned, lighting is flat instead of focused, the audience whispers, enters, or exits with relative freedom, the stage is bare instead of carefully designed, the presented visuals are often textual, static, or basic instead of graphic, dynamic, and complex, and the audio narration is more likely to be monotonous than lively. For these reasons and others, the conscious experience of watching a 2-h movie is likely very different from that of attending a 2-h lecture.

Other experiments, imagined or real, might be equally revealing. For example, why does the conscious experience of a lecturer differ so greatly from those of the lectured? While students listening to a lecturer wander in their thoughts about a third of the time, the lecturer is typically able to maintain her attention during the same time period and in the same physical space. Why does this simple shift of perspective make such a difference? Might it be the distinction between activity and passivity (e.g., active engagement via intermittent quizzing seems to help), or the asymmetry of the social dynamics between student and instructor? Indeed, recent studies of online learning suggest that asking students to take the perspective of the instructor and teach concepts to virtual students helps to improve retention of course content (Chase et al., 2009 ). Furthermore, perhaps the dramatically different perspective between the lecturer and the lectured furthers the problem of student mind wandering: If the lecture is extremely engaging for the lecturer but less so for students, then this difference of perspective might discourage lecturers from better designing instruction to engage student attention.

Finally, although we have focused considerable attention on the possible pitfalls of mind wandering during classroom and online learning, there also exists the possibility that mind wandering may in some instances benefit the learner. For instance, Baird et al. ( 2012 ) recently demonstrated that the occurrence of mind wandering during a period of incubation was positively correlated with the ability of students to generate solutions to problems designed to test creativity. Under what circumstances might mind wandering benefit classroom or online learning? Do individual differences in the characteristics of mind wandering episodes or propensity to engage in mind wandering predict whether mind wandering might help or hinder learning? Studies designed to answer these and similar questions might not only result in concrete recommendations to students and instruction, but might also uncover new insights into mind wandering, attention, and psychology.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

• Advancing the science of art, teaching. (2013). Available online at: http://harvardmagazine.com/2013/05/harvard-learning-and-teaching-innovations
• Aiken E. G., Thomas G. S., Shennum W. A. (1975). Memory for a lecture: effects of notes, lecture rate, and information density . J. Educ. Psychol . 67 , 439–444 10.1037/h0076613 [ CrossRef ] [ Google Scholar ]
• Baird B., Smallwood J., Mrazek M. D., Kam J. W. Y., Franklin M. S., Schooler J. W. (2012). Inspired by distraction: mind wandering facilitates creative incubation . Psychol. Sci . 23 , 1117–1122 10.1177/0956797612446024 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bjork R. A., Dunlosky J., Kornell N. (2013). Self-regulated learning: beliefs, techniques, and illusions . Annu. Rev. Psychol . 64 , 417–444 10.1146/annurev-psych-113011-143823 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bligh D. (2000). What's the Use of Lectures? San Francisco, CA: Jossey-Bass [ Google Scholar ]
• Brown G. L. (1927). A cause of mind wandering and inferior scholarship . J. Educ. Res . 15 , 276–279 [ Google Scholar ]
• Bunce D. M., Flens E. A., Neiles K. Y. (2010). How long can students pay attention in class? A study of student attention decline using clickers . J. Chem. Educ . 87 , 1438–1443 10.1021/ed100409p [ CrossRef ] [ Google Scholar ]
• Burke L. A., Ray R. (2008). Re-setting the concentration levels of students in higher education: an exploratory study . Teach. Higher Educ . 13 , 571–582 10.1080/13562510802334905 [ CrossRef ] [ Google Scholar ]
• Burns R. A. (1985). Information impact and factors affecting recall , in Presented at Annual National Conference on Teaching Excellence and Conference of Administrators. ERIC Document Reproduction Service No. ED 258 639 , (Austin, TX: ). [ Google Scholar ]
• Cameron P., Giuntoli D. (1972). Consciousness sampling in the college classroom or is anybody listening? Intellect 101 , 63–64 [ Google Scholar ]
• Cepeda N. J., Pashler H., Vul E., Wixted J. T., Rohrer D. (2006). Distributed practice in verbal recall tasks: a review and quantitative synthesis . Psychol. Bull . 132 , 354–380 10.1037/0033-2909.132.3.354 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Chase C. C., Chin D. B., Oppezzo M. A., Schwartz D. L. (2009). Teachable agents and the protégé effect: increasing the effort towards learning . J. Sci. Educ. Technol . 18 , 334–352 10.1007/s10956-009-9180-4 [ CrossRef ] [ Google Scholar ]
• Dunlosky J., Rawson K. A., Marsh E. J., Nathan M. J., Willingham D. T. (2013). Improving students' learning with effective learning techniques: promising directions from cognitive and educational psychology . Psychol. Sci. Public Interest 14 , 4–58 10.1177/1529100612453266 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Dyson B. J. (2008). Assessing small-scale interventions in large-scale teaching: a general methodology and preliminary data . Active Learn. Higher Educ . 9 , 265–282 10.1177/1469787408095856 [ CrossRef ] [ Google Scholar ]
• Ehrensberger R. (1945). An experimental study of the relative effectiveness of certain forms of public speaking . Speech Monogr . 12 , 94–111 10.1080/03637754509390108 [ CrossRef ] [ Google Scholar ]
• Geerligs T. (1995). Students' thoughts during problem-based small-group discussions . Instr. Sci . 22 , 269–278 10.1007/BF00891780 [ CrossRef ] [ Google Scholar ]
• Glanzer M., Kunitz A. R. (1966). Two storage mechanism in free recall . J. Verbal Learn. Verbal Behav . 5 , 351–360 10.1016/S0022-5371(66)80044-0 [ CrossRef ] [ Google Scholar ]
• Hartley J., Cameron A. (1967). Some observations on the efficiency of lecturing . Educ. Rev . 20 , 30–37 10.1080/0013191670200103 [ CrossRef ] [ Google Scholar ]
• Hurlburt R. T. (1979). Random sampling of cognitions and behavior . J. Res. Pers . 13 , 103–111 10.1016/0092-6566(79)90045-X [ CrossRef ] [ Google Scholar ]
• Jersild A. (1929). Primacy, recency, frequency, and vividness . J. Exp. Psychol . 12 , 58–70 10.1037/h0072414 [ CrossRef ] [ Google Scholar ]
• Johnstone A. H., Percival F. (1976). Attention breaks in lectures . Educ. Chem . 13 , 49–50 [ Google Scholar ]
• Kane M. J., Brown L. H., McVay J. C., Silvia P. J., Myin-Germeys I., Kwapli T. R. (2007). For whom the mind wanders, and when: an experience-sampling study of working memory and executive control in daily life . Psychol. Sci . 7 , 614–621 10.1111/j.1467-9280.2007.01948.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Khan S. (2012). The One World School House: Education Reimagined . London: Hodder and Stoughton [ Google Scholar ]
• Killingsworth M. A., Gilbert D. T. (2010). A wandering mind is an unhappy mind . Science 330 , 932 10.1126/science.1192439 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Koller D. (2011). Death Knell for the Lecture: Technology as a Passport to Personalized Education . Avialable online at: http://www.nytimes.com/2011/12/06/science/daphne-koller-technology-as-a-passport-to-personalized-education.html?pagewanted=alland_r=0
• Lindquist S. I., McLean J. P. (2011). Daydreaming and its correlates in an educational environment . Learn. Individ. Dif . 21 , 158–167 10.1016/j.lindif.2010.12.006 [ CrossRef ] [ Google Scholar ]
• Lloyd D. H. (1968). A concept of improvement of learning response in the taught lesson . Vis. Educ . October, 23–25 [ Google Scholar ]
• Locke E. A. (1977). An empirical study of lecture note taking among college students . J. Educ. Res . 77 , 93–99 [ Google Scholar ]
• Maddox H., Hoole E. (1975). Performance decrement in the lecture . Educ. Rev . 28 , 17–30 10.1080/0013191750280102 [ CrossRef ] [ Google Scholar ]
• McClendon P. I. (1958). An experimental study of the relationship between the note-taking practice and listening comprehension of college freshmen during expository lectures . Speech Monogr . 25 , 222–228 10.1080/03637755809375236 [ CrossRef ] [ Google Scholar ]
• McLeish J. (1968). The Lecture Method. Cambridge Monographs on Teaching Methods (No. 1) . Cambridge: Cambridge Institute of Education [ Google Scholar ]
• McVay J. C., Kane M. J., Kwapli T. R. (2009). Tracking the train of thought from the laboratory into everyday life: an experience-sampling study of mind wandering across controlled and ecological contexts . Psychon. Bull. Rev . 16 , 857–863 10.3758/PBR.16.5.857 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Middendorf J., Kalish A. (1996). The “change-up” in lectures . Natl. Teach. Learn. Forum 5 , 1–12 [ Google Scholar ]
• Moneta G. B., Csikszentmihalyi M. (1996). The effect of perceived challenges and skills on the quality of subjective experience . J. Pers . 64 , 275–310 10.1111/j.1467-6494.1996.tb00512.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Myers C., Jones T. (1993). Promoting Active Learning: Strategies for the College Classroom . San Francisco, CA: Jossey-Bass [ Google Scholar ]
• Olmsted J. A. (1999). The mid-lecture break: when less is more . J. Chem. Educ . 76 , 525–527 10.1021/ed076p525 [ CrossRef ] [ Google Scholar ]
• Pashler H., Bain P., Bottge B., Graesser A., Koedinger K., McDaniel M., et al. (2007). Organizing Instruction and Study to Improve Student Learning (NCER 2007–2004) . Washington, DC: National Center for Education Research, Institute of Education Sciences, U.S. Department of Education [ Google Scholar ]
• Risko E. F., Anderson N., Sarwal A., Engelhardt M., Kingstone A. (2012). Everyday attention: variation in mind wandering and memory in a lecture . Appl. Cogn. Psychol . 26 , 234–242 10.1002/acp.1814 [ CrossRef ] [ Google Scholar ]
• Risko E. F., Buchanan D., Medimorec S., Kingstone A. (2013). Every attention: mind wandering and computer use during lectures . Comput. Educ . 26 , 234–242 10.1037/acp.1814 [ CrossRef ] [ Google Scholar ]
• Roediger H. L., Karpicke J. D. (2006). The power of testing memory: basic research and implications for educational practice . Perspect. Psychol. Sci . 1 , 181–210 10.1111/j.1745-6916.2006.00012.x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Rohrer D. (2012). Interleaving helps students to distinguish among similar concepts . Educ. Psychol. Rev . 24 , 355–367 10.1007/s10648-012-9201-3 [ CrossRef ] [ Google Scholar ]
• Rosengrant D., Hearrington D., Alvarado K., Keeble D. (2011). Following student gaze patterns in physical science lectures . AIP Conf. Proc . 1413 , 323–326 [ Google Scholar ]
• Scerbo M. W., Warm J. S., Dember W. N., Grasha A. F. (1992). The role of time and cuing in a college lecture . Contemp. Educ. Psychol . 17 , 312–328 10.1016/0361-476X(92)90070-F [ CrossRef ] [ Google Scholar ]
• Schoen J. R. (1970). Use of consciousness sampling to study teaching methods . J. Educ. Res . 63 , 387–390 [ Google Scholar ]
• Smallwood J. (2013). Distinguishing how from why the mind wanders: a process-occurrence framework for self-generated mental activity . Psychol. Bull . 139 , 519–535 10.1037/a0030010 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Smallwood J., Beach E., Schooler J. W., Handy T. C. (2008). Going AWOL in the brain: mind wandering reduces cortical analysis of external events . J. Cogn. Neurosci . 20 , 458–469 10.1162/jocn.2008.20037 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Smallwood J., Fishman D. J., Schooler J. W. (2007). Counting the cost of an absent mind: mind wandering as an underrecognized influence of educational performance . Psychon. Bull. Rev . 14 , 230–236 10.3758/BF03194057 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Smallwood J., Schooler J. W. (2006). The restless mind . Psychol. Bull . 132 , 946–958 10.1037/0033-2909.132.6.946 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Smilek D., Carriere J. S. A., Cheyne J. A. (2010). Out of mind, out of sight: eye blinking as indicator and embodiment of mind wandering . Psychol. Sci . 21 , 786–789 10.1177/0956797610368063 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Stuart J., Rutherford R. J. D. (1978). Medical student concentration during lectures . Lancet 312 , 514–516 10.1016/S0140-6736(78)92233-X [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Szpunar K. K., Khan N. Y., Schacter D. L. (2013). Interpolated memory tests reduce mind wandering and improve learning of online lectures . Proc. Natl. Acad. Sci. U.S.A . 110 , 6313–6317 10.1073/pnas.1221764110 [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Szpunar K. K., McDermott K. B., Roediger H. L. (2008). Testing during study insulates against the buildup of proactive interference . J. Exp. Psychol. Learn. Mem. Cogn . 34 , 1392–1399 10.1037/a0013082 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Thomas E. J. (1972). The variation of memory with time for information during a lecture . Stud. Adult Educ . 4 , 57–62 [ Google Scholar ]
• Unsworth N., McMillan B. D., Brewer G. A., Spillers G. J. (2012). Everyday attention failures: an individual differences investigation . J. Exp. Psychol. Learn. Mem. Cogn . 38 , 1765–1772 10.1037/a0028075 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Weinstein Y., McDermott K. B., Szpunar K. K. (2011). Testing protects against proactive interference in face-name learning . Psychon. Bull. Rev . 18 , 518–523 10.3758/s13423-011-0085-x [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Wilson K., Korn J. H. (2007). Attention during lectures: beyond ten minutes . Teach. Psychol . 34 , 85–89 10.1080/00986280701291291 [ CrossRef ] [ Google Scholar ]
• Wissman K. T., Rawson K. A., Pyc M. A. (2011). The interim test effect: testing prior material can facilitate the learning of new material . Psychon. Bull. Rev . 18 , 1140–1147 10.3758/s13423-011-0140-7 [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Young M. S., Robinson S., Alberts P. (2009). Students pay attention!: combating the vigilance decrement to improve learning during lectures . Act. Learn. Higher Educ . 10 , 41–55 10.1177/1469787408100194 [ CrossRef ] [ Google Scholar ]

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Review article, benefits of mind wandering for learning in school through its positive effects on creativity.

• Educational Psychology, Department of Psychology, Faculty of Human Sciences, University of Potsdam, Potsdam, Germany

There is broad agreement among researchers to view mind wandering as an obstacle to learning because it draws attention away from learning tasks. Accordingly, empirical findings revealed negative correlations between the frequency of mind wandering during learning and various kinds of learning outcomes (e.g., text retention). However, a few studies have indicated positive effects of mind wandering on creativity in real-world learning environments. The present article reviews these studies and highlights potential benefits of mind wandering for learning mediated through creative processes. Furthermore, we propose various ways to promote useful mind wandering and, at the same time, minimize its negative impact on learning.

Introduction

Mind Wandering (MW) is commonly conceived as a loss of mental focus on a given primary activity in favor of thoughts that are unrelated to this activity ( Smallwood and Schooler, 2006 ; Smallwood and Schooler, 2015 ). For example, while reading a book for school, one may start to think about some event in the past or ruminate about a current problem. This definition implies that shifting one’s mental focus to something other than the current task is likely to be detrimental for task performance. Indeed, a large number of studies have shown reduced task performance due to MW in various domains of cognitive functioning (e.g., Smallwood et al., 2006 ; McVay and Kane, 2009 ; Galéra et al., 2012 ; Unsworth et al., 2012 ; Stawarczyk and D’Argembeau, 2016 ). The range of related observations spans from lower reaction times and more errors in in laboratory tasks, to weaker performance in everyday activities such as safely driving a car in a concentrated manner ( Galéra et al., 2012 ) or actively engaging in a conversation without being distracted ( Unsworth et al., 2012 ). Most relevant to this article is the observation that particularly performance in educational contexts seems to be negatively associated with the occurrence of MW (e.g., Dixon and Bortolussi, 2013 ). For example, several studies found negative effects of MW on text comprehension in university students (e.g., Lindquist and McLean, 2011 ; Risko et al., 2012 ; Unsworth and McMillan, 2013 ; Wammes et al., 2016 ; Soemer and Schiefele, 2019 , 2020 ) as well as secondary school students (e.g., Soemer et al., 2019 ). Likewise, MW has been found to affect learning during lectures ( Hollis and Was, 2016 ; Kane et al., 2021 ).

Despite these negative effects of MW on learning, several other studies have found positive effects of MW on learning-related constructs, in particular on creativity (e.g., Baird et al., 2012 ; Agnoli et al., 2018 ). Since creativity is commonly considered as beneficial for learning (e.g., Dollinger, 2011 ; Lee et al., 2014 ; Leopold et al., 2019 ), previous research linking MW to reduced task performance might indeed miss potentially useful aspects of MW for learning that are mediated through creative processes. Thus, in the following, we present a more balanced view on MW highlighting both its well-known detrimental effects and its potential benefits on learning with a particular focus on creativity.

Mind Wandering

According to a common definition ( Smallwood and Schooler, 2015 ), MW is a phenomenon consisting of three characteristics: (1) There is a primary task to be carried out. (2) The mind is losing focus of the primary task and follows, instead, thoughts that are unrelated to the primary task. (3) This shift of attention is self-generated and not triggered by an external stimulus (e.g., acoustic or visual distractors in the environment).

Noteworthy, MW shows some overlap with the phenomenon of “daydreaming” ( Klinger, 2009 ; McMillan et al., 2013 ). Both constructs involve internally generated thoughts that are not cued by an external event. However, in contrast to MW, the definition of daydreaming does not presuppose a concurrent primary task; in other words, daydreaming also includes situations such as having a walk in the park or riding a bus. In an early approach, Singer (1966) identified different styles of daydreaming, one of which was labeled “positive constructive daydreaming.” This style of daydreaming is characterized by playful, wishful imagery, and creative thought. Moreover, positive constructive daydreaming was later related by Singer to the arousal of positive emotions and the efficiency of future plans (see McMillan et al., 2013 ). Singer also identified two less “beneficial” daydreaming styles: “guilty-dysphoric daydreaming” and “poor attentional control,” the latter corresponding to what is typically associated with the term MW nowadays. Importantly, these latter two styles of daydreaming were found to be associated with negative consequences in a wide variety of domains and were not related to creativity (e.g., Huba et al., 1977 , 1981 ). Interestingly, however, contemporary research on the more narrowly defined construct of MW has rarely made a comparable distinction between positive and negative forms of MW, although it is theoretically possible to do so, as we will argue below.

On the other hand, MW researchers have differentiated between forms of MW with regard to their intentionality (i.e., intentional vs. spontaneous MW) and situation-specificity (situation-specific state-level vs. dispositional trait-level MW; e.g., Soemer et al., 2019 ). Spontaneous MW involves an unintentional und uncontrollable shift of an individual’s attention from the primary task to self-generated thoughts, whereas intentional MW is considered to be induced deliberately or at least tolerated whenever it occurs spontaneously (that is, individuals do not try to focus back on the primary task once they notice, see Seli et al., 2016a ). State-level MW means that individuals’ MW occurs only in specific situations but this may be context-induced and not a general trait of an individual. In contrast, trait-level MW refers to the fact that some individuals have a relatively stable (high or low) level of MW when working on various tasks. Accordingly, trait-level MW shows considerable definitional overlap with the aforementioned construct of daydreaming, the former being a slightly more restricted form of the latter.

Mentioning daydreaming in this article, which otherwise focuses specifically on MW, is important for two reasons. First, research on daydreaming illustrates that it has long been suspected that creativity may be related to an individual’s propensity to pursue internally generated mental content (e.g., Singer and Antrobus, 1963 ). Second, the primary focus of daydreaming research on the individual differences level highlights the need for greater differentiation in modern MW research on this topic. This includes identifying commonalities and differences of the above-mentioned subtypes of MW (e.g., state-level vs. trait-level MW) and examining their potentially diverse relationships to other constructs (e.g., for a contrasting effect of state vs. trait level MW on reading comprehension, see Soemer et al., 2019 ), which includes creativity. For convenience reasons, however, we will equate daydreaming with trait-level MW throughout the remainder of this paper.

Creativity and Its Measurement

Creativity has been characterized as the ability to create something novel, unique, or unusual (summarized as “original”) that is considered to be useful, appropriate, or fitting (i.e., efficient; Runco and Jaeger, 2012 ). Individual differences in creativity seem to be strongly connected to individual cognitive characteristics such as intelligence and, in particular, “divergent thinking” ( Guilford, 1967 ). Due to its continuing importance in creativity research, we will address divergent thinking first. However, relying solely on divergent thinking as a measure of creativity has its flaws, as explained below. Therefore, this review introduces another facet of creativity, namely creative problem solving , in order to look on creativity from a different perspective and to offer an alternative way of measuring it. At the end of this chapter, we will elaborate on the creative process.

Divergent Thinking

Divergent thinking is characterized by generating a large number of possible answers to a given problem. In contrast, “convergent thinking” is directed at producing the single best answer to a given problem ( Guilford, 1967 ). Some authors use the term “divergent thinking” synonymously with the term “creativity” (e.g., Frith et al., 2021 ), whereas others consider creativity to be a much broader construct that entails divergent thinking as one of its facets (e.g., Lubart et al., 2013 ; Silvia, 2015 ). Because of its ease of measurement and relevance for creativity, however, divergent thinking has been widely used as the main measure of creativity, as is also the case in most of the research being discussed in the following.

For a proper evaluation of the following studies, it is essential to recognize some of the flaws in the measurement of creativity in the sense of divergent thinking. These flaws originate in the assessment methods that were developed by Wallach and Kogan (1965) based on the work of Guilford (1957) . Notably, Wallach and Kogan (1965) basically equate creativity and divergent thinking. Their test battery relies on evaluating the creativity (or divergent thinking) of individuals in terms of the “uniqueness” of their answers to a given problem. For example, the “unusual uses task” (also known as the “alternative uses task”) requires the participants to name multiple unique unusual uses for different every-day objects, such as a brick or an empty bottle. Each response that is given by no other participant is judged as being “unique” and the answering person is awarded one point. This traditional method of measuring creativity/divergent thinking has been criticized (cf. Silvia, 2015 ) but is used until today (e.g., Baird et al., 2012 ).

There are two main problems with the traditional measure of creativity. First, the traditional measure only accounts for the originality facet of creativity but ignores the efficiency facet ( Runco and Jaeger, 2012 ). For a comprehensive measure of creativity, it is necessary to evaluate if a given answer is not only unique but also appropriate or useful. Second, the uniqueness of each response is inversely related to the number of participants being tested, because each participant increases the chance for a repetition.

In an alternative approach to divergent thinking, Torrance (1966 , 1974 , 2008) addresses the problem of neglecting the efficiency facet of creativity through adding other factors (e.g., fluency and elaboration) to the measurement that also account for appropriateness. The Torrance Tests of Creative Thinking (TTCT; Torrance, 1966 , 1974 , 2008 ) measures divergent thinking using a variety of tasks, such as the unusual uses task. In addition to the creativity facet originality , the TTCT assesses response characteristics such as the amount of relevant details provided (i.e., elaboration ) and the number of interpretable, meaningful, and pertinent responses (i.e., fluency ). Moreover, another factor, flexibility , refers to the number of distinct categories to which relevant responses can be assigned. Noteworthy, all of these dimensions (with the exception of originality) implicitly include a verification of the efficiency facet (e.g., for the dimension fluency: “Are the responded details really pertinent?”). However, the creativity facet efficiency still seems neglected, given its indirect implementation through these dimensions. Originality, in contrast, is a discrete dimension of the TTCT by itself and receives therefore more attention in this approach. More recent approaches to assess creativity/divergent thinking suggest other ways to avoid the problems of the traditional method. On the one hand, Smeekens and Kane (2016) addressed the need for more appropriate task instructions. Accordingly, Beaty et al. (2014b , p. 1189) suggested to ask participants “to come up with something clever, humorous, original, compelling, or interesting.” This type of instruction seems more likely to motivate participants to produce responses that are both original and appropriate, whereas the traditional method emphasized uniqueness ( Torrance, 2008 ) and quantity of answers. On the other hand, researchers have suggested procedures to assess the aspect of appropriateness more directly. This can be accomplished by letting expert raters independently judge the appropriateness (in addition to the originality) of the participants’ responses ( Silvia, 2015 ). As an example, Amabile (1982) has developed the Consensual Assessment Technique (CAT) for rating the creativity of a wide variety of products (see Baer and Kaufman, 2019 ).

Creative Problem Solving

Creative problem solving can be described as the ability to successfully engage in problems whose solution demands to gain a deeper insight into the problem itself by restructuring the mental representation of that problem (cf. Weisberg, 2015 ; He and Wong, 2021 ). In more detail, a first attempt to solve those kind of problems usually fails due to insufficient or hidden information that is needed for solving (i.e., it is a so-called ill-defined problem; DeYoung et al., 2008 ). In order to restructure the initial mental model of the problem one must rephrase the own problem-solving approach by changing the viewpoint on the problem after realizing that the initial approach will not lead to the solution (see Beaty et al., 2014a ). Furthermore, ill-defined problems could be conceived of as the antithesis to well-defined problems. While well-defined problems consist of clear specifications for the three elements of the problem space, namely (a) the problem situation, (b) rules and strategies to solve the problem and (c) the characteristics of the goal state, ill-defined problems are missing at least one of these elements ( Newell and Simon, 1972 ). Tasks that capture creative problem-solving ability through ill-defined problems are referred to as insight problems . One example for a verbal insight problem is “A man in a town married 20 Women in the town. He and the women are still alive, and he has had no divorces. He is not a bigamist and is not a Mormon and yet he broke no law. How is that possible?” (Solution: The man is the minister who married the 20 women to their respective husbands; Weisberg, 2015 , p. 7). In addition to such verbal-only formulated insight problems other insight problems provide additional visual input (e.g., a sketch) that must be processed for solving the problem (e.g., the pigpen problem; Lin et al., 2012 ).

Characteristic of insight problems is only one solution is correct, in contrast to divergent thinking tasks in which a person is supposed to generate as many answers as possible. Moreover, contrary to divergent thinking tasks that overemphasize the originality facet of creativity but neglect the efficiency facet, creative problem solving tasks such as insight problems assess both facets of creativity since there is only one correct answer that is actually original. In conclusion, one needs to compensate for the missing parts of the problem (i.e., the missing specifications of the problem situation, the solving mechanisms and/or the goal state) in order to solve ill-defined problems such as insight problems, whereas misspecification is not a problem in divergent thinking tasks.

The Creative Process

One common approach to conceptualize creative processes is the classic four-stage model of the creative process ( Wallas, 1926 ), which many contemporary models of creativity are based on (e.g., the componential model of creativity, Moriarty and VandenBergh, 1984 ; Amabile, 1996 ). As its name suggests, the classic model divides the creative process into four stages that ultimately lead to a creative output: preparation , incubation , illumination and verification . Although an individual usually proceeds through the stages sequentially one by one, Wallas stated that returning to former stages is possible if the problem to be solved requires this.

According to Wallas (1926) the preparation stage serves to preliminarily analyze, define and set up a given problem using problem-relevant knowledge and analytical skills. Noteworthy, individuals carry out these steps consciously, whereas in the following incubation stage the mind starts to work unconsciously on the problem. This second stage is characterized by taking a break from the problem and turning attention to other subjects. However, while being engaged in something different, the mind is still working on the “old problem” in a hidden way, forming many trains of associations, rejecting most of them as being useless but sometimes encountering a promising idea. When this happens, the next stage, illumination, begins and the formerly hidden idea breaks through into consciousness accompanied by a feeling of sudden enlightenment. The last stage, verification, serves to refine, develop and evaluate the produced idea. This stage proceeds in a fully conscious way again.

The Contributions of Creativity to School Learning

Our assumption of a positive effect of MW on learning through enhanced creativity presupposes a significant relation between creativity and learning. Substantial evidence for this relation has been provided in the past. For example, in their meta-analysis, Gajda et al. (2017) reviewed the data from 120 studies and reported an average correlation between creativity and academic achievement of r = 0.22. The authors identified two influential moderator variables: the type of creativity measure (e.g., self-reports vs. standardized tests) and the type of learning measure (e.g., grade point average vs. subject knowledge tests). It was found that the relation between creativity and learning performance was stronger when creativity was assessed through standardized tests (e.g., the TTCT; Torrance, 1966 , 1974 , 2008 ; Divergent thinking tasks, such as the unusual uses task; Wallach and Kogan, 1965 ) than through self-report scales. On the other hand, they found a weaker association between creativity and learning performance when the latter was measured as grade point average compared to standardized achievement tests. In conclusion, Gajda et al. suggested the development of more precise measurement instruments that are better suited to investigate the nature of this relationship between creativity and learning. In accordance with this suggestion, Karwowski et al. (2020) presented a new instrument to measure both creativity and learning [Creativity and Learning in School Achievement Test (CLISAT)] that particularly differs from other instruments for measuring creativity and learning by using a domain-specific assessment. Accordingly, the CLISAT measures both creativity and learning in a particular school subject related domain, such as math or language, while using school-based material. To give an example for a math task, one task from the test demands students to match the correct grid of a cuboid out of four alternatives with a given three-dimensional illustration of a cube. Accordingly, a creative task in the same domain asks the students to divide different forms into parts of equal size.

While validating psychometric properties (e.g., validity and reliability measures) of the CLISAT on 2,372 students of primary and middle school, Karwowski et al. (2020) used their instrument for a further investigation of the association between creativity and learning. They found that having academic knowledge particularly in math was inductive for creative performance in tasks of the same domain (i.e., math). However, for language they could not find evidence for this association. On the other hand, creativity performance in both math and language-related tasks positively predicted academic performance in tasks of the same domain. Intriguingly, in the case of math, particularly weak task performance was predicted by the creativity measure. Regarding this finding, Karwowski et al. assume that having high creativity skills could particularly be beneficial in generating and testing solutions to easy mathematical problems, since these allow various approaches. In contrast, difficult mathematical tasks would be more limited to be solved by only one correct approach. In the domain of language the domain-specific creativity measure predicted performance in language-related tasks over the whole difficulty range. Given these findings, the authors propose a mutual relationship between creativity and school learning.

Some other work pinpointed the significance of creativity for other domains than general learning. In his review regarding the importance of creativity for mathematics Mann (2006) elaborates over the meaning of an additional promotion of creativity for (gifted) students of mathematics. The author concludes that particularly in mathematics, traditional teaching relying on methods involving demonstration and practice using closed problems with predetermined answers, will rather produce computational experts that lack the ability to use their skills in meaningful ways. Thus, although it may seem counterintuitive at first, mathematics in particular could benefit from having an antithesis (i.e., a creative perspective) to the logical, predefined ways of approaching a problem. In contrast to mathematics, the connection between creativity and writing appears more obvious. For example, there is evidence, that the amount of time spent with reading and writing activities of university students is associated with them showing better creative performances ( Wang, 2012 ). Intriguingly, this study also indicated that just having a positive attitude toward reading and writing activities is connected to better creative performances. Moreover, particularly the writing in foreign languages may be connected to higher creative performances ( Wang, 2012 ; Niño and Páez, 2018 ).

Concludingly, despite the positive evidence for a stronger relation between creativity and school learning, a number of open questions remain. These refer in particular to the unresolved causal nature of the creativity-learning relation. In our present theoretical analysis, however, we regard a reciprocal relationship to be most probable. As has been argued by Gajda et al. (2017) , the process of being creative would ultimately lead to learning outcomes and the process of learning will ultimately result in creative outcomes.

Mind Wandering and Its Relation to Creativity

Mind wandering and divergent thinking.

In one of the first studies directly addressing the relation between MW and creativity, Baird et al. (2012) examined whether MW could account for the well-known enhancement of creative problem solving after a break. In what we will call “incubation paradigm” in the following ( Sio and Ormerod, 2009 ), participants are confronted with a problem they have to solve within a given period of time. In terms of the four-stage model ( Wallas, 1926 ), this confrontation can be classified as the first stage of the creative process, preparation. After expiration of the given time, the participants are offered an intervening break during which they do not process the task. This part constitutes the incubation stage of creative process. When the break is over, the participants continue to process the initial task again. Intriguingly, participants’ ability to come up with sudden intuitive solutions to creative problems is usually found to be improved through this break (i.e., the incubation effect). Furthermore, a recent meta-analysis found the incubation effect to be stronger when the break is filled with a mentally non-demanding task ( Sio and Ormerod, 2009 ). In terms of the four stage model manipulating the incubational stage through providing a non-demanding filler task can be regarded as a kind of enhancement of the idea-generating effect that is typically associated with this phase. Baird et al. (2012) tried to replicate the incubation effect and hypothesized that the better performance after a break may be associated with a higher frequency of MW. According to their hypothesis, being engaged in a non-demanding filler task during the break would increase the likelihood that participants engage in MW (which is consistent with the finding that MW is more frequent in non-demanding relative to demanding tasks; e.g., Smallwood et al., 2003a ; Seli et al., 2018 ). More MW, in turn, would promote creative processes that are associated with creative problem solving. In their study, participants were randomly assigned to one out of four experimental groups. The groups differed in the filler task that participants had to perform during the break and thus, in the demands of the tasks. In particular, participants of one group had to perform a low-demanding reaction-to-a-stimulus task that was expected to maximize MW and thereby promote problem solving during the incubation break. Participants of the other three groups performed a highly demanding n-back task ( Kirchner, 1958 ), no task or had no break at all. After the break, participants were asked to estimate how frequently their minds lost focus from the filler task (i.e., MW frequency). The main task in this study was the unusual uses task ( Wallach and Kogan, 1965 ) that was presented before and after the break. Indeed, the results showed the highest MW rates for participants occupied with the low-demanding task when compared to the participants of all the other groups. Furthermore, participants of the low-demanding task group showed the highest improvements in their amount of responses in the primary task after the incubation break when compared to their performance before the break. Baird et al. (2012) suggest that the higher MW frequency in the low-demand task group may lead to better creative insights (during the incubation break) which, in turn, is reflected in better results on the main task (i.e., the unusual uses task). Noteworthy, thoughts related to the main task did not differ between the groups meaning that these thoughts could not account for performance differences between groups.

While suggesting a close relationship between MW and creative processes, the positive association between MW frequency and creative performance does not necessarily imply a causal relationship between the two constructs, because MW was not directly manipulated between groups. On the other hand, it should be noted, that an experimental manipulation of MW is difficult to achieve (however, for an attempt to experimentally induce MW see McVay and Kane, 2013 ). Additionally, Baird et al. (2012) concluded that an increase in MW frequency during a break facilitates the incubation effect as a single element of the creative process (see also Wallas, 1926 ), but not creative problem solving in general. In addition to that, we argue that the unusual uses task used by Baird et al. is not ideal for measuring creative problem solving due to its neglect of the appropriateness facet of creativity that is best measured with insight problems (cf. He and Wong, 2021 ). Instead, the authors showed a connection between MW and divergent thinking that is technically not a measure of creative problem solving, although it can be considered a component of creativity. Smeekens and Kane (2016) argued that the applied manipulation of the task (i.e., alternating the demands) could certainly explain both the increase in the frequency of MW and also improvements in divergent thinking, in line with prior studies (e.g., Smallwood et al., 2003b ; Sio and Ormerod, 2009 ). Critically, the conclusion that MW causes this increase in divergent thinking would not be compelling based on this experimental design.

Mind Wandering and Its Relation to Creative Problem Solving

Another study supporting the hypothesis that MW relates to creativity was conducted by Tan et al. (2015) . This study likewise utilized the incubation paradigm to trigger creative solutions, while examining participants’ MW activity. However, in contrast to the work of Baird et al. (2012) , this study did not manipulate the filler task; that is, all participants had to perform the same relatively non-demanding version of the “sustained attention response task” (SART; Robertson et al., 1997 ). Furthermore, this study used a different main task as a measure of creativity (i.e., creative problem solving), the number-reduction task ( Wagner et al., 2004 ) that required participants to match numbers and respond in a rule-based fashion by returning another number until the seventh response of each trial was given. Participants were informed that only the seventh response would be scored, while the former responses served to determine this last one. Crucially, there was a hidden mechanism that generated the numbers meaning that the participants were able to shortcut the whole trial; that is, they could simply submit their seventh response number early. Tan et al. (2015) assumed that only those participants who figured out the hidden mechanism were able to reliably submit the correct seventh number early. In addition, participants were asked at the end of the experiment what rules (if any) they applied to determine the seventh response. As a result, participants that discovered the hidden rule had more frequent MW occurrences than participants that did not, while participants of both groups did not differ in various control variables (e.g., working memory capacity, motivation and meta-awareness for MW). These results suggest that the SART is a suitable filler task to improve creative output during the incubation period in addition to the reaction to a stimulus task used by Baird et al. (2012) . Moreover, Tan et al. showed that in addition to divergent thinking also creative problem solving can be promoted through performing a non-demanding task during the incubation stage of creative process. However, given the absence of any experimental manipulation of MW in this study, evidence for a causal relation between MW and creativity is still lacking.

Subtypes of Mind Wandering and Their Relations to Both Components of Creativity

Another important study by Agnoli et al. (2018) supports the hypothesis that MW is positively associated with creativity while extending the findings of Baird et al. (2012) and Tan et al. (2015) in two ways. First, the study succeeded in generalizing previous findings on the relation between MW and creativity to a novel paradigm. Instead of using the incubation paradigm, creativity was assessed both as a trait through a questionnaire that asked participants about accomplishments in 10 different domains of creativity such as creative writing or culinary arts (i.e., Creative Achievement Questionnaire; Carson et al., 2005 ) and by the so-called “titles task” ( Guilford, 1968 ). This task measures divergent thinking by requiring participants to produce multiple alternative titles for widely known movies or books. On the other hand, everyday MW (i.e., trait-level MW) was measured by the Five Facets Mindfulness Questionnaire (FFMQ; Baer et al., 2006 ) and two self-report scales that differentiated between intentional and spontaneous MW (MW-D and MW-S; Carriere et al., 2013 ). One advantage of the Creative Achievement Questionnaire is that it inquires about accomplishments of the past in a standardized way, which makes it largely objective and independent from the ongoing study. Furthermore, the questionnaire measures creativity on a relatively stable trait level, not in a particular situation. This trait-level measure is complemented by the titles task that captures situation-specific creativity (i.e., divergent thinking). A second extension of previous findings consists of differentiating between intentional and spontaneous MW (e.g., Seli et al., 2016b ) and relating these two forms of MW to creativity. Indeed, the authors found different associations between intentional and spontaneous MW, on the one hand, and situation-specific creativity (i.e., divergent thinking), on the other. That is, intentional MW was positively related to their measure of divergent thinking, whereas spontaneous MW was negatively related to divergent thinking. However, they did not succeed in finding a relation between MW and trait-level creativity.

Similarly, to Agnoli et al. (2018) a study from Preiss et al. (2016) showed positive correlations between trait-level MW and measures of creativity. They investigated whether trait-level MW can be associated with both divergent thinking and creative problem solving. Whereas the former was measured with the unusual uses task (corrected for appropriate answers), the latter was measured with a test, in which participants were presented with three words to which they had to find a matching word. Participants had to consider a given rule for the matching of the words. For instance, one rule was to find a word that can be used to produce a meaningful compound word with each of the three presented words (e.g., the response word “stone” for the words “mile,” “age,” and “sand”; see Bowden and Jung-Beeman, 2003 ). Trait-level MW was measured using the Daydreaming Frequency Scale from the Imaginal Processes Inventory (IPI; Singer and Antrobus, 1966/1970 ). The results showed trait-level MW to be a predictor of both creativity measures even when fluid intelligence and a measure of participants’ existing reading problems were taken into account. This result suggests that a differentiation of the MW construct into a state-level and a trait-level form could be useful to further investigate the MW-creativity relationship. However, it should be noted that this study only provides evidence for a correlational association between trait-level MW and measures of creativity, and it did not take into account state-level MW.

Studies That Contradict a Connection Between Mind Wandering and Creativity Measures

In contrast to those studies that found positive evidence for a connection between MW and creativity there are several other studies showing null results (e.g., Smeekens and Kane, 2016 ; Frith et al., 2021 ). Interestingly, a study from Smeekens and Kane (2016) directly addressed the results from Baird et al. (2012) and contrasted them with their own findings. Like Baird et al. (2012) , their study used an incubation paradigm. However, although their study design matched that of Baird et al. (2012) closely, Smeekens and Kane (2016) failed to replicate the results within three relatively similar experiments, one of them being an approximate replication of Baird et al. (2012) study. However, both studies differed in a number of details, because Smeekens and Kane used an online measure of mind wandering compared to a retrospective questionnaire used in Baird et al. (2012) study. Additionally, the study from Smeekens and Kane differed from Baird et al. (2012) study in the instructions given to participants, the assessment of divergent thinking (i.e., a subjective assessment was used) and some minor details. The authors reported that there was no evidence for a positive association between the frequency of MW during an incubation period and an improvement in divergent thinking after that break. These null results were considered by the authors to be more credible than the findings from the study of Baird et al. (2012) because of a number of methodological problems in the latter study, such as measuring MW in a retrospective way that, in their view, may be inaccurate due to memory biases and mental aggregation errors.

Similarly to Smeekens and Kane (2016) and Frith et al. (2021) did not find evidence for a positive relationship between state-level MW and divergent thinking. Their main study goal, however, was to examine whether attentional control can account for the well-known association between fluid intelligence and creativity (see also Silvia, 2015 ). Here, attentional control is defined as “overarching term that incorporates various complex control processes responsible for regulating goal-directed thought and behavior” ( Frith et al., 2021 , p. 2). It was assessed through three laboratory measures of attentional restraint (see McVay and Kane, 2012 ; Kane et al., 2016 ). Furthermore, this study defines MW as being a failure of attentional control. Therefore, an investigation of the effect of mind wandering on divergent thinking was of minor nature. State-level MW was measured by thought probes. Using this setup, Frith et al. did not find a significant relation between MW and divergent thinking when fluid intelligence and attentional control were controlled for.

It should be noted, however, that the study of Frith et al. (2021) used a relatively demanding task during the incubation break, in contrast to the majority of previous studies examining the relation between MW and creativity. As we will argue below, this might be a crucial difference between this study and other studies, because task difficulty is known to affect intentional and spontaneous MW differently (e.g., Seli et al., 2016b ; Soemer and Schiefele, 2019 ). Furthermore, the MW measure was not differentiated (e.g., in its intentionality) and only state-level MW was assessed.

Summary and Evaluation

The existence of a relationship between MW and creativity is a controversial issue based on currently available research. On the one hand, it is theoretically well conceivable that MW has positive impacts on creativity because it consists of self-generated contents (e.g., mental images, elaborations, metacognitive thoughts) that could potentially be important for a task at hand that requires some degree of creativity. In line with this hypothesis, early daydreaming research beginning in the mid of the last century as well as a number of contemporary studies have provided evidence for a positive relationship between two components of creativity—divergent thinking and creative problem solving—and MW (e.g., Singer, 1966 ; Baird et al., 2012 ; Preiss et al., 2016 ; Agnoli et al., 2018 ). On the other hand, some recent studies have reported null results suggesting that the circumstances under which positive associations can be found still need to be examined in more detail (e.g., Smeekens and Kane, 2016 ). In addition, it is well known that MW occurring during task execution can be detrimental to task performance in various domains (e.g., Smallwood et al., 2008 ; Galéra et al., 2012 ; Soemer and Schiefele, 2019 ), so why should this be different for tasks that require creative processes?

Evaluating the results of the above reviewed studies, it appears that the relationship between MW and creativity will not be as simple as stating that MW that occurs during a task requiring creative processing would directly bring improvements for that task. Instead, we propose that one needs to distinguish between different forms of MW and examine whether these forms differ in their relationship with creativity (i.e., whether some of them show more positive or negative correlations than others). Particularly, two meaningful distinctions of MW were suggested in some MW studies: the intentionality of MW (e.g., Forster and Lavie, 2009 ; Carriere et al., 2013 ; Seli et al., 2015a , b ; Agnoli et al., 2018 ; Soemer and Schiefele, 2020 ) and the trait-level vs. state-level distinction (e.g., Preiss et al., 2016 ; Soemer et al., 2019 ). We propose that the omission of such distinctions could at least in part be responsible for the contradictory results of the aforementioned studies.

Regarding the intentionality dimension, there is evidence that intentional and spontaneous MW exert different effects on divergent thinking, an important dimension of creativity. Specifically, the study of Agnoli et al. (2018) suggests that the intentional (but not the spontaneous) form of MW may be positively related to divergent thinking. For this reason, studies examining the relation between MW and creativity are more likely to find supportive evidence if they particularly focus on intentional MW and set up conditions in which intentional MW becomes the dominant form of MW. One factor affecting the balance between intentional and spontaneous MW, for example, are the demands of a task; that is, easy tasks are more likely to shift this balance to intentional MW, whereas difficult tasks are more likely to do the opposite (e.g., Seli et al., 2016b ). For this reason, studies that use a highly demanding filler task for the incubation period are less likely to find evidence for a positive relation between MW and creativity. This may in fact be one of the primary reasons for Frith et al. (2021) failure to demonstrate a positive association between MW and creativity.

Regarding the second meaningful distinction between trait-level and state-level MW, the majority of recent studies has primarily focused on the latter. Indeed, general MW research has highlighted the detrimental effects of state-level MW while carrying out a given primary task, on performance in that task (e.g., Soemer et al., 2019 ), contrary to some studies in the field of creativity. However, one crucial difference here is that studies on MW in other fields (including learning) examined the effects of MW on the same task during which it occurred (e.g., the effect of MW during reading on later comprehension). The incubation paradigm used in many studies on the relation between MW and creativity, in contrast, examined the effects of MW while executing a filler task on a primary task that requires some degree of creativity. 1 Moreover, the filler task of the incubation period provides an optimal moment for MW to occur without having negative effects, since the performance in that task itself is not important. On the other hand, MW during the incubation period could have positive effects on creative performance that seem to outlast the break. However, this is in contrast to the performance in most other fields that demands one’s sustained attention (e.g., driving a car, reading a text for an exam, following a conversation) that could be distracted and therefore be interfered by MW over the whole time. Eventually, state-level MW might not be as detrimental in creative domains that include an incubation period as it is for other domains. Distinguishing between MW at the state level and at the trait level in future research could help to find some evidence for this hypothesis.

In terms of trait-level MW, Preiss et al. (2016) showed that students’ trait-level MW was positively associated with two scores of creativity suggesting that the more MW the participants experienced in their daily lives, the more creative they were. This finding is in-line with earlier daydreaming research that showed positive associations between measures of daydreaming and creative problem solving (e.g., Singer, 1966 ; Huba et al., 1977 ). Interestingly, the results of a recent study by Soemer et al. (2019) suggests that trait-level MW might actually have opposite effects on a given primary task. Replicating previous studies on MW during reading, they found a negative association between state-level MW and comprehension, whereas trait-level MW had two opposing effects on comprehension. First, there was a negative effect mediated by state-level MW meaning that trait-level MW was positively associated with state-level MW which in turn had a negative effect on comprehension. Second, there was a direct positive effect of trait-level MW on comprehension. Soemer et al. (2019) hypothesized that trait-level MW, like daydreaming, is composed of different dimensions (i.e., positive-constructive, poor attention etc.). Accordingly, the direct positive effect of trait-level MW might be related to elaborative processes occurring during reading; that is, individuals scoring high on their trait-level scale of MW presumably engaged in more elaborative processes during reading which, in turn, improved comprehension. This would be in accordance to findings of the daydreaming research that showed the positive-constructive type of daydreaming to be associated with the exploration of ideas and openness to new experiences (e.g., to allow for new unfamiliar thoughts; Tang and Singer, 1997 ). Unfortunately, to our best knowledge, no study has yet investigated the relationships between trait and state MW with creativity simultaneously.

Finally, it should be noted that each of the studies that investigated the association between MW and creativity was based on the hypothesis of an existing association between those constructs. However, a general caveat interpreting studies that fail to find evidence for a relation between MW and creativity is that non-significant hypothesis tests, as important as they may be, do not support the null hypothesis of no relation between MW and creativity. This is because the general framework of null hypothesis significance testing (NHST) does not allow for accepting the null hypothesis upon a non-significant result (see Nickerson, 2000 , for a thorough discussion).

Educational Implications

Overall, the reviewed body of research suggests that creativity is positively related to, at least, certain forms of MW. Creativity in turn, is known to promote various forms of learning (e.g., Hattie, 2009 ; Karwowski et al., 2020 ). We thus argue that educational practitioners should not blindly aim at reducing MW during a session but they should pay attention to the conditions that promote “beneficial” MW. In the following, we will make a number of suggestions on how to accomplish this.

One particular outcome of the reviewed studies is that breaks can help finding solutions to tasks requiring divergent thinking or gaining insight into a problem (i.e., creative problem solving). This outcome may not sound entirely new. Generations of teachers and learners have intuitively known that making a break and refresh one’s mind can lead to the solution of a problem ( Wallas, 1926 ). On the scientific side, early experimental research by the Russian psychologist Zeigarnik demonstrated that individuals who take a break from a given task and engage in task-unrelated activities (such as playing) will remember better what they did before the break than individuals that complete their task before the break ( Zeigarnik, 1927 ). More recent research in this field suggests that breaks may serve as incubation periods for creative problem solving and, therefore, should be introduced into classroom sessions ( Rae, 1997 ; Webster et al., 2006 ). In terms of the four-stage model of creative process ( Wallas, 1926 ), breaks provide space for the second stage, incubation, so the absence of a break during a creative task would be tantamount to skipping this important second phase of the creative process. Moreover, most learning tasks in school are treated “uninterruptable,” such as reading a long text to its end in order to earn the break first. In contrast, it might be useful for teachers to look for a suitable place for a short break within the learning material that allows learners for creative incubation and process what they have learned so far.

Going beyond the previous literature, however, a main contribution of the studies reviewed here is that they reveal MW as a potential mediator process for the effect of an incubation period for creative problem solving. Furthermore, some studies suggest that the activity carried out during the incubation period is an important factor to consider. In particular, this activity should be easy enough to allow for sufficient levels of MW ( Baird et al., 2012 ). Similarly, performing in no activity during the incubation period does not contribute to MW. A task too difficult, however, could not only hinder the creative idea generation during incubation stage of creative process but also shift the proportion of beneficial intentional MW to a more detrimental form, spontaneous MW ( Seli et al., 2016b ). Taken together, these findings highlight the importance of choosing an activity (in contrast to having no activity) with an easy level of difficult, to perform during a break. Fortunately, it has been found that easy to realize stimulus-response tasks can improve MW occurrence during incubation periods (e.g., Baird et al., 2012 ). On the other hand, tasks such as the SART are also capable of stimulating MW ( Tan et al., 2015 ), but they are limited to the laboratory and are hardly applicable in educational settings. It seems not too difficult to find other tasks that meet both requirements, meaning that they are beneficial to MW as well as easy to implement into breaks. However, unless there are any new findings, the scope of application is primarily limited to creative performance in divergent thinking tasks and insight problem solving. It remains to be evaluated whether these results can also be transferred to real teaching situations, as an earlier examination showed no evidence for a relation between performance in solving insight problems and real-world creative achievement as well as creative behavior ( Beaty et al., 2014a ).

General Conclusion

MW is often considered as an obstacle to performances in various domains of learning and cognitive functioning in general. However, many researchers have pointed out that MW occurs too often in daily life to simply represent a mere dysfunction of our brain (e.g., Mooneyham and Schooler, 2013 ; Schooler et al., 2013 ; Smallwood and Andrews-Hanna, 2013 ). Indeed, like these researchers, we argue that MW may actually serve an important cognitive function in our lives. One of these functions is to facilitate creative output in form of divergent thinking and creative problem solving, as suggested by several reviewed studies on the relation between MW and creativity. We further argue that because creativity is an important predictor of learning in various contexts, specific forms of MW occurring at the right time may actually promote certain learning tasks, in particular, when these tasks require original and appropriate solutions (i.e., creative problem solving).

That being said, evidence to support our claim is somewhat indirect and limited to the incubation paradigm and two subdomains of creativity (i.e., divergent thinking and creative problem solving). We therefore suggest that results from studies using the incubation paradigm should be transferred to more realistic learning contexts. In addition, future research addressing the relationship between MW and creativity should pay more attention to the different forms of MW.

Author Contributions

All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.

This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Projektnummer 491466077.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

• ^ Interestingly, a MW episode that occurs during the filler task may be classified as on-task behavior with regard to the primary task in this paradigm, if the episode deals with topics of the primary task.

Agnoli, S., Vanucci, M., Pelagatti, C., and Corazza, G. E. (2018). Exploring the link between mind wandering, mindfulness, and creativity: a multidimensional approach. Creat. Res. J. 30, 41–53. doi: 10.1080/10400419.2018.1411423

CrossRef Full Text | Google Scholar

Amabile, T. M. (1982). Social psychology of creativity: a consensual assessment technique. J. Pers. Soc. Psychol. 43, 997–1013. doi: 10.1037/0022-3514.43.5.997

Amabile, T. M. (1996). Creativity in Context. Boulder: Westview.

Google Scholar

Baer, J., and Kaufman, J. C. (2019). “Assessing creativity with the consensual assessment technique,” in The Palgrave Handbook of Social Creativity Research , eds I. Lebuda and V. P. Glaveanu (Cham: Springer International Publishing), 27–37. doi: 10.1007/978-3-319-95498-1_3

Baer, R. A., Smith, G. T., Hopkins, J., Krietemeyer, J., and Toney, L. (2006). Using self-report assessment methods to explore facets of mindfulness. Assessment 13, 27–45. doi: 10.1177/1073191105283504

PubMed Abstract | CrossRef Full Text | Google Scholar

Baird, B., Smallwood, J., Mrazek, M. D., Kam, J. W. Y., Franklin, M. S., and Schooler, J. W. (2012). Inspired by distraction: mind wandering facilitates creative incubation. Psychol. Sci. 23, 1117–1122. doi: 10.1177/0956797612446024

Beaty, R. E., Silvia, P. J., Nusbaum, E. C., Jauk, E., and Benedek, M. (2014b). The roles of associative and executive processes in creative cognition. Mem. Cogn. 42, 1186–1197. doi: 10.3758/s13421-014-0428-8

Beaty, R. E., Nusbaum, E. C., and Silvia, P. J. (2014a). Does insight problem solving predict real-world creativity? Psychol. Aesthet. Creat. Arts 8, 287–292. doi: 10.1037/a0035727

Bowden, E. M., and Jung-Beeman, M. (2003). Normative data for 144 compound remote associate problems. Behav. Res. Meth. Instrum. Comput. 35, 634–639. doi: 10.3758/BF03195543

Carriere, J. S. A., Seli, P., and Smilek, D. (2013). Wandering in both mind and body: Individual differences in mind wandering and inattention predict fidgeting. Can. J. Exp. Psychol. 67, 19–31. doi: 10.1037/a0031438

Carson, S. H., Peterson, J. B., and Higgins, D. M. (2005). Reliability, validity, and factor structure of the creative achievement questionnaire. Creat. Res. J. 17, 37–50. doi: 10.1207/s15326934crj1701_4

DeYoung, C. G., Flanders, J. L., and Peterson, J. B. (2008). Cognitive abilities involved in insight problem solving: an individual differences model. Creat. Res. J. 20, 278–290. doi: 10.1080/10400410802278719

Dixon, P., and Bortolussi, M. (2013). Construction, integration, and mind wandering in reading. Can. J. Exp. Psychol. 67, 1–10. doi: 10.1037/a0031234

Dollinger, S. J. (2011). “Standardized minds” or individuality? Admissions tests and creativity revisited. Psychol. Aesthet. Creat. Arts 5, 329–341. doi: 10.1037/a0023659

Forster, S., and Lavie, N. (2009). Harnessing the wandering mind: the role of perceptual load. Cognition 111, 345–355. doi: 10.1016/j.cognition.2009.02.006

Frith, E., Kane, M. J., Welhaf, M. S., Christensen, A. P., Silvia, P. J., and Beaty, R. E. (2021). Keeping creativity under control: contributions of attention control and fluid intelligence to divergent thinking. Creat. Res. J. 33, 1–20. doi: 10.1080/10400419.2020.1855906

Gajda, A., Karwowski, M., and Beghetto, R. A. (2017). Creativity and academic achievement a meta-analysis. J. Educ. Psychol. 109, 269–299. doi: 10.1037/edu0000133

Galéra, C., Orriols, L., M’Bailara, K., Laborey, M., Contrand, B., Ribéreau-Gayon, R., et al. (2012). Mind wandering and driving: responsibility case-control study. BMJ 345:e8105. doi: 10.1136/bmj.e8105

Guilford, J. P. (1957). Creative abilities in the arts. Psychol. Rev. 64, 110–118. doi: 10.1037/h0048280

Guilford, J. P. (1967). The Nature of Human Intelligence. New York:NY: McGraw-Hill.

Guilford, J. P. (1968). Intelligence, Creativity, and Their Educational Implications. San Diego, CA: Edits Pub.

Hattie, J. (2009). Visible learning: A synthesis of Over 800 Meta-Analyses Relating to Achievement. London: Routledge.

He, W. J., and Wong, W. C. (2021). Gender differences in the distribution of creativity scores: domain-specific patterns in divergent thinking and creative problem solving. Front. Psychol. 12:626911. doi: 10.3389/fpsyg.2021.626911

Hollis, R. B., and Was, C. A. (2016). Mind wandering, control failures, and social media distractions in online learning. Learn. Instr. 42, 104–112. doi: 10.1016/j.learninstruc.2016.01.007

Huba, G. J., Aneshensel, C. S., and Singer, J. L. (1981). Development of scales for three second-order factors of inner experience. Multivar. Behav. Res. 16, 181–206. doi: 10.1207/s15327906mbr1602_4

Huba, G. J., Segal, B., and Singer, J. L. (1977). Consistency of daydreaming styles across samples of college male and female drug and alcohol users. J. Abnorm. Psychol. 86, 99–102. doi: 10.1037/0021-843X.86.1.99

Kane, M. J., Carruth, N. P., Lurquin, J. H., Silvia, P. J., Smeekens, B. A., von Bastian, C. C., et al. (2021). Individual differences in task-unrelated thought in university classrooms. Mem. Cognit. 49, 1247–1266. doi: 10.3758/s13421-021-01156-3

Kane, M. J., Meier, M. E., Smeekens, B. A., Gross, G. M., Chun, C. A., Silvia, P. J., et al. (2016). Individual differences in the executive control of attention, memory, and thought, and their associations with schizotypy. J. Exp. Psychol. Gen. 145, 1017–1048. doi: 10.1037/xge0000184

Karwowski, M., Jankowska, D. M., Brzeski, A., Czerwonka, M., Gajda, A., Lebuda, I., et al. (2020). Delving into creativity and learning. Creat. Res. J. 32, 4–16. doi: 10.1080/10400419.2020.1712165

Kirchner, W. K. (1958). Age differences in short-term retention of rapidly changing information. J. Exp. Psychol. 55, 352–358. doi: 10.1037/h0043688

Klinger, E. (2009). “Daydreaming and fantasizing: thought flow and motivation,” in Handbook of Imagination and Mental Simulation , eds K. D. Markman, W. M. Klein, and J. A. Suhr (New York:NY: Psychology Press), 225–239.

Lee, C. S., Huggins, A. C., and Therriault, D. J. (2014). A measure of creativity or intelligence? Examining internal and external structure validity evidence of the remote associates test. Psychol. Aesthet. Creat. Arts 8, 446–460. doi: 10.1037/a0036773

Leopold, C., Mayer, R. E., and Dutke, S. (2019). The power of imagination and perspective in learning from science text. J. Educ. Psychol. 111, 793–808. doi: 10.1037/edu0000310

Lin, W. L., Hsu, K. Y., Chen, H. C., and Wang, J. W. (2012). The relations of gender and personality traits on different creativities: a dual-process theory account. Psychol. Aesthet. Creat. Arts 6, 112–123. doi: 10.1037/a0026241

Lindquist, S. I., and McLean, J. P. (2011). Daydreaming and its correlates in an educational environment. Learn. Individ. Differ. 21, 158–167. doi: 10.1016/j.lindif.2010.12.006

Lubart, T., Zenasni, F., and Barbot, B. (2013). Creative potential and its measurement. Int. J. Talent Dev. Creat. 1, 41–51.

Mann, E. L. (2006). Creativity: The essence of mathematics. J. Educ. Gift. 30, 236–260. doi: 10.4219/jeg-2006-264

McMillan, R. L., Kaufman, S. B., and Singer, J. L. (2013). Ode to positive constructive daydreaming. Front. Psychol. 4:626. doi: 10.3389/fpsyg.2013.00626

McVay, J. C., and Kane, M. J. (2009). Conducting the train of thought: working memory capacity, goal neglect, and mind wandering in an executive-control task. J. Exp. Psychol. Learn. Mem. Cogn. 35, 196–204. doi: 10.1037/a0014104

McVay, J. C., and Kane, M. J. (2012). Why does working memory capacity predict variation in reading comprehension? On the influence of mind wandering and executive attention. J. Exp. Psychol. Gen. 141, 302–320. doi: 10.1037/a0025250

McVay, J. C., and Kane, M. J. (2013). Dispatching the wandering mind? Toward a laboratory method for cuing “spontaneous” off-task thought. Front. Psychol. 4:570. doi: 10.3389/fpsyg.2013.00570

Mooneyham, B. W., and Schooler, J. W. (2013). The costs and benefits of mind-wandering: a review. Can. J. Exp. Psychol. 67, 11–18. doi: 10.1037/a0031569

Moriarty, S. E., and VandenBergh, B. G. (1984). Advertising creatives look at creativity. J. Creat. Behav. 18, 162–174. doi: 10.1002/j.2162-6057.1984.tb00380.x

Newell, A., and Simon, H. A. (1972). Human Problem Solving. New Jersey.NJ: Englewood Cliffs.

Nickerson, R. S. (2000). Null hypothesis significance testing: a review of an old and continuing controversy. Psychol. Methods 5, 241–301. doi: 10.1037/1082-989x.5.2.241

Niño, F. L., and Páez, M. E. V. (2018). Building writing skills in English in fifth graders: analysis of strategies based on literature and creativity. English Lang. Teach. 11:102. doi: 10.5539/elt.v11n9p102

Preiss, D. D., Cosmelli, D., Grau, V., and Ortiz, D. (2016). Examining the influence of mind wandering and metacognition on creativity in university and vocational students. Learn. Individ. Differ. 51, 417–426. doi: 10.1016/j.lindif.2016.07.010

Rae, C. M. (1997). The creative power of doing nothing. Writer 110, 13–15.

Risko, E. F., Anderson, N., Sarwal, A., Engelhardt, M., and Kingstone, A. (2012). Everyday attention: Variation in mind wandering and memory in a lecture. Appl. Cogn. Psychol. 26, 234–242. doi: 10.1002/acp.1814

Robertson, I. H., Manly, T., Andrade, J., Baddeley, B. T., and Yiend, J. (1997). ‘Oops!’: Performance correlates of everyday attentional failures in traumatic brain injured and normal subjects. Neuropsychologia 35, 747–758. doi: 10.1016/S0028-3932(97)00015-8

Runco, M. A., and Jaeger, G. J. (2012). The standard definition of creativity. Creat. Res. J. 24, 92–96. doi: 10.1080/10400419.2012.650092

Schooler, J. W., Mrazek, M. D., Franklin, M. S., Baird, B., Mooneyham, B. W., Zedelius, C. M., et al. (2013). “The middle way: finding the balance between mindfulness and mind-wandering,” in The Psychology Of Learning and Motivation , ed. B. H. Ross (Amsterdam: Elsevier Science), 1–33. doi: 10.1016/B978-0-12-800090-8.00001-9

Seli, P., Cheyne, J. A., Xu, M., Purdon, C., and Smilek, D. (2015a). Motivation, intentionality, and mind wandering: implications for assessments of task-unrelated thought. J. Exp. Psychol. Learn. Mem. Cogn. 41, 1417–1425. doi: 10.1037/xlm0000116

Seli, P., Konishi, M., Risko, E. F., and Smilek, D. (2018). The role of task difficulty in theoretical accounts of mind wandering. Conscious. Cogn. 65, 255–262. doi: 10.1016/j.concog.2018.08.005

Seli, P., Risko, E. F., Smilek, D., and Schacter, D. L. (2016a). Mind-wandering with and without intention. Trends Cogn. Sci. 20, 605–617. doi: 10.1016/j.tics.2016.05.010

Seli, P., Risko, E. F., and Smilek, D. (2016b). On the necessity of distinguishing between unintentional and intentional mind wandering. Psychol. Sci. 27, 685–691. doi: 10.1177/0956797616634068

Seli, P., Smallwood, J., Cheyne, J. A., and Smilek, D. (2015b). On the relation of mind wandering and ADHD symptomatology. Psychon. Bull. Rev. 22, 629–636. doi: 10.3758/s13423-014-0793-0

Silvia, P. J. (2015). Intelligence and creativity are pretty similar after all. Educ. Psychol. Rev. 27, 599–606. doi: 10.1007/s10648-015-9299-1

Singer, J. L. (1966). Daydreaming: An Introduction to the Experimental Study of Inner Experience. Daydreaming: an Introduction to the Experimental Study of Inner Experience. New York, NY: Crown Publishing Group/Random House.

Singer, J. L., and Antrobus, J. S. (1963). A factor-analytic study of daydreaming and conceptually-related cognitive and personality variables. Percept. Mot. Skills 17, 187–209. doi: 10.2466/pms.1963.17.1.187

Singer, J. L., and Antrobus, J. S. (1966/1970). in Imaginal Processes Inventory , eds L. S. Jerome and S. A. John (New York:NY: Center for Research in Cognition and Affect Graduate Center).

Sio, U. N., and Ormerod, T. C. (2009). Does incubation enhance problem solving? A meta-analytic review. Psychological Bulletin 135, 94–120. doi: 10.1037/a0014212

Smallwood, J., and Andrews-Hanna, J. R. (2013). Not all minds that wander are lost: The importance of a balanced perspective on the mind-wandering state. Front. Psychol. 4:441. doi: 10.3389/fpsyg.2013.00441

Smallwood, J., McSpadden, M., and Schooler, J. W. (2008). When attention matters: The curious incident of the wandering mind. Mem. Cogn. 36, 1144–1150. doi: 10.3758/MC.36.6.1144

Smallwood, J., Obonsawin, M., and Heim, D. (2003a). Task unrelated thought: The role of distributed processing. Conscious. Cogn. 12, 169–189. doi: 10.1016/S1053-8100(02)00003-X

Smallwood, J., Obonsawin, M., and Reid, H. (2003b). The effects of block duration and task demands on the experience of task unrelated thought. Imagin. Cogn. Pers. 22, 13–31. doi: 10.2190/TBML-N8JN-W5YB-4L9R

Smallwood, J., Riby, L. M., Heim, D., and Davies, J. B. (2006). Encoding during the attentional lapse: accuracy of encoding during the semantic sustained attention to response task. Conscious. Cogn. 15, 218–231. doi: 10.1016/j.concog.2005.03.003

Smallwood, J., and Schooler, J. W. (2006). The restless mind. Psychol. Bull. 132, 946–958. doi: 10.1037/0033-2909.132.6.946

Smallwood, J., and Schooler, J. W. (2015). The science of mind wandering: Empirically navigating the stream of consciousness. Annu. Rev. Psychol. 66, 487–518. doi: 10.1146/annurev-psych-010814-015331

Smeekens, B. A., and Kane, M. J. (2016). Working memory capacity, mind wandering, and creative cognition: an individual-differences investigation into the benefits of controlled versus spontaneous thought. Psychol. Aesthet. Creat. Arts 10, 389–415. doi: 10.1037/aca0000046

Soemer, A., Idsardi, H. M., Minnaert, A., and Schiefele, U. (2019). Mind wandering and reading comprehension in secondary school children. Learn. Individ. Differ. 75, 1–11. doi: 10.1016/j.lindif.2019.101778

Soemer, A., and Schiefele, U. (2019). Text difficulty, topic interest, and mind wandering during reading. Learning & Instruction 61, 12–22. doi: 10.1016/j.learninstruc.2018.12.006

Soemer, A., and Schiefele, U. (2020). Working memory capacity and (in)voluntary mind wandering. Psychono. Bull. Rev. 27, 758–767. doi: 10.3758/s13423-020-01737-4

Stawarczyk, D., and D’Argembeau, A. (2016). Conjoint influence of mind-wandering and sleepiness on task performance. J. Exp. Psychol. Hum. Percept. Perform. 42, 1587–1600. doi: 10.1037/xhp0000254.supp

Tan, T., Zou, H., Chen, C., and Luo, J. (2015). Mind wandering and the incubation effect in insight problem solving. Creat. Res. J. 27, 375–382. doi: 10.1080/10400419.2015.1088290

Tang, Z., and Singer, J. L. (1997). Daydreaming styles, emotionality and the big five personality dimensions. Imagin. Cogn. Pers. 16, 399–414. doi: 10.2190/ATEH-96EV-EXYX-2ADB

Torrance, E. P. (1966). The Torrance Tests of Creative Thinking - Norms-Technical Manual Research Edition - Verbal Tests, Forms A and B - Figural Tests, Forms A and B. Princeton. Oxford: Personnel Press.

Torrance, E. P. (1974). The Torrance Tests of Creative Thinking - Norms-Technical Manual Research Edition - Verbal Tests, Forms A and B - Figural Tests, Forms A and B. Princeton. Oxford: Personnel Press.

Torrance, E. P. (2008). The Torrance Tests of Creative Thinking Norms-Technical Manual Figural Forms A & B. Bensenville: Scholastic Testing Service.

Unsworth, N., and McMillan, B. D. (2013). Mind wandering and reading comprehension: Examining the roles of working memory capacity, interest, motivation, and topic experience. J. Exp. Psychol. Learn. Mem. Cogn. 39, 832–842. doi: 10.1037/a0029669

Unsworth, N., McMillan, B. D., Brewer, G. A., and Spillers, G. J. (2012). Everyday attention failures: an individual differences investigation. J. Exp. Psychol. Learn. Mem. Cogn. 38, 1765–1772. doi: 10.1037/a0028075

Wagner, U., Gais, S., Haider, H., Verleger, R., and Born, J. (2004). Sleep inspires insight. Nature 427, 352–355. doi: 10.1038/nature02223

Wallach, M. A., and Kogan, N. (1965). Modes of Thinking in Young Children: a Study of the Creativity-Intelligence Distinction. New York, NY:: Holt, Rinehart, & Winston.

Wallas, G. (1926). The art of thought. London, UK: Jonathan Cape.

Wammes, J. D., Seli, P., Cheyne, J. A., Boucher, P. O., and Smilek, D. (2016). Mind wandering during lectures II: Relation to academic performance. Scholarsh. Teach. Learn. Psychol. 2, 33–48. doi: 10.1037/stl0000055

Wang, A. Y. (2012). Exploring the relationship of creative thinking to reading and writing. Think. Skills and Creat. 7, 38–47. doi: 10.1016/j.tsc.2011.09.001

Webster, A., Campbell, C., and Jane, B. (2006). Enhancing the creative process for learning in primary technology education. Int. J. Technol. Des. Educ. 16, 221–235. doi: 10.1007/s10798-005-5633-0

Weisberg, R. W. (2015). Toward an integrated theory of insight in problem solving. Think. Reason. 21, 5–39. doi: 10.1080/13546783.2014.886625

Zeigarnik, B. (1927). Das Behalten erledigter und unerledigter handlungen. Psychol. Forsch. 9, 1–85.

PubMed Abstract | Google Scholar

Keywords : mind wandering, creativity, divergent thinking, incubation effect, school learning, creative problem solving

Citation: Gericke C, Soemer A and Schiefele U (2022) Benefits of Mind Wandering for Learning in School Through Its Positive Effects on Creativity. Front. Educ. 7:774731. doi: 10.3389/feduc.2022.774731

Received: 12 September 2021; Accepted: 23 March 2022; Published: 15 April 2022.

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Copyright © 2022 Gericke, Soemer and Schiefele. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Christian Gericke, [email protected]

† These authors have contributed equally to this work and share senior authorship

It’s normal for your mind to wander. Here’s how to maximise the benefits

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Have you ever found yourself thinking about loved ones during a boring meeting? Or going over the plot of a movie you recently watched during a drive to the supermarket?

This is the cognitive phenomenon known as “ mind wandering ”. Research suggests it can account for up to 50% of our waking cognition (our mental processes when awake) in both western and non-western societies .

So what can help make this time productive and beneficial?

Mind wandering is not daydreaming

Mind wandering is often used interchangeably with daydreaming. They are both considered types of inattention but are not the same thing.

Mind wandering is related to a primary task, such as reading a book, listening to a lecture, or attending a meeting. The mind withdraws from that task and focuses on internally generated, unrelated thoughts.

On the other hand, daydreaming does not involve a primary, active task. For example, daydreaming would be thinking about an ex-partner while travelling on a bus and gazing out the window. Or lying in bed and thinking about what it might be like to go on a holiday overseas.

If you were driving the bus or making the bed and your thoughts diverted from the primary task, this would be classed as mind wandering.

The benefits of mind wandering

Mind wandering is believed to play an important role in generating new ideas , conclusions or insights (also known as “aha! moments”). This is because it can give your mind a break and free it up to think more creatively.

This type of creativity does not always have to be related to creative pursuits (such as writing a song or making an artwork). It could include a new way to approach a university or school assignment or a project at work. Another benefit of mind wandering is relief from boredom, providing the opportunity to mentally retreat from a monotonous task.

For example, someone who does not enjoy washing dishes could think about their upcoming weekend plans while doing the chore. In this instance, mind wandering assists in “passing the time” during an uninteresting task.

Mind wandering also tends to be future-oriented. This can provide an opportunity to reflect upon and plan future goals, big or small. For example, what steps do I need to take to get a job after graduation? Or, what am I going to make for dinner tomorrow?

Read more: Alpha, beta, theta: what are brain states and brain waves? And can we control them?

What are the risks?

Mind wandering is not always beneficial, however. It can mean you miss out on crucial information. For example, there could be disruptions in learning if a student engages in mind wandering during a lesson that covers exam details. Or an important building block for learning.

Some tasks also require a lot of concentration in order to be safe. If you’re thinking about a recent argument with a partner while driving, you run the risk of having an accident.

That being said, it can be more difficult for some people to control their mind wandering. For example, mind wandering is more prevalent in people with ADHD.

Read more: How your brain decides what to think

What can you do to maximise the benefits?

There are several things you can do to maximise the benefits of mind wandering.

• be aware : awareness of mind wandering allows you to take note of and make use of any productive thoughts. Alternatively, if it is not a good time to mind wander it can help bring your attention back to the task at hand

context matters : try to keep mind wandering to non-demanding tasks rather than demanding tasks. Otherwise, mind wandering could be unproductive or unsafe. For example, try think about that big presentation during a car wash rather than when driving to and from the car wash

content matters : if possible, try to keep the content positive. Research has found , keeping your thoughts more positive, specific and concrete (and less about “you”), is associated with better wellbeing. For example, thinking about tasks to meet upcoming work deadlines could be more productive than ruminating about how you felt stressed or failed to meet past deadlines.

• Consciousness
• Daydreaming
• Concentration
• Mind wandering

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Understanding the behavioral and neurocognitive relation between mind wandering and learning

In the last decade, tremendous advances have been made in the effort to understand mind wandering, yet many questions remain unanswered. Chief among them is how mind wandering relates to learning. Insofar as mind wandering has been linked to poor learning, finding ways to reduce the propensity to mind wander could potentially improve learning. Two experiments were conducted to examine this. The first experiment evaluated how difficulty of the to-be-learned materials affected one’s tendency to mind wander and revealed that people mind wandered when there was a mismatch between their level of expertise and the difficulty of materials studied. The second experiment compared whether participants were more likely to mind wander in blocked or interleaved conditions and showed that participants were more likely to mind wander when materials were presented in a blocked fashion. Together, these results indicate that techniques such as studying materials specific to one’s own level of mastery or changing the way in which one studies might reduce mind wandering and improve learning. Of equal importance is the question of what happens on in the brain when a person mind wanders. While the effect of mind wandering on early sensory processing is known, the impact it has on learning-related processing is not. In two event-related potential (ERP) experiments, participants were asked to report whether they were mind wandering or not while studying materials they were later tested on. Analyses revealed that elaborative semantic processing – indexed by a late, sustained slow wave that was maximal at posterior parietal electrode sites – was attenuated when participants mind wandered. Crucially, the pattern when people were on task rather than mind wandering was similar to the subsequent memory effect previously reported by other memory researchers, suggesting that mind wandering disrupts the deep level of processing required for learning.

• Cognitive psychology
• Learning, Psychology of
• Cognitive neuroscience

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Frontiers for Young Minds

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The Wandering Mind: How the Brain Allows Us to Mentally Wander Off to Another Time and Place

A unique human characteristic is our ability to mind wander—these are periods of time when our attention drifts away from the task-at-hand to focus on thoughts that are unrelated to the task. Mind wandering has some benefits, such as increased creativity, but it also has some negative consequences, such as mistakes in the task we are supposed to be performing. Interestingly, we spend up to half of our waking hours mind wandering. How does the brain help us accomplish that? Research suggests that when we mind wander, our responses to information from the external world around us are disrupted. In other words, our brain’s resources are shifted away from processing information from the external environment and redirected to our internal world, which allows us to mentally wander off to another time and place. Even though we pay less attention to the external world during mind wandering, our ability to detect unexpected events in our surrounding environment is preserved. This suggests that we are quite clever about what we ignore or pay attention to in the external environment, even when we mind wander.

How Do Scientists Define Mind Wandering?

Imagine this: you are sitting in a classroom on a sunny day as your science teacher enthusiastically tells you what our brain is capable of doing. Initially, you pay close attention to what the teacher is saying. But the sound of the words coming out of her mouth gradually fade away as you notice your stomach growling and you begin to think about that delicious ice cream you had last night. Have you ever caught yourself mind wandering in similar situations, where your eyes are fixed on your teacher, friends, or parents, but your mind has secretly wandered off to another time and place? You may be recalling the last sports game you watched, or fantasizing about going to the new amusement park this upcoming weekend, or humming your favorite tune that you just cannot get out of your head. This experience is what scientists call mind wandering, which is a period of time when we are focused on things that are not related to the ongoing task or what is actually going on around us (as shown in Figure 1 ).

• Figure 1 - Real-world example of on-task and mind wandering states among students in a classroom.
• In a science class in which the teacher asks a question about the brain, some students may be focused on what is being taught, while others may be thinking about yesterday’s basketball tournament, humming their favorite tune, or thinking about getting ice cream after school. The students thinking about the brain during class would be considered to be “on task,” while students thinking about things unrelated to the brain would be considered to be “mind wandering.”

Our Tendency to Mind Wander

Humans on average spend up to half of their waking hours mind wandering. There are differences across individuals in their tendency to mind wander and many factors that affect this tendency. For instance, older adults on average tend to mind wander less than younger adults. Also, individuals who are often sad or worried mind wander more frequently compared with individuals who are happy and have nothing to worry about. We also mind wander more when we perform tasks that we are used to doing, compared with when we perform novel and challenging tasks. There are also different types of mind wandering. For example, we may sometimes mind wander on purpose when we are bored with what we are currently doing. Other times, our mind accidentally wanders off without us noticing.

What are the Pros and Cons of Mind Wandering?

Since we spend so much time mind wandering, does this mean that mind wandering is good for us or not? There are certainly benefits to mind wandering. For example, one of the things the mind does when it wanders is to make plans about the future. In fact, we are more likely to make plans when we mind wander than we are to fantasize about unrealistic situations. Planning ahead is a good use of time as it allows us to efficiently carry out our day-to-day tasks, such as finishing homework, practicing soccer, and preparing for a performance. When mind wandering, we are also likely to reflect upon ourselves. This process of thinking about how we think, behave, and interact with others around us is a crucial part of our self-identity. Mind wandering has also been tied to creative problem-solving. There are times when we get stuck on a challenging math problem or feel uninspired to paint or make music, and research suggests that taking a break from thinking about these problems and letting the mind wander off to another topic may eventually lead to an “aha” moment, in which we come up with a creative solution or idea.

However, mind wandering can also have negative outcomes. For example, mind wandering in class means you miss out on what is being taught, and mind wandering while doing your homework may result in mistakes. Taken to an extreme, people who are diagnosed with depression constantly engage in their own thoughts about their problems or other negative experiences. In contrast, individuals diagnosed with attention-deficit/hyperactivity disorder who continually change their focus of attention may have a hard time completing a task. Taken together, whether mind wandering is good or bad depends on when we mind wander and what we mind wander about [ 1 ].

Scientific Measures of Mind Wandering

If you were to conduct an experiment, how would you measure mind wandering? Scientists have come up with several methods, one of which is called experience sampling . As research volunteers are doing a computer task in a laboratory, or as they are doing chores in their day-to-day lives, they are asked at random intervals to report their attention state. That is, they have to stop what they are doing and ask themselves what they were thinking about in the moment: “Was I on-task?” (that is, was I paying attention to the task-at-hand) or “Was I mind wandering?” (that is, did my mind wander off to another time and place). Therefore, experience sampling samples the volunteer’s in-the-moment experience, allowing scientists to understand how frequently people mind wander and how mind wandering affects the way people interact with their environments.

Scientists also study mind wandering by recording electroencephalogram (EEG) , a test that measures the electrical activity of the brain. This electrical activity, which looks like wavy lines during an EEG recording (see Figure 2 , Step 2), is observed in all parts of the brain and is present throughout the day, even when we are asleep. Measurements of the brain’s electrical activity help scientists understand how the brain allows us to think, speak, move, and do all the fun and creative and challenging things that we do! In order to record EEG, scientists place special sensors called electrodes on the scalp of a volunteer ( Figure 2 , Step 1), with each electrode recording activity of numerous neurons (brain cells) in the area under the electrode ( Figure 2 , Step 2). Scientists then examine the brain’s activity in response to images (such as a picture of a basketball in Figure 2 ) or sounds presented to the volunteer. The scientists present the same sound or picture to the volunteer multiple times and take the average of the brain’s activity in response to the image or sound, because that method results in a better EEG signal. The averaged brain activity produces something called an event-related potential (ERP) waveform that contains several high and low points, called peaks and troughs ( Figure 2 , Step 3), which represent the brain’s response to the image or sound over time. Some commonly seen peaks and troughs are assigned specific names as ERP components. For instance, a peak that occurs around 300 ms (only 3/10 of a second!) following the presentation of a picture or a sound is often called the P300 ERP component. Based on decades of research, scientists have shown that these ERP components reflect our brain’s response to events we see or hear. The size of the ERP components (measured in voltage) reflects how strong the response is, while the timing of these ERP components (measured in milliseconds) reflects the timing of the response. Now, PAUSE! I would like you to ask yourself, “Was I paying full attention to the previous sentence just now, or was I thinking about something else?” This is an example of experience sampling. And as you may realize now, when we are asked about our current attention state, we can quite accurately report it.

• Figure 2 - Recording electroencephalogram (EEG) in humans.
• Step 1. To record EEG, electrodes are attached to a cap that is placed on the scalp of a research volunteer. Step 2. Each wavy line represents the amount of activity recorded by each electrode. Research volunteers are usually presented with some images (e.g., a basketball) or sounds a number of times while their brain activity is being recorded. Step 3. Scientists calculate the average EEG activity across multiple presentations of the same picture/sound. This results in an Event-Related Potential (ERP) waveform, where time (in milliseconds) is plotted on the x-axis and the voltage (in microvolts, indicating the size of the ERP components) is plotted on the y-axis. On the x-axis, 0 indicates the time at which the stimulus (e.g., image of a basketball) was presented. The ERP waveforms contain multiple high and low points, called peaks and troughs. Some of the peaks and troughs are given specific labels. For example, the peak that occurs around 300 ms after an image is presented is often called the P300 ERP component.

What Happens to Our Interaction with the Environment When We Mind Wander?

Scientists have proposed an idea—called the “Decoupling Hypothesis”—stating that during mind wandering, the brain’s resources are shifted away from our surrounding environment and are redirected to our internal world in order to support our thoughts [ 2 ]. This hypothesis assumes that the brain has a certain amount of resources, which means that once mind wandering has used the resources it needs to focus on our thoughts, only a limited amount of brain resources remains for responding to our surrounding environment.

To test this hypothesis, scientists combined experience sampling with EEG to explore how mind wandering affects our interaction with the environment. One of the first studies to test this hypothesis asked research volunteers to categorize a series of images by responding whenever they saw rare targets (e.g., images of soccer balls) among a whole bunch of non-targets (e.g., images of basketballs). Throughout the task, EEG was recorded from the volunteers, and they were also asked at random times to report their attention state as “on task” or “mind wandering.” Based on their EEGs and experience sampling reports, scientists found that the brain’s response to the non-targets was reduced during periods of mind wandering compared with periods of being on task [ 3 ]. This can be seen in Figure 3A , where there is a smaller P300 ERP component during mind wandering (the green lines) compared with the P300 ERP component during the time when the volunteer was on task (the gray line). The data suggest that the brain’s response to events happening in our environment is disrupted when we engage in mind wandering.

• Figure 3 - Mind wandering affects our ability to process events in the environment.
• A. The brain’s processing of external events (e.g., images of basketballs and soccer balls) is reduced during periods of mind wandering. This is indicated by the smaller P300 ERP component during mind wandering (green lines) compared with on-task (gray line). The ERP waveform was recorded from the electrode site circled in red, which is located on the back of the head. B. Mind wandering impairs our ability to monitor our own performance, making it more likely that we will make mistakes. This is shown by the smaller feedback error-related negativity ERP component, a trough occurring around 250 ms, for mind wandering (green line) compared with on-task (gray line). The ERP waveform was recorded from the electrode site circled in red, which is located near the front of the head.

Have you ever noticed that if your mind wanders while you are doing homework, you are more likely to make mistakes? Many experiments have also shown that this happens! This led some scientists to question what is happening in the brain when we make mistakes. They specifically measured something called the feedback error-related negativity ERP component, which gives scientists an idea of how closely we are monitoring the accuracy of our responses when we perform a task. The scientists found that the feedback error-related negativity ERP component was reduced during mind wandering compared with on-task periods, as shown in Figure 3B . This suggests that mind wandering negatively affects our ability to monitor our performance and adjust our behavior, making it more likely that we will make mistakes [ 4 ]. All of these studies provide evidence supporting the hypothesis that when the mind wanders, our responses to what is going on in the environment around us are disrupted.

Does Mind Wandering Impair all Responses to the Environment?

At this point, you may wonder: are all responses to the world around us impaired during mind wandering? This seems unlikely, because we are usually quite capable of responding to the external environment even when we mind wander. For example, even though we may mind wander a lot while walking, most of us rarely bump into things as we walk from place to place. A group of scientists asked the same question and looked specifically at whether we can still pay attention to our environment at some level even when we are mind wandering. To test this question, research volunteers were asked to read a book while they were listening to some tones unrelated to the book. Most of the tones were identical, but among these identical tones was rare and different tone that naturally grabbed the attention of the volunteers. These scientists found that the volunteers paid just as much attention to this rare tone when they were mind wandering compared to when they were on task. In other words, our minds appear to be quite smart about which attention processes to disrupt and which processes to preserve during mind wandering. Under normal circumstances, our minds ignore some of the ordinary events in our environment in order for us to maintain a train of thought. However, when an unexpected event occurs in the environment, one that is potentially dangerous, our brain knows to shift our attention to the external environment so that we can respond to the potentially dangerous event. Imagine walking down the street and thinking about the movie you want to watch this weekend. While doing this, you may not clearly perceive the noise of the car engines or the pedestrians chatting around you. However, if a car suddenly honks loudly, you will hear the honk immediately, which will snap you out of your mind wandering. Therefore, even when the mind is wandering, we are still clever about what we ignore and what we pay attention to in the external environment, allowing us to smartly respond to the unusual, or potentially dangerous, events that may require us to focus our attention back on the external environment.

In summary, the brain appears to support mind wandering by disrupting some of the brain processes that are involved in responding to our surrounding external environment. This ability is important for protecting our thoughts from external distractions and allowing us to fully engage in mind wandering. We are only beginning to understand this mysterious experience of thinking, and scientists are actively researching what goes on in the brain when we mind wander. Increasing our knowledge about mind wandering will help us better understand how to take advantage of its benefits while avoiding the problems linked to mind wandering.

Mind Wandering : ↑ Periods of time when an individual is thinking of something that is unrelated to the task he/she is performing.

Experience Sampling : ↑ A scientific method in which a person is asked to report their experience; that is, whether he or she is paying attention or mind wandering at random intervals in the laboratory setting or in the real world.

Electroenceph-Alogram (EEG—“elec-tro-en-sef-a-lo-gram”) : ↑ Electrical activity of many neurons in the brain that is measured by electrodes placed on the scalp.

Event-Related Potential (ERPs) : ↑ Peaks or troughs in the averaged EEG signal that reflect the brain’s responses to events we see or hear.

P300 : ↑ An ERP component that typically peaks around 300 ms (therefore “300”) after a person sees a picture or hears a sound. It reflects the brain’s processing of the information that is seen or heard. an ERP component that typically peaks around 300 ms (therefore “300”) after a person sees a picture or hears a sound. It reflects the brain’s processing of the information that is seen or heard.

Feedback Error-Related Negativity : ↑ An ERP component that reflects how much a person is monitoring the accuracy of his/her performance.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

[1] ↑ Smallwood, J., and Andrews-Hanna, J. 2013. Not all minds that wander are lost: the importance of a balanced perspective on the mind-wandering state. Front. Psychol. 4:441. doi:10.3389/fpsyg.2013.00441

[2] ↑ Smallwood, J. 2013. Distinguishing how from why the mind wanders: a process-occurrence framework for self-generated mental activity. Psychol. Bull. 139(2013):519–35. doi:10.1037/a0030010

[3] ↑ Smallwood, J., Beach, E., Schooler, J. W., and Handy, T. C. 2008. Going AWOL in the brain: mind wandering cortical analysis of external events. J. Cogn. Neurosci. 20:458–69. doi:10.1162/jocn.2008.20037

[4] ↑ Kam, J. W. Y., Dao, E., Blinn, P., Krigolson, O. E., Boyd, L. A., and Handy, T. C. 2012. Mind wandering and motor control: off-task thinking disrupts the online adjustment of behavior. Front. Hum. Neurosci. 6:329. doi:10.3389/fnhum.2012.00329

META Lab | Psychological & Brain Sciences | UC Santa Barbara

Mind wandering.

 Our mind-wandering research can be roughly divided into five categories.

Related Questions

Selected publications.

• Unaware yet reliant on attention: Experience sampling reveals that mind-wandering impedes implicit learning
• The retention of manual flying skills in the automated cockpit
• An Antidote for Wandering Minds
• The Decoupled Mind: Mind-wandering Disrupts Cortical Phase-locking to Perceptual Events
• The Middle Way: Finding the Balance between Mindfulness and Mind-Wandering
• Insights from Quiet Minds: The Converging Fields of Mindfulness and Mind-Wandering
• Thoughts in Flight: Automation Use and Pilots’ Task-Related and Task-Unrelated Thought
• Window to the Wandering Mind: Pupillometry of Spontaneous Thought While Reading
• The default modes of reading: Modulation of posterior cingulate and medial prefrontal cortex connectivity associated with subjective and objective differences in reading experience
• The silver lining of a mind in the clouds: Interesting musings are associated with positive mood while mind-wandering
• Unnoticed intrusions: Dissociations of meta-consciousness in thought suppression
• Thinking one thing, saying another: The behavioral correlates of mind-wandering while reading aloud
• Mindfulness Training Improves Working Memory Capacity and GRE Performance While Reducing Mind Wandering.
• Escaping the here and now: Evidence for a role of the default mode network in perceptually decoupled thought
• Disentangling Decoupling: Comment on Smallwood
• Mindfulness and mind-wandering: Finding convergence through opposing constructs
• Inspired by Distraction Mind Wandering Facilitates Creative Incubation
• Insulation for daydreams: a role for tonic norepinephrine in the facilitation of internally guided thought
• The role of mind-wandering in measurements of general aptitude.
• Cooperation between the default mode network and the frontal–parietal network in the production of an internal train of thought
• Back to the future: Autobiographical planning and the functionality of mind-wandering
• Pupillometric Evidence for the Decoupling of Attention from Perceptual Input during Offline Thought
• Medicine for the wandering mind: Mind wandering in medical practice
• Meta-awareness, perceptual decoupling and the wandering mind
• Threatened to distraction: Mind-wandering as a consequence of stereotype threat
• Catching the mind in flight: Using behavioral indices to detect mindless reading in real time.
• Self-reflection and the temporal focus of the wandering mind.
• Out for a smoke: The impact of cigarette craving on zoning out while reading
• Slow fluctuations in attentional control of sensory cortex
• Eye movements during mindless reading.
• Mind-Wandering
• Experience sampling during fMRI reveals default network and executive system contributions to mind wandering
• Lost in the Sauce The effects of alcohol on mind wandering
• When attention matters: the curious incident of the wandering mind
• Going AWOL in the brain: mind wandering reduces cortical analysis of external events
• Counting the cost of an absent mind: Mind wandering as an underrecognized influence on educational performance
• The lights are on but no one’s home- the decoupling of executive resources when the mind-wanders
• Mind-wandering with and without awareness: An fMRI study of spontaneous thought processes
• The restless mind
• Zoning out while reading: Evidence for dissociations between experience and metaconsciousness.
• Pushing the Limits: Cognitive, Affective, & Neural Plasticity Revealed by an Intensive Multifaceted Intervention
• Early event-related brain potentials and hemispheric asymmetries reveal mind-wandering while reading and predict comprehension
• Language facilitates introspection: verbal mind-wandering has privileged access to consciousness
• Mindfulness in education: Enhancing academic achievement and student well-being by reducing mind-wandering
• Can I get me out of my head? Exploring strategies for controlling the self-referential aspects of the mind-wandering state during reading
• Meditation training influences mind wandering and mindless reading.
• Mind wandering minimizes mind numbing: Reducing semantic-satiation effects through absorptive lapses of attention.
• Mind-wandering and meta-awareness in hypnosis and meditation: Relating executive function across states of consciousness.
• Mind wandering “Ahas” versus mindful reasoning: alternative routes to creative solutions
• Mind Wandering While Driving What Does it Mean and What do we do about it?
• Motivating meta-awareness of mind wandering: A way to catch the mind in flight?
• The Richness of Inner Experience: Relating Styles of Daydreaming to Creative Processes.
• The science of mind wandering: empirically navigating the stream of consciousness
• Stimulating minds to wander
• Vigilance impossible: diligence, distraction, and daydreaming all lead to failures in a practical monitoring task
• Tracking Distraction: The Relationship Between Mind-Wandering, Meta-Awareness, and ADHD Symptomatology
• Young & restless: Validation of the Mind-Wandering Questionnaire (MWQ) reveals disruptive impact of mind-wandering for youth
• States of mind: Characterizing the neural bases of focus and mind-wandering through dynamic functional connectivity

Researchers

Jonathan Schooler

My lab’s research takes a “big picture” perspective in attempting to understand the nature of mental life, and in particular consciousness. Combining empirical, philosophical, and contemplative traditions, we address broad questions that cross traditional disciplinary boundaries.

James Elliott

James Elliott, Ph.D, is a cognitive neuroscientist with a background in behavioral, EEG, and fMRI methodologies. He has a keen interest in exploring how traditional meditation techniques can be used to help inform a scientific understanding of consciousness. 

Michael Mrazek

Michael Mrazek, Ph.D. is the director of research at the University of California's Center for Mindfulness & Human Potential. His research identifies innovative ways to increase the effectiveness of mindfulness training, particularly in high schools. He also tests the limits of how much a person can improve through intensive evidence-based training programs that target health, mindfulness, and self-control. 

Madeleine Gross

Madeleine studies the psychological basis of creative idea generation and insight. Using eye tracking technology, she also investigates how inter-individual differences in eye movement behavior may relate to dopamine-related cognition and personality traits, such as curiosity, schizotypy, and creativity.

Alissa Mrazek

Alissa Mrazek is a Research Assistant Professor in the Department of Psychology at UT Austin as well as a long-time collaborator with the META Lab. Alissa conducted a post-doctoral fellowship at the Center for Mindfulness and Human Potential with Dr. Jonathan Schooler from 2016-2020. Before working at UCSB, Alissa completed her Ph.D. in 2016 at Northwestern University where she began appreciating the synergistic benefits of integrative interventions—particularly when combining mindset training with strategy training. 

Claire Zedelius

One line of Claire's research focuses on the role meta-awareness plays in the dynamic changes between states of mind wandering and focused attention. Another line examines the relationship between different types of mind wandering, creativity and curiosity. 

Dharma Lewis

Dharma is a Mexico City native who is passionate about education and outreach. She earned her Biopsychology B.S. at UCSB where she studied the link between mindfulness, growth mindset, and mind-wandering as META Lab Manager. Her work currently focuses on pedagogical implications of meta-cognition, and the role of culture and mindsets in mindfulness.

Anusha Garg

Anusha studies the mechanisms and content of mind wandering. In the past, she's worked on assessing the content of the spontaneous stream of consciousness. She's currently investigating the differences between the quality of thoughts obtained during think aloud and silent mind wandering protocols. 

Shivang Shelat

Shivang's interests lie in interactions between mind-wandering, memory, and attentional capture. He also uses principles in attention neuroscience to better understand human-computer interactions. He is co-advised by Barry Giesbrecht.

My name is Jinny Kim, and I am a 3rd year Biopsychology major and Applied Psychology minor. I am assisting James Elliott regarding fluctuations of experience and EEG during meditation. My specific interests are dream analysis and psychotherapy for criminals.

Research Collaborators

Jonathan smallwood.

What is the Research on Daydreaming

Can You Focus Your Daydreaming

Dyslexic Advantage Mind Wandering with Dr Jonathan Schooler

How Is Day Dreaming Useful?

It Took You Three Attempts to Read That Simple Paragraph Here's Why 1

Mind Wandering and Meta-Awareness

Wegstock 18 Mind Wandering Jonathan Schooler

What is Day Dreaming?

What's the connection between daydreaming and ADHD 1

Who daydreams and what does it mean?

• U.S. Department of Education, Institute of Educational Science. (2011-2015) Mind-wandering During Reading

Longitudinal Associations between Metacognition and Spontaneous and Deliberate Mind Wandering During Early Adolescence

Affiliations.

• 1 Collaborative Innovation Center of Assessment Toward Basic Education Quality, Beijing Normal University, Beijing, China.
• 2 Faculty of Psychology, Beijing Normal University, Beijing, China.
• 3 Department of Psychology, School of Sociology, China University of Political Science and Law, Beijing, China. [email protected].
• PMID: 38600263
• DOI: 10.1007/s10964-024-01979-8

Although metacognition plays a pivotal role in theoretical accounts of mind wandering, their longitudinal relationships have not yet been investigated during the important developmental period of early adolescence. This study aimed to examine the developmental trajectories of spontaneous and deliberate mind wandering and the dynamic associations between metacognition and two types of mind wandering in early adolescence. A sample of 4302 Chinese students beginning in Grade 4 (47.4% female; initial M age = 9.84, SD age = 0.47) completed questionnaires on five occasions over 2.5 years. The results showed that deliberate mind wandering, but not spontaneous mind wandering, gradually increased from Grade 4 to Grade 6. Metacognition was negatively related to spontaneous mind wandering but positively related to deliberate mind wandering. These findings provide empirical evidence for theoretical viewpoints from both individual differences and developmental perspectives.

Keywords: Early Adolescence; Longitudinal association; Metacognition; Mind wandering; Trajectory.

© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Grants and funding

• 23BSH124/National Social Science Foundation of China

ASU honors student explores the depths of neuroscience, machine learning

Katrina Ager is earning a Bachelor of Science in neuroscience.

Editor’s note:  This story is part of a series of profiles of  notable spring 2024 graduates .

Katrina Ager's academic journey has been fueled by a deep curiosity about the human mind. 

From understanding cognition to unraveling behavior, she has been enthralled by the complexities and mathematical nature of the brain. This passion led her to pursue a Bachelor of Science in neuroscience from ASU’s Department of Psychology, a unit within The College of Liberal Arts and Sciences, as well as certificates in applied business data analytics and computational life sciences .

During her academic tenure, Ager completed an internship at the world-famous Allen Institute for Neural Dynamics , where she contributed to the OpenScope Databook , a resource that addresses reproducibility issues and teaches computational analysis techniques to analyze publicly available data. This experience amplified her passion, particularly at the intersection of neuroscience and technologies like machine learning.

"There is so much about the brain that remains a mystery, and it may not be understood in my lifetime, but it is something that will captivate me for the rest of my life," Ager said. “I have always been fascinated by the human condition: what it means to think, feel, love, interact, contemplate and experience life in deep ways.”

A member of Barrett, The Honors College , Ager excelled, maintaining a 4.0 GPA and earning a place on the Dean's List each semester. Financial assistance from programs like ASU’s President Barack Obama Scholars Program and the New American University President’s scholarship supported her academic journey.

Read more about Ager’s ASU experience and plans moving forward.

Question: What’s the best piece of advice you’d give to those still in school?

Answer: Never judge anyone before you get to know them and try to be curious about other people's experiences and perspectives. I have met some of my best friends and learned so much from people I might never have interacted with if I had not actively tried to get to know my peers. I believe you can learn something from everyone you meet, and it's important to be open to new perspectives and friendships during a time when everyone is learning about themselves and life.

Question: Was there a specific professor or mentor that significantly impacted your time at ASU?

Answer: Professor Samuel McClure has, without a doubt, been the person who has taught me the most important lessons and supported me throughout my academic career. If you talk to anyone who has taken his class, they would agree that Dr. McClure is a person who truly cares about his students and provides the support they need to excel academically and in life. Dr. McClure has continuously inspired me, shown me the value of working hard and staying curious, and helped me achieve my goals inside and outside of the classroom. I think this campus is a better place with people like him, and I am extremely grateful to have had his mentorship over the past four years.

Question: Were there any specific experiential learning opportunities that significantly influenced your academic and personal growth during your time at ASU?

Answer: Working as a lab manager for Dr. Gene Brewer ’s Memory and Attention Control Lab at ASU has significantly impacted my academic journey. Exploring different research labs as an undergraduate was essential to figuring out what interested me. I am fortunate to be surrounded by a supportive and caring team at the MAC Lab, and I genuinely look forward to going to work and interacting with my lab mates. Being a lab manager has contributed to my understanding of how research is conducted, taught me how to ask powerful questions to gain insights and how to work effectively with a team. 

Question: What did your honors thesis explore?

Answer: For my honors thesis, I worked under the mentorship of Dr. McClure to understand how a new machine learning model lets us measure neurotransmitter concentrations in the human brain. The model was developed by Dr. Read Montague at Virginia Tech, and his team has been incredibly supportive in allowing me to use their model and data for my thesis. This research is groundbreaking, as it can track sub-second changes in concentrations of neurotransmitters such as dopamine, norepinephrine and serotonin.

Question: What is something you learned while at ASU — in the classroom or otherwise — that surprised you or changed your perspective?

Answer: One thing that has changed my perspective has been recognizing the importance of interacting with my peers, truly listening when they speak and approaching everything with a curious mind. During my sophomore year, I took a special topics class on dopamine with Professor Samuel McClure and Assistant Research Professor Kimberlee D’Ardenne that revealed the importance of community for me. It was one of the first in-person classes I had after being on Zoom for a year-and-a-half due to COVID, and everyone was extremely eager to connect face-to-face. Aside from being very informative and interesting academically, the happiness, support and genuine interest in connection among people in the class were unmatched. 

That excitement bred many interesting conversations and led to a deeper understanding about the topics being discussed. I absorbed so much knowledge from listening to my friends in the class. It has made me put effort into approaching other areas of my life with the same curiosity. That class has been instrumental in my education because it made me realize that no matter what I end up doing with my degree, as long as I am surrounded by supportive, curious and passionate people, I will be just fine.

Question: Can you share more about your plans after graduation?  

Answer: I am excited to have recently accepted a position at the Dynamical Inference Lab at the Institute of Computational Biology of Helmholtz Munich. Under the mentorship of Steffen Schneider, I will be gaining experience in software development, computational neuroscience and machine learning. I also plan to simultaneously pursue a master’s degree while I am working abroad. I am eager to move to Germany in the fall and will be staying for one to two years. In the future, I hope to transition into industry and work for a company — or start one myself — that is grounded in a humanitarian mission while being on the cutting edge of science and technology.

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