6
Attention

Attention

Attention is notoriously hard to define, but is essential for learning to occur. Our attentional resources are limited and must be directed towards the most important information.

“Pay attention!” “You’re not paying attention.” “If only you had been paying attention…”

Surely, you’ve heard or even said such things many times. But what is this attention that we speak of? Do we have an agreed-upon definition of attention? William James (often known as the father of psychology) seemed to think that we do:

Everyone knows what attention is. It is the taking possession by the mind, in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thought. (1890, pp. 403–404)

William James

In the introduction to his book on attention published more than a century later, on the other hand, cognitive psychologist Hal Pashler took the opposite stance:

The present book takes a more empirical and more skeptical tack, assuming instead that no one knows what attention is. (1999, p. 1)

Hal Pashler

In fact, many researchers are indeed unsure about the nature of attention – though they have tried to capture and define this elusive concept. Is attention a physical thing? What does it mean to “pay” attention – is it like a fee? What does it mean to “give something your full attention”? Is attention a cause (e.g., something that helps learning), or an effect (e.g., something that is increased by learning; Anderson, 2011)?

Attention is a cognitive process that is very hard to pin down.

It turns out that attention is very hard to pin down – so hard that certain contemporary researchers have thrown up their hands and decided that perhaps attention as it is currently defined cannot be studied: Britt Anderson discussed this in his provocatively titled article, “There is no Such Thing as Attention”:

… despite all this time and the many investigations, our knowledge of attentional phenomena is little changed from that of the ancient Greeks. (2011, p. 1)

Britt Anderson

Nevertheless, most cognitive psychologists do agree that attention is an important concept to teach their students. The most commonly accepted definition of attention among cognitive psychologists is focus on a specific stimulus, or the ability to focus on specific stimuli or locations (if talking about an individual difference).

Attention is typically thought of as a “limited-capacity resource” (Moray, 1967). You might think of your financial budget as an analogy. You have a certain amount of money, and you apportion it to different expenses. If you spend a lot of money on a dress this month, you might not be able to eat out. If you had bought the cheap dress instead, you may have been able to afford a meal at a fancy restaurant.

Attention is typically thought of as a “limited-capacity resource.”

The same can be said of attention, according to the limited capacity resource model: you have a certain amount of attention, and you apportion it to different tasks. If you’re doing a really difficult task that requires a lot of attention to be paid to it, you won’t have much attention left for anything else. If you’re doing an easy task, you might have some attention “left over” for other tasks.

Cognitive load

Cognitive Load Theory has helped teachers focus on the efficiency of their explanations to avoid any inadvertent overload.

The idea that we have limited attentional resources places a certain limitation on how much information we can process at any one time. The amount of information requiring our attention is known in the literature as “cognitive load,” and an overabundance of it is known as “cognitive overload” (Sweller & Chandler, 1994). Two theories of cognitive load have dominated the field: one known simply as Load Theory (Lavie, Hirst, De Fockert, & Viding, 2004), and the other as Cognitive Load Theory (CLT; Chandler & Sweller, 1991).

Lavie’s Load Theory distinguishes between different types of load: perceptual load, which describes the amount of bottom-up information that has to be processed (see Chapter 5), and cognitive load, which describes the demand on working memory (see below). This theory is rather nuanced, and allows us to disentangle positive and negative impacts of load on learning. For example, a recent study showed that while increased perceptual load decreased memory for an advertisement, increased cognitive load actually increased learning (Wang & Duff, 2016).

Sweller’s Cognitive Load Theory is more familiar to teachers, as much of the work on this theory has been applied directly to education (e.g., Chandler & Sweller, 1991; Chang & Ley, 2006). The basic idea behind this theory is that since we can only process a limited amount of information at any one time, it is very important to avoid overloading attention with unnecessary or extraneous material. This has implications for how we design presentations, write textbooks, and create multimedia materials (Mayer & Moreno, 2003). In Chapters 9 and 11, we talk more about how to reduce cognitive overload.

The myth of multi-tasking

You probably don’t realize this, but an important feature of your attentional mechanism – no matter which of the theories above you subscribe to – is being able to selectively focus on just one stimulus (a location, object, or message) at any one time.

An important feature of attention is the ability to selectively focus on just one stimulus at a time.

We are now going to tell you something you will have trouble believing. The data point strongly to the conclusion that it is almost impossible to pay attention to more than one thing at the exact same time. You might protest – “but I can drive while listening to music, I can eat while reading a book, I can have the TV on in the background while studying these lecture notes.” I wonder how many of you have some kind of distraction – be it the TV, music, kids, or a partner – present while you are reading this sentence? You may not think that the thing you listed is a distraction at all. Perhaps it’s something you are used to having on in the background (e.g., the TV), or something that you feel is complementary rather than interfering with this material (e.g., music).

Well, it turns out that your intuitions are almost certainly wrong. If you are paying attention to this sentence, you’re probably not meaningfully processing the music. If you are able to tell me in detail what is happening on the TV, you probably couldn’t give me a good summary of what you’ve just read – at least, not as good as if you were fully focusing on the one task. But if you still feel like you can do these things, then you may have figured out how to switch back and forth between the two tasks very quickly. When you feel like you’re multi-tasking, or paying attention to two things at once, you’re actually switching back and forth between the two things you’re trying to pay attention to, and as we’ll learn later, that diminishes efficiency for both of the tasks.

One important aspect of attention is the finding that going back and forth between two different tasks involves switch costs that decrease efficiency and slow down reaction speeds in both tasks (Gopher, Armony, & Greenshpan, 2000).

Here is a very simple yet powerful demonstration of task switching costs that you can try out on your own or – if you are a teacher – with a class of students. This is a demonstration that students can take part in alone, in pairs, in groups of three, or as a class with one student volunteering to be the “case study” that the rest of the class observes. In this demonstration, students are invited to time themselves performing two separate tasks, and then attempting to switch back and forth between the two tasks.

Switching between two tasks decreases efficiency and slows down reaction speeds in both tasks.

The demonstration

The demonstration involves doing three very short tasks:

Yep, that’s it! If you want to do this task on yourself, you can simply do each of the three tasks, and time yourself completing each one. Try it right now – before you read the rest of the chapter.

How long did each of the three tasks take you to complete? I (Yana) had 27 students in my online class complete the three tasks alone and tell me the time it took them to complete each task (in seconds) as part of a weekly quiz. Here were the results:

Importantly, every single student took longer to complete the combined Task 3 than the sum of the time it took them to complete both of the other tasks (Task 1 + Task 2). So, every student in my sample experienced task-switching costs.

If you want to use the demonstration as a classroom activity, you can try it out in various ways. In pairs, one student can act as the timer and the other as the participant (this will take about five minutes). Also in pairs, students can take turns to act as timer and participant (this will take about ten minutes, and is good for smaller groups if you want to generate sufficient data to analyze as a class). An alternative version that does not require students breaking out into groups is to ask one volunteer to demonstrate all three tasks in front of the class. Since task-switching costs in this paradigm are so robust, even a single-participant case study can serve to demonstrate the effect.

What drives attention towards learning?

The Increased Saliency Theory of attention states that attentional resources constantly shift around so that some things become more salient than others – that is, more noticeable or important. For instance, let’s say you’re looking at a Where’s Waldo? puzzle or Where’s Wally? puzzle (US and UK terminology for the game, respectively). Everyone is wearing the same kind of outfit as him, so it’s nearly impossible to find him. Your job is to direct your attention to Waldo, but your attention is being directed all over the picture because everyone looks like Waldo! Now imagine I remove the color from the image, except for the area in which you can find Waldo, so that everything except Waldo is in black and white. Bam! Now Waldo pops out.

The Increased Salience Theory describes attention in terms of this kind of pop-out effect – whatever it is we are currently paying attention to is highlighted in our minds. For instance, let’s say I ask you to count all of the things in your current location that are colored red. Isn’t it amazing that you can glance around and pick out those things, ignoring everything else? That is attentional focus due to increased salience.

In an educational context, the degree to which students are paying attention to what they are trying to learn can be determined to some extent by the saliency of the material.

The likelihood that a student will pay attention is determined in part by the saliency of the material.

This saliency can come from many sources: it can be coming from the student’s own motivation, the interest level of the material in terms of meaning, the way the information is presented by the teacher, or even more bottom-up features such as bright colors and loud sounds (see Chapter 5 for more on bottom-up and top-down processes).

Yana occasionally claps her hands or says a loud unexpected word in the middle of class to draw students’ attention back to the lesson! Megan sometimes says to her students, if she thinks they’re not fully attending to the lesson: raise your hand if you’re breathing. And then becomes silent. Some students chuckle and raise their hands. Some, who were only partially paying attention to the lesson, look around the room, a bit confused, while raising their hands. Finally, the remainder of students all of a sudden get the sense that a question was asked and realize they have shifted their attention to something else entirely!

Hidi and Harackiewicz (2000) distinguished between two types of interest that an individual can have in a subject: individual interest, and situational interest. Using this book as an example, individual interest is the extent to which you yourself are already interested in applying cognitive psychology to education, whereas situational interest is how absorbing our text is or how enjoyable you find the illustrations. In an educational setting, for example, a high school student may have a personal interest in gender, so they pay more attention in classes that are relevant to this topic than any other classes. Or, students might have a goal that is addressed by certain classes more than others – for example, they may be interested in a chemistry class if they plan to go on to medical school.

Situational interest, on the other hand, is how engaging the teacher makes the class. Situational interest can be increased through many different teaching techniques: for example, through clear communication of ideas targeted at the right difficulty level (Rotgans & Schmidt, 2011), social activities such as having students research information and then teach each other (Hidi, Weiss, Berndorff, & Nolan, 1998), and using concrete examples (Tapola, Veermans, & Niemivirta, 2013; see also Chapter 9). Both individual and situational interest affect the extent to which we pay attention in a learning situation. As teachers, we are in control of situational interest, but not of individual interest.

Both individual and situational interest affect the extent to which we pay attention in a learning situation.

Note that this is not the same thing as intrinsic versus extrinsic motivation, which, broadly speaking, describes whether students are driven by learning for its own sake, or external rewards and punishments (Reiss, 2012). This distinction is particularly important because extrinsic rewards and punishments can be detrimental to existing intrinsic motivation (Deci, Koestner, & Ryan, 1999; though, note that when there is a lack of intrinsic motivation, such as in dull tasks, extrinsic motivation can be helpful [Deci, Koestner, & Ryan, 2001]). On the other hand, situational interest has not been found to undermine inherent interest – on the contrary, situational interest can actually help maintain or even strengthen inherent interest (Hidi & Harackiewicz, 2000).

What are the consequences of not paying attention?

No matter how motivated you are, you must admit that sometimes you get distracted from what you are supposed to be doing or thinking about. When these distractions come from inside your head, psychologists call them mind-wandering (Smallwood & Schooler, 2006). Cognitive psychologists refer to things you are intending to be paying attention to as a “task set.” For instance, if your intention is to be reading this chapter, then your current task set is “reading the chapter.” If you start having unrelated or irrelevant thoughts while reading these words, such as “I wonder what I’ll be eating for dinner,” this would be classified as losing the task set of “reading the chapter.”

Mind-wandering involves getting distracted from a task by your own thoughts.

Mind-wandering levels vary depending on what the person is doing. Mind-wandering has an interesting relationship with task difficulty: people tend to mind-wander more when they are doing an easy task than when doing a difficult task (Forster & Lavie, 2009), but also more when they are doing a very difficult task (Feng, D’Mello, & Graesser, 2013). Because of these differences, as well as differences in methodologies for measuring mind-wandering (Weinstein, 2018), it is difficult and perhaps almost meaningless to give an “average” mind-wandering rate. However, researchers have proposed that about half the time, students are not paying attention to what the teacher is saying in class (Smallwood, Fishman, & Schooler, 2007).

Mind-wandering can be problematic because it can result in students missing important information.

Early in the 20th century, researchers tried to measure mind-wandering in the classroom. In 1941, Edmiston and Braddock had observers record whether students were attending to a lecture by identifying any behavior such as a “physical attitude” or “expression of the eyes” that suggested students were no longer attending to the lesson.

A student in Cohen et al.’s (1956) bell-pushing study

In 1956, Cohen, Hansel, and Sylvester put students in a classroom with bell-pushes every desk, and students were asked to push the bell to indicate that their minds had wandered away from the lecture; the information fed through to a light in an adjacent room, and the average number of mind-wandering reports were presented in the paper in five-minute increments. Cohen et al. reported that mind-wandering varied widely from student to student.

Most mind-wandering research has used adults as participants. However, children are thought to develop the ability to engage in self-regulated learning by the age of 11 (Roebers, 2006). Mrazek, Phillips, Franklin, Broadway, and Schooler (2013) gathered mind-wandering data from middle and high school students. This study demonstrated that students as young as those in 6th grade are able to accurately report on the focus of their thoughts. In addition, mind-wandering was also negatively related to comprehension in this young sample.

When we are trying to understand and learn, we need to combine whatever we are studying with our internal world. Mind-wandering can be problematic when it comes to education because it can result in students missing important information (Smallwood et al., 2007). The amount of mind-wandering students report during study correlates with later reading comprehension (Smallwood, McSpadden, & Schooler, 2008) and memory performance (Risko, Anderson, Sarwal, Engelhardt, & Kingstone, 2012), though it is important to note that this correlation does not mean that mind-wandering causes poor performance (see Chapter 2).

Finally, mind-wandering can occur not only during study, but also during a test. Students themselves believe that mind-wandering during a test leads to poor time management and possible exam failure (Ling, Heffernan, & Muncer, 2003).

Capacity of short-term memory

One area of intense research has focused around the capacity of short-term memory, not just in terms of time, but in terms of how many separate pieces of information can be stored in short-term memory for any one time. The simplest task used to measure the capacity of short-term memory is the “memory span task.” In the experiment, the experimenter will read out a series of digits to the participant, and the participant will try to repeat them back in the same order. If they succeed, the number of digits is increased for the next trial, until they are no longer able to correctly repeat back the numbers in order. So, if you correctly repeated back eight digits but failed when there were nine, you would be said to have a “digit span” of eight. Most people tend to have a digit span of five to nine items.

Only five to nine items? That seems like very little. However, our clever minds come to the rescue, as we have actually found a way to circumvent this limitation. Here’s how. Imagine we asked you to repeat back from memory the following string of letter and numbers, in this order:

It should be fairly obvious that if you tried to repeat this back without looking at the page, you wouldn’t get the whole string correct (but do try it for yourself!).

What if we rearranged these letter and numbers into something more meaningful?

All of a sudden, it’s a piece of cake! That’s because of something we call “chunking” (yes, that’s a real, scientific term). Chunking allows for more information to be stored in short-term memory, so that you’re still only remembering five to nine items, but each item contains more information. One subject, S. F., was able to increase his digit span to roughly 80 digits (Ericsson & Chase, 1982)! That’s right, the researcher read off 80 digits, and the subject was able to recite them back in the same order. This took hundreds of hours of practice across two years, and the subject had to chunk the numbers into meaningful units for himself (track times with which he was familiar). Of course, we don’t really need to increase our short-term memory capacities in this way, and increasing our digit span isn’t likely to help us learn and remember educationally relevant material.

However, while researchers originally thought of short-term memory as just a very small temporary storage capacity, after this initial approach cognitive psychologists realized that short-term memory actually did a lot more than simply store information. In addition to storage, our short-term memory processes also allow us to manipulate information (e.g., doing mathematical calculations in your head) and switch between tasks – though not as efficiently as if you were just doing one task at a time.

However, in the context of learning information in the long run, what’s most important is getting that information from short-term into long-term memory. Your short-term memory process essentially decides what’s worth keeping and what can be forgotten after the 15–30-second window (see Chapter 7).

Working memory

Cognitive psychologists have attempted to describe the processes involved in attention through a model called “working memory.” What do we mean by a model? A cognitive model can be thought of as a framework that defines various different processes that go on in the mind. In this particular case, it is a model that describes our ability to hold information for a short time, manipulate it, send it to/from long-term memory, and it can help us switch between tasks (though not particularly efficiently, as you read above). In particular, cognitive psychologists are interested in three key processes that they believe define working memory: the phonological loop, the visuospatial sketchpad, and the central executive (Baddeley & Hitch, 1974; Baddeley, 2003).

The phonological loop stores and also rehearses verbal/auditory information. “Rehearsal” is essentially just repeating things over and over in your head so that you can remember it for a little while. It’s a way of getting around the short time span of short-term memory, and you probably do this without realizing. Imagine you are on your smartphone looking up a phone number. But annoyingly, when you get to the number you can’t just tap it to make the call because it’s not in the right format (it’s not a clickable link). Instead, you have to remember the number while you switch from your browser app to your phone app and then type in the number. In order to hold the number in your mind, you start reciting it subvocally (in your head), “555 6792, 555 6792, 555 6792” until you’re finally able to type it in. When you’re reciting in this example, you’re using your phonological loop.

If your phonological loop is busy doing something else, though, it won’t help you retain information. What if I asked you to remember that phone number while repeating “the-the-the” out loud? What would happen is that you would have a harder time remembering the number, because your phonological loop was busy with the noise of “the-the-the” and so could not effectively rehearse the numbers you were trying to remember.

The visuospatial sketchpad, on the other hand, helps you store visual information and plan using visual imagery. The visuospatial sketchpad enables you to create mental maps and spatial images. For example, imagine I asked you how you get from your bedroom to your kitchen. You might answer this question by picturing yourself walking through your house from one room to the other. This imagination process is thought to utilize the visuospatial sketchpad.

The visuospatial sketchpad appears to work somewhat independently from the phonological loop. For example, if I was asking you to do a visual imagery task instead of remembering a phone number as in the previous example, you might be able to repeat the sound “the-the-the” and still do the visual imagery task; this suggests that the visuospatial sketchpad and phonological loop involve separate cognitive processes.

The third and final process of the working memory model is called the central executive. It is still not completely clear what this part of the model does, but it is generally thought to involve all of the remaining processes of working memory, and is very closely linked to attention: determining what specifically to focus on, determining what information to send to/from long-term memory, and interfacing between the phonological loop and visuospatial sketchpad.

Individual differences in attention

Many theories have tried to account for individual differences in attention and its components. One of the difficulties involved in making sense of these theories is that the terminology has evolved over the years. For example, the notion of mind-wandering has been mentioned in the educational literature since as early as the 19th century (Loisette, 1896). Researchers have called it different things throughout the years: goal neglect (Kane & Engle, 2003); stimulus-independent thought (Teasdale et al., 1995); day-dreaming (Schupak & Rosenthal, 2009); and absent-mindedness (Reason & Mycielska, 1982).

Regardless of the label used, the tendency to disengage from concentrating on a task differs from person to person and throughout the life span. For example, older adults tend to report less mind-wandering than younger adults (Jackson & Balota, 2012). Other things that may be related to mind-wandering are individual differences in distractibility (Forster & Lavie, 2014) and mood (negative mind-wandering leading to greater mind-wandering; Smallwood, Fitzgerald, Miles, & Phillips, 2009).

Mind-wandering also has a complex and heavily disputed relationship with individual differences in attention (McVay & Kane, 2012). Below we describe three theories that have attempted to account for individual differences in attention, and why some people might find it more difficult than others to direct and maintain focus.

Theory 1 of 3: Working memory capacity

As we described above, working memory allows you to juggle things in your head (such as if I ask you to multiply 15 by 7), and it allows you to remember the beginning of this sentence without glancing back up a few lines. The Working Memory Theory of attention states that the amount of “attentional resources” we have is dependent on how much information we can hold and manipulate at any one time. This theory is popular in educational contexts, as some studies have shown correlations between working memory capacity and academic performance (e.g., Gathercole, Pickering, Knight, & Stegmann, 2004).

Theory 2 of 3: Processing speed

The Processing Speed Theory involves describing our attentional resources in terms of how quickly we can process information (Kail & Salthouse, 1994). The idea is that we learn how to do very simple tasks very fast. These simple tasks could be something like recognizing shapes, colors, and letters. According to this theory, our attentional resources capacity is dependent upon how quickly we can do these simple tasks – the quicker we can process things, the better we can perform on tasks that require us to process multiple pieces of information. This is another theory that has been linked to education, with correlations between processing speed and academic achievement (e.g., Bull & Johnston, 1997).

Theory 3 of 3: Attentional control

The Attentional Control Theory, on the other hand, puts the onus on our ability to focus on whatever we choose in any given moment. According to this theory, those who have better attentional control are able to more effectively select what to focus on, and maintain this focus for longer without getting distracted or starting to mind-wander (McVay & Kane, 2009). Having said that, attentional control alone cannot account for all of the variation between individuals in terms of mind-wandering, suggesting that other factors are also at play (Stawarczyk, Majerus, Catale, & D’Argembeau, 2014).

It is far beyond the scope of this book for us to distinguish between these theories; in fact, no scientific consensus has yet been reached, so this would not even be possible. The big picture is that we know a number of factors related to attention can vary between individuals, and some or all of these may be related to academic achievement, though in complex and interconnected ways. However, these individual differences are to a large extent outside our control, and this is important to accept.

Recent interest in “brain training” indicates a desire to overcome some of these individual differences. The idea is that with practice, we can change our working memory capacity, processing speed, and/or attentional control. Based on early results suggesting this might be possible (Klingberg, Forssberg, & Westerberg, 2002), commercial companies created brain training products and promoted them with unsubstantiated claims (Andrews, 2016). Unfortunately, all the users of these games can really expect is an improvement in their performance on the games themselves; transfer from the games to real-life tasks involving attention and working memory has not been found consistently in the research (Melby-Lervåg & Hulme, 2013).

For this reason, we prefer not to focus on these questionable interventions – instead, we focus on effective learning strategies that have decades of consistent research behind them (Weinstein, Madan, & Sumeracki, 2018; see Chapters 8 through 10).

Chapter summary

Attention is often defined as a “limited-capacity resource.” As with a financial budget, you have a certain amount of attention, and you apportion it to different tasks. An important feature of our attentional mechanism is being able to selectively focus on just one location, object, or message at any one time. Importantly, the data point strongly to the conclusion that it is almost impossible to pay attention to more than one thing at the same time. In an educational context, not paying attention can severely impede learning. The extent to which students pay attention in educational settings depends on internal and external factors, some of which are within the instructor’s control.

References

Anderson, B. (2011). There is no such thing as attention. Frontiers in Psychology, 2, 246.

Andrews, J. (2016). We must challenge any company that claims to tackle dementia. Nursing Standard, 30, 32–32.

Baddeley, A. (2003). Working memory: Looking back and looking forward. Nature Reviews Neuroscience, 4, 829–839.

Baddeley, A. D., & Hitch, G. (1974). Working memory. Psychology of Learning and Motivation, 8, 47–89.

Bull, R., & Johnston, R. S. (1997). Children’s arithmetical difficulties: Contributions from processing speed, item identification, and short-term memory. Journal of Experimental Child Psychology, 65, 1–24.

Chandler, P., & Sweller, J. (1991). Cognitive Load Theory and the format of instruction. Cognition & Instruction, 8, 293–240.

Chang, S. L., & Ley, K. (2006). A learning strategy to compensate for cognitive overload in online learning: Learner use of printed online materials. Journal of Interactive Online Learning, 5, 104–117.

Cohen, J., Hansel, C. E. M., & Sylvester, J. D. (1956). Mind wandering. British Journal of Psychology, 47, 61–62.

Deci, E. L., Koestner, R., & Ryan, R. M. (1999). A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychological Bulletin, 125, 627–688.

Deci, E. L., Koestner, R., & Ryan, R. M. (2001). Extrinsic rewards and intrinsic motivation in education: Reconsidered once again. Review of Educational Research, 71, 1–27.

Edmiston, R. W., & Braddock, R. W. (1941). A study of the effect of various teaching procedures upon observed group attention in the secondary school. J. Educ. Psychol., 32, 665. doi: 10.1037/h0062749

Ericsson, K. A., & Chase, W. G. (1982). Exceptional memory: Extraordinary feats of memory can be matched or surpassed by people with average memories that have been improved by training. American Scientist, 70, 607–615.

Feng, S., D’Mello, S., & Graesser, A. C. (2013). Mind wandering while reading easy and difficult texts. Psychonomic Bulletin & Review, 20, 586–592.

Forster, S., & Lavie, N. (2009). Harnessing the wandering mind: The role of perceptual load. Cognition, 111, 345–355.

Forster, S., & Lavie, N. (2014). Distracted by your mind? Individual differences in distractibility predict mind wandering. Journal of Experimental Psychology: Learning, Memory, and Cognition, 40, 251–260.

Gathercole, S. E., Pickering, S. J., Knight, C., & Stegmann, Z. (2004). Working memory skills and educational attainment: Evidence from national curriculum assessments at 7 and 14 years of age. Applied Cognitive Psychology, 18, 1–16.

Gopher, D., Armony, L., & Greenshpan, Y. (2000). Switching tasks and attention policies. Journal of Experimental Psychology: General, 129, 308–339.

Hidi, S., & Harackiewicz, J. M. (2000). Motivating the academically unmotivated: A critical issue for the 21st century. Review of Educational Research, 70, 151–179.

Hidi, S., Weiss, J., Berndorff, D., & Nolan, J. (1998). The role of gender, instruction and a cooperative learning technique in science education across formal and informal settings. In Interest and learning: Proceedings of the Seeon conference on interest and gender (pp. 215–227). Kiel, Germany: IPN.

Jackson, J. D., & Balota, D. A. (2012). Mind-wandering in younger and older adults: Converging evidence from the sustained attention to response task and reading for comprehension. Psychology and Aging, 27, 106–119.

James, W. (1890). The principles of psychology (Vol. 1). New York: Holt.

Kail, R., & Salthouse, T. A. (1994). Processing speed as a mental capacity. Acta Psychologica, 86, 199–225.

Kane, M. J., & Engle, R. W. (2003). Working-memory capacity and the control of attention: The contributions of goal neglect, response competition, and task set to Stroop interference. Journal of Experimental Psychology: General, 132, 47–70.

Klingberg, T., Forssberg, H., & Westerberg, H. (2002). Training of working memory in children with ADHD. Journal of Clinical and Experimental Neuropsychology, 24, 781–791.

Lavie, N., Hirst, A., De Fockert, J. W., & Viding, E. (2004). Load theory of selective attention and cognitive control. Journal of Experimental Psychology: General, 133, 339–354.

Ling, J., Heffernan, T. M., & Muncer, S. J. (2003). Higher education students’ beliefs about the causes of examination failure: A network approach. Social Psychology of Education, 6, 159–170.

Loisette, A. (1896). Assimilative memory, or, how to attend and never forget. New York and London: Funk & Wagnalls Company.

Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38, 43–52.

McVay, J. C., & Kane, M. J. (2009). Conducting the train of thought: Working memory capacity, goal neglect, and mind wandering in an executive-control task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35, 196–204.

McVay, J. C., & Kane, M. J. (2012). Why does working memory capacity predict variation in reading comprehension? On the influence of mind wandering and executive attention. Journal of Experimental Psychology: General, 141, 302–320.

Melby-Lervåg, M., & Hulme, C. (2013). Is working memory training effective? A meta-analytic review. Developmental Psychology, 49, 270.

Moray, N. (1967). Where is capacity limited? A survey and a model. Acta Psychologica, 27, 84–92.

Mrazek, M. D., Phillips, D. T., Franklin, M. S., Broadway, J. M., & Schooler, J. W. (2013). Young and restless: Validation of the Mind-Wandering Questionnaire (MWQ) reveals disruptive impact of mind-wandering for youth. Frontiers in Psychology, 4.

Pashler, H. (1999). The psychology of attention. Cambridge, MA: MIT Press.

Reason, J. T., & Mycielska, K. (1982). Absent minded? The psychology of mental lapses and everyday errors. Englewood Cliffs, NJ: Prentice Hall.

Reiss, S. (2012). Intrinsic and extrinsic motivation. Teaching of Psychology, 39, 152–156.

Risko, E. F., Anderson, N., Sarwal, A., Engelhardt, M., & Kingstone, A. (2012). Everyday attention: Variation in mind wandering and memory in a lecture. Applied Cognitive Psychology, 26, 234–242.

Roebers, C. M. (2006). Developmental progression in children’s strategic memory regulation. Swiss Journal of Psychology, 65, 193–200.

Rotgans, J. I., & Schmidt, H. G. (2011). The role of teachers in facilitating situational interest in an active-learning classroom. Teaching and Teacher Education, 27, 37–42.

Schupak, C., & Rosenthal, J. (2009). Excessive daydreaming: A case history and discussion of mind wandering and high fantasy proneness. Consciousness and Cognition, 18, 290–292.

Smallwood, J., & Schooler, J. W. (2006). The restless mind. Psychological Bulletin, 132, 946–958.

Smallwood, J., Fishman, D. J., & Schooler, J. W. (2007). Counting the cost of an absent mind: Mind wandering as an underrecognized influence on educational performance. Psychonomic Bulletin & Review, 14(2), 230–236.

Smallwood, J., McSpadden, M., & Schooler, J. W. (2008). When attention matters: The curious incident of the wandering mind. Memory & Cognition, 36, 1144–1150.

Smallwood, J., Fitzgerald, A., Miles, L. K., & Phillips, L. H. (2009). Shifting moods, wandering minds: Negative moods lead the mind to wander. Emotion, 9, 271–276.

Stawarczyk, D., Majerus, S., Catale, C., & D’Argembeau, A. (2014). Relationships between mind-wandering and attentional control abilities in young adults and adolescents. Acta Psychologica, 148, 25–36.

Sweller, J., & Chandler, P. (1994). Why some material is difficult to learn. Cognition and Instruction, 12, 185–233.

Tapola, A., Veermans, M., & Niemivirta, M. (2013). Predictors and outcomes of situational interest during a science learning task. Instructional Science, 41, 1047–1064.

Teasdale, J. D., Dritschel, B. H., Taylor, M. J., Proctor, L., Lloyd, C. A., Nimmo-Smith, I., & Baddeley, A. D. (1995). Stimulus-independent thought depends on central executive resources. Memory & Cognition, 23, 551–559.

Wang, Z., & Duff, B. R. (2016). All loads are not equal: Distinct influences of perceptual load and cognitive load on peripheral ad processing. Media Psychology, 19, 589–613.

Weinstein, Y. (2018). Mind-wandering, how do I measure thee with probes? Let me count the ways. Behavior Research Methods, 50, 642–661.

Weinstein, Y., Madan, C. R., & Sumeracki, M. A. (2018). Teaching the science of learning. Cognitive Research: Principles and Implications, 3, 1–17.