Introduction

Previous chapters have provided evidence of the impact of digital technologies on young people’s lives, particularly the way in which they communicate with their peer group and develop new and highly complex digital literacy skills. Ofcom’s (2010) UK-wide survey showed a tipping point when adolescents and young adults preferred use of digital technology. For the first time 16 to 24 year olds declared their mobile phones and the Internet more important than television, although the majority of post-24 year olds remained wedded to the television. Similarly, Carrier, Cheever, et al. (2009) in their cross-generational study in the United States found that those born between 1982 and 2001 were spending more time than previous generations on media-related activities such as web surfing, texting and video games. So are there any benefits for education of all this tech-time? The evidence at first sight is equivocal. While Davies and Good (2009), for example, have found a positive relationship between personal access to the Internet and the extent to which learners use the technology for their school or college work, students are acutely aware of the clear boundaries between technology for school and technology for leisure activities.

Returning to the Ofcom survey, it found that in 2009 almost half of young people aged between 8 and 17 have a profile on a social networking site such as Facebook. Social media are now integral to most young people’s everyday behaviours. This is not confined to the university sector, as the Ofcom data show some pre-adolescents are using adolescent and adult social networking sites despite an age embargo. The question remains to what extent engagement with digital technology affects learning and whether those impacts are largely positive or detrimental? The shift to interactive digital technologies by the young has both increased opportunities and raised concerns and, because of the extensive adoption of social media by students across a wide age-range, there is a great deal of interest in how these media activities impact on academic performance. In this chapter we look at what is different about the way in which we interact in a digitally rich world and how those changes affect cognitive abilities. At the heart of most definitions of cognitive abilities is the perception of the potential of the individual’s mind but Salomon has argued that once those abilities are coupled with ‘intelligent technologies’, then it is the performance of the joint system on which an assessment of performance should be based (Salomon, Perkins, & Globerson, 1991). Whether systems such as Facebook should be classified as ‘intelligent technologies’ in a Salomonesque way, they do nevertheless impact on cognition and behaviours – although they are not necessarily an enhancement of human abilities. This is a point that Salomon also makes when he if can technology can do too much, thus rendering the human input to a subsidiary role resulting in loss of performance without technology. Children’s declining performance in mental arithmetic following the introduction of the calculator is an example of abilities that have atrophied. A key theme of this chapter is the relationship between technology use and cognitive skills: in particular we explore in some depth the effect of multitasking on performance. However, first we turn to the relationship between technology use and the users’ health and wellbeing. Much has been written on the ills of technology but here we focus on the emotive issue of technology addiction and the less sensitive issue of time wasting.

Addiction and Wellbeing

There are many scare stories in the media about technology addiction particularly in relation to smart phones and video games. So we find headlines in the media such as ‘Student addiction’ to technology ‘similar to drug cravings’¹ and magazine articles reporting the damaging effects of addiction (Codey, 2011). For some the fact that many young people text while driving, even though they know it is dangerous, is seen as an example of their inability to control their technological urges, although personal observation suggests that the use of mobile phones while driving is not confined to the young. While there is, currently, evidence of a weak link between heavy electronic media use and mild attention problems the anticipated link to more serious attention deficits, such as ADHD, is not established (Schmidt & Vandewater, 2008; Schnabel, 2009). Indeed, when students with ADHD played a computer game that they enjoyed they exhibited similar positive behaviours, such as fewer errors, less impulsive responses and an increased ability to stay on task, performing in a similar way to their typically developing peers (Shaw, Grayson, & Lewis, 2005).

Nevertheless, ‘Internet addiction disorder’ is already accepted as a psychological diagnosis in China, Taiwan and South Korea and it is included in the fifth edition of the Diagnostic and Statistical Manual for Mental Disorders (DSM-V). However, we need to question whether addiction to the Internet is a real condition that needs to be treated just like any other addiction, with care and caution, or is it an obsession? Montag, Kirsch, et al. (2012) have argued not only that Internet addiction exists but also that it has the same genetic cause as smoking addiction. His comparative study of 132 problem Internet users and controls showed that a gene mutation, which promotes addictive behaviour, was more prevalent in those participants in the study who scored highly on the Internet Addiction Test Questionnaire. However, the gene variant was largely confined to female problematic Internet users, rather than male users described as having online addiction.

Work on Facebook shows some corroborating evidence that this addiction is a real phenomenon and that females are a particularly vulnerable group. A Swedish survey of 1,000 adults aged 17 to 73 years, found that 85 per cent of the respondents use Facebook as part of their daily routine (Denti, et al., 2012). Further there was an inverse relationship between the level of Facebook use and general wellbeing. This negative correlation only held for a subset of high users comprising females with low incomes or less highly educated individuals in general. Both groups rated themselves as feeling less happy and less content with their lives than their more affluent and well-educated peers. In addition individuals who compared themselves to other Facebook users also felt less happy. Indeed, students who spend more time on Facebook are more inclined to perceive others as living happier lives in comparison to their own life (Chou & Edge, 2012). One partial explanation for these findings is that engagement with Facebook is habit forming. So is our engagement with digital technology nothing more than Internet addiction to which females are more vulnerable than males? As we saw in the previous chapter, SNS may have a detrimental effect on educational learning (Hew, 2011), but is the extensive engagement with SNSs also having a negative impact on our general wellbeing?

Montag and colleagues (2012) acknowledge that previous research has tended to show males as more prone to problematic Internet use than females, so the link to genetics in his own study is, as he freely admits, puzzling. It could be argued that only females are affected by their biology but perhaps a more straightforward explanation, one that is well established in the social psychology literature, is that perhaps females are more assiduous in filling out questionnaires and therein lies the potential bias. There has been some unease in the research community about the level of reliance on questionnaire data in the absence of any corroborating evidence. Other information gathering techniques are available and have been widely used in studies of decision-making and reasoning. Atchley and Warden (2012) borrowed one such technique from the decision-making literature to explore young people’s addiction to texting, which was measured by the ability of the young person to resist answering a text from a significant person in their lives. They offered cash rewards to induce the young people to delay their response to the text. The longer they delayed the higher the monetary reward. Thirty-five students answered a series of questions based on scenarios, such as: You receive a text from a significant other. You can have $5.00 now if you choose to reply immediately, or you can have $100 in 60 minutes if you wait and reply then. The waiting time varied between 1 minute and 480 minutes (8 hours). Such choices have been used to demonstrate the impulsivity of people addicted to alcohol or drugs. Those deemed addicted tended to choose an immediate response over a delayed but highly rewarded response, addicts showing a massively skewed preference for smaller cash plus immediate rewards.

Atchley and Warden (2012) found no such immediacy effect: the students were able to delay their responses to achieve a financial gain. However, the lure of money in the future was tempered by the desire to respond to a text. While in a control condition receiving $100 after a two-week delay was valued at 25 per cent lower than receiving $100 instantly, when money was combined with texts, this discounting speeded up. It took just a 10 minute wait for $100 plus text to lose 25 per cent of its value and the students seemed to view the reward of texting in the same way as the financial reward of money, offsetting one against the other. However, the need for an immediate reward was not overwhelming, as one would expect to find if the individual was addicted. This contradicts the notion that students make decisions about texting in the way an addict makes decisions about drugs.

When the importance of the individual trying to make contact was varied, that is when the text was from someone less significant, a friend or a casual acquaintance, then the willingness to delay the response and reap the money also varied. Only when receiving a text from a significant other did the students agree to forgo the cash incentive and respond quickly. Again this suggests that their text-based decision-making was thoughtful rather than impulsive. This research supports the conclusion that young people are not addicted to their phones like an addict is to a drug although, as with the questionnaire studies, the findings here are based on self-reported behaviour and are not corroborated in any way. Is the students’ engagement with digital technology here better described as a thoughtful rather than an addictionive or impulsive behaviour?

Time Wasting

So addiction may not be the issue but obsessive behaviour leading to wasted time could be a downside of digital activity. At a simplistic level there is a pervading view that the digital technologies are leading to non-productive activity: they are distractions for the Internet users. There can be very few lecturers who have not had the experience of their students deeply focused, not on what they are saying, but on a small screen tucked under the desk by the shy or waved around in the air by the brazen. This is shown by one unattributable student’s response on an open discussion forum to the question: ‘Why text when you can talk on the phone?’: If you are texting or IMing, you can do it in places where you shouldn't be talking. Library, meeting, class, work.

An extensive set of surveys has led to researchers at the Kaiser Family Foundation to conclude that although computers have educational potential, they are largely used for pure entertainment rather than meaningful content creation. Moreover, their recent study has shown that those children in lower socio-economic groups spend more time in such activities. The 2010 Kaiser Family Foundation Youth Lifestyle Study (YLS) found that children and adolescents whose parents do not have a college degree used digital media for 90 minutes more per day than children from higher socio-economic families. This media-use gap was only 19 minutes in 1988 (Dunedin Multidisciplinary Health and Development Study, DMHDS, 1998; Robertson, McAnally, & Hancox, 2013). So the use of technology is widening the time-wasting gap (Rideout, Ulla, et al., 2010). It is anticipated that this in turn will lead to a wider achievement gap with children from low socio-economic families falling further behind.

The entry into the digital world, either passively through television or more actively through online exploration, has been found to impact on real-world relationships. For example, more time spent television viewing and less time spent reading and doing homework was associated with low attachment to parents for both cohorts. In these two Kaiser surveys taken 16 years apart, among the YLS cohort, more time spent playing on a computer was also associated with low attachment to parents. Among the DMHDS cohort, more time spent television viewing was associated with low attachment to peers (Richards, McGee, et al., 2010). This is a global phenomenon. Students in China reported difficulty controlling the amount of time they spent online blaming the Internet for diminished face-to-face communications and message misinterpretations. However, enlightened employers argue that a little downtime, either shopping or watching YouTube, leads to a more productive workforce. There is a cultural shift promoting a ‘work–life balance’ as opposed to a work culture in which employees increasingly answer work emails outside office time. Such employees see a little downtime during the workday as simply part of the general flow (Salary.com. 2012).

However, one study looks at the time issue and its impact on core educational skills using a randomized controlled trial of the effects of video-game ownership on the academic and behavioural functioning of young boys (Weis & Cerankosky, 2010). Encouraged participation in the study was achieved by offering boys (elementary/middle school) who did not have a video-game system in their home access to a machine loaded with interesting games. Half of the sample of 64 young adolescents was rewarded immediately with a machine while the control group received the reward of a game system 4 months later after the final assessment. Overall, boys who received the video-game system at the beginning of the study showed relatively stable and somewhat below average reading and writing achievement while the control group showed increased reading and writing achievement across the duration of the study. The lower academic achievement scores displayed by boys in the experimental condition were observable by teachers: boys who received the video-game system earned significantly higher Learning Problems scores, which reflect delays in reading, writing, spelling and other academic tasks; boys in the experimental condition spent more time playing video games and less time engaged in after-school academic activities than boys in the control group. Their time was absorbed by the technology resulting in a lack of improvement in core educational skills. Consistent with those of Roberts, Foehr, and Rideout (2005), the authors conclude that video-game ownership may impair academic achievement for some boys in a manner that has real-world significance.

Driven by the Fear of Missing Out (FOMO)

There is an increasing awareness in the literature that engagement in digital worlds may not be a manifestation of addiction to the technology per se but by social anxiety termed FOMO (the fear of missing out) (Przybylski, Murayama, et al., 2013). Przybylski and colleagues found that the condition was most common in those who had unsatisfied psychological needs such as wanting to be loved and respected. The condition is particularly associated with SNSs that provide constant opportunity for comparison of one’s status. It manifests itself in repetitive behaviours, for example, as continual mobile phone checking. He found that from his sample of 500 undergraduates, 38 per cent reported that they were unable to last more than 10 minutes before checking their laptop, smartphone, tablet or e-reader. Rosen, Carrier, and Cheever (2013) have similar findings for adolescents and undergraduates endeavouring to complete their work in the home environment. The average length of time the participants stayed on task before switching was less than six minutes and this loss of focus was most often due to technological distractions including social media and texting. Students who switched tasks most frequently had more distracting technologies available in the form of open desktop windows and the mobile to hand. While having a positive attitude toward technology did not affect being on-task during studying, those students with multiple technologies available were more likely to be off-task than peers who limited their distractions.

FOMO has been linked to the fear of being ostracized from the group. William’s (2009) needs–threat model of ostracism resonates with the concept of FOMO as it suggests that the fear of social exclusion, whether perceived or real, will result in an individual exhibiting an innate need to increase his or her sense of belonging and control in order to compensate for decreases in life-satisfaction and self-esteem. Ostracizm is life-threatening (Williams & Zadro, 2005) as has been clearly demonstrated by the tragic cases of adolescent suicides in the United Kingdom and elsewhere. Przybylski and colleagues (2013) suggest that in the context of online social networking use, FOMO results in individuals seeking to reaffirm their identity by spending more and more time online, leading in turn to further fears of missing out, and an increased capacity for exposure to risk through self-disclosing and friending behaviours.

The Interplay of Cognition and Internet Activity

Zhong, Hardin, and Sun (2011) have posed questions about cognitive behaviours associated with SNS use. For example, they have questioned the quality of thinking associated with high SNS use. Specifically they asked whether effortful thinking, that is seeking out and finding enjoyment in cognitively demanding tasks, was compatible with high SNS use. At the same time they asked whether innovativeness, defined as openness to new experiences and novelty is associated with SNS use (Agarwal & Prasad, 1998). Their work suggests that those individuals who actively seek out cognitive stimulation through demanding tasks (that is show a high ‘need for cognition’) tend to be lower users of SNS than their peers. Such individuals were also significantly less likely to add anyone to their SNS accounts than low NFC individuals. However, there was no difference between types of thinkers in terms of maintaining several SNS accounts or sharing information through these sites. In this case the variation in use was due to a desire for cognitive stimulation. So why should different types of thinkers respond in such diverse ways to digital technologies? Is there something inherently different in the nature of the interactions promoted by the use of such media? A behaviour frequently commented upon is the propensity of users to multitask when working with and through technology. Multitasking has become part of the media routine in the lives of Internet users. Media multitasking, or the involvement in several concurrent activities at least one of which is related to media use, increased significantly during the 2000s (Foehr, 2006). The younger generation of media users tend to multitask more than older generations such as the ‘Baby Boomers’ (Carrier, et al., 2009). So multitasking is often the norm when using digital technologies. Our students listen to their iPods while surfing the net and texting or messaging their friends or peers.

A study by Pew International (2012) has shown that the active use of the mobile (cell) phone is common while watching TV. These ‘connected viewers’ used their mobile phones for a wide range of activities, for example over one-fifth exchange text messages about the programme with friends who were watching the same programme in a different location, while 11 per cent check what others are saying about the programme. Television viewing has become interactive and connected. While some view this requirement to multitask as a strength of such activities, others argue that multitasking necessarily leads to sub-standard, shallow learning. Davies and Good (2009) report that a substantial proportion of learners multitask while engaged in homework activities, in ways that are likely to be distracting for some and constructive for others. It is also clear that multitasking, often using Facebook, can have a detrimental effect on the quality of students’ learning, both within formal and informal contexts (Hew, 2011). So multitasking is an essential aspect of technology use but it comes with both benefits and costs. To understand the source of those costs we turn to studies in cognitive psychology and neuroscience.

What are the relationships, if any between SNS use, media multitasking and behavioural factors, such as total Internet time and online time for work or study? Zhong, et al. (2011) found little difference between low, medium and high ‘need for cognition’ groups as far as media multitasking was concerned, indicating that it is now both pervasive and routine behaviour among the young. We should remember that Holmes (2011) has found a substantial number of young people are not engaged with digital technology, although whether they simply refuse to engage or have a lack of access to technology is unknown. In fact, new data within the United Kingdom has shown that as many as a third of young people are only partially engaged with the Internet, while the reaming two-thirds are engaged but do not present an homogenous group, but rather a number of different groups each pursuing a number of different online activities (see Holmes, 2011).

Does multitasking require a qualitatively different type of attention and if so what are the implications for cognitive skills in both development and learning? William James, in The Principles of Psychology (1890), identified qualitatively different forms of attention. He considered steady attention to be the default condition of a mature mind. Mature attention, he argued, was in large part the result of personal mastery and discipline, a sense of discipline that we seem to find increasingly elusive. This seems a world away from the buzz of a multitasking adult in the modern world. James’s solution to the buzzing cacophony of the modern world was to advocate ‘acquired inattention’. In modern parlance that is to treat texts, tweets, emails, and the call of the mobile phone or mp3/4 player as background noise or distraction. So for the younger generation of multitaskers, the multitasking behaviour is an expected part of their everyday life.

When the brain is forced to respond to several stimuli at once, as happens when multitasking, then task-switching behaviour occurs. Functional magnetic resonance imaging (fMRI) scans of people engaged in task switching have found evidence of a bottleneck when the brain is forced to respond to several stimuli at once. As a result, task switching leads to time lost as the brain determines which task to perform. Our ability to perform simultaneous tasks is limited and we can only successfully perform multiple tasks when these tasks are automated (Broadbent 1957; Fisch 2000). If a task requires focused attention, as is the case for any academic work, the learning of students engaging in multiple activities will be impaired (Kirschner & Karpinski, 2010). So, as the brain cannot fully focus when multitasking, people take longer to complete tasks and are predisposed to errors.

Further, Foerde, Knowlton, and Poldrack (2006) have shown that while people can and do learn things while multitasking, the learning is less flexible, more specialized and hence more difficult to recall when needed. The state of constant intentional self-distraction, it is argued, is detrimental to individuals as their attention is split among many competing tasks. As individuals attempt to learn new things while multitasking they compromise the quality of that learning. In addition, the more the task requires attention and concentration, such as learning a new subject, the more the learning will be negatively affected by multitasking and therefore represents a poor long-term strategy for learning.

Is multitasking always detrimental? Studies are now appearing that show that this shift in activity is having deleterious effects on young people’s academic performance. While multitasking is not new, it is a characteristic feature of the younger generation, particularly in association with the use of communication technologies. The question asked by many researchers is whether this spread of attention leads to more rounded learning or whether attentional switching leads to a loss of performance. In one study over half the students surveyed agreed that their high level of instant messaging while engaged in academic activities had a detrimental effect on their schoolwork and resulted in a failure to complete essential learning tasks (Junco & Cotten, 2011).

Fox, Rosen, and Crawford (2009) addressed the issue of multitasking by investigating the impact of instant messaging (IM) on student performance in a reading task. The students completed a reading comprehension task uninterrupted or while holding an IM conversation. Participants in the latter condition took significantly longer to complete the reading task, indicating that concurrent IM use negatively affects efficiency. However, there was no decrement in performance and IM use did not affect reading comprehension scores. Those students self-reporting extensive time spent messaging had lower reading comprehension scores and lower self-reported performance in US national tests.

Lee, Lin, and Robertson’s (2012) study at first sight offers a more complex picture of the multitasking behaviour in learning environments. Their findings supported the assertion that we retain less information when we perform more than one task at a time. In this case reading a text versus simultaneously reading the text and watching a related video on which they would also be tested, lead to a decrement in recall from the reading task when the students were presented with multiple rather than single information sources. However, when not told that the video would be part of the post-test, there was no loss of performance on the reading task, although the students retained little information from the video when presented with a surprise test on its contents.

Lee and colleagues (2012) argue that the observed differences in performance are related to the differences in the cognitive load of the tasks. If the video was treated as background noise – the TV in the corner of the room or music playing down the headphones – then there is less need to focus their attention on that material. What we find interesting about their study is the ease with which students could tune out irrelevant information to focus on the task in hand. The study tells us less about multitasking and more about students’ abilities to selectively attend when the need arises – a very encouraging message for all educators.

So attentional switching has limited affect if going from an unfamiliar to familiar task that makes very limited cognitive demands. Moving from the familiar to the unfamiliar takes additional processing capacity that is increased if the unfamiliar task is not simple (Rubenstein, Meyer, and Evans, 2001). However, learners can focus their attention and block-out unwanted ‘noise’ when they need to. Meyer and colleagues (1995) have long argued that rather than causing a bottleneck in the brain a process of adaptive executive control takes place when prioritizing task processing. While this is not a controversial stance, Meyer has argued that, with training, the brain can learn to task-switch more effectively, and there is some evidence that certain simple tasks are amenable to such practice. Again the picture is not all positive, as research has also found that multitasking contributes to the release of stress hormones and adrenaline, which can cause long-term health problems.

Are Multitaskers Always at a Disadvantage?

The question as to whether heavy multitaskers are always at a disadvantage is taken up by Lui and Wong (2012). Multitaskers have been shown to perform poorly in certain cognitive tasks involving task switching, selective attention and working memory, possibly because they tend to pay superficial attention to lots of information without paying sufficient focus on the information that is most relevant to the task at hand. However, there is evidence that this cognitive style may not detrimentally affect performance in all tasks. Lui and Wong found heavy media multitaskers performed better in a multisensory integration task than others due to their extensive experience in integrating information from different modalities.

A number of studies have shown positive effects of playing video games as they have found that games can promote divided attention skills, the perceptual foundation for multitasking. A more recent study employed a tool that measures how effectively a participant performs on four tasks carried out simultaneously (Dye & Bavelier, 2010; Dye, Green, & Bavelier, 2009; Green & Bavelier, 2003). One study showed that participants who played two hours of a shooting game called Counter-Strike had higher multitasking scores than those in a control group who did not play the game. There was a potential facilitation of development of attentional skills in children who were avid players of action video games. Playing video games improved visual attention in youths aged 7 to 22, in terms of allocating attention and filtering out irrelevant information. Other research teams have also shown positive impacts of playing video games as they enhance the ability to divide visual attention in college students (Greenfield, deWinstanley, et al., 1994). While the use of electronic visual media may enhance skills of visual attention and visual–spatial processing, it may not adequately cultivate higher-order cognitive processing skills (Greenfield, 2009).

Video gaming requires multitasking and gamers have been shown to be highly effective on tasks such as driving while using a hands-free mobile phone. Testing gamers and non-gamers in a driving simulator, Telner, Wiesenthal, et al. (2008) showed the standard decrement in driving performance for non-gamers when using a mobile, whereas, gamers were significantly less impaired by the dual task challenge presented by driving and using their mobile. So video games promote skills in multitasking, but many parents, educators and researchers are left asking whether multitasking is fundamentally a good thing. Recent studies have investigated whether someone performs better or processes a task more deeply if it is executed alone rather than in a multitasking environment.

Going with the Flow

Game playing leads us to a consideration of flow theory. A state of flow, a phenomenon first articulated by Csikszentmihalyi and Csikszentmihalyi (1975) in their study of individuals involved in activities such as rock climbing and chess, has been shown to enhance student learning. Flow is characterized by the complete absorption or engagement in an activity and refers to an optimal experience (Csikszentmihalyi, 1990, 2002): a state of consciousness that is sometimes experienced by individuals who are deeply involved in an enjoyable activity to the exclusion of everything around them (Inal & Cagiltay, 2007; Kiili, 2005). To achieve a state of flow an individual must be involved in an activity with a clear set of goals and progress that has appropriate and immediate feedback. In addition there must be a balance between the perceived challenges of the task and the individual’s own perceived skills. So an individual going with the flow or ‘in the zone’ has an optimal experience in which they are so involved in the activity that it becomes spontaneous with a level of automaticity and as a result they stop being aware of themselves as separate from the actions they are performing.

Why should we be interested in flow theory? Csikszentmihalyi (1990) suggests that enhancing the time spent in flow makes our lives happier and more successful and it has been shown to be associated with states of enjoyment, positive affect and psychological wellbeing (Bryce & Haworth, 2002). Studies of video gamers have found that flow is associated with gaming enjoyment and positive affect (Klimmt, Hartmann, & Frey, 2007; Smith, 2012). Sweetser and Wyeth’s (2005) GameFlow model identifies eight elements that result in an enhanced game enjoyment: concentration, challenge, skills, immersion, control, clear goals, feedback and social interaction. This evidence suggests that gaming is intrinsically motivating and provides positive experiences for those who engage in the activity.

However, flow experiences have been shown to foster addiction and it has been argued that it is related to an increase in engaging in risky behaviours such as rock climbing (Schüler, 2012). While Keller, Bless, et al. (2011) have shown that even during pleasurable flow experience, maintaining a balance of personal skills versus task demands results in reduced heart rate variability indicating enhanced mental workload, and this is accompanied by stress as indicated by relatively high levels of salivary cortisol. These findings are consistent with those of Meyer, et al. (1995). Reaching a state of flow then is hard and demanding work, yet individuals seek out this state and it might be argued this is how we move forward as a species, testing ourselves on the edge.

So what are Young People Learning?

Young people spend a considerable amount of time in their technologically-rich world but does this have any academic spin-off? There are those that will point to young dot-com millionaires and say of course the hours spent ‘playing’ in the digital world are of value. The expertise literature at first sight would seem to support this assertion: ‘10,000 hours’ practice is required to acquire expertise is now well evidenced and widely accepted. However, simple time spent ‘doing’ an activity is not enough to take command of a skill. Ericsson, Charness, et al. (2006) point out that time spent on any activity must be quality hours of ‘deliberate practise’. Practising already acquired skills quickly leads to a learning plateau. To advance you need to push the limits of your understanding and target weaknesses as this allows you to broaden your skill set. The question then is not a simple one of what young people are failing to learn when engaged with social networks but what they are learning and, as a consequence of this refocusing of their endeavours, what skill and abilities valued by society are not being honed? This leads to a further question that we have yet to answer as a society: whether those valued skills are still relevant and, if so, how do we encourage their development when there is no realistic chance of weaning the young off their enthusiasm for digital technologies?

Risks, Skills and Opportunities

Risks are often associated with the dangers of multitasking and becoming immersed within the digital world of technology. Many parents, educators and researchers are left asking whether multitasking is fundamentally a good thing? Not only can multitasking have negative influences on family relations and attachment to parents (Richards, et al., 2010), but this can also have a detrimental effect on the quality of students’ learning both within and outside formal educational contexts. There are concerns that students are being absorbed by this technology, which is resulting in a detrimental effect on their health and psychological wellbeing and leads them to engage in non-productive, time-wasting activities. Of course, the media hype regarding the use of mobile phones while driving warns us about the inherent risks of multitasking and road safety. We know that texting while driving can be a regular source of distraction and this is most problematic for young drivers who are more often attracted to and more ready to adopt new communication technologies (Lee, et al., 2011). But there are real opportunities too and the pros may outweigh the costs. Practising the skills associated with multitasking may surely allow individuals to become better at attentional-switching, visual-spatial processing and other quite advanced higher-order cognitive skills.

Conclusions

Learners are enticed by the range of technological tools available and often find themselves immersed within the range of tools available to them, whether these tools facilitate social networking, downloading music or instant messaging. What we do know is that within the current net generation, people are not always content on doing one thing at a time. Frequently, they multitask: they engage in multiple tasks aimed at attaining multiple goals simultaneously. Given that people rapidly switch their attention back and forth across tasks, they falsely believe that they can ‘multitask’ but in reality, they cannot, and, by trying to do so, neither task receives optimal attention or focus. This is because multitasking is both cognitively and physically demanding, requiring the refinement of cognitive skills involving task switching, selective attention and placing additional constraints on working memory capacity. We often find that those individuals who do prefer to multitask are those who are impulsive, have low behavioural inhibitions and are often sensation seekers (see Sanbonmatsu, et al., 2013). However, we do know that multitasking is not detrimental to all individuals as it can allow the development of multisensory integration and a better awareness of flexible task-switching. As discussed in the next chapter, multitasking through video game playing can have real benefits and promote divided attention skills, and a refinement of behavioural, cognitive and affective skills that are needed to engage within a digitally rich social environment.