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Cell phone effects on the academic performance of students review of related literature

Open in a separate window The majority of studies in this field also employ self-report questionnaires that provide only a narrow window into the relevant behaviors, and that may in some cases provide unreliable indices of the target behavior Baumgartner et al. Indeed, the limited evidence we have regarding the compatibility between subjective and objective usage measures indicates that self-report estimates of usage are likely to be of limited reliability, and only modestly correlated if at all with actual usage Andrews et al.

Relatedly, the fact that smartphones are a relatively recent development precludes the existence of any broadly generalizable longitudinal evidence. Thus, even when connections between technology and cognition are established, we do not know the extent to which these impacts are lasting. Attempts to assess smartphone-related habits questionnaires, diaries, etc. In spite of these many challenges, some foundational research has been conducted, and some intriguing patterns are beginning to emerge.

In the following sections, we discuss recent research in the areas of attention, memory and knowledge, delay of gratification, and conclude with a consideration of studies investigating more general effects on academic performance and other domains.

A Study on Some of the Common Health Effects of Cell-Phones amongst College Students

Mobile Technology Use and Attention A concern that pre-dates smartphone technology is the rising incidence in the diagnosis of attentional difficulties, most specifically ADHD, in children and adolescents e. Considered together with the rise in the prevalence of multimedia devices, this correlation may be perceived by the public to be evidence of a causative relationship. One specific manifestation of this concern is that the current generation of children and adolescents are developing increasingly shorter attention spans due to their increased contact with smartphone technology, and use onset at younger ages Nikken and Schols, 2015.

Here we consider the empirical research concerning the potential impacts of smartphone-related technologies on divided attention and focused attention. Focused attention refers to the capacity to attend to only one source of information while ignoring other incoming stimuli.

Focused attention also encompasses sustained attention — the ability to maintain a directed attentional focus over an extended period of time. Conversely, divided attention typically refers to the ability to perform two or more functions simultaneously, otherwise known as multitasking. Perhaps the most recognizable, and obvious, impact of smartphone technology in our everyday lives is the way in which it can acutely interfere with, or interrupt, ongoing mental and physical tasks.

It may be useful to think of smartphone-related interruptions as coming in two forms: These endogenously driven drifts of attention might arise from a desire for more immediate gratification when ongoing goal-directed activities are not perceived as rewarding Melcher, 2013a point to which we return below.

Once attention has been shifted to the smartphone for one purpose e. Importantly, smartphones are capable of interfering with focused attention even when the user attempts to ignore them. In one recently published study, for instance, researchers demonstrated that exposure to smartphone notifications significantly decreased performance on a concurrent attention-based task, even when the participant did not take the time to view the notification Stothart et al. Simply hearing the sound or feeling the vibration that signified the alert was enough to distract the participants and decrease their ability to focus attention on the primary task.

The researchers posited that that the notifications prompted task-irrelevant thoughts, which manifested themselves in poorer performance on the primary task.

Further evidence suggests that even the mere awareness of the physical presence of a cell phone may impact cognitive performance.

Each task involved two levels of difficulty. Participants in the cell phone condition performed significantly worse on the more difficult parts of the digit cancelation and trail-making task than participants in the notebook condition, but performance on the easier parts of the tasks was similar. The researchers replicated these findings in a follow-up study for which half of the participants were asked to place their own cell phones on their desks.

The researchers concluded that the mere presence of a phone is sufficiently distracting to affect cognitive functioning, but only during demanding tasks. Deleterious effects of smartphones on attention are particularly concerning in situations where attention is crucial for safety, such as in the case of distracted driving. A substantial body of work over the past 12 years has considered the effects of texting on driving abilities using driving simulators or closed tracks.

They reported that texting consistently led to decreased attention to the road, slower response time to hazards, greater lateral variance across the lane, and more crashes. Reading text messages without responding resulted in similar findings, albeit with smaller effect sizes. The tendency to commit resumption errors increases steeply when the interruption duration exceeds 15 s Monk et al. Smartphone interruptions frequently exceed this 15 s threshold Leiva et al.

At this point, very limited empirical evidence lends backing to this concern. Given the lack of longitudinal research in this domain, the best data available are derived from correlational studies.

However, findings from those studies are somewhat mixed with respect to the claim that smartphone usage is linked to a diminished attentional capacity beyond the time in which an individual is actively engaged with the device. One study intimating that smartphone habits diminish sustained attentional abilities was conducted by Lee et al. The researchers administered three questionnaires to a large sample of university students, measuring level of smartphone addiction, tendency for self-regulated learning, and capacity for learning flow.

The results showed that the individuals who scored highest on the smartphone addiction scale scored significantly lower on the self-regulated learning and learning flow scales. The authors suggest that the smartphone addiction causes a reduced ability to achieve flow and to be self-regulated cell phone effects on the academic performance of students review of related literature.

Of course, it is equally possible that individuals who are able to be self-regulated learners and more easily achieve flow are also more capable of controlling their impulses with respect to smartphone usage, and thus scored lower on the smartphone addiction questionnaire, or that smartphone use and learning flow exert bidirectional influences on one another.

Given the correlational nature of the data, we cannot infer any directionality for the relationship, but the data at least hint that excessive smartphone usage could have a negative impact on the ability to maintain the form of sustained focused attention assessed by the flow index.

Despite the obvious link to work on divided attention, studies exploring media-multitasking are generally not focused on the acute impacts of media engagement on concurrent cognitive activities e.

In a seminal experiment on this behavior, Ophir et al.

Introduction

The data revealed that those who reported engaging in more media multitasking were also less able to filter environmental distractions task stimuli that were inessential to the primary task. Additionally, frequent media multitaskers exhibited higher switch-costs in a task-switching paradigm, indicating that they were less able to suppress the activation of task set representations that were no longer relevant to performance Monsell, 2003.

These data suggest that frequent multitasking of this sort may be associated with a tendency toward allowing bottom-up environmental inputs to capture attention and conversely, a stronger tendency toward exploratory information gathering. Some subsequent studies have replicated and extended aspects of this influential paper.

For instance, using a shorter form of the Media Use Questionnaire, Moisala et al. Specifically, the participants who had higher MMI scores made significantly more errors on a task measuring their ability to ignore distractors that interfered with task completion.

Moreover, Cain and Mitroff 2011 found that the link between distractibility and media multitasking habits was associated specifically with individual differences in the scope of attention [and not differences in working memory; see also Yap and Lim 2013 cell phone effects on the academic performance of students review of related literature related results].

For instance, concurrent with the behavioral deficit they observed in performance of a focused attention task, Moisala et al. The authors interpreted this result as evidence that increased daily multitasking leads individuals to experience greater difficulty in recruiting cognitive control resources. Relatedly, Loh and Kanai 2015 found reduced gray matter in the anterior cingulate cortex of frequent media multitaskers, indicating that this habit may have a direct impact on the structural properties of an important locus of attentional control in the brain though it should be noted that other functions have also been ascribed to this region; Shenhav et al.

While these behavioral and neuroimaging findings are intriguing, some research using MMI scores has failed to reproduce the originally observed associations Minear et al. Indeed, some evidence suggests the opposite pattern of relationship — that high MMI scores correlate with better performance on certain attentionally demanding tasks. For instance, Lui and Wong 2012 created a task that required participants to integrate incoming information from multiple sensory modalities vision and audition.

Their findings revealed that individuals who reported heavier multitasking outperformed light multitaskers in their ability to integrate the information arriving from multiple modalities. Findings suggesting an attentional benefit associated with heavier media multitasking are also compatible with studies demonstrating positive and transferable impacts of training, through repetitive task practice, in divided attention tasks Dux et al.

Perhaps because the Media Multiuse Questionnaire was the first questionnaire of its kind to be employed in a study published in a major scientific journal, the measure has been widely adopted as an assessment of media-related behavior, and as such, is the basis of many additional empirical studies. The use of this questionnaire across laboratories and to explore different dimensions of functioning has provided the field some much needed grounding.

The Media Multiuse Questionnaire does, however, have some limitations that might constrain the generalizability of these studies. One potential issue is that the MMI is calculated by submitting subject responses into a formula that applies the same weight to each of 132 potential forms of multitasking the crossing of 12 different media-related behaviors with any of the 11 remaining behaviors.

Placing the same mathematical weight on all forms of multitasking included in this index likely muddies the outcomes, making it difficult to distinguish those media multitaskers who engage in the types of difficult pairings [like those used as the basis of training in studies showing beneficial effects of practice with divided attention; e.

The limited specificity of the MMI might also account for the recent observation that individuals who fall somewhere in the middle of the media multitasking spectrum may perform better on attentionally demanding tasks than either high or low media multitasking participants Cardoso-Leite et al. While media multitasking appears, at least under certain circumstances, to be negatively correlated with the ability to task-switch and filter distractions, one form of media included on the questionnaire has been associated with improvements in multitasking: As Cardoso-Leite et al.

Nonetheless, positive associations between gaming and skills like selective attention, sustained attention, task-switching, and visual short-term memory have been demonstrated in numerous correlational and experimental studies for a review, see Green and Bavelier, 2012. The specificity of this relationship highlights another limitation of the MMI: Of note, action video games are typically played on computers or gaming consoles, whereas many popular smartphone games e.

Summary The research reviewed above provides some limited empirical support for claims about the effect of smartphone technology on our attentional capacities.

  1. The between-subjects design required half of the participants to study a map of the environment for as long as they wished before hitting the road in an attempt to reach their destination using the most direct route possible. For example, Snapchat — a tool rapidly rising in popularity, especially among youth Lenhart, 2015 — allows user to send and post pictures and videos that can only be viewed a limited number of times or for a finite period Instagram recently debuted a similar feature.
  2. For instance, concurrent with the behavioral deficit they observed in performance of a focused attention task, Moisala et al. A few answered in the affirmative about some amount of sleeplessness as mentioned above.
  3. Moreover, it is possible that those with higher cognitive scores are able to conduct searches more efficiently. This is comparable with the study done by MACRO in Mumbai in 2004 [ 9 ] where respondents were in the age group 15-29 years, and it was observed that exposure to cell phones has increased drastically in those below the age of 20.
  4. In one relevant study Baumgartner et al.

While there is clear evidence that engagement with smart devices can have an acute impact on ongoing cognitive tasks, the evidence on any long-term impacts of smartphone-related habits on attentional functioning is quite thin, and somewhat equivocal. Generally, the evidence does point to a negative relationship between smartphone usage and attention, but correlational and self-report data dominate the literature. Where more controlled assessment of attentional performance has been deployed, such as with media multitasking, the results are mixed, with some studies even yielding a positive relationship with the ability to filter distractions.

The limitations of current methods used to measure media-related behavior and wide variation in the specific tasks used to assess attentional performance may account for some mixed results in the literature. Mobile Technology Use, Memory, and Knowledge Smartphones provide constant access to an endless and ever-improving database of collective knowledge.

Cell phone usage and academic performance

Having this access enables people to search for, locate, and learn seemingly any fact that they desire. Prior to the advent of the World Wide Web, the closest available approximation of this sort of resource was a multi-volume encyclopedia, the cost and limited portability of which precluded ubiquitous use.

Internet search engines enable anyone on a connected device to have access to an unfathomably large amount of information, often at very low cost. Moreover, smartphone technology allows people to take this information wherever they wish, and access it within a matter of seconds. Though it may seem as if constant access to a limitless database of knowledge should improve cognition, much has been written about how the rapidly changing landscape of technology is negatively affecting how we remember our own lives, the places we have been, and those with whom we have interacted e.

However, as with attentional impact, the body of empirical evidence demonstrating tangible effects of mobile media devices on memory and knowledge is limited. One topic that has been investigated is the oft-cited claim that modern technology is leading us to depend upon our devices to store information for us. In a highly influential and informative study, Sparrow et al. Half of the participants were told that the computer would store their typed information for them and that they would be able to access it later, whereas the other half believed that the information would soon be erased.

The individuals who believed they would maintain access to the typed information performed more poorly on a later recall task. Importantly, an explicit instruction to remember the facts vs. To further investigate this theory, the researchers conducted an additional experiment using a design similar to that described above, but with three within-subject conditions.

The remaining third of the questions were followed by a prompt that informed the participants that the information they typed was immediately deleted. The results of this experiment indicated that participants were better able to recall the name of the folder in which the relevant information was located than the information itself. A potential experimental confound that Sparrow et al. Future research should attempt to create more balance between the trivia statements and the folder names.

  1. In the following sections, we discuss recent research in the areas of attention, memory and knowledge, delay of gratification, and conclude with a consideration of studies investigating more general effects on academic performance and other domains.
  2. They found that difficulty sleeping was a significant mediator in the relationship between electronic media use and depressive symptoms. Though the results from the self-report measures were not corroborated by any of the performance-based measures of executive functioning used in that study, very recently published work conducted by Cain et al.
  3. Mobile Technology Use, Delay of Gratification, and Reward Processing In addition to their effects on memory and attention, smartphones and related media are often implicated as the cause of a perceived cultural shift toward a necessity for immediate gratification Alsop, 2014.
  4. Indeed, the limited evidence we have regarding the compatibility between subjective and objective usage measures indicates that self-report estimates of usage are likely to be of limited reliability, and only modestly correlated if at all with actual usage Andrews et al.
  5. The individuals who believed they would maintain access to the typed information performed more poorly on a later recall task.

In their experiment, Barr et al. Finally, participants were also asked to provide an estimation of how much time per day they spend on their smartphones overall, as well as an estimation of how much time they spend specifically using internet search engines on their smartphones. Moreover, individuals who indicated that they spend a large amount of time using the search engine function on their smartphones scored most poorly on these cognitive measures.

Of course, since these results are derived from self-reported data, it is conceivable that participants who highly weight their desire for knowledge may also inflate their memory for and estimates of the time they devote to using search engines. Interpreted in a different light, Barr et al. Reinterpreted in this way, individuals with higher cognitive scores might have more semantic knowledge already accessible to them, and thus would not need to resort to using their smartphones as often.

Moreover, it is possible that those with higher cognitive scores are able to conduct searches more efficiently.