Case Study 13-2: The Multitasking Myth — Why Heavy Media Multitaskers Are Worse at Multitasking

Background

The history of the "multitasking" concept is a history of a word migrating from a technical domain (computer science, where multitasking describes a processor's capacity to run multiple programs by switching between them rapidly) to an everyday context (human cognition, where it is used to describe performing multiple tasks simultaneously) without the conceptual translation being fully completed.

Computers can genuinely multitask in the technical sense: a modern processor can execute millions of instructions per second across multiple programs, interleaving them so rapidly that the simultaneous execution appears continuous. The processes do share resources, and performance on any single process degrades under high multi-process load, but the degree of parallelism achievable in silicon is orders of magnitude beyond what biological neural systems can manage.

Human beings cannot truly multitask in the computer science sense for most cognitive tasks. The cognitive systems responsible for attention, working memory, and language processing are fundamentally sequential: they process one stream of information at a time. What looks like multitasking in humans is, in almost all cases, rapid sequential switching between tasks rather than genuine simultaneous processing. The quality of the output from both tasks therefore depends on the speed and effectiveness of the switching and on how much each task interferes with the other.

By 2009, when Eyal Ophir, Clifford Nass, and Anthony Wagner published their landmark study on media multitasking at Stanford, the cultural assumption that multitasking was a valuable and learnable skill — that young people who had grown up in the multimedia environment of the internet were becoming better at managing multiple information streams — was widespread. Ophir and colleagues designed their study specifically to test this assumption empirically.

Timeline

Early 2000s: The Multitasking Skill Assumption The early 2000s see substantial popular and quasi-academic discussion of what is sometimes called the "digital native" thesis: the claim that young people who have grown up with digital technology have developed cognitive adaptations that enable them to use it more effectively. Multitasking is often invoked as one such adaptation. The popular assumption — backed by little research — is that heavy media multitaskers have developed an enhanced capacity for managing multiple information streams through practice.

This assumption influences educational discussions: some educators argue that traditional lecture-based instruction is poorly suited to digital natives who are accustomed to receiving information from multiple simultaneous sources, and that educational environments should be redesigned to accommodate multitasking rather than demanding the sustained linear attention that traditional pedagogy requires.

2007–2008: Ophir, Nass, and Wagner Begin Their Research Eyal Ophir is a graduate student in Clifford Nass's Communication Department lab at Stanford. Nass is a communication scholar known for research on human-computer interaction and the psychology of media. Anthony Wagner is a cognitive neuroscientist in the Department of Psychology. The collaboration brings together communication studies, psychology, and neuroscience perspectives on a question that sits at their intersection.

The research team designs a series of cognitive tasks specifically aimed at measuring the attention and cognitive control abilities that multitasking is presumed to require: the ability to filter out irrelevant information (selective attention), the ability to switch between tasks efficiently (task-switching), and the ability to maintain multiple items in working memory simultaneously (working memory capacity).

2009: The Landmark Publication Ophir, Nass, and Wagner publish "Cognitive control in media multitaskers" in the Proceedings of the National Academy of Sciences — one of the most prestigious scientific journals, giving the finding immediate visibility across scientific disciplines and in mainstream media. The paper reports that heavy media multitaskers (HMMs) perform significantly worse than light media multitaskers (LMMs) on all three attention and cognitive control measures.

The finding generates immediate and widespread attention. The counterintuitive reversal of the expected finding — that experience with multitasking degrades rather than builds multitasking capacity — challenges a widely held assumption and invites multiple interpretations, extensions, and challenges.

2010–2015: Replication Attempts and Extensions The Stanford finding generates a substantial secondary literature. Some studies replicate the core finding; others find more qualified or null results. The variation appears to depend on how media multitasking is measured, what cognitive tasks are used, and what populations are sampled. The field develops a more nuanced picture: the relationship between media multitasking and cognitive performance is real but heterogeneous, and the mechanisms are still being worked out.

Critically, several neuroimaging studies examine whether heavy media multitaskers show structural or functional brain differences compared to light multitaskers. Some find differences in prefrontal cortex activation and anterior cingulate cortex structure associated with cognitive control functions, consistent with the behavioral findings. These neuroimaging results are correlational and do not establish causation, but they add a biological dimension to the cognitive performance differences.

2014: The Rosen Replication and Extensions Larry Rosen and colleagues at California State University extend the multitasking research to academic settings, finding that college students who used social media or texted while studying retained significantly less information from their study sessions and performed worse on subsequent tests than those who studied without technological interruption. The classroom and study setting extension of the Ophir findings gives the research immediate applied relevance.

2016–2022: The Academic Performance Literature Expands A substantial literature accumulates on the relationship between media multitasking and academic performance. Meta-analyses of the field find consistent negative associations, with variation in magnitude across studies attributable to differences in multitasking measurement, outcome assessment, and population. The overall pattern is clear: media multitasking during study is associated with worse academic performance.

A smaller literature examines whether the relationship is moderated by individual differences in cognitive control capacity, finding that students with lower baseline working memory capacity show stronger negative effects of multitasking on performance. This suggests that the students most harmed by the notification environment are also those with the least cognitive resources to manage it.

2020–Present: The Smartphone-Specific Extension As smartphones have become the dominant platform for media multitasking, researchers increasingly focus on phone-specific multitasking: using social media or messaging while studying or working. The findings are consistent with the original Ophir et al. work and with the Ward et al. brain drain research: phone-based media multitasking during cognitive tasks impairs performance on those tasks, independently of whether students are aware of the impairment.

Analysis

What the Finding Means and What It Does Not

The most common misinterpretation of the Ophir et al. finding is the causal claim: that heavy media multitasking causes cognitive impairment. Ophir et al.'s study was correlational — it identified an association between media multitasking habits and cognitive performance, not a causal direction. The causal direction could run in either direction, or both.

Direction 1 (Practice degrades capacity): Heavy media multitasking, because it involves frequent switching between attention targets and tolerance of irrelevant distraction, trains the cognitive systems responsible for attentional control in ways that degrade their function. Practice at distracted attention produces better distracted attention — and worse focused attention.

Direction 2 (Pre-existing differences attract multitasking): People who have lower capacity for sustained focused attention find monotasking aversive and are attracted to the more varied, stimulating experience of media multitasking. The lower cognitive control capacity is prior to the multitasking behavior; the multitasking behavior is a symptom rather than a cause.

Direction 3 (Bidirectional): Both directions operate simultaneously. Pre-existing tendencies toward lower focused attention attract heavy media multitasking, and the multitasking behavior further conditions reduced attentional focus, in a mutually reinforcing cycle.

Subsequent research has attempted to distinguish among these possibilities. Longitudinal studies that measure cognitive function before and after periods of heavy vs. light multitasking behavior would provide the strongest causal evidence. The available longitudinal data, while limited, leans toward a bidirectional interpretation: both pre-existing individual differences and ongoing multitasking behavior appear to contribute to the observed associations.

The Attention Filter Hypothesis

Ophir et al.'s proposed mechanism — that heavy media multitaskers are worse at filtering out irrelevant information — is supported by the specific pattern of their findings. The strongest effects were found on a task that required participants to ignore irrelevant information while focusing on relevant targets: heavy multitaskers showed greater interference from the irrelevant information than light multitaskers.

This "attention filter" hypothesis has a plausible mechanism: if heavy multitasking conditions the cognitive system to treat a wide range of stimuli as potentially relevant (because in a multitasking environment, the source of the next important input is unpredictable), the attentional filter that normally excludes irrelevant stimuli may become chronically broader than optimal for focused single-task contexts.

In everyday terms: the heavy multitasker's attention is calibrated for an environment in which anything might be important. When placed in an environment where one specific thing is important and everything else should be ignored, that broadly calibrated attention system is disadvantaged relative to one calibrated for focused engagement with a single task.

The relevance to social media specifically is that social media use is a paradigmatic form of media multitasking. The typical social media session involves simultaneous processing of: visual content (images, videos), text content (captions, comments, news), social information (who posted, what their relationship to the viewer is, what the social implications of the content are), and notification monitoring (is there something else happening that requires attention?). The feed architecture is designed for multi-track attention rather than focused engagement.

If the Ophir et al. mechanism is correct — if heavy media multitasking trains the attentional filter to be broader, making focused attention harder — then habitual social media use is a form of attentional training with potentially adverse effects on the kind of sustained, focused attention that academic and professional tasks require.

This is not a claim that social media is uniquely harmful; any habitual practice of distracted, multi-track attention might produce similar effects. But social media is, for many adolescents and young adults, the dominant daily attentional environment — consuming more hours than any other single activity outside of school. The attentional training effects of the dominant attentional environment are, accordingly, potentially significant.

Educational Implications

The Ophir et al. finding and its extensions have clear implications for educational practice. Students who regularly use social media or other media during studying may be both performing worse in the immediate session (reduced encoding due to divided attention and distraction) and developing attentional patterns that make sustained focus progressively harder over time.

Research on classroom technology policy reflects this understanding. Studies comparing classrooms with strict no-phone policies to those with permissive policies consistently find higher academic performance in no-phone conditions, with the effects strongest for students at lower academic performance levels. The students who most need the cognitive resources that focused attention provides are also the students whose performance is most degraded by the distracted attentional environment of phone-permitted classrooms.

The equity dimension here is significant. Students from lower socioeconomic backgrounds tend to have less access to quiet, device-free study environments at home. School may be the one environment in which the physical design could support focused attention — if the policy choices are made to implement that design. Permissive phone policies in schools disproportionately harm students who lack alternative access to device-free environments.

The Self-Assessment Problem

A particularly important aspect of the media multitasking research is what it reveals about the accuracy of self-assessment. Heavy media multitaskers, in study after study, believe themselves to be effective multitaskers. They feel more comfortable in multitasking environments; they find monotasking aversive. Their subjective sense of their multitasking ability does not match their objective performance.

This disconnect between subjective confidence and objective performance is characteristic of the Dunning-Kruger pattern: in domains where one lacks skill, one also tends to lack the metacognitive capacity to accurately assess one's own lack of skill. The heavy media multitasker, having practiced distracted attention extensively, has become comfortable with distracted attention — which feels like competence — without recognizing that their focused attention capacity has not kept pace.

The practical implication is that self-assessment is not a reliable guide to attentional management needs. Students who believe they can study effectively while monitoring social media may be systematically wrong about their own cognitive performance — and the evidence suggests that the students most confidently wrong are those whose performance is most impaired.

What This Means for Users

The multitasking myth has several practical implications for students and knowledge workers:

Confidence in your multitasking ability is not evidence of actual multitasking competence. The Ophir et al. research shows that heavy media multitaskers are simultaneously more confident in and worse at focused attention tasks than light multitaskers. If you believe you are good at studying while using social media, that belief is more likely to reflect comfort with divided attention than actual maintained learning effectiveness.

The damage may not be immediate or visible. Students who study while monitoring social media often feel they are learning normally. The performance deficit typically shows up on assessments — tests, papers, long-term retention — rather than in the immediate subjective experience of studying. The absence of immediate discomfort is not evidence of effective learning.

The effect may be stronger for lower-achieving students. Research on moderating variables consistently finds that students with lower baseline cognitive control show stronger negative effects of media multitasking on performance. If you are already struggling academically, the cognitive overhead of the notification environment is likely costing you more than it costs high-performing students.

Creating phone-free study environments is a learning equity issue. Students who lack access to quiet, device-free home study environments are more dependent on school environments for focused learning. Classroom phone policies are not merely about individual performance; they are about whether the institutional environment supports the learning of students who most need institutional support.

Discussion Questions

The Ophir et al. study was correlational, leaving the causal direction uncertain. If subsequent research established that the causal direction runs primarily from pre-existing low attentional capacity to heavy multitasking (rather than from multitasking to reduced capacity), how would this change the educational and policy implications of the finding?
Heavy media multitaskers feel more comfortable in multitasking environments and may genuinely find monotasking aversive. Is discomfort with monotasking a problem to be fixed, or might it be a reasonable response to a genuinely changed information environment? What is the value of the capacity for sustained monotasking in a world where attention is routinely divided?
Research finds that no-phone classroom policies improve performance most strongly for lower-achieving students. Does this finding create an obligation for schools to implement such policies? What are the arguments against this obligation, and how should they be weighed?
The chapter argues that self-assessment of multitasking ability is unreliable — heavy multitaskers overestimate their competence. What are the implications of this finding for how students should approach their own study habit decisions? Should they trust their own experience, or defer to the research even when it conflicts with their experience?
If social media use is a form of attentional training that degrades focused attention capacity, what does this suggest about the appropriate age at which children and adolescents should be introduced to social media? What evidence would you want to see to confidently answer this question?