Reducing Distractions¶

Strategy · All strategies
Evidence · 2 claims (2 for) · 8 studies (6 causal, 2 quant-synthesis), q2–q4 · 2 of 8 report an effect size

Description¶

Reducing distractions is the deliberate removal or suppression of stimuli that compete with the learning task for attention — extraneous on-screen decoration, background noise, irrelevant media, notifications, and multitasking demands. It is carried out through environment design (physical and digital), message design (what is presented), and task design (what learners are asked to do simultaneously).

Design Implications¶

Working memory is severely limited, and attention allocated to irrelevant input is unavailable for schema construction Cognitive overload degrades learning. [+S]. The multimedia coherence research shows that deleting interesting-but-irrelevant text, graphics, and background music improves learning, contrary to the intuition that added stimulation increases engagement Decorative illustrations do not improve learning. [+S]. Multitasking is not a viable learner workaround: media multitasking during learning measurably reduces comprehension and note-taking quality, and the cost extends to nearby peers who can see the distracting screen [-S].

Context¶

Requirements¶

• A clear analysis of which stimuli are relevant to the learning goal — reduction requires knowing what to keep
• Control over the presentation layer: clean slides, legible layout, purposeful media (Clear Structure & Presentation)
• For digital environments: notification management, single-task task design, and device policies agreed with learners rather than imposed unilaterally

Constraints¶

• Over-sanitized environments can reduce engagement and motivation; mild novelty and contextual richness support interest when they serve the goal [~M]
• Distraction reduction targeted at learners with high prior knowledge can be redundant or even counterproductive — experts can ignore irrelevant material that overwhelms novices [~M]
• Device bans without accompanying task design shift multitasking off-screen (daydreaming, off-task conversation) rather than eliminating it [-W]
• In open or collaborative spaces, some ambient stimulation is unavoidable; suppression strategies must be paired with individual attention-regulation skills

Implementation Variability¶

• Message design: apply coherence, signaling, and contiguity principles to strip and highlight what matters in materials
• Environment design: seating, acoustics, and noise management (Acoustics and Noise Management)
• Digital design: remove autoplay, ads, and navigation clutter; segment video; default to closed captions off unless needed
• Learner self-management: teach learners to self-regulate attention (phone out of room, single-tab work, planned breaks) rather than relying solely on external control

Target Learners¶

• Novices, who lack the prior knowledge to distinguish relevant from irrelevant input and are most harmed by extraneous load Cognitive overload degrades learning. [+S]
• Learners with attention difficulties, for whom environmental structure has outsized effects
• Less critical for experts, who can down-regulate irrelevant input themselves [~M]

Target Learning Goals¶

• Any goal dependent on building new schemas in working memory — factual, conceptual, and procedural learning
• Especially goals requiring sustained comprehension (reading, lecture, video) rather than brief retrieval or review

Instructions¶

1. Audit the learning task and identify the elements essential to the objective; treat everything else as a candidate for removal.
2. Strip extraneous material from materials and slides — decorative images, tangential anecdotes, background audio Decorative illustrations do not improve learning. [+S].
3. Signal structure so attention is guided rather than captured — headings, highlighting, and Advance Organizers direct attention to what matters.
4. Break complex material into manageable units (Chunking) so learners are not holding irrelevant intermediate content in mind.
5. Design tasks as single tasks: one window, one goal, no simultaneous demands.
6. Establish shared norms for devices and notifications, and teach learners the self-regulation rationale rather than only the rule.
7. Reintroduce richness selectively — authentic contexts and Authentic Audiences & Purposes — once core content is secured.

Related Strategies¶

• Chunking — reduces intrinsic load per unit; complements distraction reduction by shrinking what must be held at once
• Signaling and Highlighting — guides attention to relevant content rather than only removing irrelevant content
• Segmenting — pacing control prevents overload from continuous streams
• Acoustics and Noise Management — the physical-environment arm of the same goal
• Consider a focused more is more approach combining minimized extraneous processing with prompts for generative processing
• Keep the video player user interface consistent when pausing for self-explanation prompts to avoid extraneous reorientation

Examples¶

• Multimedia course design: applying the coherence principle by replacing decorative stock photos in an online biology module with diagrams tied to the explained process (Clark & Mayer, 2016).
• Laptop classrooms: research by Sana et al. (2013) found that students multitasking on laptops scored significantly lower on comprehension tests — and peers seated in view of the multitasking screen were also impaired — informing many instructors' device policies.
• Video platforms: Khan Academy videos use a minimal visual field (blackboard-style, single problem, no background music), consistent with coherence findings.

Key Sources¶

• Sana, F., Weston, T., & Cepeda, N. J. (2013). Laptop multitasking hinders classroom learning for both users and nearby peers. Computers & Human Behavior, 29(3), 706–709. doi:10.1016/j.compedu.2012.10.003
• Clark, R. C., & Mayer, R. E. (2016). E-Learning and the Science of Instruction (4th ed.). Wiley. doi:10.1002/9781119239086
• Mayer, R. E. (2021). Multimedia Learning (3rd ed.). Cambridge University Press. doi:10.1017/9781316941355
• Sweller, J., Ayres, P., & Kalyuga, S. (2011). Cognitive Load Theory. Springer. doi:10.1007/978-1-4419-8126-4