Digital Distractions from the Point of View of Higher Education Students

1. Introduction

• Technology supports inclusion, engagement, interaction, and new learning opportunities, but can also distract students and hinder learning.Removing classroom technology could increase inequality between students with and without access outside class and increase digital illiteracy among younger learners.Source: §1 · pp. 1–2
• The study identifies the main technology-related classroom distractors from students’ perspectives at a central-Spain engineering school.The authors conducted the study during the 2021–2022 academic year as part of an educational innovation project.Source: §1 · p. 2
• The paper presents the sustainability challenge, examines classroom distractions, describes data collection, and then reports results and conclusions.Source: §1 · pp. 2–3

2.1. Necessity and Challenges of Sustainable Digital Uses in College Classrooms

• Instructors need technological skills to integrate classroom technology effectively, while monitoring students’ off-task use is also important for sustained use.Students bring devices for purposes such as notetaking or research, but devices can also enable internet distraction.Source: §2.1 · p. 3

2.2. Digital Distractions in College Classrooms

• Digital distractions compete with limited attention and working-memory resources, while multitasking can prolong tasks and impair learning and academic performance.The background describes alerts and messages as making it difficult to focus, and notes that returning to a task takes extra effort.Source: §2.2 · pp. 3–4

2.3. Impact of Digital Distractions in College Classrooms

• Research has examined off-task behaviors, consequences, and determinants, while the background also describes monitoring and active instruction as ways to address distraction.The cited research reports varied consequences of media multitasking for social and psychological well-being and an inverted U-shaped association between out-of-class cyberloafing and academic performance.Source: §2.3 · pp. 4–6
• Prior studies report diverse off-task activities, including messaging, email, social media, and browsing, and link some of them to weaker learning outcomes or retention.Reported findings include lower lecture-quiz performance with off-task texting and reduced long-term retention with divided attention.Source: §2.3 · pp. 5–6

3.1. Settings

• The study took place at a telecommunications engineering school where instructors and students regularly use technology in academic activities.The school offers engineering programs related to Telecommunication Technologies and serves students approximately 17 to 25 years old.Source: §3.1 · p. 6

3.2. Participants

• A total of 105 students participated across subjects selected to reach many enrolled students while avoiding repeat participation.The subjects covered several engineering areas and included undergraduate and master’s-level courses.Source: §3.2 · pp. 6–7

3.3. Identification of Classroom Distractors

• The researchers adapted a prior comprehensive list of classroom distractors to their engineering-school context and classified items as digital or non-digital.Digital distractors were marked with an asterisk in the list presented in Table 2.Source: §3.3 · p. 7

3.4. Procedure

• During laboratory classes, students selected the distractors they considered most impactful, suggested others, and answered questions about time use and digital versus non-digital distractions.The procedure also included a moderated small-group discussion following data collection.Source: §3.4 · pp. 7–8

4.1. Classroom Distractors

• Table 2 reports global and subject-level counts and percentages for classroom distractors, including social networks, messaging, email, and device sounds.Digital distractors are marked with an asterisk and listed at the end of the table.Source: §4.1 · pp. 8–10, Table 2 · p. 8

4.2. Additional Distractors

• Most students considered the proposed distractor list complete, while students in two subjects additionally identified insects and noise from open windows or hallways.The insects were identified by third-year RTCI students and first-year PRO students; PRO students also named the two noise sources.Source: §4.2 · p. 10

4.3. Use of Time

• Students were asked whether they thought they could make better use of their laboratory time, with percentages reported by subject and plotted in Figure 1a.Table 3 also identifies each subject’s year and engineering study program.Source: §4.3 · p. 10, Table 3 · p. 10, Figure 1 · p. 11

4.4. Digital vs. Non-Digital Distractors

• Students were asked whether digital distractions had more influence than non-digital distractions, with percentages reported by subject and plotted in Figure 1b.Table 4 identifies each subject’s year and engineering study program.Source: §4.4 · p. 11, Table 4 · p. 11, Figure 1 · p. 11

5.1. Classroom Distractors

• Students reported distractions from talking (50.73%), unnecessary comments (36.73%), unclear explanations (48.98%), equipment problems (52.04%), and unsuitable temperatures (63.27%); no consistent year-of-study trend emerged.Unsuitable temperatures reached 100% in two fourth-year subjects.Source: §5.1 · pp. 12–13
• Social networks (43.88%) and messaging apps (41.84%) were the most reported digital distractors, ahead of email and music (13.27% each); device sounds distracted 56.12%.Students described low-volume music as potentially aiding concentration in some individual coding labs.Source: §5.1 · p. 12

5.2. Additional Distractors

• Students also identified insects and noise from open windows or hallways as additional distractions amid pandemic ventilation practices.Open windows and doors improved air quality but brought outside noise and climate problems into the laboratories.Source: §5.2 · p. 13

5.3. Use of Time

• On average, 69.20% thought they could use lab time better, with no year-of-study trend; responses ranged from 100% in RTCI to 26.92% in DAD.DAD attendance was optional, and students said they preferred to finish tasks during lab and avoid homework; affirmative responses were 77.42% in PRO and 85.71% in ISTR.Source: §5.3 · pp. 13–14

5.4. Digital vs. Non-Digital Distractors

• On average, 47.57% thought digital distractions outweighed non-digital ones, with no consistent year trend; responses were 85.71% in master’s ISTR and 32.26% in first-year PRO.The authors suggest first-year students’ continual device use may limit their critical awareness of inappropriate use.Source: §5.4 · p. 14

5.5. In-Depth Discussion of Results

• Web browsing was the only distraction significantly correlated with students’ belief that they could use lab time better (Pearson coefficient 0.878).The authors identify it as the digital distraction most associated with lab performance and recommend limiting its impact while reinforcing self-control.Source: Table 5 · p. 15, §5.5 · p. 15
• Perceived digital dominance correlated with repetitive movements (0.923) and social-network, messaging, and web use (0.887, 0.953, and 0.870); digital distractions also correlated with one another.The authors note that repetitive movements correlated with social-network and web browsing (0.878 each), potentially involving other students and the broader classroom environment.Source: §5.5 · pp. 15–17
• Equipment problems correlated with gaming and device sounds (0.755 and 0.842), while unnecessary comments correlated with music (0.871).Repetitive movements correlated with messaging (0.874) and unusual clothing with music (0.848); difficult-to-understand explanations correlated with device sounds (0.933). The authors used Pearson correlations except when both variables failed normality, when they used Spearman.Source: §5.5 · pp. 14, 16

• Digital distractions were judged comparable to non-digital ones despite three times as many non-digital examples; over two thirds saw lab performance as improvable across subject years.The authors report no meaningful difference in perception across the subject years studied.Source: §6 · p. 18
• Unlike prominent non-digital distractions often caused by others or conditions, social networks and messaging are student-driven, making awareness and self-control direct avenues to reduce their influence.Source: §6 · p. 18
• Off-task web browsing alone correlated significantly with students’ belief they could use lab time better, and it also correlated with social-network, messaging, and email use.Source: §6 · pp. 18–19
• Technology itself is not the problem; the authors call for monitoring, awareness, self-regulation, and motivated engagement to sustain effective educational use.They note that students may be susceptible to distraction when they are not fully engaged in learning.Source: §6 · p. 19
• Appropriate communication channels can help incidents involving laboratory equipment or climate conditions be reported promptly, since these issues may be readily corrected.Source: §6 · p. 19
• The authors call for more research into technology’s understudied negative effects, including student distraction, and urge students to control digital overload.Source: §6 · p. 19