Scroll or Study? The Impact of Social Media on Academic Performance

105 topics across 7 chapters

Chapter 1

Context and key concepts

What counts as “academic performance”?

3 subtopics

Objective outcomes: grades, GPA, test scores

Learning outcomes: retention, participation, engagement

Self-reported vs. objective measures (bias and validity)

Social media behaviors and usage patterns

3 subtopics

Active vs. passive use (posting/messaging vs. scrolling)

Multitasking during study (second-screen behavior)

Notifications and “always-on” communication

Digital wellbeing basics (attention, sleep, mental health)

3 subtopics

Attention and cognitive load primer

Sleep and circadian disruption pathways

Stress/anxiety and social comparison effects

Chapter 2

Mechanisms linking social media to learning

Distraction and task switching

2 subtopics

Design a mini-study: interruption timing and comprehension (Pomodoro variant)

Context-switching costs: reading/writing performance under interruptions

Time displacement (time spent online replaces study time)

2 subtopics

Collect time-use diaries and summarize study vs. social time

Opportunity cost framing: translating minutes into expected grade impact (conceptual)

Potential benefits: social capital and peer support

2 subtopics

Peer learning via groups/communities (Discord/GroupMe/etc.)

Help-seeking behavior and belonging (who benefits, when)

Motivation, procrastination, and self-control loops

2 subtopics

Self-regulation and executive function basics

Habit formation: cues, routines, rewards in phone checking

Algorithmic feeds and reinforcement design

2 subtopics

Engagement metrics and persuasive design patterns

Personalization effects (feeds, recommendation) in academic contexts

Chapter 3

Research design and ethics

From literature review to hypotheses

2 subtopics

Build a search strategy (databases, keywords) and set inclusion/exclusion criteria

Create a conceptual model (variables, pathways, expected directions)

Study designs (survey, longitudinal, experimental)

4 subtopics

Survey studies: questionnaire structure and pitfalls

Experience Sampling / EMA: capturing in-the-moment use and attention

Randomized interventions: designing and evaluating digital behavior changes

Natural experiments and quasi-experiments (policy or platform changes)

Sampling, confounders, and causal thinking

3 subtopics

Identify key confounders (SES, prior achievement, mental health, course difficulty)

Causal inference basics: DAGs, controls, and backdoor paths

Power analysis and sample size planning (practical rules of thumb)

Ethics, privacy, and consent

2 subtopics

De-identification: what to remove/aggregate in student digital data

Research with minors: assent, parental consent, and extra safeguards

Chapter 4

Measurement and data collection

Instruments and questionnaires

2 subtopics

Choose validated scales (problematic use, FoMO, attention, wellbeing)

Pilot test: reliability (e.g., Cronbach’s alpha) and item refinement

Digital trace data (screen time, app logs, LMS logs)

3 subtopics

Collect screen-time data (iOS/Android exports) and define usage metrics

Track study sessions (timers/extensions) and align with phone-use windows

Securely link logs to outcomes (pseudonymous IDs and key management)

Study environment and covariates

2 subtopics

Control for course load, deadlines, and schedule constraints

Study habits and metacognition measures (planning, monitoring, reflection)

Data quality, missing data, and cleaning

2 subtopics

Missingness types (MCAR/MAR/MNAR) and simple handling strategies

Data cleaning checklist (outliers, duplicates, inconsistent timestamps)

Chapter 5

Data analysis and interpretation

Descriptive statistics and visualization

2 subtopics

Create an EDA pack: distributions, scatterplots, time-series summaries

Report effect sizes and uncertainty (CIs) instead of only p-values

Correlation vs causation (and how to write limitations)

2 subtopics

↗ Causal inference basics: DAGs, controls, and backdoor paths (see Chapter 3)

List common causal fallacies and draft a limitations paragraph for your study

Modeling relationships (regression and mixed models)

3 subtopics

Regression assumptions and variable coding (continuous, categorical, interactions)

Multilevel models (students within classes/schools) and repeated measures

Diagnostics: residuals, collinearity, influential points

Mediation and moderation (why and for whom effects happen)

2 subtopics

Mediation example: sleep or attention as pathways from social media to grades

Moderation example: age, baseline self-control, or anxiety as effect modifiers

Robustness, sensitivity, and researcher degrees of freedom

2 subtopics

Preregistration and multiple comparisons (controlling false positives)

Sensitivity analysis for unmeasured confounding (conceptual and practical)

Chapter 6

Interventions and practical strategies

Student-level habit and self-management strategies

3 subtopics

Notification management: batching, focus modes, and contact exceptions

Implementation intentions: “If X happens, then I do Y” plans for checking

Balanced use plan vs. detox: setting goals, boundaries, and review cadence

Teaching and course design strategies

2 subtopics

Active learning tactics to reduce off-task device use (structured activities)

In-class device policies: design options and unintended consequences

Tools and technology supports

2 subtopics

Time-limit and blocking tools: selecting, configuring, and measuring adherence

Learning analytics dashboards: using feedback without surveillance creep

Policy and campus-wide programs

2 subtopics

Media literacy and digital wellbeing curriculum components

Support services integration (advising, counseling, accommodations)

Evaluating interventions (what works, for whom, and at what cost)

2 subtopics

↗ Randomized interventions: designing and evaluating digital behavior changes (see Chapter 3)

Intervention evaluation plan: outcomes, follow-up windows, and fidelity checks

Chapter 7

Communicating findings (papers, presentations, stakeholders)

Writing a research report

2 subtopics

IMRaD structure: turning results into a clear argument

Reporting standards: methods detail, limitations, and reproducibility checklist

Visualizing results for stakeholders

2 subtopics

Figures for models: coefficient plots, marginal effects, and predicted outcomes

Avoid misleading visuals: axes, binning, color, and cherry-picked ranges

Replication and open science practices

3 subtopics

↗ Preregistration and multiple comparisons (controlling false positives) (see Chapter 5)

Share data/code responsibly (repositories, documentation, and privacy constraints)

Registered reports: separating confirmatory vs exploratory analyses

Talks, posters, and executive summaries

2 subtopics

Write a 1-page brief for administrators/parents (key findings + recommendations)

Presentation narrative and Q&A: anticipating critiques and alternatives