Assess students' ability to analyze how social media recommendation algorithms influence political polarization, including mechanisms (filter bubbles, echo chambers, engagement-based amplification), cognitive biases (confirmation bias, selective exposure), measurable effects (opinion divergence, network segregation), empirical methods for study (A/B testing, network and sentiment analysis, causal inference), and evaluate mitigation strategies and policy responses; require interpretation of evidence, identification of algorithmic incentives, and critical assessment of proposed interventions.