Smartphone App Usage Among English Majors with Personality and Academic Metrics

MAUT data tracks smartphone app usage among 31 third-year English majors at a Chinese university perceived to be addicted. The dataset includes 2 weeks of objective app-tracking data, a 50-item personality questionnaire, academic performance metrics, and qualitative reflections. It was authored by Qian Wang and last updated on 2026-05-05.

Use Cases

• Analyze correlations between smartphone usage time and personality traits based on the 50-item questionnaire.
• Investigate the relationship between app usage patterns and academic performance metrics.
• Study motivations for smartphone use based on qualitative reflections on communication, study, and entertainment drivers.
• Model perceived addiction versus functional engagement based on objective tracking data and self-reported denial/admission rates.

Strengths

• Includes objective app-tracking data for 2 weeks, totaling 150,551 minutes on top apps.
• Combines multiple data sources: personality questionnaire (50 items), academic metrics, and qualitative reflections.
• Focuses on a specific cohort of 31 English majors, providing context-specific insights.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The sample size is small (31 participants), limiting generalizability.

Provenance

Source

figshare

Collection Method

Mixed-methods approach using app-tracking data, questionnaires, academic metrics, and qualitative reflections.

Time Range

Data collected over 2 weeks (Week 1 and Week 2).

Freshness

Last updated 2026-05-05 17:21:28; freshness should be verified.

Geography

Data collected from a Chinese university.