Student Insomnia and Educational Outcomes Dataset

This dataset consists of 985 rows (responses) and 16 columns (features), focusing on the relationship between insomnia and its impact on educational outcomes. It includes self-reported data on sleep patterns, quality, fatigue, stress levels, academic performance, and lifestyle habits. The survey was conducted using Google Forms, ensuring broad accessibility and ease of participation.

Data Collection: The data was collected through an online survey administered via Google Forms in Oct-Nov 2024. Respondents were asked to provide insights into their sleep behaviors and the effects on their academic and daily activities.

Key Features:
1. Demographics: Year of study and gender.
2. Sleep Patterns: Frequency of difficulty falling asleep, hours of sleep, night awakenings, and overall sleep quality.
3. Cognitive and Academic Effects: Impact on concentration, fatigue, class attendance, assignment completion, and overall academic performance.
4. Lifestyle Factors: Electronic device usage before sleep, caffeine consumption, and physical activity frequency.
5. Stress Levels: Self-reported stress related to academic workload.

This dataset can be used for:
1. Machine learning analysis to model and predict academic performance based on sleep and lifestyle factors.
2. Statistical studies investigating the connection between sleep disturbances and educational outcomes.
3. Developing behavioral and educational interventions to improve student well-being and performance.

Format: The dataset consists of 16 columns in categorical or ordinal formats. It contains 785 rows with no missing data, making it ready for analytics and machine learning applications.