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Online Education Mental Well-being Data
Mental Health & Wellness
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Free
About
This dataset captures student responses concerning their mental health status during online learning. Collected via surveys, it delves into various psychological and behavioural aspects influenced by remote education. It is ideal for exploratory data analysis, data visualisation, and predictive modelling to gain insight into how online education impacts student mental well-being.
Columns
- Name: First name of the student; non-essential for analysis and can be anonymised.
- Gender: Gender of the respondent (Male, Female, Other).
- Age: Age of the student in years, typically ranging from 15 to 26.
- Education Level: Academic level, such as Class 8, BTech, or MSc.
- Screen Time (hrs/day): Average daily screen exposure in hours during online learning, typically ranging from 2 to 12.
- Sleep Duration (hrs): Average daily sleep duration in hours, typically ranging from 4 to 9.
- Physical Activity (hrs/week): Weekly time spent on physical exercise in hours, typically ranging from 0 to 10.
- Stress Level: Self-assessed stress level, categorised as Low, Medium, or High.
- Anxious Before Exams: Indicates whether the student feels anxious before exams (Yes/No).
- Academic Performance Change: Student’s perceived change in academic performance (Improved, Same, Declined).
Distribution
The dataset contains 1,000 entries and 10 columns. It is provided in a CSV format and is approximately 50.12 kB in size.
Usage
This dataset can be utilised for:
- Exploratory data analysis (EDA) to uncover patterns and anomalies related to student mental health.
- Data visualisation to illustrate trends and relationships between lifestyle factors and well-being.
- Predictive modelling to forecast student mental well-being outcomes under various conditions.
- Understanding the impact of online education on mental health.
- Developing targeted interventions and support systems for students in remote learning environments.
Coverage
The dataset covers demographic details, lifestyle habits, and self-reported mental health indicators of students aged 15 to 26 years, across various academic levels. The data specifically reflects the period of online learning. No specific geographic scope is mentioned within the provided material. The dataset is not expected to be updated.
License
CC0: Public Domain
Who Can Use It
This dataset is intended for a diverse range of users, including:
- Researchers studying educational psychology, public health, and remote learning impacts.
- Educators and academic institutions to inform student support services and curriculum development.
- Policy makers to develop guidelines for online learning environments that prioritise student well-being.
- Data scientists for building predictive models related to mental health indicators.
- Mental health professionals for understanding student stressors and developing interventions.
Dataset Name Suggestions
- Student Mental Health in Online Learning
- Online Education Mental Well-being Data
- Remote Learning Student Mental Health Survey
- Student Digital Learning Psychological Impact Data
Attributes
Original Data Source: Online Education Mental Well-being Data
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