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Academic Impact of Gaming Data
Education & Learning Analytics
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About
This dataset offers valuable insights into student demographics, gaming behaviours, and academic performance. It captures various attributes, including student gender, school identifiers, and detailed gaming habits such as years of experience, frequency of play, and average daily gaming hours. The dataset also distinguishes between active gamers and non-gamers. Beyond gaming, it incorporates socioeconomic factors like family annual income and parental education levels. A key component is the "Grade" variable, measuring academic standing. This rich dataset facilitates the exploration of correlations between gaming habits, socioeconomic background, and academic success, providing a foundation for research into how these factors might influence or hinder educational outcomes. It presents an excellent opportunity for analysis to identify trends and inform policies on gaming, parental involvement, and educational strategies.
Columns
- Sex: The student's gender, categorised as either "Female" or "Male".
- School Code: A unique numerical identifier for each educational institution.
- Playing Years: Represents the number of years a student has been engaging in gaming activities, indicating long-term habits versus newer activities.
- Playing Often: Quantifies the frequency of student gaming, likely measured on a scale from 1 to 5 to represent gaming intensity.
- Playing Hours: The average number of hours a student dedicates to gaming each day, useful for assessing the impact of extended gaming sessions.
- Playing Games: A binary indicator showing whether a student actively plays games or not, valuable for comparative studies.
- Parent Revenue: The annual income of the student's family, used to examine the influence of economic background on behaviour.
- Father Education: The education level of the student's father, providing insight into parental educational background.
- Mother Education: The education level of the student's mother, offering further details on parental educational background.
- Grade: A critical measure of the student's academic standing and performance.
Distribution
This dataset is provided in a CSV format, specifically named 'gameandgrade new.csv', with a file size of 27.8 kB. It comprises 11 distinct columns and contains 770 individual records, ensuring a consistent number of valid entries across all variables.
Usage
This dataset is ideal for various analytical applications, including:
- Academic Research: Exploring the relationship between gaming frequency and student academic performance.
- Socioeconomic Studies: Investigating whether students from higher-income families exhibit different gaming habits, such as spending more or fewer hours gaming.
- Educational Policy Development: Analysing the impact of parental education levels on gaming choices and duration, informing strategies for parental involvement and educational support.
- Behavioural Analysis: Identifying trends and generating insights that can inform policies related to student gaming habits and overall educational strategies.
Coverage
The dataset focuses on the demographic and behavioural aspects of students. It includes details such as gender, school affiliation, various facets of gaming habits (experience, frequency, daily hours), and socioeconomic factors like parental income and education levels. Academic performance is also covered through the "Grade" variable. Specific geographic or time range information for the data collection is not detailed within the provided materials.
License
CC0: Public Domain
Who Can Use It
This dataset is particularly useful for:
- Researchers and Academics: To conduct in-depth studies on student behaviour, academic outcomes, and socioeconomic influences.
- Data Analysts: For uncovering correlations and patterns between gaming habits, family background, and educational success.
- Educators and Policy Makers: To inform educational strategies, develop guidelines on student screen time, and understand the role of parental involvement.
- Organisations focused on Youth Development: To create programmes that balance leisure activities with academic responsibilities.
Dataset Name Suggestions
- Student Gaming Habits and Academic Performance
- Youth Gaming and Educational Outcomes
- Student Lifestyle and Grades Dataset
- Academic Impact of Gaming Data
Attributes
Original Data Source:Academic Impact of Gaming Data
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