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Impact of Virtual Reality on Education

✓ Published0🌍 Public
KKal
Last edited Dec 10, 2025
Created on Sep 16, 2025
Forked from Tech and Education

This visualization compares learning outcomes between students using virtual reality and a control group across immersion levels. The line chart displays average learning gain by weekly VR hours, with spline-smoothed traces for each group and unified hover tooltips showing both metrics simultaneously. Built with Plotly.js and D3 for data processing, the interactive dashboard supports zooming, panning, and toggleable legend controls. The visualization draws from a Kaggle dataset of 50 students measuring VR's educational impact across demographics and subjects.

AI-generated description

Impact of Virtual Reality on Education

Description

This dataset explores how immersive learning (VR-based) compares to traditional teaching methods in educational settings. It measures the impact of virtual reality on student engagement, learning outcomes, and overall educational effectiveness across different demographics and fields of study.

Source: Kaggle — Impact of Virtual Reality on Education by waqi786
Link: https://www.kaggle.com/datasets/waqi786/impact-of-virtual-reality-on-education

Dataset Overview

  • Total Records: 50 students
  • Time Period: Cross-sectional study
  • Coverage: Multiple grade levels, fields of study, and geographic regions

Attributes and Types

Attribute Type Description
Student_ID Categorical (Nominal) Unique identifier for each participant
Age Quantitative (Ratio) Participant's age in years
Gender Categorical (Nominal) Gender of the participant
Grade_Level Categorical (Ordinal) High School, Undergraduate, Postgraduate
Field_of_Study Categorical (Nominal) Subject area (Science, Engineering, Arts, etc.)
Usage_of_VR_in_Education Categorical (Binary) Yes/No indicator for VR usage
Hours_of_VR_Usage_Per_Week Quantitative (Ratio) Weekly VR engagement time in hours
Engagement_Level Quantitative (Ordinal) Scale 1–5 measuring student engagement
Improvement_in_Learning_Outcomes Categorical (Binary) Yes/No indicator for learning improvement
Subject Categorical (Nominal) Course subject (Math, Physics, Computer Science, etc.)
Instructor_VR_Proficiency Categorical (Ordinal) Beginner, Intermediate, Advanced
Perceived_Effectiveness Quantitative (Ordinal) Scale 1–5 for perceived VR effectiveness
Perceived_Sentiment Categorical (Nominal) Positive, Neutral, Negative sentiment
Geographic_Location Categorical (Nominal) Region where study took place
Additional_Support Categorical (Binary) Yes/No for supplementary learning resources

Key Research Questions

  1. Does VR usage correlate with improved learning outcomes?
  2. How does instructor VR proficiency impact student engagement?
  3. Are there demographic differences in VR effectiveness?
  4. What is the relationship between weekly VR hours and learning gains?
  5. How do students perceive VR effectiveness across different subjects?

Visualization Features

The interactive dashboard displays:

  • Primary Visualization: Line chart comparing VR Group vs Control Group learning outcomes by immersion score
  • Interactive Legend: Click to toggle group visibility
  • Unified Hover: View both groups' metrics simultaneously at each data point
  • Zoom & Pan: Explore specific immersion score ranges
  • Responsive Design: Adapts to different screen sizes

Data Quality Notes

  • Check for missing or incomplete participant data before analysis
  • Normalize engagement and effectiveness scores if mixing with different measurement scales
  • Treat ordinal variables (Engagement_Level, Instructor_VR_Proficiency) appropriately in statistical tests
  • Geographic regions include: North America, South America, Europe, Asia, Africa, Oceania
  • Gender categories include: Male, Female, Non-binary, Prefer not to say

Insights to Explore

  • Engagement vs. Outcomes: Do higher engagement levels predict learning improvement?
  • Instructor Impact: How does instructor proficiency moderate VR effectiveness?
  • Subject Differences: Which subjects benefit most from VR-based learning?
  • Usage Thresholds: Is there an optimal number of weekly VR hours for learning?
  • Demographic Patterns: Do age groups or grade levels show different VR adoption patterns?

Technologies Used

  • D3.js: Data processing and manipulation
  • Plotly.js: Interactive charting and visualization
  • Rollup: Module bundling
  • CSS3: Responsive styling with CSS custom properties

Getting Started

  1. Install dependencies: npm install
  2. Build the project: npm run build
  3. Start development mode: npm run dev
  4. Open index.html in a web browser to view the visualization
MIT Licensed

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