Determination and Development Of Sustainable Energy Awareness Of High School Students: Başakşehi̇r Case
Description
This study examines the awareness and attitudes of high school students in Turkey towards renewable energy across four grade levels (from 9th to 12th grade), focusing on socio-economic factors, educational influences, and sustainable energy education strategies. The findings reveal an overall positive trend in awareness levels, with senior students showing greater interest in renewable energy careers. Socio-economic factors, family background, and educational influences emerge as key determinants of students’ awareness levels. Challenges include resource limitations and dependence on traditional energy sources, prompting the study to emphasize the importance of comprehensive sustainable energy education. The research recommends innovative educational strategies and inclusive initiatives to address these challenges. Additionally, the study explores behavioral development factors, suggesting strategies to overcome obstacles and enhance sustainable energy behaviors among students. In conclusion, this research contributes valuable insights to the discourse on sustainable energy education and provides a roadmap for promoting a more sustainable future.
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Steps to reproduce
Steps to Reproduce the Research: 1. Survey Creation: - Question Selection: I selected survey questions from a well-known expert in the field of sustainable energy. After obtaining permission to use these questions, I adapted them for my research. - Google Form: The survey was created using Google Forms, ensuring it was accessible and easy to distribute. 2. Data Collection: - Distribution: The Google Form survey was distributed to high school students in the Başakşehir district. - Response Gathering: Responses were collected over a defined period, ensuring a representative sample size. 3. Data Processing: - Export to Excel: The collected data from Google Forms was exported as an Excel file for further analysis. - Data Cleaning: Basic data cleaning was performed in Excel to ensure accuracy and consistency. 4. Data Analysis: - Python Script: I developed a Python script to analyze the data. The script performed several key functions: - Calculate Means: It calculated the mean response for each question by grade level. - Overall Means: It computed the overall mean response for each grade across all questions. - Visualization: Using Python libraries (such as Matplotlib or Seaborn), the script generated graphs to visually represent the data. 5. Tools and Software: - Google Forms: For survey distribution and initial data collection. - Microsoft Excel: For data export and preliminary cleaning. - Python: For data analysis and visualization. Key libraries used included: - Pandas: For data manipulation and analysis. - NumPy: For numerical operations. - Matplotlib/Seaborn: For creating graphs and visualizations. 6. Region of Study: - Başakşehir District: The research focused on high school students within the Başakşehir district, providing a specific context for the findings.