Factors Determining Bangladeshi University Students' Perception, Knowledge and Attitude About Climate Change: A Cross-Sectional Study
Description
This dataset is generated during the research article "Factors Determining Bangladeshi University Students' Perception, Knowledge and Attitude About Climate Change: A Cross-Sectional Study" (DOI: 10.1002/hsr2.70722). It contains comprehensive data collected from 1,500 university students across Bangladesh and is structured to explore the determinants of students’ knowledge, perception, and attitude toward climate change. Dataset Structure The Excel file comprises three sheets: 1. raw Sheet Contains 34 categorical variables, including: Socio-demographic characteristics: Gender, educational level, study discipline, individual monthly expenditure, residency, and parental education levels. Information sources: Where students primarily learn about climate change. Knowledge and perception indicators: Students’ awareness of climate change, beliefs about local manifestations (e.g., extreme weather, floods, droughts, riverbank erosion), and perceived health impacts. Attitudinal components: Opinions on media's role, necessity for climate education, and willingness to stay informed. 2. coded Sheet A quantitatively transformed version of the raw data with 40 columns. Includes: Recoded responses into numerical formats (e.g., Agree = 1, Neutral = 0.5, Disagree = 0). Composite indicators: Total Knowledge Score and Knowledge Level (Good vs. Poor) Total Attitude Score and Attitude Classification Ready for statistical analysis including regression, correlation, and ANOVA. 3. codebook Sheet Provides the labeling scheme and coding guide. Maps variable names to simplified labels (e.g., K1 for the first knowledge item) and outlines the numerical values assigned to Likert-scale responses. Study Background The dataset originates from a cross-sectional survey aimed at understanding how various factors shape Bangladeshi university students’ awareness and attitude toward climate change, with implications for future education and policy initiatives. The associated article investigates the interplay between socio-demographic traits and climate literacy and offers insights for integrating climate topics into higher education curricula in low- and middle-income countries. Applications This dataset is suitable for: Descriptive analysis of climate change awareness among youth. Inferential analysis (e.g., binary logistic regression, t-tests) of determinants influencing knowledge and attitudes. Modeling the role of socioeconomic and educational background in shaping climate perceptions. It serves as a valuable resource for public health researchers, environmental educators, and policymakers interested in climate education and youth engagement in climate resilience efforts in Bangladesh and similar contexts.