This study is concerned with the perceptions of university students in Bangladesh regarding climate change. A self-administered questionnaire survey was filed out by 650 final-year undergraduate students studying in a variety of academic disciplines at Shahjalal University of Science and Technology (SUST), Sylhet, Bangladesh. This study found that a majority of respondents perceive temperatures in Bangladesh as increasing and rainfall as decreasing. A majority also think that climate change is due to human activities such as deforestation, dredging rivers, extracting sand from rivers, the development of industry, and carbon emissions from vehicles, while a significant but smaller proportion perceived it as punishment from God for human sin. We examined the effects of selected variables—students’ sex, religious affiliation, involvement in an environmental organization, completion of university courses related to the environment or climate change, academic discipline of study, and past experience of extreme weather events in their home locality—using three multinomial logistic regression (MLR) models on perceived changes in temperature, perceived changes in rainfall, and perceived causes of climate change. The MLR analysis regarding the perceived changes in temperature indicates that effects of sex, experience of extreme weather event in their home locality, and the completion of climate change-related courses are statistically significant. For perceived changes in rainfall, these are significantly explained by all predictors except completion of a climate change-related course. And finally, for perceived causes of climate change, the effects of students’ experiences with extreme weather events in their hometown and involvement in an environmental organization were found to be statistically significant.

这项研究与孟加拉国大学生对气候变化的看法有关。在孟加拉国锡尔赫特的Shahjalal科技大学（SUST）的650名在不同学科学习的最后本科生进行了自我管理的问卷调查。这项研究发现，大多数受访者认为孟加拉国的温度在上升，而降雨在下降。多数人还认为，气候变化是由于人类活动造成的，例如森林砍伐，疏river河流，从河流中抽沙，工业发展以及车辆产生的碳排放，而相当大比例的人却认为这是上帝对人类罪的惩罚。我们研究了选定变量的影响-学生的性别，宗教信仰，参与环境组织，完成与环境或气候变化有关的大学课程，学术研究学科以及他们所在地的极端天气事件的以往经验-使用三个多项式Lo​​gistic回归（MLR）模型来感知温度变化，降雨的感知变化以及气候变化的感知原因。关于温度变化感知的MLR分析表明，性别，家中极端天气事件的经历以及与气候变化有关的课程的完成在统计学上具有显着意义。对于降雨量的感知变化，除了完成与气候变化有关的课程外，所有预测因素都可以对这些变化做出显着解释。最后，对于引起气候变化的原因，