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We would like to train our data analytics skills and this project is the perfect moment to do so. By the end of it, we hope that our fundamental skills are good enough to prepare us for future data analytics projects in other courses or our own careers. As beginners, we would like to start with a dataset that is not too complicated but deep enough to do some analysis. As students ourselves, we went through the same debacle with the COVID-19 pandemic and all of our classes moving to an online environment. Hence, we were interested in this dataset of people from Bangladesh measuring their students’ adaptability to the change to online education. Furthermore, we wish to explore how different factors such as Socio-Economic status, Device ownership, and Maturity levels affect levels of adaptability in students and which factors matter more than others. Besides, it is possible to produce a dashboard with this dataset and in general, we will certainly include charts and graphs such as a pie chart that visualize the proportion of students based on their adaptivity level (High, Moderate, Low) and other data visualization that help answer each of our research question(s).
This dataset includes data collected between December 10, 2020, and February 5, 2021, by Department of Computer Science and Engineering (CSE) & Department of Computing and Information Systems (CIS) of Daffodil International University in Dhaka, Bangladesh. It explores the adaptability level of students based on their Age, Gender, Education Level, Institution Type, IT Student, Location in Town, Load-shedding, Financial Condition, Internet Type, Network Type, Class Duration, Self LMS, and Device being used for the education. The data was collected from universities, schools, and colleges via student surveys distributed by teachers and professors for the 12th International Conference on Computing Communication and Networking Technologies and then uploaded to Kaggle by MD. Mahmudul Hasan Suzan. It was then used by the education sector to get a proper idea about the current online education system and the level of adaptability of the students to online education. It was also used to measure how machine learning models performed at predicting students' adaptability levels given the 13 variables.
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Darvesh Singh Dhillon: I am a Data Science Minor and a Psychology Major so knowing how online education affected people is really interesting and right up my ally.
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Shawn Goh: I am a Computer Science major who is interested in the Data Science field.
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Ahmad Firdaus Azri: I am a beginner Data Science student who hopes his first project will be beneficial for his future projects.
