Undoubtedly, the Covid-19 crisis has changed students’ habits a lot. Old habits, such as hanging out, drinking beers, watching movies and even studying together have almost torn apart since most countries are experiencing the second Coronavirus wave.

As a student, I decided to take advantage of the time gained from the situation to work on myself, my skills and my academic performance. Especially when the University’s workload increases, keeping yourself disciplined and focused on your goals becomes even harder.

During these times, working in a study group is really helpful. Working as a team with your fellow students helps you maintain your focus and motivation. Even the days you don’t feel like studying, although you need to, your team encourages you to keep on completing your tasks.

Also, the whole team gets the advantage of each individual’s strengths. Usually, students tend to like some courses more than others. Using this, team members help each other and save valuable time and effort from browsing through course’s notes in Elearning platform.

Choosing the right platform that best suits your needs is crucial. My group prefers Google Meet. We consider it as the most stable and user-friendly free video calling software right now. Occasionally, we also use Skype, Zoom, Messenger or Discord.

Additionally, I need to mention the socialising part of group studying. Social distancing will last for at least some more months. Socialising, even virtually, is crucial for student’s mental health. As shown in the pie chart, communicating with your teammates for extracurricular activities is a main part of this habit and helps students to keep their social life at a balance. Also, after completing your coursework, you can work on your hobbies, such as side projects or gaming.

To conclude, although this chart seems to be very descriptive, in my opinion, that small percentage of “actually studying” time is so efficient that it is worth giving a try to make a study group.

Greek student studying Computer Engineering and Informatics at the Cyprus University of Technology. Highly interested in Data Science and Machine Learning.