Exploring Research in Esports

What is the primary purpose of conducting research in esports?

• To confirm personal opinions

• To systematically investigate and establish facts

• To entertain the audience

• To increase social media followers

Which of the following is a key characteristic of scientific research?

• Putting your own opinions on research or picking people who will respond how you want them to (Subjectivity)

• Making sure you get the results you want (Bias)

• Being completely hands off with how the research goes (Objectivity)

• Making sure the research is so random participants don't know what they are doing or why (Randomness)

In esports research, what does "literature review" refer to? (HINT looking at what is already out there)

• A summary of the latest games

• A critical analysis of existing research on a topic

• A list of popular esports players

• A collection of game reviews

What is a hypothesis in research?

• A proven fact

• An educated guess that can be tested

• A random statement

• A summary of findings

What is the importance of data analysis in research?

• To confuse the audience

• To interpret and make sense of collected data

• To fill up pages in a report

• To avoid drawing conclusions

What is quantitative research?

• Answering questions

• Finding answers with data only

• Looking at pictures

• Looking at peoples experiences

What is the role of ethics in research?

• To ensure the research is conducted in a morally acceptable manner

• To make the research more complicated

• To limit the research

• To increase the cost of research

Which of the following is a potential benefit of research in esports?

• Improved game design and player experience

• Increased game prices

• Reduced interest in esports

• Decreased player performance

What is Qualitative Research?

• Looking at patterns in data

• Reading articles

• Looking at peoples experiences

• Adding up money

What is a common challenge faced in esports research?

• Lack of interest in the field

• Rapidly changing technology and trends

• Too much funding

• Overabundance of data