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| Let`s listen to the Winner of the Lecture Award! | "My teaching goal is to help students find
2022.09.14 Views 1743 국제실
| Let's listen to the Winner of the Lecture Award! | Professor Kihoon Kim
"Let's listen to the Winner of the Lecture Award!" interview of this semester, which is part of the KUBS(Dean=Johnseok Bae) Teaching Committee Program, is joined by Professor Kihoon Kim, who won the Excellence Lecture Award through the MBA Teaching Award in the fall semester of 2021. Through this interview, some of Professor Kim's teaching methods will be revealed.
"My teaching goal is to help students find their own logical basis"
Professor Kihoon Kim (Major in LSOM, winner of the MBA Teaching Award for the fall semester of 2021)
Q1. Congratulations on winning the MBA Teaching Award for the fall semester of 2021 [Data Analytics and Statistics] subject! Please briefly introduce what kind of course this is.
A few years ago, 'Business Statistics', a compulsory subject during the K-MBA program, was reorganized into a class called 'Data Analytics and Statistics'. Recently, the demand for data analytics has been increasing, so the curriculum has been changed to a course that addresses the need. The course was able to be reorganized thanks to the changing the name and curriculum of the course that swims with the tides and hope to meet the needs of the students.
[Data Analytics and Statistics] course adds 'Visualization' that is required in this era in addition to the Statistics classes that were conducted in the past. I used Excel before, but now I use an open-source program called 'R'. Recently, the programs that are usually implemented in practice are R and Python, and I lecture with R. For students, statistics course was a boring and dull subject in the past. Recently, however, there have been many students interested in analyzing data, and my class focuses on how to actually use, express, and analyze statistics. Statistical knowledge is important, of course, but I focus on how to use it to analyze data, for example, using statistical techniques to determine whether this promotion is effective or not.
There are three ways to analyze data: Descriptive analysis, Predictive analysis, and Prescriptive analysis. In the case of descriptive analysis, if Analysis method analyzes data that has occurred in the past and derives insights, Predictive analysis is an analysis method that identifies possibilities for the future, and Prescription analysis is an analysis method that finds the best alternative in the future, such as a doctor's "prescription." My [Data Analytics and Statistics] course could be described as a class that contains some descriptive and predictive analysis.
Q2. What do you think the students liked so much about this course?
When I checked the Lecture Evaluation sruvey, many students said, "It was good to learn statistics that are actually helpful." I tend to give tasks that can be used in practice, such as drawing a graph using data directly, or finding out the relationship between 2 variables, not just the theory in the book. Since the tests are all open books and open notes, there is no need to memorize the theory, and it is not difficult if you follow the class well and understand it properly. There seem to be many students who get intimidated by ‘statistics’ at first, saying that it is difficult because you need to memorize everything, but I think students liked the course because it was a class that teaches practical knowledge, not statistical knowledge that only needs to be memorized.
Throughout the class, students who were originally experienced in statistical analysis seemed to be making much better use of it, and students who say, "I have nothing to do with statistics at all" seemed to be actually applying analysis to statistics. There are many people who are worried about whether they can follow the class, but my class focuses on "utilization," so I encourage them that if they follow one by one, they will do well. So that after the class is over, students who had difficulty in the beginning could also feel confident that they really could.
Q3. Was there anything that didn't go well or that didn't go well as you thought in this class?
It has been a while since I moved to R from Excel, but I think there was a lot of class workload when I first changed the program. In addition to teaching about statistics, I gave my students the task of analyzing with field data as a final project. I remember the students having a hard time at that time. So I had no choice but to skip the project in the next course. I'm still sad about this part. I think what's really helpful for students is to perform analysis with field data. If I have a chance, I want to deliver the theory in a compact way and incorporate project using business data in my class again. I am planning to continue to think about this.
Q4. You won the Excellence Lecture Award during the non-face-to-face lecture due to COVID-19. Please share your experience in running an online class.
Actually, I did a survey of students after the Midterms, and only 2 students said that they would come to the face-to-face class. So I kept the class going online. And as I often have excercises in class, many students actually said that non-face-to-face was better. Especially with two electronic devices, it was icing on the cake. I think it would have been more effective if you were using one to listen to the class, and the other to conduct excercises.
I think the advantage of non-face-to-face classes was that you can ask questions through online chat. Students would ask and answer simple questions to each other freely even if I didn't answer them during the class. Among the statistics classes, there were not many students in my class, and I think the class had small number of students because there is a prejudice that it is difficult to take classes with R, not Excel. Maybe it was because there were not many students, but it was convenient to answer address the questions one by one.
For me, the good thing about face-to-face classes is that I can catch up faster on whether students are following well. Since non-face-to-face is only shared on the online screen, you can only ask students if they can follow you during the class. It's okay if students ask questions on their own, but if they don't, it's sometimes like shouting in the air. At that time, I think I had to take a break or raise new problems.
Q5. What do you have in mind the most when you first give a lecture?
First of all, I like to find out the background of the students. During self-introduction time at the beginning of the class, I often ask the students about how much experience they have in data analysis and how much statistics they have used in actual work. I find out about how many students have no experience at all and how many students are more advanced than I thought, and think about how to take the pace of this class before starting the course.
Of course, there are bound to be people who have no experience in statistics. In that case, there are times when I explain it more slowly in class. On the other hand, there are students who have been actively using R, but these students often do not know the statistical knowledge. For those who know how to use R well, I think I can help them in terms of statistical knowledge.
Q6. Do you have any methods or know-how on communicating effectively with students in class?
First of all, I recall actively used the chat window in the non-face-to-face class. In my class, I always have time to practice with data after explaining the theory, and in face-to-face classes, I used to walk around the classroom and look at the practice screen and receive questions. In fact, this part of online class was not so easy, so I had no choice but to explain it with words or show my screen. Still, problems that could not be solved were asked while sharing the screen with screen capture. I think on this aspect, online class was a little difficult.
And I use a program called 'Classum' to communicate with students. When asked by e-mail, there were many overlapping questions among students and it was a little cumbersome to answer them every time, but in Classum, students can answer each other when they post questions and see other people's questions and answers. I think it’s more efficient and active Q&A is possible because there are cases where students freely post questions that they wouldn’t ask professors, and answer each other. Although the utilization of Classum varies from class to class, if it is operated well for the first two weeks of class, it will be able to be used well throughout the entire course.
Q7. How do you discover and use the materials necessary for class (e.g., example cases, readings, assignments, etc.)?
Data materials can be found in textbooks, or public data. I actively utilize public data, such as when, where, and how much you rent in a bike sharing program.
And in my class, there is always a practice using data, so I share the materials used in the practice using a program called Dropbox. Dropbox synchronizes immediately when you modify a file, so you don't have to download the data everytime. Dropbox folders can be created and used directly on the desktop, making it convenient for students and me to share materials.
Q8. Lastly, is there your own teaching philosophy and educational philosophy that you would like to share?
Actually, when I was a student, I struggled when I was learning statistics. It wasn't fun and I didn't know how to use statistical theory. I don't remember having any fun with things like "Hypothesis Verification." So I aim to give a lecture to students so that they can actually utilize statistics as much as possible.
Therefore, I tend to give lectures with the main focus of "Can I teach students to understand easily?" I think the key point I think in all subjects, including Operations Management, Statistics, and Game theory, as well as this subject, is "How can students easily follow and express their understanding with their own thoughts?"
All the tests in my subject are 'Open book, Open notes'. This is because I think how to combine and utilize the learned knowledge to solve real problems, and the making knowledge yours is important. It means that you don't have to memorize class contents such as models, formulas, etc. and you should 'understand'. I hope that students will use their heads to learn how to apply the contents of the class and develop logic. I contemplate to give students to problems that can be solved if they understand, not memorize the lecture content no matter how new the type of problem is.
In fact, there are many cases where there are no correct answers in practice. I play a role in leading the students to the making a logical supporting basis for themselves based on given data and knowledge. I think the biggest goal of the lecture is to develop students' ability to find solutions with their own thoughts and logic.