Doctoral graduate's excitement for teaching music spans international borders

December 9, 2020

Editor's note: This story is part of a series of profiles of notable fall 2020 graduates.

Doctoral graduate Soyeon “Sally” Kang always understood that for a performance, practice makes perfect. But after a decade of teaching music, she realized she didn’t understand how that translated to her teaching career. Soyeon "Sally" Kang Download Full Image

“As a music teacher, I was still looking for an answer to the question ‘What makes good teaching?’” said Kang, who graduates this month with her PhD in music learning and teaching. “With this question in mind, the following year I started a new chapter of my life as a music educator and scholar in a new cultural environment.”

She decided the best way to answer that question was to further her own education. She relocated to the United States in 2013 from South Korea to pursue her graduate degree in music learning and teaching at the School of Music, Dance and Theatre in Arizona State University's Herberger Institute for Design and the Arts.

“At the time, I was in the middle of my 11th year of teaching music in South Korean elementary schools,” she said.

Born in Seoul, South Korea, Kang was raised in Gwangju, South Korea, where she continued her education and began a successful K–6 teaching career in music education.

Kang earned a Bachelor of Education in music education (2003) and a Master of Education in culture and arts education (2013) with a specialization in general music at Gwangju National University of Education. She then pursued a Master of Music in music education at ASU (2014). 

“While completing my ASU master's and doctoral degrees, I was inspired by every moment of learning, growing and thriving through the challenges,” Kang said.  “While attending conferences and professional development around the United States as a graduate student, I realized how grateful I was to be a member of ASU and encounter outstanding ASU alumni who contribute to music education and impact our professional communities and music educators.”

Kang’s teaching experience includes grades K–12, college courses, student teaching supervision and private piano studio lessons in different countries.

“Through my experience of working with diverse students, I became interested in what inspires music teachers, like myself, to make changes in their teaching practice,” Kang said.

She received the 2017 ASU Graduate and Professional Student Association’s Teaching Excellence Award for her innovative perspectives and commitment to creating learning environments focused on student mutual engagement.

Kang has served on the board of the Arizona Orff and Arizona Kodály Teachers Society, presented professional development workshops for music teachers in Arizona and South Korea, was a master’s thesis committee member, a research grant reviewer for the Graduate and Professional Student Association, supervised student teachers and served as summer curriculum coordinator for the School of Music, Dance and Theatre (formerly the School of Music).

She is also active in the Phoenix community teaching private piano lessons, serving as an accompanist and working with the music education program at her church.

Question: What’s something you learned while at ASU — in the classroom or otherwise — that surprised you or changed your perspective?

Answer: Studying in a master’s and then a doctoral degree program at ASU became an opportunity for me to see how my professional knowledge and experience played a role in my teaching practice. My formal and informal learning in this academic community helped me develop new perspectives as a teacher/scholar.

Q: Why did you choose ASU?

A: When my husband and I were looking for universities to attend in the United States, he was guaranteed funding from the Physical Education Department (later Teachers College) at ASU, so we both applied to the university. While applying, I researched ASU music education professors and their research interests. Their varied interests inspired me to be open to various issues in music education. I had completed my master's degree in South Korea but looked forward to having more opportunities to explore music education in the United States and decided to pursue a master's degree at ASU.

Q: Which professor taught you the most important lesson while at ASU?

A: Near the beginning of my second semester in the doctoral program in music learning and teaching, my adviser Dr. Sandra Stauffer asked me if I would be interested in teaching a course entitled “Music for Children and Youth” the next semester. I was still adjusting to the new learning and living environment so teaching a college-level music course seemed like tossing up a third ball while I was already juggling two. Even with my prior teaching experiences, I thought that it would take a lot of nerve to teach in this new environment. Throughout my life, however, I had discovered that there was no job more exciting to me than teaching music. I believed that it was pure luck for me, an evolving educator who grew up in a different cultural and educational context, to get to teach American college students. I said “yes,” and it was the best decision that I ever made.

Q: What’s the best piece of advice you’d give to those still in school?

A: My advice for music education majors would be to work with your fellow music educators and become a mutually supportive community of practice where artist/teachers inspire one another’s growth creatively, artistically and professionally.

Q:What was your favorite spot on campus, whether for studying, meeting friends or just thinking about life?

A: I don’t have a favorite place on campus, but rather a favorite course. I taught “Music for Children and Youth,” an elective music course for all majors, for seven consecutive semesters from spring of 2015 to spring of 2018. Every semester while teaching this course, I was astonished to discover new ideas about how I could improve my practice and each time I implemented these ideas into my practice.

Q: What are your plans after graduation?

A: I will continue teaching approximately 20 piano students aged 4 to 60, and working as a music director at Grace Korean Presbyterian Church. I am also currently applying for music learning and teaching faculty positions.

Lynne MacDonald

communications specialist, School of Music


Unlocking Alzheimer's through statistical methods

W. P. Carey School Professor Jeffrey Wilson dives into statistics to uncover insights into treatment options for Alzheimer’s, other neurodegenerative diseases

December 9, 2020

Jeffrey Wilson, professor of statistics and biostatistics in the economics department at Arizona State University's W. P. Carey School of Business, a former chair of the editorial board of the American Journal of Public Health and a director of the biostatistics core in the NIH Center for Alzheimer’s at ASU, joined Lori La Bey with Alzheimer’s Speaks Radio to discuss his book, "Fundamental Statistical Methods for Analysis of Alzheimer’s and Other Neurodegenerative Diseases."

Brittany Dugger, co-author of the book and assistant professor of pathology and laboratory medicine at the University of California, Davis, and co-leader of the Neuropathology Core within the University of California, Davis' Alzheimer’s Disease Center, joined Wilson for the interview. portrait of ASU Professor Jeffrey Wilson Jeffrey Wilson, professor of statistics and biostatistics in the economics department at ASU's W. P. Carey School of Business. Download Full Image

Their work dives into statistics that help uncover insights into treatment options for Alzheimer’s and other neurodegenerative diseases and focuses on uncovering how data analytics can aid in unlocking the secrets of this devastating disease.

Editor's note: Questions and answers have been edited for length and clarity.

Question: Why do people fight the disease differently than others?

Dugger: So much of our life is due to serendipitous circumstances. I have been very blessed to have opportunities to work with such great people on this disease, including Drs. Wilson and Irimata, which has led to our certain approach to fighting the disease through statistical analyses. Both my grandmothers were diagnosed with the disease but had very different behaviors. If they hadn’t had dementia, I might not have known about its impact so early in my career.

Q: Have you been touched by dementia?

Wilson: During my time at Iowa State University, I had a mentor named George Jackson. He was very influential in my life. About 10 years ago, I went to see him in a Florida Alzheimer’s home and could hardly recognize him. The visits taught me how difficult it is dealing with the disease and I realized soon that I was more useful in providing family support. After his funeral, I realized his impact and am grateful for the many years our paths crossed, and I was glad he was able to inspire my life to such an extent. 

Q: Why was there a need to write a book consisting of analyzing statistics and Alzheimer’s data?

Dugger: This goes back to when Dr. Wilson and I met. I was working on a dementia project and trying to understand topics such as cardiovascular risk factors. Many results were showing factors such as obesity, hypertension and diabetes relate to dementia — but what is the driving force, as cardiovascular risk factors are very intertwined? As a scientist, I needed a collaborator with the skill sets to help answer these questions. I was put in contact with Dr. Wilson about 10 years ago. During that time, we both realized how necessary a book was on the topic of statistics and Alzheimer’s.

Q: How does data tie into Alzheimer’s?

Dugger: This is a disease that gains momentum as it goes on. Most persons who get dementia end up with the disease later in life. Over time, people have an accumulation of event choices and/or exposures. If someone has cardiovascular risk factors, they may have diabetes as well as obesity and hypertension. If symptoms are intertwined, it’s called co-linearity. Also, it’s necessary to know that people can have multiple types of dementia. A patient can have Alzheimer’s disease and vascular dementia (brain damage caused by multiple strokes), too. All of these items are data, and analyzing these types of data aid in understanding the disease, leading to better prognosis, treatments and diagnoses.

Q: How do you explain this in terms of statistics?

Wilson: In statistics, we have basic principles that we use to determine the results. Researchers measure one response variable at a time. These observations are usually treated as coming from a mechanism that is unrelated to each other. However, consider a patient; each provides several different outcomes. To use a separate outcome analysis is to ignore any interrelationship. Our book pays attention to the usual neglectful perspective of correlation, as it shows instances of the shortcomings when it is ignored. It also helps readers to understand various simultaneous responses regarding the disease.

Q: Can you explain how Alzheimer’s is different than other neurodegenerative diseases?

Dugger: Both my grandmothers had dementia, and their presentations varied. This was due to them having perhaps different underlying causes or neurodegenerative diseases. For instance, when a person has a stomach ache and high fever, what is the underlying cause? With my grandmother on my mom’s side, she had hallucinations, thinking people were coming out of the TV. She would have personality changes as well. On the opposite side was my dad’s mom, who had more classic memory problems associated with dementia. Every Sunday she would go to church and sit in the same spot but couldn’t remember who I was.

Dementia in the clinical sense is when a person has cognitive impairment as well as a decrease in activities of daily living. And with neurodegenerative disease, these are the underlying mechanisms of this outward clinical symptom of dementia. One type of neurodegenerative disease is Alzheimer’s disease. Other types are out there, too, including dementia with Lewy bodies and frontotemporal dementia. These neurodegenerative diseases can only be definitively diagnosed after death. 

We work with data from what's called the National Alzheimer's Coordinating Center. It compiles data from over 30 sites from around the country. They're called Alzheimer’s Disease Research Centers. And a lot of them are in major cities. We have one at the University of California, Davis. There's one in Arizona where they have a consortium that includes Banner Sun Health Research Institute and Arizona State University.

Q: What would you say are some of the challenges with explaining your work to potential readers?

Wilson: For the reader, we build on what is commonly known. So, the book builds on what readers understand in basic approaches. For instance, if you have one predictor such as age and whether or not someone has dementia, you would want to look at the logistic regression model with two variables. But if you have baseline knowledge, our work would give you opportunities to incorporate past information along with several outcomes. The book tries to simplify things while maintaining the accuracy of the analysis. Simplicity and accuracy are the aims of the book. We focus a great deal on correlated observations. By correlated observations, we mean the mechanism by which the observations are obtained are related.

Dugger: Statistics consists of a lot of jargon and has a unique vocabulary, so this can be a hurdle for many. The book tries to break down these hurdles by providing motivating examples. Researchers do this frequently, where we discuss how certain variables will affect Alzheimer’s patients. For example, we study obesity and dive into whether weight is different between people who had Alzheimer’s and people who didn’t. In the book, we walk through these factors and, in a step-by-step manner, we give the workflows for the use of the correct statistical model with certain programs.

Q: How does this book differ from other statistical books? 

Wilson: This book has 12 chapters and talks about different statistical methods such as survival analysis and hierarchical models or Bayesian statistics: when different things happen with the same patient, a doctor would be looking at these different measures. That’s because, in the doctor's mind, they’re related. We know that all these things together are correlated. Because we know they’re correlated, we know that you can’t treat medical diagnoses separately. They’re not independent observations.

Q: How is this book organized?

Dugger: The book is organized to serve as a statistical guide for those who wish to analyze data focused on Alzheimer’s disease. Statistical techniques are presented, addressing questions regarding data analysis. It begins with simple introductions and builds to more complex models. In the book, we present different models of analysis, and this is important as one can get different results depending on what model they use. For example, this occurred in a recent clinical trial with an Alzheimer’s drug where the initial statistical model was composed, and they ended up stopping the drug trial based on the results. Then, after re-analyzing the data with a different model and getting different results, they restarted the trial. It matters how you look at the data and how you’re modeling things. Our understanding of how we can improve is growing, especially since there currently is no cure for Alzheimer’s disease.

One last concept to touch upon is the notion that most data published on Alzheimer’s disease is based on wealthier white people. We know this disease affects people from various cultures, socioeconomic statuses and life experiences. To succeed in research, we must pursue an inclusive process. Many people are struggling, and we hope this book and the way it’s organized will aid many people in being able to analyze data.

Wilson: Also, this book includes basic statistical programs that people are more likely to use in conjunction with Alzheimer’s and dementia, and some case studies are highlighted. Let me thank Johns Hopkins University Press for publishing this book on our behalf. Also thanks to the other co-author (Dr. Katherine Irimata), who was instrumental in our effort.

To order a copy of “Fundamental Statistical Methods for Analysis of Alzheimer's and Other Neurodegenerative Diseases," visit Johns Hopkins University Press. Use the code HTWN.

Madeline Sargent

Copy writer , W. P. Carey School of Business