Shuyin Jiao - 矫书音

Shuyin Jiao - 矫书音

Research

Computing Education Research

My current research focuses on exploring pedagogical methods and developing tools to help students learn computer science courses more effectively, while also aiding instructors in teaching these courses more efficiently. I believe that the future of education is divergent, given that students are diverse in terms of their knowledge backgrounds and preferred learning strategies, even when sitting in the same classroom. Therefore, it is crucial to provide more flexible ways of learning that cater to individual learning styles. The increasing demand for computer science education makes teaching and learning more challenging than ever, particularly with the significant increase in class sizes. However, I am optimistic that advanced technologies can assist us in addressing these challenges.

I am currently leading the CERES lab at NCSU. If you are interested in collaborating with me, please feel free to send me an email!

For undergraduate students, I typically offer research projects every Fall/Spring semester through COE REU or CSC 498/499. Recruitment for these positions is initiated at the CSC Undergraduate Research Lightning Talks event, which is usually hosted on the first Friday of the Fall and Spring semesters. If you are interested in working with me, please send me an email with your CV attached and keep an eye on this website for updates on the event.

Course Redesigns

Critical Path Course Redesign of CSC 111 Introduction to Computing: Python

Funding: NC State DELTA Course Redesign Grant [$21,156 (2021-2022) + $10,250 (2022-2023)], Scholarship of Teaching and Learning Institute Grant [$1,250 (2022-2023)]

Principal Investigator: Shuyin Jiao

Summary: CSC 111 is a required course for students majoring in Civil, Construction, and Environmental Engineering, and it is also open to students in other majors. The course is offered every Fall/Spring semester, with typical class enrollments ranging between 90 and 180 students. Due to the large class size and the difficulty of the course subject, several instructional challenges need to be addressed, including keeping every student engaged throughout the lecture, reducing the DFUW rate, grading programming assignments consistently and efficiently while providing high-quality feedback, and stimulating the interest of students who are not majoring in Computer Science. The goal of this project is to address these challenges and improve the overall quality of instruction. We anticipate that students will be more engaged in class, have a better understanding of the course content, achieve grades above the C- wall, and be more confident in completing every step of the programming process independently, including designing algorithms and writing, testing, and debugging programs in Python.

Publications:

Computer System Research

My research interests center on analyzing code inefficiencies and developing tools to assist developers in conducting performance analysis, with a specific focus on C, C++, Java, and Python applications.

Publications: