Emma (Wengran) Wang

What I do as a Computing Education researcher:

Despite the growing national interest in recruiting more computer science students, computer science remains a subject that contains stereotypes, gender bias, racial discriminations, and curriculums that constantly lose students, who perceive computer science as being "boring and irrelevant" .

My research goal is to help novice students see computing as a tool they could use to pursue their personal ideas and interests, and build things that are interesting, meaningful, and creative to them.

In specific, my research focus on the following two areas:

1. Data-driven, automated feedback for programming practice assignments. Students can easily get stuck and feel frustrated when working on a programming assignment. I have built multiple tools to help students feel motivated and progress through programming practices:

• Crescendo, a self-paced programming practice environment that combines the block-based and visual, interactive programming of Snap.
• Step Tutor, a tool that helps struggling students during programming by presenting them with relevant, step-by-step examples.
• SnapCheck, which conducts dynamic testing to Snap programs.
• Execution-Trace-Based Feature Engineering Approach, which extracts sequential patterns from execution traces to perform code classification and feedback generation tasks.

2. Example support for creative, open-ended programming. The second part of my work focus on how to use code examples to support open-ended programming.

• My work on Novices' Learning Barriers When Using Code Examples in Open-Ended Programming investigated the challenges of example use during open-ended programming.
• My work on Exploring Design Choices to Support Novices' Example Use During Creative Open-Ended Programming presents the design of a remodeled system Example Helper, encouraging students to test and modify examples before integrating them into their own code.
• I built a record-and-replay tool called Pinpoint. Using Pinpoint, students can understand and reuse an existing program by isolating the code responsible for specific events during program execution.

My research spans across the communities and venues including Computing Education Research (e.g., SIGCSE and ITiCSE), Human-Computer Interation (e.g., VL/HCC), Software Engineering (e.g., ESE) and Learning Analytics (e.g., LAK and EDM).

Before joining HINTS Lab, I did my undergraduate study in Zhejiang University, Hangzhou, China.

Please email me (wwang33 AT ncsu.edu) to tell me about your ideas or ask me any questions!