Ogden News

Dr. Guangming Xing and Dr. Huanjing Wang, both Professors of Computer Science in the WKU School of Engineering and Applied Sciences, have been awarded a $305,326 grant from the National Science Foundation (NSF) to develop a tool designed to transform how students learn introductory programming.

The three-year project, titled "Improving Conceptual Understanding in Introductory Programming through an Interactive Flowchart-to-Code Environment," addresses high drop-fail-withdraw rates in introductory Computer Science courses. By focusing on algorithmic reasoning before code syntax, the project targets barriers that lead many students to step away from STEM fields early in their academic journeys.

Through ChartCode, an interactive software platform built to reverse the traditional programming learning curve, beginners will design their algorithms visually first, instead of struggling through complex language rules while attempting to build logic.

"Today, students write syntax first and hope the logic follows," Dr. Xing said. "ChartCode has them build the algorithm visually, watch it execute step-by-step, execution pointer moving, variables changing in memory, and only then see the Python, Java, or C++ generated from their own logic. Programming becomes something visible rather than something that happens invisibly inside the machine."

In an era of generative AI, where software can produce complete code without revealing underlying logic, ChartCode acts as a transparent "glass box," helping students visualize and understand how programs execute.

While WKU serves as the development hub for the project, research is being conducted in collaboration with faculty at Texas A&M University–San Antonio, Purdue University, El Camino College, and Oakland Community College.

"The consortium is a deliberate cross-section of undergraduate computing," Dr. Xing said. "WKU is an EPSCoR regional university serving rural and first-generation students; Texas A&M–San Antonio is a Hispanic-Serving Institution reaching a rapidly growing segment of the national student population; Purdue's CIT program is applied, high-enrollment computing; El Camino and Oakland Community College represent the two-year-to-four-year transfer pathway. That variation is the research design, it lets us ask whether the tool's benefit is universal or context-dependent."

Across the partner institutions, approximately 20 faculty members will incorporate ChartCode into their gateway courses, tracking classroom outcomes and contributing to research on effective teaching methods. Over the course of the project, about 1,200 students will participate across the consortium.

The NSF grant directly supports WKU undergraduate and graduate student researchers. Students will play active roles implementing platform features, managing learning management system integration, resolving accessibility standards, building exercise libraries, and running usability testing prior to pilot semesters. Graduate students will also assist with cleaning and analyzing de-identified interaction data supporting the study's findings.

Participating students will gain hands-on experience working on a live, multi-institutional system alongside researchers across the country, with opportunities to co-author papers for premier computing education conferences.

Upon completion of the grant period in September 2029, WKU’s School of Engineering and Applied Sciences will host the platform permanently, releasing turnkey learning management system course packages as open educational resources for institutions nationwide.

"It establishes WKU as a lead institution, not a junior partner — the platform was architected here and the national research agenda is set here, with an R1 and an HSI collaborating on the project," Dr. Xing said. "That's a meaningful statement about research capacity at a regional university in an EPSCoR state. It also puts WKU's CS program into the national computing-education conversation, funds substantive student research positions, and directly improves the courses where our own students are most likely to leave computing.”