Research & Development
My research lab members work on different aspects of computing education, including studying effective pedagogical approaches, tracking & analyzing learning behaviors, and developing next generation technologies supporting learning and teaching of programming. Some recently published papers and open-sourced software from my lab include:
Early Identification of Student Struggles at the Topic Level Using Context-Agnostic Features
Kai Arakawa, Qiang Hao, Wesley Deneke, Indie Cowan, Steven Wolfman, and Abigayle Peterson
Proceedings of the 52nd ACM Tech-nical Symposium on Computer Science Education (SIGCSE ’22). ACM, New York, NY, USA.
In Situ Identification of Student Self-RegulatedLearning Struggles in Programming Assignments
Kai Arakawa, Qiang Hao, Tyler Greer, Lu Ding, Christopher D. Hundhausen, and Abigayle Peterson
Proceedings of the 52nd ACM Tech-nical Symposium on Computer Science Education (SIGCSE ’21). ACM, New York, NY, USA.
Towards Modeling Student Engagement with Interactive Computing Textbooks: An Empirical Study
David H. Smith IV, Qiang Hao, Christopher D. Hundhausen, Filip Jagodzinski, Josh Myers-Dean, and Kira Jaeger
Proceedings of the 52nd ACM Tech-nical Symposium on Computer Science Education (SIGCSE ’21). ACM, New York, NY, USA.
Towards understanding the effective design of automated formative feedback for programming assignments
Qiang Hao , David H. Smith IV , Lu Ding , Amy Ko , Camille Ottaway , Jack Wilson , Kai H. Arakawa , Alistair Turcan , Timothy Poehlman & Tyler Greer
Computer Science Education, 1–23.
Towards understanding online question & answer interactions and their effects on student performance in large-scale STEM classes
David H. Smith IV, Qiang Hao, Venessa Dennen, Michail Tsikerdekis, Bradley Barnes, Lilu Martin, Nathan Tresham
International Journal of Educational Technology in Higher Education, 17:20, 1-15.
Referencer
Qiang Hao, Jack Wilson, Kai Hicks
A Google Docs Add-on that automates cross-references for figures, tables, and section titles. GSuite Market, Google.
Quantifying the Effects of Prior Knowledge in Entry-Level Programming Courses
David H. Smith IV, Qiang Hao, Filip Jagodzinski, Yan Liu, and Vishal Gupta
ACM 2019 Conference on Global Computing Education. Chendu, China.
On the Effects of Active Learning Environments in Computing Education
Tyler Greer, Qiang Hao, Mengguo Jing, Bradley Barnes
2019 ACM Technical Symposium on Computer Science Education (SIGCSE ‘19). Minneapolis, MN.
Investigating the Essential of Meaningful Automated Formative Feedback for Programming Assignments
Qiang Hao, Jack Wilson, Camille Ottaway, Naitra Iriumi, Kai Hicks and David Smith
2019 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). Memphis, TN.