CV

Education

• Ph.D. in Learning, Design and Technology, University of Georgia, 2017
• M.Sc. in Computer Science, University of Georgia, 2017
• M.Sc. in Information Technology Studies, University of Hong Kong, 2012

Publications

• Journal Articles

  • Hao, Q., Smith IV, D. H., Ding, L., Ko, A., Ottaway, C., Wilson, J., Arakawa, K. H., Turcan, A., Poehlman, T., & Greer, T. (2021). Towards understanding the effective design of automated formative feedback for programming assignments. Computer Science Education, 1–23.

  • Hao, Q., Barnes, B. & Jing, M. (2020). Quantifying the effects of active learning environments: separating physical learning classrooms from pedagogical approaches. Learning Environment Research.

  • Smith, D., Hao, Q., Dennen, V., Tsikerdekis, M., Barnes, B., Martin, L., & Tresham, N. (2020). Towards Understanding Online Question & Answer Interactions and their effects on student performance in large-scale STEM classes. International Journal of Educational Technology in Higher Education, 17(1), 1-15.

  • Hao, Q., Smith, D., Iriumi, N., Tsikerdekis, M. & Ko, A. J. (2019). A Systematic Investigation of Replications in Computing Education Research. ACM Transactions on Computing Education, 19(4), 1-18.

  • Hao, Q., Barnes, B., Branch, M. R., & Wright, E. (2017). Predicting Computer Science Students’ Online Help-Seeking Tendencies. Knowledge Management & E-Learning, 9(1), 19-32.

  • Hao, Q., Barnes, B., Wright, E., & Branch, M. R. (2017). The Influence of Achievement Goals on Online Help Seeking of Computer Science Students. British Journal of Educational Technology, 48(6), 1273-1283.

  • Hao, Q., Wright, E., Barnes, B., & Branch, M. R. (2016). What Are the Most Important Predictors of Computer Science Students’ Online Help-Seeking Behaviors? Computers in Human Behaviors, 62, 467-474.

  • Lu, J., Hao, Q., & Jing, M. (2016). Consuming, Sharing, and Creating Content: How Young Students Use New Social Media In and Outside School. Computers in Human Behaviors, 64, 55-64.

  • Hao, Q., Branch, M. R., & Jensen, L. (2016). The Effect of Precommitment on Student Achievement Within a Technology-Rich Project-Based Learning Environment. TechTrends, 60, 442-448.

  • Lu, J., & Hao, Q. (2014). What Factors Impact on Primary School Students’ Online Engagement for Learning and Entertainment at Home. Journal of Computers in Education, 1(2-3), 133-150.

• Conference Proceedings

  • Nils Rys-Recker and Qiang Hao. (2024, June) Early identification of struggling students in large computer science courses: A replication study. In the Proceedings of 48th IEEE International Conference on Computers, Software, and Applications. IEEE.

  • Parsons, R., Hao, Q., & Ding, L. (2023, June). Exploring Differences in Planning between Students with and without Prior Experience in Programming. In 2023 ASEE Annual Conference & Exposition.

  • Arakawa, K., Hao, Q., Deneke, W., Cowan, I., Wolfman, S., & Peterson, A. (2022, February). Early Identification of Student Struggles at the Topic Level Using Context-Agnostic Features. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (pp. 147-153). ACM, New York, NY, USA.

  • Liu, Y., Chau, L. H., & Hao, Q. (2021). Examine Educational Opportunity and Inequality Using Machine Learning Methods with US National Data. In International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation.

  • Arakawa, K., Hao, Q., Greer, T., Ding, L., Hundhausen, C. D., & Peterson, A. (2021, March). In Situ Identification of Student Self-Regulated Learning Struggles in Programming Assignments. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (pp. 467-473). ACM, New York, NY, USA.

  • Smith IV, D. H., Hao, Q., Hundhausen, C. D., Jagodzinski, F., Myers-Dean, J., & Jaeger, K. (2021, March). Towards Modeling Student Engagement with Interactive Computing Textbooks: An Empirical Study. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (pp. 914-920). ACM, New York, NY, USA.

  • Hao, Q., & Tsikerdekis, M. (2019). How Automated Feedback is Delivered Matters: Formative Feedback and Knowledge Transfer. In Proceedings of 2019 IEEE Frontiers in Education Conference (FIE) (pp. 1-6). IEEE.

  • Hao, Q., Wilson, J., Ottaway, C., Iriumi, N., Arakawa, K., Smith, D. (2019). Investigating the Essential of Meaningful Automated Formative Feedback for Programming Assignments. In Proceedings of 2019 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). Memphis, TN, pp. 151-155.

  • Smith, D., Hao, Q., Jagodzinski, F., Liu, Y., Gupta, V. (2019). Quantifying the Effects of Prior Knowledge in Entry-Level Programming Courses. In Proceedings of the 1st ACM Global Computing Education Conference (CompEd’19). ACM, New York, NY, USA, 30-36.

  • Greer, T., Hao, Q., Jing, M., Barnes, B. (2019). On the Effects of Active Learning Environments in Computing Education. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (SIGCSE ‘19). ACM, New York, NY, USA, 267-272.

  • Hao, Q., Galyardt, A., Barnes, B., Wright, E., & Branch, M. R. (2018). Automatic Identification of Ineffective Online Student Questions in Computing Education. In Proceedings of 2018 IEEE Frontier in Education (FIE ’18), San Jose, CA.

  • Wright E., Hao, Q., Rasheed K., Liu Y. (2018). Feature Selection of Post-graduation Income of College Students in the United States. In International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation (pp. 38-45). Springer, Cham.

  • Hao, Q., Barnes, B., Wright, E., & Kim. E. (2018). Effects of Active Learning Environments and Instructional Methods in Computer Science Education. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE ‘18). ACM, New York, NY, USA, 934-939.

• Dissertation & Thesis

  • Hao, Q. (2017). Online help seeking in computer science education (Doctoral dissertation). University of Georgia.

  • Hao, Q. (2017). Feature selection and classification of post-graduation income of college students in United States (Master’s thesis). University of Georgia.

Teaching

• Mobile Device Programming, Western Washington University
• Database Systems, Western Washington University
• Object Oriented Design, Western Washington University
• Web Scripting, Western Washington University
• Data Structures, Western Washington University
• Computer Programming and Linear Data Structures, Western Washington University
• Computing Education Research, Western Washington University
• Database Systems, University of Georgia
• Creativity, Technology, and How the Brain Learns, University of Georgia
• Introduction to Computing for Teachers, University of Georgia
• Instructional Design, University of Georgia

Service

• Conference Committee Membership
  • ACM Technical Symposium on Computer Science Education
  • ACM Global Computing Education Conference
  • IEEE International Conference on Advanced Learning Technologies
  • IEEE Frontier in Education
  • International Conference on Computer Supported Collaborative Learning
  • AERA Annual Meeting
  • SITE Annual Conference
• Invited Review
  • National Science Foundation
  • Review of Educational Research
  • Computers in Human Behavior
  • Journal of Educational Technology & Society
  • IEEE Transactions on Education
  • Journal of Technology, Knowledge and Learning
  • Journal of Computers in Education
  • Journal of Information Systems Education
  • Journal of Online Learning Research
  • Journal of Technology and Teacher Education
  • Contemporary Issues in Technology & Teacher Education
  • International Journal of E-Learning & Distance Education

Awards & Grants

• 2019 NASA Space Grant
• 2019 WWU Open Education Resource Award
• 2018 AERA Division C Selective New Faculty Mentoring Program
• 2016 AECT Division of Distance Learning Journal Article Award