Failure rates in introductory programming revisited (2014)
Conference Proceeding
Watson, C., & Li, F. W. (2014). Failure rates in introductory programming revisited. In Å. Cajander, M. Daniels, T. Clear, & A. Pears (Eds.), Proceedings of the 2014 conference on Innovation & technology in computer science education (ITiCSE '14) (39-44). https://doi.org/10.1145/2591708.2591749

Whilst working on an upcoming meta-analysis that synthesized fifty years of research on predictors of programming performance, we made an interesting discovery. Despite several studies citing a motivation for research as the high failure rates of int... Read More about Failure rates in introductory programming revisited.

No Tests Required: Comparing Traditional and Dynamic Predictors of Programming Success (2014)
Conference Proceeding
Watson, C., Li, F. W., & Godwin, J. L. (2014). No Tests Required: Comparing Traditional and Dynamic Predictors of Programming Success. In J. . D. Dougherty, K. Nagel, A. Decker, & K. Eiselt (Eds.), Proceedings of the 45th ACM Technical Symposium on Computer Science Education (469-474). https://doi.org/10.1145/2538862.2538930

Research over the past fifty years into predictors of programming performance has yielded little improvement in the identification of at-risk students. This is possibly because research to date is based upon using static tests, which fail to reflect... Read More about No Tests Required: Comparing Traditional and Dynamic Predictors of Programming Success.

Predicting Performance in an Introductory Programming Course by Logging and Analyzing Student Programming Behavior (2013)
Conference Proceeding
Watson, C., Li, F. W., & Godwin, J. L. (2013). Predicting Performance in an Introductory Programming Course by Logging and Analyzing Student Programming Behavior. In Proceedings of the 2013 IEEE 13th International Conference on Advanced Learning Technologies (ICALT 2013) (319-323). https://doi.org/10.1109/icalt.2013.99

The high failure rates of many programming courses means there is a need to identify struggling students as early as possible. Prior research has focused upon using a set of tests to assess the use of a student's demographic, psychological and cognit... Read More about Predicting Performance in an Introductory Programming Course by Logging and Analyzing Student Programming Behavior.

BlueFix: Using Crowd-sourced Feedback to Support Programming Students in Error Diagnosis and Repair (2012)
Conference Proceeding
Watson, C., Li, F. W., & Godwin, J. L. (2012). BlueFix: Using Crowd-sourced Feedback to Support Programming Students in Error Diagnosis and Repair. In E. Popescu, Q. Li, R. Klamma, H. Leung, & M. Specht (Eds.), Advances in Web-Based Learning - ICWL 2012: 11th International Conference, Sinaia, Romania, September 2-4, 2012 ; proceedings (228-239). https://doi.org/10.1007/978-3-642-33642-3_25

Feedback is regarded as one of the most important influences on student learning and motivation. But standard compiler feedback is designed for experts - not novice programming students, who can find it difficult to interpret and understand. In this... Read More about BlueFix: Using Crowd-sourced Feedback to Support Programming Students in Error Diagnosis and Repair.