Towards improving programming habits to create better computer science course outcomes
暂无分享,去创建一个
[1] Nickolas J. G. Falkner,et al. A fast measure for identifying at-risk students in computer science , 2012, ICER '12.
[2] John Mason,et al. Why the high attrition rate for computer science students: some thoughts and observations , 2005, SGCS.
[3] Ma. Mercedes T. Rodrigo,et al. Predicting at-risk novice Java programmers through the analysis of online protocols , 2011, ICER.
[4] James B. Fenwick,et al. Another look at the behaviors of novice programmers , 2009, SIGCSE '09.
[5] Stephen H. Edwards,et al. Mining Data from an Automated Grading and Testing System by Adding Rich Reporting Capabilities , 2008, EDM.
[6] Michael Kearns. Designing a Digital Future: Federally Funded Research and Development in Networking and Information Technology , 2010 .
[7] Paulo Blikstein,et al. Using learning analytics to assess students' behavior in open-ended programming tasks , 2011, LAK.
[8] Stephen H. Edwards,et al. Using software testing to move students from trial-and-error to reflection-in-action , 2004, SIGCSE '04.
[9] Gail E. Kaiser,et al. Retina: helping students and instructors based on observed programming activities , 2009, SIGCSE '09.
[10] Jussi Kasurinen,et al. Estimating programming knowledge with Bayesian knowledge tracing , 2009, ITiCSE.
[11] Stephen H. Edwards,et al. Comparing effective and ineffective behaviors of student programmers , 2009, ICER '09.
[12] Lori Carter. Why students with an apparent aptitude for computer science don't choose to major in computer science , 2006, SIGCSE '06.
[13] David Hovemeyer,et al. Software repository mining with Marmoset , 2005, MSR.
[14] Neil Brown,et al. Web-scale data gathering with BlueJ , 2012, ICER '12.
[15] Matthew C. Jadud. A First Look at Novice Compilation Behaviour Using BlueJ , 2005, Comput. Sci. Educ..