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New Trends in Automated Project Grading for Web Programming Classes

This study by Dr. Xiang Fu and colleagues introduces APOGEE, an automated grader that offers instant feedback and fair grading for web programming projects. The system includes features like Project Failure Analysis and Virtual Execution, enhancing efficiency and faculty productivity. It also incorporates TAF strategy, allowing students to Submit, Revise, and Design their projects for optimal learning. Post-survey results reveal positive feedback on learning effectiveness and consistency. Future directions include enhancing security scanning and data collection for continual improvement. APOGEE stands out with 24x7 service and advanced features, creating a platform for reciprocal learning and peer challenge. The project is supported by NSF grants and acknowledges Ms. Thays Franca for artistic contributions.

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New Trends in Automated Project Grading for Web Programming Classes

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  1. New Trends in Automated Project Grading for Web Programming Classes Dr. Xiang Fu, Hofstra University, cscxzf@hofstra.edu  Dr. Kai Qian, Southern Polytechnic State University, kqian@spsu.edu Boris Peltsverger, Georgia Southwestern State University, plz@canes.gsw.eduKent Palmer, Wingate University, epalmer@wingate.edu Chong-weiXu, Kennesaw State University, cxu@kennesaw.eduYu Zhang, Bainbridge College, yzhang@bainbridge.edu

  2. TAF (Trial and Failure) Strategy Submit Project Revise Design Instant Feedback

  3. APOGEE – Automated Grader

  4. Project Specification

  5. Instant Report

  6. Test Case Failure Report

  7. Preliminary Evaluation

  8. Pre-Survey Results

  9. Pre-Survey Questions • Q1a. Work experience. (1 for yes, 0 for no). • Q1b. Total work experiences in months • Q7a. Experiences with C/C++? (1 for yes, 0 for no) • Q7b. Experiences with Java? (1/0) • Q7c. Experiences with C#? (1/0) • Q11. I learn better by seeing examples worked out on the board. (Scale 1 to 5) • Q12. I learn better by listening to lectures (1 to 5) • Q13. I learn better personally doing through examples. (1 to 5) • Q14. I learn better reading materials on my own. (1 to 5) • Q15. I learn better by having a learning/tutorial system that provides feedback. (1 to 5) • Q16c. Level of familiarity with SQL injection (1 to 3) • Q16d. Level of familiarity with XSS attack (1 to 3) • Q17. Are you comfortable with fixing vulnerabilities? (1/0) • Q18. Students are asked to identify the vulnerability of SQL injection in a piece of ASP.Net C# or Java code. (1 for success, 0 for failure or no response)

  10. Post-Survey Results

  11. Post-Survey Questions • Q1. I like being able to submit a project several times and get feedback before getting a final grade for a project. • Q2. The automated tutoring available through APOGEE helps me learn more. • Q3. APOGEE’s grading of my projects has been consistent and fair. • Q4. I am better able to learn from my mistakes using APOGEE than with traditional methods of grading projects. • Q5. The fact that APOGEE’s feedback is instant has been helpful to me. • Q6. The automated demos showing errors are helpful for learning internet technology. • Q7. I learned more using APOGEE’s automated grading system than I would have using a traditional grading system on the same projects. • Q8. Compared to other automated testing and grading software I have seen, APOGEE is better.

  12. Conclusion • Future Directions • Efficiency • Data Collection • Project Benchmark • Security Scanning • Load Testing • Session Recording • Project Failure Analysis • Virtual Execution • TAF Benefits • Reciprocal Learning • Cyclic Improvement • Peer Challenging • APOGEE Advantages • 24x7 Service • Instant Feedback • Fair Grading • Faculty Productivity

  13. Acknowledgement • This work is supported by NSF under contract DUE 0836859 , 0837275 and 0837020. • We thank Ms. Thays Franca for creating the art work of this presentation.

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