A perspective of Automated programming error feedback Approaches in problem solving exercises
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| internalnotes | [1] N. Le, S. Strickroth, S. Gross, and N. Pinkwart, A Review of AI-Supported Tutoring Approaches for Learning Programming, vol. 479. Heidelberg: Springer International Publishing, 2013, pp. 267–279. [2] M. Rubio-sánchez, P. Kinnunen, C. Pareja-flores, and Á. Velázquez-iturbide, “Student perception and usage of an automated programming assessment tool,” Computers in Human Behavior, vol. 31, pp. 453–460, 2014. [3] R. Queirós, I. La, D. Ipp, and J. P. Leal, “PETCHA A Programming Exercises Teaching Assistant,” in 17th ACM Annual Conference on Innovation and Technology in Computer Science Education, 2012, pp. 192–197. [4] H. Mungunsukh and Z. Cheng, “An Agent Based Programming Language Learning Support System,” in International Conference on Computers in Education (ICCE), 2002, pp. 148–152. [5] A. Yadin, “Reducing the dropout rate in an introductory programming course,” ACM Inroads, vol. 2, no. 4, pp. 71–76, 2011. [6] M. A. Brito and F. De Sá-soares, “Assessment frequency in introductory computer programming disciplines,” Computers in Human Behavior, vol. 30, no. 30, pp. 623–628, 2013. [7] C. L. Jeffery, “Generating LR syntax error messages from examples,” ACM Transactions on Programming Languages and Systems, vol. 25, no. 5, pp. 631–640, Sep. 2003. [8] E. R. Sykes, “Qualitative Evaluation of the Java Intelligent Tutoring System,” Journal of Systemics, Cybernetics and Informatics, vol. 3, no. 5, pp. 49–60, 2005. [9] M. M. Ben-ari, “Compile and Runtime Errors in Java,” Israel, 2007. [10] W. L. Johnson, “Understanding and debugging novice programs,” Artificial Intelligence, vol. 42, no. 1, pp. 51–97, Feb. 1990. [11] J. S. Song, “AN INTELLIGENT TUTORING SYSTEM FOR INTRODUCTORY C LANGUAGE COURSE,” Computers & Education, vol. 28, no. 2, pp. 93–102, 1997. [12] E. R. Sykes and F. Franek, “An Intelligent Tutoring System Prototype for Learning to Program Java TM,” in IEEE International Conference on Advanced Learning Technologies (ICALT 2003), 2003, no. figure 2, p. 7695. [13] R. Singh, S. Gulwani, and A. Solar-lezama, “Automated Feedback Generation for Introductory Programming Assignments,” in ACM Programming Language Design and Implementation (PLDI), 2013, pp. 15–26. [14] M. Gaudencio, A. Dantas, and D. D. S. Guerrero, “Can Computers Compare Student Code Solutions as Well as Teachers ?,” in 45th ACM Technical Symposium on Computer Science Education, 2014, pp. 21–26. [15] B. E. Vaessen, F. J. Prins, and J. Jeuring, “Computers & Education University students ’ achievement goals and help-seeking strategies in an intelligent tutoring system,” Computers & Education, vol. 72, pp. 196–208, 2014. [16] “Programmr,” 2014. [Online]. Available: http://www.programmr.com/. [Accessed: 10-Apr-2014]. [17] “Codeforces,” 2014. [Online]. Available: http://codeforces.com/. [Accessed: 10-Apr-2014]. [18] “Codechef,” 2014. [Online]. Available: http://www.codechef.com/. [Accessed: 10-Apr-2014]. [19] “UVa Online Judge,” 2014. [Online]. Available: http://uva.onlinejudge.org/. [Accessed: 31-Mar-2014]. [20] “Topcoder,” 2014. [Online]. Available: http://www.topcoder.com/. [Accessed: 10-Apr-2014]. [21] A. Papancea, J. Spacco, and D. Hovemeyer, “An open platform for managing short programming exercises,” in Proceedings of the ninth annual international ACM conference on International computing education research - ICER ’13, 2013, pp. 47–51. [22] P. Denny, A. Luxton-reilly, E. Tempero, and J. Hendrickx, “CodeWrite : Supporting Student-Driven Practice of Java,” in Proceedings of the 42nd ACM technical symposium on Computer Science education, 2011, pp. 471–476. [23] A. Kurnia, A. Lim, and B. Cheang, “Online Judge,” Computers & Education, vol. 36, no. 4, pp. 299–315, May 2001. [24] A. Casamayor, A. Amandi, and M. Campo, “Intelligent assistance for teachers in collaborative e-learning environments,” Computers & Education, vol. 53, no. 4, pp. 1147–1154, 2009. [25] C. Fernandez-Medina, J. R. Pérez-Pérez, V. M. Álvarez-García, and M. D. P. Paule-Ruiz, “Assistance in computer programming learning using educational data mining and learning analytics,” in Proceedings of the 18th ACM conference on Innovation and technology in computer science education - ITiCSE ’13, 2013, pp. 237–242. [26] A. Vihavainen, T. Vikberg, M. Luukkainen, and M. Pärtel, “Scaffolding Students ’ Learning using Test My Code,” in Annual Conference on Innovation and Technology in Computer Science Education, 2013, vol. 68, pp. 117–122. [27] “Stack Overflow,” 2014. [Online]. Available: https://stackoverflow.com/tour. [Accessed: 22-May-2014]. [28] C.-H. Lai, W.-C. Lin, B.-S. Jong, and Y.-T. Hsia, “Java Assist Learning System for Assisted Learning on Facebook,” IEEE Learning and Teaching in Computing and Engineering, pp. 77–82, Mar. 2013. [29] P. Denny, A. Luxton-Reilly, E. Tempero, and J. Hendrickx, “Understanding the syntax barrier for novices,” Proceedings of the 16th annual joint conference on Innovation and technology in computer science education - ITiCSE ’11, p. 208, 2011. [30] M. S. Othman, S. M. Suhaimi, L. M. Yusuf, N. Yusof, and N. Mohamad, “An Analysis of Social Network Categories: Social Learning and Social Friendship,” Procedia - Social and Behavioral Sciences, vol. 56, no. Ictlhe, pp. 441–447, Oct. 2012. [31] E. Verdú, L. M. Regueras, M. J. Verdú, J. P. Leal, J. P. de Castro, and R. Queirós, “A distributed system for learning programming on-line,” Computers & Education, vol. 58, no. 1, pp. 1–10, Jan. 2012. [32] K. M. Y. Law, V. C. S. Lee, and Y. T. Yu, “Computers & Education Learning motivation in e-learning facilitated computer programming courses,” Computers & Education, vol. 55, no. 1, pp. 218–228, 2010. [33] N. Drljevic and I. Boticki, “Leveraging Social Networks to Increase Motivation in Learning Programming,” in 54th International Symposium ELMAR, 2012, no. September, pp. 12–14. [34] P. Ihantola, T. Ahoniemi, V. Karavirta, and O. Seppälä, “Review of recent systems for automatic assessment of programming assignments,” in Proceedings of the 10th Koli Calling International Conference on Computing Education Research - Koli Calling ’10, 2010, pp. 86–93. [35] V. Pieterse, “Automated Assessment of Programming Assignments,” in ACM Computer Science Education Research Conference, 2013, no. April, pp. 4–5. [36] N. Truong, P. Roe, and P. Bancroft, “Automated Feedback for ‘ Fill in the Gap ’ Programming Exercises,” vol. 42, pp. 117–126, 2005. [37] R. Romli, S. Sulaiman, and K. Z. Zamli, “Automatic Programming Assessment and Test Data Generation,” in IEEE International Symposium in Information Technology (ITSim), 2010, pp. 1186–1192. [38] P. Reimann, M. Kickmeier-rust, and D. Albert, “Problem solving learning environments and assessment : A knowledge space theory approach,” Computers & Education, vol. 64, pp. 183–193, 2013. [39] M. Joy, N. Griffiths, and R. Boyatt, “The BOSS Online Submission and Assessment System,” vol. 5, no. 3, 2005. [40] C. Douce, “Automatic Test-Based Assessment of Programming : A Review,” ACM Journal of Educational Resources in Computing, vol. 5, no. 3, pp. 1–13, 2006. [41] T. Wang, X. Su, P. Ma, Y. Wang, and K. Wang, “Computers & Education Ability-training-oriented automated assessment in introductory programming course,” Computers & Education, vol. 56, no. 1, pp. 220–226, 2011. [42] S. A. Naser, “AN AGENT BASED INTELLIGENT TUTORING SYSTEM,” Journal of Theoretical and Applied Information Technology, vol. 4, no. 7, pp. 585–589, 2008. |
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| spelling | 11364 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=11364 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Article Journal UniSZA Unisza unisza image/jpeg inches 96 96 1417 756 33 33 2015-01-13 09:38:35 1417x756 5596-01-FH02-FIK-15-02374.jpg UniSZA Private Access A perspective of Automated programming error feedback Approaches in problem solving exercises Journal of Theoretical and Applied Information Technology Programming tools are meant for student to practice programming. Automated programming error feedback will be provided for students to self-construct the knowledge through their own experience. This paper has clustered current approaches in providing automated error programming feedback to the students during problem solving exercises. These include additional syntax error messages, solution template mismatches, test data comparison, assisted agent report and collaborative comment feedback. The study is conducted based on published papers for last two decades. The trends are analyzed to get the overview of latest research contributions towards eliminating programming difficulties among students. The result shows that future direction of automated programming error feedback approaches may combine agent and collaborative feedback approaches towards more interactive, dynamic, end-user oriented and specific goal oriented. Such future direction may help other researchers fill in the gap on new ways of assisting learners to better understand feedback messages provided by automated assessment tool. 70 1 Asian Research Publishing Network Asian Research Publishing Network 121-129 [1] N. Le, S. Strickroth, S. Gross, and N. Pinkwart, A Review of AI-Supported Tutoring Approaches for Learning Programming, vol. 479. Heidelberg: Springer International Publishing, 2013, pp. 267–279. [2] M. Rubio-sánchez, P. Kinnunen, C. Pareja-flores, and Á. Velázquez-iturbide, “Student perception and usage of an automated programming assessment tool,” Computers in Human Behavior, vol. 31, pp. 453–460, 2014. [3] R. Queirós, I. La, D. Ipp, and J. P. Leal, “PETCHA A Programming Exercises Teaching Assistant,” in 17th ACM Annual Conference on Innovation and Technology in Computer Science Education, 2012, pp. 192–197. [4] H. Mungunsukh and Z. Cheng, “An Agent Based Programming Language Learning Support System,” in International Conference on Computers in Education (ICCE), 2002, pp. 148–152. [5] A. Yadin, “Reducing the dropout rate in an introductory programming course,” ACM Inroads, vol. 2, no. 4, pp. 71–76, 2011. [6] M. A. Brito and F. De Sá-soares, “Assessment frequency in introductory computer programming disciplines,” Computers in Human Behavior, vol. 30, no. 30, pp. 623–628, 2013. [7] C. L. Jeffery, “Generating LR syntax error messages from examples,” ACM Transactions on Programming Languages and Systems, vol. 25, no. 5, pp. 631–640, Sep. 2003. [8] E. R. Sykes, “Qualitative Evaluation of the Java Intelligent Tutoring System,” Journal of Systemics, Cybernetics and Informatics, vol. 3, no. 5, pp. 49–60, 2005. [9] M. M. Ben-ari, “Compile and Runtime Errors in Java,” Israel, 2007. [10] W. L. Johnson, “Understanding and debugging novice programs,” Artificial Intelligence, vol. 42, no. 1, pp. 51–97, Feb. 1990. [11] J. S. Song, “AN INTELLIGENT TUTORING SYSTEM FOR INTRODUCTORY C LANGUAGE COURSE,” Computers & Education, vol. 28, no. 2, pp. 93–102, 1997. [12] E. R. Sykes and F. Franek, “An Intelligent Tutoring System Prototype for Learning to Program Java TM,” in IEEE International Conference on Advanced Learning Technologies (ICALT 2003), 2003, no. figure 2, p. 7695. [13] R. Singh, S. Gulwani, and A. Solar-lezama, “Automated Feedback Generation for Introductory Programming Assignments,” in ACM Programming Language Design and Implementation (PLDI), 2013, pp. 15–26. [14] M. Gaudencio, A. Dantas, and D. D. S. Guerrero, “Can Computers Compare Student Code Solutions as Well as Teachers ?,” in 45th ACM Technical Symposium on Computer Science Education, 2014, pp. 21–26. [15] B. E. Vaessen, F. J. Prins, and J. Jeuring, “Computers & Education University students ’ achievement goals and help-seeking strategies in an intelligent tutoring system,” Computers & Education, vol. 72, pp. 196–208, 2014. [16] “Programmr,” 2014. [Online]. Available: http://www.programmr.com/. [Accessed: 10-Apr-2014]. [17] “Codeforces,” 2014. [Online]. Available: http://codeforces.com/. [Accessed: 10-Apr-2014]. [18] “Codechef,” 2014. [Online]. Available: http://www.codechef.com/. [Accessed: 10-Apr-2014]. [19] “UVa Online Judge,” 2014. [Online]. Available: http://uva.onlinejudge.org/. [Accessed: 31-Mar-2014]. [20] “Topcoder,” 2014. [Online]. Available: http://www.topcoder.com/. [Accessed: 10-Apr-2014]. [21] A. Papancea, J. Spacco, and D. Hovemeyer, “An open platform for managing short programming exercises,” in Proceedings of the ninth annual international ACM conference on International computing education research - ICER ’13, 2013, pp. 47–51. [22] P. Denny, A. Luxton-reilly, E. Tempero, and J. Hendrickx, “CodeWrite : Supporting Student-Driven Practice of Java,” in Proceedings of the 42nd ACM technical symposium on Computer Science education, 2011, pp. 471–476. [23] A. Kurnia, A. Lim, and B. Cheang, “Online Judge,” Computers & Education, vol. 36, no. 4, pp. 299–315, May 2001. [24] A. Casamayor, A. Amandi, and M. Campo, “Intelligent assistance for teachers in collaborative e-learning environments,” Computers & Education, vol. 53, no. 4, pp. 1147–1154, 2009. [25] C. Fernandez-Medina, J. R. Pérez-Pérez, V. M. Álvarez-García, and M. D. P. Paule-Ruiz, “Assistance in computer programming learning using educational data mining and learning analytics,” in Proceedings of the 18th ACM conference on Innovation and technology in computer science education - ITiCSE ’13, 2013, pp. 237–242. [26] A. Vihavainen, T. Vikberg, M. Luukkainen, and M. Pärtel, “Scaffolding Students ’ Learning using Test My Code,” in Annual Conference on Innovation and Technology in Computer Science Education, 2013, vol. 68, pp. 117–122. [27] “Stack Overflow,” 2014. [Online]. Available: https://stackoverflow.com/tour. [Accessed: 22-May-2014]. [28] C.-H. Lai, W.-C. Lin, B.-S. Jong, and Y.-T. Hsia, “Java Assist Learning System for Assisted Learning on Facebook,” IEEE Learning and Teaching in Computing and Engineering, pp. 77–82, Mar. 2013. [29] P. Denny, A. Luxton-Reilly, E. Tempero, and J. Hendrickx, “Understanding the syntax barrier for novices,” Proceedings of the 16th annual joint conference on Innovation and technology in computer science education - ITiCSE ’11, p. 208, 2011. [30] M. S. Othman, S. M. Suhaimi, L. M. Yusuf, N. Yusof, and N. Mohamad, “An Analysis of Social Network Categories: Social Learning and Social Friendship,” Procedia - Social and Behavioral Sciences, vol. 56, no. Ictlhe, pp. 441–447, Oct. 2012. [31] E. Verdú, L. M. Regueras, M. J. Verdú, J. P. Leal, J. P. de Castro, and R. Queirós, “A distributed system for learning programming on-line,” Computers & Education, vol. 58, no. 1, pp. 1–10, Jan. 2012. [32] K. M. Y. Law, V. C. S. Lee, and Y. T. Yu, “Computers & Education Learning motivation in e-learning facilitated computer programming courses,” Computers & Education, vol. 55, no. 1, pp. 218–228, 2010. [33] N. Drljevic and I. Boticki, “Leveraging Social Networks to Increase Motivation in Learning Programming,” in 54th International Symposium ELMAR, 2012, no. September, pp. 12–14. [34] P. Ihantola, T. Ahoniemi, V. Karavirta, and O. Seppälä, “Review of recent systems for automatic assessment of programming assignments,” in Proceedings of the 10th Koli Calling International Conference on Computing Education Research - Koli Calling ’10, 2010, pp. 86–93. [35] V. Pieterse, “Automated Assessment of Programming Assignments,” in ACM Computer Science Education Research Conference, 2013, no. April, pp. 4–5. [36] N. Truong, P. Roe, and P. Bancroft, “Automated Feedback for ‘ Fill in the Gap ’ Programming Exercises,” vol. 42, pp. 117–126, 2005. [37] R. Romli, S. Sulaiman, and K. Z. Zamli, “Automatic Programming Assessment and Test Data Generation,” in IEEE International Symposium in Information Technology (ITSim), 2010, pp. 1186–1192. [38] P. Reimann, M. Kickmeier-rust, and D. Albert, “Problem solving learning environments and assessment : A knowledge space theory approach,” Computers & Education, vol. 64, pp. 183–193, 2013. [39] M. Joy, N. Griffiths, and R. Boyatt, “The BOSS Online Submission and Assessment System,” vol. 5, no. 3, 2005. [40] C. Douce, “Automatic Test-Based Assessment of Programming : A Review,” ACM Journal of Educational Resources in Computing, vol. 5, no. 3, pp. 1–13, 2006. [41] T. Wang, X. Su, P. Ma, Y. Wang, and K. Wang, “Computers & Education Ability-training-oriented automated assessment in introductory programming course,” Computers & Education, vol. 56, no. 1, pp. 220–226, 2011. [42] S. A. Naser, “AN AGENT BASED INTELLIGENT TUTORING SYSTEM,” Journal of Theoretical and Applied Information Technology, vol. 4, no. 7, pp. 585–589, 2008. |
| spellingShingle | A perspective of Automated programming error feedback Approaches in problem solving exercises |
| summary | Programming tools are meant for student to practice programming. Automated programming error feedback will be provided for students to self-construct the knowledge through their own experience. This paper has clustered current approaches in providing automated error programming feedback to the students during problem solving exercises. These include additional syntax error messages, solution template mismatches, test data comparison, assisted agent report and collaborative comment feedback. The study is conducted based on published papers for last two decades. The trends are analyzed to get the overview of latest research contributions towards eliminating programming difficulties among students. The result shows that future direction of automated programming error feedback approaches may combine agent and collaborative feedback approaches towards more interactive, dynamic, end-user oriented and specific goal oriented. Such future direction may help other researchers fill in the gap on new ways of assisting learners to better understand feedback messages provided by automated assessment tool. |
| title | A perspective of Automated programming error feedback Approaches in problem solving exercises |
| title_full | A perspective of Automated programming error feedback Approaches in problem solving exercises |
| title_fullStr | A perspective of Automated programming error feedback Approaches in problem solving exercises |
| title_full_unstemmed | A perspective of Automated programming error feedback Approaches in problem solving exercises |
| title_short | A perspective of Automated programming error feedback Approaches in problem solving exercises |
| title_sort | perspective of automated programming error feedback approaches in problem solving exercises |