TY - GEN
T1 - Automatic Assessment of Programming Exercises Using Syntactic Analysis
AU - Ramirez-Trejos, Ellioth
AU - Gonzalez-Torres, Antonio
AU - Sancho-Chavarria, Lilliana
AU - Navas-Su, Jose
AU - Garita, Cesar
AU - Monge-Fallas, Jorge
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper proposes a method to grade programming exam questions automatically. Our motivation is that there are no robust and scalable automatic methods for the analysis of computational thinking from source code programmed by elementary-level students. The approach to this problem supports the improvement of PC development in primary and secondary school students. The validation of the method is performed through the assessment of the answers of primary school students to programming exercises using a programming language called LIE++. The method assesses student answers using several techniques such as the analysis of programming structures, code clones and the execution of code based on input and output values defined during the specification of the exercises. The use of these techniques provides specific scores to obtain a grade of the student's answer. The source code analysis and scoring of exercise answers is carried out using high-performance computing for improving system response time. This research contributes a scalable method for the automatic evaluation of exams, which we expect to support the development of PC.
AB - This paper proposes a method to grade programming exam questions automatically. Our motivation is that there are no robust and scalable automatic methods for the analysis of computational thinking from source code programmed by elementary-level students. The approach to this problem supports the improvement of PC development in primary and secondary school students. The validation of the method is performed through the assessment of the answers of primary school students to programming exercises using a programming language called LIE++. The method assesses student answers using several techniques such as the analysis of programming structures, code clones and the execution of code based on input and output values defined during the specification of the exercises. The use of these techniques provides specific scores to obtain a grade of the student's answer. The source code analysis and scoring of exercise answers is carried out using high-performance computing for improving system response time. This research contributes a scalable method for the automatic evaluation of exams, which we expect to support the development of PC.
KW - abstract syntax trees
KW - Automatic evaluation
KW - source code analysis
UR - http://www.scopus.com/inward/record.url?scp=85179006773&partnerID=8YFLogxK
U2 - 10.1109/SCCC59417.2023.10315732
DO - 10.1109/SCCC59417.2023.10315732
M3 - Contribución a la conferencia
AN - SCOPUS:85179006773
T3 - Proceedings - International Conference of the Chilean Computer Science Society, SCCC
BT - 2023 42nd IEEE International Conference of the Chilean Computer Science Society, SCCC 2023
PB - IEEE Computer Society
T2 - 42nd IEEE International Conference of the Chilean Computer Science Society, SCCC 2023
Y2 - 23 October 2023 through 26 October 2023
ER -