Development and Evaluation of Learning Support System Based on Automatic Classification of Students' Programs According to Difference from Standard Algorithm
“…In addition, if a teacher finds that a program has a distinctive difference from the standard algorithm, he/she may want to search for the same distinctive point in other students’ programs. Therefore, the monitoring system also applies an automatic classification module to student programs, which detects differences from the standard algorithm (Kogure et al, 2010).…”
Section: Methodsmentioning
confidence: 99%
“…1 shows positionDiff() and contentDiff() examples. Thus, a teacher can find programs with the same positionDiff j (s,j,k) or both the same positionDiff j (s,j,k) and the same contentDiff j (s,j,k) using an existing module (Kogure et al, 2010). Fig.…”
Section: Reused Modulesmentioning
confidence: 99%
“…Thus, several automated methods have been developed for the evaluation of student programs, such as LAURA (Adam & Laurent, 1980) and PROUST (Johnson, 1990). We also developed a teacher support environment that focused on supporting teachers during programming education (Kogure, Takatsu, Konishi, and Itoh, 2010). The environment made it easier for teachers to grade programs and text reports.…”
In this study, we developed a programming practice monitoring system to facilitate teachers to give appropriate instructions to students at the appropriate time during classroom lectures. To help teachers to provide appropriate instruction to learners, we identified parameters that would be useful for teachers during programming exercise in classroom lecture. We constructed a monitoring system with five functions. The system automatically acquired the programs written by students to evaluate their performance, and the teacher can obtain their performance using the five functions. We asked four subjects to test our proposed monitoring system during a simulation of a classroom lecture. The evaluation revealed that the system had a high accuracy in evaluating student programs.
“…In addition, if a teacher finds that a program has a distinctive difference from the standard algorithm, he/she may want to search for the same distinctive point in other students’ programs. Therefore, the monitoring system also applies an automatic classification module to student programs, which detects differences from the standard algorithm (Kogure et al, 2010).…”
Section: Methodsmentioning
confidence: 99%
“…1 shows positionDiff() and contentDiff() examples. Thus, a teacher can find programs with the same positionDiff j (s,j,k) or both the same positionDiff j (s,j,k) and the same contentDiff j (s,j,k) using an existing module (Kogure et al, 2010). Fig.…”
Section: Reused Modulesmentioning
confidence: 99%
“…Thus, several automated methods have been developed for the evaluation of student programs, such as LAURA (Adam & Laurent, 1980) and PROUST (Johnson, 1990). We also developed a teacher support environment that focused on supporting teachers during programming education (Kogure, Takatsu, Konishi, and Itoh, 2010). The environment made it easier for teachers to grade programs and text reports.…”
In this study, we developed a programming practice monitoring system to facilitate teachers to give appropriate instructions to students at the appropriate time during classroom lectures. To help teachers to provide appropriate instruction to learners, we identified parameters that would be useful for teachers during programming exercise in classroom lecture. We constructed a monitoring system with five functions. The system automatically acquired the programs written by students to evaluate their performance, and the teacher can obtain their performance using the five functions. We asked four subjects to test our proposed monitoring system during a simulation of a classroom lecture. The evaluation revealed that the system had a high accuracy in evaluating student programs.
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