HandSnap++: an android application for debugging handwritten C++ code using image processing through optical character recognition and compiler
Paper coding, where students write C++ codes on paper during assessments, enhances logical and problem-solving skills but still has challenges, particularly in manual debugging. HandSnap++ is an innovative application that extracts handwritten C++ codes utilizing Optical Character Recognition (OCR),...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | en |
| Published: |
Academica Press Solutions
2025
|
| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/128914/1/128914.pdf https://doi.org/10.64382/mjii.v4i4.120 https://ir.uitm.edu.my/id/eprint/128914/ https://journal.academicapress.org/aps/index.php/mjii |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Paper coding, where students write C++ codes on paper during assessments, enhances logical and problem-solving skills but still has challenges, particularly in manual debugging. HandSnap++ is an innovative application that extracts handwritten C++ codes utilizing Optical Character Recognition (OCR), compiles the scanned codes, provides debugging feedback, and scores the students’ codes. This study employed a descriptive and developmental method within the quantitative research framework, gathering interviews and evaluations from 20 instructors and 20 students in the department of computer studies to assess the effectiveness of the HandSnap++ application in achieving its objectives that greatly contribute to the educational field and institution. The application, upon its development, proved to be an effective alternative tool for debugging in resource-limited environments, such as in computer laboratories, especially in state universities, as the app is portable. It also reduces overlooking errors in checking through OCR, provides timely feedback on scores for students, stores their answers digitally, and helps students adapt to utilizing compilers in an application. The application was evaluated with ISO 25010, and among the categories, its functional suitability attained the high score average while its performance efficiency was scored last. Even with these results, it is recommended to explore OCR models focused on improving special character recognitions as well as to expand the supported language, not just C++, for compiling. |
|---|