.png){kind=icon}
.png){kind=icon}
Return
LectoKids: supporting reading comprehension through generative artificial intelligence-based software
.png){kind=icon}
OA
AI
DOI：10.18845/tm.v39i5.8495.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Reading comprehension is essential for learning, but it often encounters resistance among young students, who even turn to artificial intelligence (AI) tools as substitutes. To address this issue, this study proposes the use of generative AI through a custom-designed web application. Based on structured interviews with elementary education professionals, the requirements for the proposed application were defined. The resulting platform integrates an adaptive reading component supported by AI models such as GPT and DALL & centerdot;E. These models are used to generate personalized texts and images tailored to each student's needs. Additionally, modules were developed to generate instructional materials and customized assessments. The application was evaluated through a user study involving students and teachers, using a usability questionnaire, interviews, and reading comprehension performance analysis. The results show that the proposed solution is a promising alternative to traditional paper-based reading and activities, offering acceptable usability and demonstrating academic effectiveness.
Keywords:
Didactic software
active learning
reading
artificial intelligence
computer-assisted instruction
Journal
T
IF:
0.1
Papers:
86
Citations:
165
Organization
No organization information available