Proposal for a System for the Identification of the Concentration of Students Who Attend Online Educational Models


Abstract:

Currently, e-learning has revolutionized the way students learn by offering access to quality education in a model that does not depend on a specific space and time. However, due to the e-learning method where no tutor can directly control the group of students, they can be distracted for various reasons, which greatly affects their learning capacity. Several scientific works try to improve the quality of online education, but a holistic approach is necessary to address this problem. Identifying students’ attention spans is important in understanding how students process and retain information. Attention is a critical cognitive process that affects a student’s ability to learn. Therefore, it is important to use a variety of techniques and tools to assess student attention, such as standardized tests, behavioral observation, and assessment of academic achievement. This work proposes a system that uses devices such as cameras to monitor the attention level of students in real time during online classes. The results are used with feedback as a heuristic value to analyze the performance of the students, as well as the teaching standards of the teachers.

Año de publicación:

2023

Keywords:

  • Computer Vision
  • blink rate
  • Artificial Intelligence

Fuente:

scopusscopus
googlegoogle

Tipo de documento:

Article

Estado:

Acceso abierto

Áreas de conocimiento:

  • Tecnología educativa
  • Educación superior

Áreas temáticas:

  • Escuelas y sus actividades; educación especial
  • Funcionamiento de bibliotecas y archivos