Pengenalan Ekspresi Wajah Pengguna Elearning Menggunakan Artificial Neural Network dengan Fitur Ekstraksi Local Binary Pattern dan Gray Level Co-occurrence Matrix

Pembelajaran eLearning merupakan sistem pembelajaran berbasis elektronik yang terdiri dari berbagai domain teknologi pembelajaran seperti desain, pengembangan, pemanfaatan, pengelolaan, dan penilaian proses dan sumber belajar elektronik, interaksi pemelajar merupakan kelemahan yang harus diperhatikan dalam pembelajaran eLearning, salah satunya dengan pengenalan ekspresi wajah pengguna eLearning. Ekspresi wajah dapat dikenali berdasarkan Perubahan fitur penting wajah sebagai parameter yaitu pada mata, alis, mulut dan dah

Detection of behavioral patterns for increasing attentiveness level

In the current world, performance is one of the most important issues concerning work and competition. Performance is strongly connected with learning and when it comes to acquiring new knowledge, attention is one the most important mechanisms as the level of the learner’s attention affects learning results. When students are doing learning activities using new technologies, it is extremely important that the teacher has some feedback from the students’ work in order to detect potential learning problems at an early stage. The goal of this research is to propose a system that measures the level of attentiveness in real scenarios, and detects patterns of behavior associated to different attention levels among different students. This system measures attention and uses this information for training a decision support system that shows the level of attention of a group of students in real time.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

An Investigation of Visual Fatigue in Elementary School Students Resulting from Reading e-books

[[abstract]]Screen-based reading with e-books, which leverages technology in order to create pertinent learning experiences for all students, has become more acceptable to digital natives. Notably, before e-books are widely adopted in academic learning, the visual burden of students during reading activities should be considered. This investigation thus examines how reading-related factors affect visual fatigue incurred when reading both e-books and paper-based books through an experiment conducted on 24 elementary school students. The results showed that the different reading materials have no significant difference in terms of affecting students’ levels of visual fatigue; that is, reading material seems inconsequential with regard to changes in the degree of visual fatigue. Furthermore, another result found that long duration reading led visual to more burden, which also mean that long periods of reading without proper rest should be avoided. As this study of the foundation of visual fatigue reveals, the findings can be as references beneficial for integrating e-books into instruction and providing suggestions for the use of e-books in education. Therefore, we suggest that future studies should consider visual fatigue as important factors in e-book learning activity to promote their more potential benefits with regard to student learning.[[notice]]補正完