This book focuses on a development for assessing mental changes using eye pupil reactions, namely extracting emotional change from the response to evaluate the viewer's interest in visual information. The pupil of the eye reacts to both brightness and emotional state, including interest, enjoyment, and mental workload. Because pupillary change is a biological signal, various artifacts influence measurements of eye images. Technical procedures are required to extract mental activities from pupillary changes, and they are summarized here step by step, although some procedures contain earlier techniques such as analog video processing. This study examines the possibility of estimating the viewer's interest and enjoyment of viewing movies by measuring the dynamic pupillary changes, blinking, and subjective interest responses. In evaluation of pupil size, there was a significant difference in pupil size between the higher and the lower shot for the degree of subject interest response in each kind of movies. The first part of the book shows a pupil reaction model for brightness changes to extract mental activities. Pupil reactions were observed for various visual stimuli in brightness changes. With regard to the characteristics of pupillary changes, a model with a three-layer neural network was developed and the performance was evaluated. Characteristics of pupil reactions during model development are summarized here. The second part examines the possibility of estimating the viewer's interest and enjoyment of television programs by measuring dynamic pupillary changes, blinking, and subjective interest responses. The final part describes a development of estimation model of pupil size for blink artifact. The model development was able to estimate pupillary changes and pupil size while the viewer was blinking and was applied to pupillary changes in viewing television programs.

The main focus of this book is presenting practical procedures for improving learning effectiveness using note taking activities during e-learning courses. Although presentation of e-learning activities recently has been spreading to various education sectors, some practical problems have been discussed such as evaluation of learning performance and encouragement of students. The authors introduce note taking activity as a conventional learning tool in order to promote individual learning activity and learning efficacy. The effectiveness of note taking has been measured in practical teaching in a Japanese university using techniques of learning analytics, and the results are shown here. The relationships between note taking activity and students' characteristics, the possibility of predicting the final learning performance using metrics of students' note taking, and the effectiveness for individual emotional learning factors are evaluated. Some differences between blended learning and fully online learning courses are also discussed. The authors provide novel analytical procedures and ideas to manage e-learning courses. In particular, the assessment of note taking activity may help to track individual learning progress and to encourage learning motivation.

This book focuses on a development for assessing mental changes using eye pupil reactions, namely extracting emotional change from the response to evaluate the viewer's interest in visual information. The pupil of the eye reacts to both brightness and emotional state, including interest, enjoyment, and mental workload. Because pupillary change is a biological signal, various artifacts influence measurements of eye images. Technical procedures are required to extract mental activities from pupillary changes, and they are summarized here step by step, although some procedures contain earlier techniques such as analog video processing. This study examines the possibility of estimating the viewer's interest and enjoyment of viewing movies by measuring the dynamic pupillary changes, blinking, and subjective interest responses. In evaluation of pupil size, there was a significant difference in pupil size between the higher and the lower shot for the degree of subject interest response in each kind of movies. The first part of the book shows a pupil reaction model for brightness changes to extract mental activities. Pupil reactions were observed for various visual stimuli in brightness changes. With regard to the characteristics of pupillary changes, a model with a three-layer neural network was developed and the performance was evaluated. Characteristics of pupil reactions during model development are summarized here. The second part examines the possibility of estimating the viewer's interest and enjoyment of television programs by measuring dynamic pupillary changes, blinking, and subjective interest responses. The final part describes a development of estimation model of pupil size for blink artifact. The model development was able to estimate pupillary changes and pupil size while the viewer was blinking and was applied to pupillary changes in viewing television programs.

This book features papers from workshops at the 10th International Conference on Methodologies and Intelligent Systems for Technology Enhanced Learning, which was hosted by the University of L'Aquila (Italy) from 17th to 19th June 2020. The workshops provided participants with the opportunity to present and discuss novel research ideas on emerging topics complementing the main conference. They particularly focused on multi-disciplinary and transversal aspects such as TEL in nursing education programs, social and personal computing for web-supported learning communities, interactive environments and emerging technologies for eLearning, and TEL for future citizens.

The main focus of this book is presenting practical procedures for improving learning effectiveness using note taking activities during e-learning courses. Although presentation of e-learning activities recently has been spreading to various education sectors, some practical problems have been discussed such as evaluation of learning performance and encouragement of students. The authors introduce note taking activity as a conventional learning tool in order to promote individual learning activity and learning efficacy. The effectiveness of note taking has been measured in practical teaching in a Japanese university using techniques of learning analytics, and the results are shown here. The relationships between note taking activity and students' characteristics, the possibility of predicting the final learning performance using metrics of students' note taking, and the effectiveness for individual emotional learning factors are evaluated. Some differences between blended learning and fully online learning courses are also discussed. The authors provide novel analytical procedures and ideas to manage e-learning courses. In particular, the assessment of note taking activity may help to track individual learning progress and to encourage learning motivation.