The learning process can be seen as an emotional and personal experience that is addictive and motivates learners to proactive behaviour. New research methods in this field are related to affective and emotional approaches to computer-supported learning and human-computer interactions. The major topics discussed are emotions, motivation, games and game-experience. The book is divided in three parts, part I, Game-based Learning, reflects upon the two-way interaction between game and student, thus enabling the game to react to the student’s emotional state. Having the possibility to detect and steer the emotional state of the student could have a positive impact on using digital games in education. It is claimed that some commercial computer games increase cognitive skills and may enhance multitasking abilities and the participants’ general ability to learn. Part II, Motivation and Learning, analyses whether the absence or presence of social and personal cues in the communication between a tutor and his or her students influence students’ learning and their satisfaction with the tutor and the course. The research showed that not all types of personal information are equally important and possibly pictorial information is more important than audible information. Part III, Emotions and Emotional Agents, discusses the production of learning environments which enhance the learner’s self esteem, ensure that the learner’s best interests are respected through paying attention to the narrative structures of the learner’s experience, and the ways in which communication can be enhanced through empathy with the learner.
This unique text brings together into a single framework current research in the three areas of discrete calculus, complex networks, and algorithmic content extraction. Many example applications from several fields of computational science are provided.