An overview of Affective Models and ICT in Education

Sotiria Foutsitzi*, Stelios Asteriadis, George Caridakis

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review


Emotion, human intelligence and learning have inextricable connections. Making sure learners' emotions arc positive during the learning procedure can increase and optimize the learning outcome. However, until recently, cognition and emotion were viewed as two separate notions. Learning materials and pedagogical strategies focusing more on how to increase and sustain the volume of knowledge, rather than how to actively engage the learner, through positive and enjoyable learning experiences, were in the focus of attention. However, in the last years, the advent of a wide variety of learning (digital) resources, such as serious games, robots, mobile devices, virtual and augmented reality, has provided the means to involve the learner in more immersive and active contexts, that place engagement and human emotions in the centre of the interaction. Moreover, the advances in artificial intelligence are now allowing for a wide availability of instruments that allow for estimating emotions based on a plethora of means, such as facial expressions, heart rate measurements, digital log files, personality analysis. The above arc leading to personalized learning that tailors the learning procedure to the (emotional and cognitive) needs of the individual learner. This paper is presenting an introduction to the role of emotion in educational settings and describes influential and promising emotional models. A brief overview of ways to infer emotions follows, while examples of works intended to make use of measured emotion in learning conditions is presented at the end of this work.

Original languageEnglish
Title of host publicationThe 10th International Conference on Information, Intelligence, Systems and Applications (IISA 2019)
Number of pages8
Publication statusPublished - 2019


  • ICT in education
  • affective computing
  • e-learning
  • emotion recognition
  • emotional models
  • personalization

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