Affective Educational Games and the Evolving Teaching Experience

Abstract

Teaching methods must adapt to learners’ expectations. Computer game-based learning environments enable learning through experimentation and are inherently motivational. However, for identifying when learners achieve learning goals and providing suitable feedback, Intelligent Tutoring Systems must be used. Recognizing the learner’s affective state enables educational games to improve the learner’s experience or to distinguish relevant emotions. This chapter discusses the creation of an affective student model that infers the learner’s emotions from cognitive and motivational variables through observable behavior. The control-value theory of ‘achievement emotions’ provides a basis for this work. A Probabilistic Relational Models (PRMs) approach for affective student modeling, which is based on Dynamic Bayesian Networks, is discussed. The approach is tested through a prototyping study based on Wizard-of-Oz experiments and preliminary results are presented. The affective student model will be incorporated into PlayPhysics, an emotional game-based learning environment for teaching Physics. PRMs facilitate the design of student models with Bayesian Networks. The effectiveness of PlayPhysics will be evaluated by comparing the students’ learning gains and learning efficiencies.

A conceptual research of college students boredom, learning attitude, academic achievement, and behavior

“…In the nursing profession, negative attitudes will affect the academic achievement of college students (Lee et al, 2015). Muñoz et al (2016) discover that student's attitudes can influence their future academic achievement and it is also the major to generating emotions.…”

Tutoring and Assessment Through Games and Emotions

“…However, currently only a few ATSs are developed as game-based environments. Prime Climb (Conati et al, 2013) created for learning number factorization skills, CRYSTAL ISLAND (Sabourin and Lester, 2014) developed as 3D narrative-centred learning environment for eighthgrade microbiology, PlayPhysics (Munoz et al, 2011) and Newton's Playground (Andres and Rodrigo, 2014) designed for tutoring basic physics concepts and principles, can be mentioned as examples of such kind of systems using embedded pedagogical activities as engaging and game-like interactions. Although emotional reactions are not widely modelled in educational games and small number of ATSs exploits GBL as main teaching approach, the application of games for the knowledge assessment is used even more rarely in tutoring systems (Li et al, 2014).…”