Affect-Aware Adaptive Tutoring Based on Human–Automation Etiquette Strategies

Objective: We investigated adapting the interaction style of intelligent tutoring system (ITS) feedback based on human–automation etiquette strategies. Background: Most ITSs adapt the content difficulty level, adapt the feedback timing, or provide extra content when they detect cognitive or affective decrements. Our previous work demonstrated that changing the interaction style via different feedback etiquette strategies has differential effects on students’ motivation, confidence, satisfaction, and performance. The best etiquette strategy was also determined by user frustration. Method: Based on these findings, a rule set was developed that systemically selected the proper etiquette strategy to address one of four learning factors (motivation, confidence, satisfaction, and performance) under two different levels of user frustration. We explored whether etiquette strategy selection based on this rule set (systematic) or random changes in etiquette strategy for a given level of frustration affected the four learning factors. Participants solved mathematics problems under different frustration conditions with feedback that adapted dynamic changes in etiquette strategies either systematically or randomly. Results: The results demonstrated that feedback with etiquette strategies chosen systematically via the rule set could selectively target and improve motivation, confidence, satisfaction, and performance more than changing etiquette strategies randomly. The systematic adaptation was effective no matter the level of frustration for the participant. Conclusion: If computer tutors can vary the interaction style to effectively mitigate negative emotions, then ITS designers would have one more mechanism in which to design affect-aware adaptations that provide the proper responses in situations where human emotions affect the ability to learn

Adaptive Gamification for Learning Environments

(Scimago Q1, ATIEF A+)International audienceIn spite of their effectiveness, learning environments often fail to engage users and end up under-used. Many studies show that gamification of learning environments can enhance learners' motivation to use learning environments. However, learners react differently to specific game mechanics and little is known about how to adapt gaming features to learners' profiles. In this paper, we propose a process for adapting gaming features based on a player model. This model is inspired from existing player typologies and types of gamification elements. Our approach is implemented in a learning environment with five different gaming features, and evaluated with 266 participants. The main results of this study show that, amongst the most engaged learners (i.e. learners who use the environment the longest), those with adapted gaming features spend significantly more time in the learning environment. Furthermore, learners with features that are not adapted have a higher level of amotivation. These results support the relevance of adapting gaming features to enhance learners' engagement, and provide cues on means to implement adaptation mechanisms

A usability assessment for a career planning educational video game

This study focused on the design, implementation and usability assessment of an educational 2D iPad job matching game The Place You’ll Go (TPYG), which meant for matching student skill sets with career profiles. The development of the game is conducted in collaboration with Purdue University’s Krannert School of Management and Polytech Institute. A total of 7 subjects, as high school teachers, participated in the usability study. TPYG as one possible solution for job matching data visualization, did not provide players with a good experience. However, conclusions and findings can be used in similar education game development. Based on survey and analysis, new feasible and scientific plans were made for future development

Innovative integrated architecture for educational games: Challenges and merits

Interactive Narrative in game environments acts as the main catalyst to provide a motivating learning experience. In previous work, we have described how the use of a dual narrative generation technique could help to resolve the conflict between allowing high player student agency and also the track of the learning process. In this paper, we define a novel architecture that assists the dual narrative generation technique to be employed effectively in an adaptive educational game environment. The architecture composes components that individually have shown effectiveness in educational games environments. These components are graph structured narrative, dynamically generated narrative, evolving agents and a student model. An adaptive educational game, AEINS, has been developed to investigate the synergy of the architecture components. AEINS aims to foster character education at 8-12 year old children through the use of various interactive moral dilemmas that attempt the different student\u27s cognitive levels. AEINS was evaluated through a study involved 20 participants who interacted with AEINS on an individual basis

A Framework for Adaptive Game Presenters with Emotions and Social Comments

More and more games today try to adjust their gameplay to fit individual players; however, little work has been carried out in the same direction towards game presenter characters. Game commentary should take into account players' personalities along with game progress in order to achieve social player-adapted comment delivery that boosts the overall gameplay, engages the players, and stimulates the audience. In our work, we discuss a framework for implementing artificial game presenter characters that are based on game actions and players' social profiles in order to deliver knowledgeable, socially oriented comments. Moreover, the presented framework supports emotional facial expressions for the presenters, allowing them to convey their emotions and thus be more expressive than the majority of the commentary systems today. We prove our concept by developing a presenter character for multiplayer tabletop board games which we further put under usability evaluation with 9 players. The results showed that game sessions with presenter characters are preferred over the plain version of the game and that the majority of the players enjoy personalized social-oriented comments expressed via multimedia and emotions