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

Area of Science:

• Educational Technology
• Human-Computer Interaction
• Artificial Intelligence in Education

Background:

• Traditional intelligent tutoring systems (ITS) primarily adapt content difficulty or feedback timing.
• Previous research indicated that varying ITS feedback interaction style through etiquette strategies impacts student motivation, confidence, satisfaction, and performance.
• User frustration levels were previously identified as a key factor in determining optimal etiquette strategies.

Purpose of the Study:

• To investigate the effectiveness of systematically adapting ITS feedback interaction style based on a rule set of human-automation etiquette strategies.
• To compare systematic adaptation of etiquette strategies against random changes in improving key learning factors.
• To determine if systematic adaptation is effective across different levels of user frustration.

Main Methods:

• Developed a rule set to systematically select etiquette strategies targeting motivation, confidence, satisfaction, or performance.
• Assigned participants to solve mathematics problems under varying frustration conditions.
• Administered feedback that dynamically changed etiquette strategies either systematically (rule-based) or randomly.

Main Results:

• Systematic adaptation of feedback etiquette strategies significantly improved motivation, confidence, satisfaction, and performance compared to random changes.
• The effectiveness of systematic adaptation was consistent across different levels of user frustration.
• This demonstrates the potential for tailored, affect-aware feedback in ITS.

Conclusions:

• Systematically adapting ITS feedback interaction style via etiquette strategies is a viable method to enhance learning outcomes.
• ITS designers can leverage affect-aware adaptations to mitigate negative emotions and improve learning.
• This research provides a novel mechanism for creating more responsive and effective intelligent tutoring systems.