Intelligent Tutoring System

Student Frustration and Human-Automation Etiquette

Human Frustration in Human-Computer Interaction (HCI)

User frustration in HCI indicates a negative feeling that occurs when efforts to achieve a goal are impeded. User frustration impacts not only the communication with the computer itself, but also productivity, learning, and cognitive workload. Affect-aware systems have been studied to recognize user emotions and respond in different ways. Affect-aware systems need to be adaptive systems that change their behavior depending on users’ emotions. Adaptive systems have four categories of adaptations. Previous research has focused on primarily function allocation and to a lesser extent information content and task scheduling. However, the fourth approach, changing the interaction styles is the least explored because of the interplay of human factors considerations.

Developing an Intelligent Tutoring System with Automation Etiquette

Three interlinked studies were conducted to investigate the consequences of user frustration and explore mitigation techniques. Study 1 showed that delayed feedback from the system led to higher user frustration, anger, cognitive workload, and physiological arousal. In addition, delayed feedback decreased task performance and system usability in a human-robot interaction (HRI) context. Study 2 evaluated a possible approach of mitigating user frustration by applying human-human etiquette strategies in a tutoring context. The results of Study 2 showed that changing etiquette strategies led to changes in performance, motivation, confidence, and satisfaction. The most effective etiquette strategies changed when users were frustrated. Based on these results, an adaptive tutoring system prototype was developed and evaluated in Study 3. By utilizing a rule set derived from Study 2, the tutor was able to use different automation etiquette strategies to target and improve motivation, confidence, satisfaction, and performance using different strategies, under different levels of user frustration.

Research Question

• How does feedback influence user emotions, cognitive workload, performance, and physiological response?
• Does changing the interaction style of feedback by using etiquette strategies mitigate user frustration?
• Does an adaptive system that employs etiquette strategies mitigate user frustration and improve motivation, confidence, satisfaction, and performance?

Conclusion

This work establishes that changing the interaction style alone of a computer tutor can affect a user’s motivation, confidence, satisfaction, and performance. Furthermore, the beneficial effect of changing etiquette strategies is greater when users are frustrated. This work provides a basis for future work to develop affect-aware adaptive systems to mitigate user frustration.

Publication

• Yang, E. & Dorneich, M. C. (2018) Evaluating Human-­Automation Etiquette Strategies to Enhance Learning. Applied Sciences. 8(6), 895.
• Yang, E. & Dorneich, M. C. (2018) Affect-Aware Adaptive Tutoring Based on Human-Automation Etiquette Strategies. Human Factors. 60(4), 510-526.
• Yang, E. (2016). Mitigating user frustration through adaptive feedback based on human automation etiquette strategies, Doctoral dissertation, Iowa State University.
• Yang, E. & Dorneich, M. C. (2016) Evaluation of Etiquette Strategies to Adapt Feedback in Affect-Aware Tutoring. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 60, No. 1, pp. 393-397). SAGE Publications.
• Iglesias, M., Montealegre, D. A., Yang, E., Zonner, J., & Dorneich, M. (2015) Measuring the Effectiveness of Etiquette Strategies to Mitigate Negative Emotions. Society for Advancement of Chicanos/Hispanics and Native Americans in Science (SACNAS) Conference. Washington D.C., October 29-31.

Standardized Test for College Admissions

Professional Learning Community (PLC)

Discovery Professional Learning Community (PLC)

A professional learning community, or PLC, is a group of educators that meets regularly, shares expertise, and works collaboratively to improve teaching skills and the academic performance of students. The term is also applied to schools or teaching faculties that use small-group collaboration as a form of professional development.

Method

Since this project was in the phase of customer discovery, we approached understanding the structure of PLC, which consists of administrator, curriculum specialists, and teachers. Employing a variety of methodologies including empathy map, user journey, contextual inquiry, personas, interview, and other proper qualitative and quantitative research techniques. Traveling to off-site locations and facilitated validation sessions such as one-on-one moderated tests and focus groups to obtain user preferences and feedback.

Deliverable

Presenting feedback and recommendations to stakeholders with the appropriate business and user experience framework.

Frequently Used Tool

Data Analysis: R, SAS, JMP, Handrail, Optimal Workshop

Design/Prototyping: Axure, Unity, Adobe Illustrator

Communication: Trello, Slack

Higher Education

Competitive Analysis on University Websites

State Universities vs. Local Universities

A state university, where wants to recruit more both domestic and international students, was wondering about their competitors based on size and locations. Their website and competitor schools' websites were evaluated by using competitor analysis, heuristic evaluation, and usability testing.

Deliverable

Presenting feedback and recommendations to stakeholders with the appropriate business and user experience framework.

Frequently Used Tool

Data Analysis: Excel, R, SAS, JMP, Handrail

Communication: Trello, Slack