Informing the Detection of the Students' Motivational State: An Empirical Study
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
Design requirements for technologies that encourage physical activity
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A behavior model for persuasive design
Proceedings of the 4th International Conference on Persuasive Technology
Creating persuasive technologies: an eight-step design process
Proceedings of the 4th International Conference on Persuasive Technology
A theory-based framework for evaluating exergames as persuasive technology
Proceedings of the 4th International Conference on Persuasive Technology
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This study addresses the general goal of designing more engaging e-learning applications through persuasive technology. The authors present and discuss two potential approaches to the design persuasive e-learning applications that differ in terms of comprehensiveness and ease of application. The more straightforward approach based on Fogg is considered for designers who may not have the time or background to invest large efforts to analyze and understand how the principles of persuasive technology can be deployed. The Oinas-Kukkonen and Harjumaa 2009 approach is presented as a different approach that does require such investment. The design approaches are complemented with a persuasive assessment grid that can be used as an inspection instrument, akin to usability inspections as found in the field of human-computer interaction. The intent is that this instrument can complement the design process by giving early feedback on issues to address. The authors report an experiment where the inspection instrument is applied to an existing e-learning application. The actual data on how students used it provides feedback on how effective the persuasive grid is for detecting issues. The results show that the application scores low on most criteria, and the usage patterns generally confirm this assessment. However, the authors also find that some students were persuaded to engage more thoroughly to use the system and conclude that large individual differences affects the factors of influence and should lead the designers of e-learning application to consider different means in the design of persuasive technology.