The personalization of feedback by an Intelligent Tutoring System has the potential to greatly improve learner motivation. This PhD investigates how an Intelligent Tutoring System can adapt to the cultural background of learners when giving feedback. The research uses the user-as-wizard method for investigation. To convey the cultural background of the learner in user studies, validated cultural stories (using Hofstede cultural dimensions) are required. These stories are then used to conduct qualitative and empirical studies to investigate how participants from a range of different cultures believe the culture of a learner should affect the kind of feedback given. The insights gathered from these studies will be unified to inspire an algorithm to allow an intelligent tutoring system to utilise these adaptations, and the effects tested on real learners.
Sidi-Ali, M. A. (2019). Adaptive E-learning: Motivating learners whilst adapting feedback to cultural background. In ACM UMAP 2019 - Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization (pp. 341–344). Association for Computing Machinery, Inc. https://doi.org/10.1145/3320435.3323464