Personality-based tailored explainable recommendation for trustworthy smart learning system in the age of artificial intelligence
Kyosuke Takami,
Brendan Flanagan,
Yiling Dai
et al.
Abstract:In the age of artificial intelligence (AI), trust in AI systems is becoming more important. Explainable recommenders, which explain why an item is recommended, have recently been proposed in the field of learning technology to improve transparency, persuasiveness, and trustworthiness. However, the methods for generating explanations are limited and do not consider the learner’s cognitive perceptions or personality. This study draws inspiration from tailored intervention research in public health and investigat… Show more
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