March 13, 2024, 4:47 a.m. | Yanhong Bai, Jiabao Zhao, Tingjiang Wei, Qing Cai, Liang He

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.07279v1 Announce Type: new
Abstract: With the long term accumulation of high quality educational data, artificial intelligence has shown excellent performance in knowledge tracing. However, due to the lack of interpretability and transparency of some algorithms, this approach will result in reduced stakeholder trust and a decreased acceptance of intelligent decisions. Therefore, algorithms need to achieve high accuracy, and users need to understand the internal operating mechanism and provide reliable explanations for decisions. This paper thoroughly analyzes the interpretability of …

abstract algorithms artificial artificial intelligence arxiv cs.cl data decisions educational however intelligence intelligent interpretability knowledge performance quality stakeholder survey tracing transparency trust type will

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