Knowledge tracing is a method used in education to assess and track the
acquisition of knowledge by individual learners. It involves using a variety of
techniques, such as quizzes, tests, and other forms of assessment, to determine
what a learner knows and does not know about a particular subject. The goal of
knowledge tracing is to identify gaps in understanding and provide targeted
instruction to help learners improve their understanding and retention of
material. This can be particularly useful in situations where learners are
working at their own pace, such as in online learning environments. By
providing regular feedback and adjusting instruction based on individual needs,
knowledge tracing can help learners make more efficient progress and achieve
better outcomes. Effectively solving the KT problem would unlock the potential
of computer-aided education applications such as intelligent tutoring systems,
curriculum learning, and learning materials recommendations. In this paper, we
will present the results of the implementation of two Knowledge Tracing
algorithms on a newly released dataset as part of the AAAI2023 Global Knowledge
Tracing Challenge.

知识追踪是一种在教育领域中用于评估和追踪个体学习者知识获取的方法，本文通过实施两种知识追踪算法并使用新发布的数据集，展示了解决知识追踪问题的结果，以推动计算机辅助教育应用（如智能辅导系统、课程学习和学习材料推荐）的发展。