Attentive knowledge tracing (AKT) 目前KT中有两个假设: 学习者过去的表现可以被压缩在一个集合的向量中,这些向量可以表示学习者当前的知识水平 (knowledge level). 学习者未来的表现可以用当前的知识水平来预测。 引入一种通用的模型,用 t 表示离散时间的索引,即一个学生第几次做的题。 rt∼f(ht),ht∼g(ht 6
ATK模型精要解读 网上对这篇论文的精读和泛读总结都有,由于只想借鉴此方法的精髓用于自己的模型设计,因此不再对内容要点做总结,只结合论文代码对ATK模型做解析。 模型效果 根据论文和代码,确实能复现出和论文指标差不多的性能。 在数据集assist2009_pid上,运行效果如下图。 python main.py --dataset assist2009_p...
这篇文章提出了AKT模型, 使用了单调性注意力机制, 考虑过去的做题记录来决策未来的做题结果, 另外使用了Rasch 模型来正则化习题和概念的嵌入。 AKT方法 1上下文感知表示和知识检索 通过两个encoder使用单调性注意力机制,分别将原始的习题嵌入 {x1,...,xt}{x1,...,xt} 编码为 {^x1,...,^xt}{x^1,...,...
Furthermore, knowledge tracing models exhibit limited interpretability compared with cognition diagnosis methods integrating educational priors. To address these issues, we propose a multi-layer context-aware deep knowledge tracing (MLC-DKT) model. Specifically, we first present the multi-layer contextual ...
Knowledge-Based Intelligent Information and Engineering Systems, 9th International Conference, KES 2005, Melbourne, Australia, September 14-16, 2005, Proceedings, Part IIKim, T.S., Kim, H.-D.: Context-Aware Computing Based Adaptable Heart Diseases Diagnosis Algorithm. In: Khosla, R., Howlett, ...
This method employs dynamic graph and knowledge tracing to model learners, it selects candidate learners for the recommendation based on the following cognitive and affective features: the total time spent on assessments, the total number of correct answers, the hints count, the attempts count, the...
Switch on the "LANGCHAIN_TRACING_V2" setting in run.py to "true" That's it. You'll get better understanding of your agents and chaing performance in LangChain admin panel. For futher reading take a look at thedocs Roadmap Lead Maintaner: Filip Michalsky ...
Paper:Context-Aware Attentive Knowledge TracingCode:github.com/arghosh/AKT ⭐ 动机 使用单调注意力网络来计算当前问题与学习者过去回答的每个问题之间的练习。 使用Rasch 模型计算问题嵌入和交互嵌入,这些嵌入能够捕获同一知识点的问题之间的个体差异,而无需使用过多的参数。 ⭐ 模型 1【 编码器和检索器 】 问...
As we have seen, the backup and the tracing functionalities in the example are activated by a different thread than the one actually affected by them. This aspect is not peculiar of our example, but is common to many self-adaptive applications designed according to the MAPE-K model, because...
(which may include, for example, elements of the training content, level of complexity, duration, and examples used to train the user), the expected medium and long-term retention of the knowledge the training intervention teaches, the languages in which the training intervention is available, ...