The recent shift to remote learning and work has aggravated long-standing problems, such as the problem of monitoring the mental health of individuals and the progress of students towards learning targets. We introduce a novel latent process model with a view to monitoring the progress of individuals towards a hard-to-measure target of interest, measured by a set of variables. The latent process model is based on the idea of embedding both individuals and variables measuring progress towards the target of interest in a shared metric space, interpreted as an interaction map that captures interactions between individuals and variables. The fact that individuals are embedded in the same metric space as the target helps assess the progress of individuals towards the target. We demonstrate, with the help of simulations and applications, that the latent process model enables a novel look at mental health and online educational assessments in disadvantaged subpopulations.

翻译：近期远程学习与工作的普及加剧了长期存在的问题，例如个体心理健康监测以及学生学业目标的进展跟踪。本文提出一种新颖的潜在过程模型，旨在监测个体在由多变量测量的难以直接观测的目标上的进展。该模型基于将个体和衡量目标进展的变量共同嵌入同一度量空间的核心思想，该空间被解释为捕捉个体与变量间交互的交互图谱。由于个体与目标位于同一度量空间中，这有助于评估个体朝向目标的进展。通过仿真实验与实际应用，我们证明该潜在过程模型能够为弱势群体的心理健康评估和在线教育评估提供全新视角。