  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.
