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The recent shift to remote learning and work has aggravated long-standingproblems, such as the problem of monitoring the mental health of individualsand the progress of students towards learning targets. We introduce a novellatent process model with a view to monitoring the progress of individualstowards 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 andvariables measuring progress towards the target of interest in a shared metricspace, interpreted as an interaction map that captures interactions betweenindividuals and variables. The fact that individuals are embedded in the samemetric space as the target helps assess the progress of individuals towards thetarget. We demonstrate, with the help of simulations and applications, that thelatent process model enables a novel look at mental health and onlineeducational assessments in disadvantaged subpopulations.

A latent process model for monitoring progress towards hard-to-measure  targets, with applications to mental health and online educational  assessments