  Computer-based interactive items have become prevalent in recent educational
assessments. In such items, the entire human-computer interactive process is
recorded in a log file and is known as the response process. This paper aims at
extracting useful information from response processes. In particular, we
consider an exploratory latent variable analysis for process data. Latent
variables are extracted through a multidimensional scaling framework and can be
empirically proved to contain more information than classic binary responses in
terms of out-of-sample prediction of many variables.
