Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algorithm for sampling from the posterior process of the GP model. This algorithm uses control variables which are auxiliary function values that provide a low dimensional representation of the function. At each iteration, t...

This research aims to explore the students' evaluations of interactivity in teaching process. The involved 361 students, 127 (35.2%) male and 234 (64.8%) female students. participants were between 18 54 years old (M = 22.32, SD 5.926). Questions related previous current education participants, their age, gender place residence included as demographic variables. Interactivity process was measure...