Stochastic decision model for arithmetic programming.
Abstract
Few if any validated guidelines exist for making decisions about the
design, media, or format of new instructional products. This study examined
strings of programmed learning responses to create general guidelines for
making such decisions. Using a Markov model, tables were developed relating
the expected proportion of students to be in a solution state at a given
accuracy level and at a given level of confidence with respect to the
length of response strings.