Blurb:

Technological advances are having a significant impact on language assessment in general and this chapter examines the opportunities machines present to better measure comprehensibility, as well as the threats that constrained tasks demanded by automated assessment might present to the construct. An overview of current models for automated rating of speech is presented (e.g. Xi, et al. 2008; Van Moere & Downey, 2016; Isaacs, 2014) and the approaches are examined from the perspective of the comprehensibility framework presented in the book, drawing on the features extrapolated in each of the preceding chapters to examine how technology does and does not offer solutions for automated assessment and feedback for learning on particular components of the comprehensibility inventory.