There’s an app for that. Both language learners and language educators are familiar with many digital resources for learning and teaching languages, but how do they work? Many testing agencies, such as the Educational Testing Service (ETS, www.ets.org), use technology to evaluate and score language proficiency, but how does the computer know what “good” language is? These, and other, questions are best understood by exploring the research and development of automated language assessment (ALA). ALA is concerned with the development of computational systems that can automate the assessment of language samples. These language samples may include spoken or written excerpts that are produced by first or second language speakers or writers. ALA allows us to objectively and efficiently evaluate large numbers of language samples, and to provide feedback to the language learners. Consider your current class – you may have anywhere from 10 to 100 classmates. Now, consider evaluating a 5-minute speech sample and providing helpful feedback for each individual. If you are in a class of 100, it would take over 8 hours just to listen to the samples. Testing agencies such as ETS evaluate thousands of written and spoken samples. ALA provides a way for effectively evaluating such large sample numbers and providing objective general feedback directly to the individual on specified features of language.