PERSONALIZED LEARNING IN ENGLISH LANGUAGE ARTS: Reading Comprehension

Students’ reading comprehension depends on their ability to connect what they are reading to what they already know. We can help readers to generate these inferences with texts with personalized topics and difficulty, and feedback tailored to their developing comprehension skills. In recent years, a number of promising methodological approaches have been tested to better personalize reading comprehension instruction. Stealth assessment, the practice of assessing students’ learning during the learning process rather than a summative test, has been improved through new tools in natural language processing. Adaptive task selection, the practice of selecting reading texts based on the students’ past performance and interests, has been enhanced through advances in artificial intelligence. These approaches have been implemented in a number of reading educational technologies, such as iSTART, SMART, and iTELL, which have been shown to improve students’ reading skills by better personalizing instruction. As these personalized learning approaches mature, reading instruction as a discipline will continue to grow more equitable and personalized for learners of all skills and backgrounds.