Artificial Intelligence and Literacy Education

an analysis of the Amira Learning platform

Abstract

This article presents an analysis of the Amira Learning platform, designed for teaching reading to students in the U.S. K-12 system. Founded in 2016 by engineers and executives from companies such as Pearson, IBM, ACT, and Renaissance, the platform uses Artificial Intelligence (AI) to provide personalized reading instruction. It currently accounts for approximately 15% of the U.S. K-12 educational technology market and serves more than 1,800 school districts. The study aims to identify the main automation mechanisms embedded in the platform and to discuss the pedagogical foundations that support them. The investigation is theoretically grounded in critical studies on the platformization of education, in literacies, and in the theory of the psychogenesis of written language. Methodologically, it adopts a qualitative approach based on analysis of materials released by the company itself. The analysis focused on the system’s latest version—the Intelligent Growth Engine—from which five functionalities that reveal its automation mechanisms were described. In addition, three intelligent agents were mapped—Amira ISIP Assess (assessment), Amira Instruct (instruction), and Amira Tutor (tutoring)—along with their respective data collection, adaptation, feedback, and recommendation flows. The results indicate that, despite its technological sophistication, Amira Learning’s pedagogical approach remains grounded in associationism and behaviorist principles, aligned with Skinnerian programmed instruction. From this perspective, learning to read is essentially conceived as decoding relationships between graphemes and phonemes—that is, associating letters with sounds—thereby restricting the learning process to recognizing such correspondences. As a result, repetitive exercises and memorization are prioritized, while the development of metacognitive skills and attention to contextual dimensions are relegated to the background. In Amira’s system, this outlook is manifest, among other aspects, in tasks that privilege the fragmentation of content, the provision of immediate feedback, and the automated personalization of learning. The study concludes that the growing adoption of platforms such as Amira Learning by schools and governmental agencies calls for careful ethical and pedagogical scrutiny of how AI technologies are shaping school practices, particularly in the fields of literacy and reading.