Leveraging Artificial Intelligence to Foster Literacy Motivation Among Students Struggling to Read

• In Event: AI for Equity, Access, and Innovation in Postsecondary Writing and Learning Contexts

Abstract

This study examines how Artificial Intelligence (AI) can enhance reading motivation in students who struggle with literacy, particularly among foreign-born Black students facing distinct linguistic, cultural, and systemic obstacles. Students from culturally and linguistically diverse backgrounds often remain disengaged from literacy instruction due to cognitive overload, instructional barriers, and inadequate personalized support, despite advancements in educational technology (Ferguson et al., 2022; Solari et al., 2022). Leveraging adaptive AI systems, including Intelligent Tutoring Systems (ITS) and utility-based intelligent agents, presents significant potential to deliver personalized, culturally responsive learning experiences that address these barriers.

Utility-based intelligent agents have demonstrated effectiveness in educational contexts due to their explicit instructional clarity, defined objectives, and real-time adaptability. AI-driven agents have been successfully integrated into serious games, especially narrative-centered discovery games that combine storytelling and exploratory gameplay to enhance intrinsic motivation (Ferguson et al., 2022). These adaptive, culturally relevant games engage struggling readers by aligning content and challenges with individual cultural identities and personal interests. When not tailored properly, however, students risk experiencing cognitive overload, which may result in decreased motivation and lower literacy performance (Smith, 1996; Ferguson & van Oostendorp, 2020).

Based on Vygotsky’s (1978) Zone of Proximal Development (ZPD), optimal learning occurs when tasks provide appropriate challenges that are neither too difficult nor too simple. AI systems help maintain students within this optimal learning zone by adjusting task difficulty based on performance metrics (Smith, 1996). Personalized adaptive feedback delivered by AI systems significantly reduces cognitive overload, enhances knowledge retention, and sustains learner engagement and intrinsic motivation (Albus et al., 2021; Wolfe, 2020; Hamari et al., 2016; Shute et al., 2017).

Research emphasizes the importance of equity-driven AI interventions designed to support minoritized students by addressing linguistic diversity and systemic biases (Smith et al., 2020; Solari et al., 2022). Integrating culturally responsive practices with AI significantly improves literacy outcomes by affirming students’ cultural and linguistic identities and increasing intrinsic motivation (Castillo & Wagner, 2019; Mucherah & Yoder, 2008). The use of culturally relevant AI practices counters negative stereotypes, boosts students' self-confidence, and encourages deeper engagement in literacy tasks.

This synthesized study highlights the role of adaptive, culturally responsive AI interventions—rather than traditional interventions alone—in overcoming systemic barriers and supporting personalized literacy instruction. By ensuring that instructional content is grounded in students’ cultural identities, personal interests, and motivational needs, AI tools can promote deeper comprehension, higher-order thinking skills, and sustained literacy engagement (Castillo, 2020; Wigfield & Guthrie, 1997).

In summary, implementing adaptive and culturally responsive AI tools in literacy instruction can enhance motivation for students who struggle with reading, monitor their progress, and enable teachers to address challenges proactively. Future research should aim to improve AI personalization, examine long-term outcomes, and evaluate the effectiveness of real-time feedback. Additionally, educational policies should be redefined to recognize diverse measures of literacy success, challenge stereotypes, and address socioeconomic factors—thereby fostering inclusive literacy practices for marginalized students.

Authors

• Temidayo Jaiyesimi, University of Kentucky

• Meenu Devi, University of Kentucky