Call for manuscripts for RiSE special series:  Emerging Trends in AI-Driven Special Education Research:  Enhancing Personalization and Inclusion in K-12 Settings

Abstract/Study Synopsis: 1,000 word Abstract/Study Synopsis due Sept 30, 2025

Introduction: This special series explores the current state of Artificial Intelligence (AI) in special education, highlighting emerging trends, innovative applications, empirical evaluations, reviews and future directions for research. Examining the intersection of AI and special education may contribute to a deeper understanding of how this rapidly evolving technology can be designed and implemented in ways that promote equity, accessibility, and inclusion, and unlock new opportunities for students with disabilities and their teachers to thrive and develop their individual strengths. 

Scope: The integration of AI in K-12 special education has the potential to enhance the way students eligible to receive special education services learn and interact with educational content, and how their teachers leverage AI in their implementation of services. Recent advances in AI are enabling the development of personalized learning systems, intelligent tutoring platforms, and adaptive assessments that cater to individual students' strengths, challenges, and learning characteristics. On one hand, a shift towards AI-driven instruction shows promise in enhancing student outcomes, increasing teacher efficiency, and promoting greater inclusion and accessibility in K-12 settings. Additionally, the evidence gained from AI applications can help inform and shape educational practices and policies specific to AI and special education. On the other hand, research has shown that widely adopted AI tools can produce disparate effects on students based on their prior knowledge, cognitive, and metacognitive skills (Shirah & Sidney, 2023; Shoufan, 2023; Taub & Azevedo, 2019; Vanbecelaere et al., 2021), underscoring the need for thoughtful and equitable design—particularly when developing AI tools for students receiving specialized instruction. 

Types of Manuscripts: Given the current AI landscape, we recommend prioritizing empirical research submissions. To expand the research base and foster a comprehensive and inclusive scholarly dialogue, we invite a variety of research types, including but not limited to descriptive studies, quantitative research, qualitative investigations, mixed-methods approaches, systemic reviews, and registered reports. In addition to research, we invite the submission of commentaries and calls to action that are grounded in the existing empirical evidence base in AI in education, fostering a diverse and inclusive scholarly dialogue at the intersection of AI and special education. We also invite authors to adopt open science practices in their submissions and encourage you to explore RiSE’s special series for more information on open science practices and their application in special education research. After the acceptance of your abstract/study synopses, manuscripts will be peer reviewed and the final decision regarding publication is made by the journal editors. 

Submission Guidelines: Manuscripts should be prepared according to the RiSE author guidelines and submitted to the RiSE submission portal. 

Key Dates: 

1.     Email to s.kiuhara@utah.edu or Chenglu.li@utah.edu your 1,000 word abstract or study synopsis: Sept 30, 2025

2.     Full manuscript: March 2026*

3.     Expected publication: September 2027*

*These dates are estimates. Specific dates for submitting manuscripts and for publication are flexible and will be determined in collaboration with authors based on their timeline. 

Contact: For more information, please contact the special series editors: Shar A. Kiuhara (s.kiuhara@utah.edu) or Chenglu Li (Chenglu.li@utah.edu)