Rethinking Neurotechnology in Education: Assessing the Role of Multimodal Learning Analytics in Supporting Gifted and Special Needs Learners in K–12 Classrooms

As educational technologies evolve, interest in their potential to improve outcomes and data-driven tools for supporting diverse learners continues to grow. While neurotechnology has been explored in K–12 settings for its potential to enhance cognitive function, ethical and practical barriers have accelerated interest in less invasive alternatives. This paper examines Multimodal Learning Analytics (MMLA) as an ethically grounded alternative for understanding and supporting gifted and special needs learners in K–12 classrooms. Through a systematic review of literature and case studies, we identify a critical gap: existing MMLA systems are predominantly designed for normative learner profiles, risking misinterpretation of behavioral and emotional signals in exceptional learners. In response, we propose the DICE framework; four design principles (Differentiated, Inclusive, Contextual, Ethical), a set of design principles for adapting Multimodal LA systems to gifted and SEN learners in K–12 contexts; to guide the adaptation of MMLA systems for gifted and SEN populations. Findings highlight implications for inclusive system design, ethical data governance, and educator professional development, contributing to more equitable EdTech deployment in diverse and under-resourced school contexts.