Empowering Multigrade Interdisciplinary Assessment through Plithogenic Offsets and Artificial Intelligence for Dynamic and Personalized Education

Abstract

This contribution addresses the issue of interdisciplinary assessment in multigrade classrooms: the diverse levels and the assessment path's unclear direction fail to render efficient learning. How can assessment be refined to avoid such discrepancies and establish a better path of equalized and contextualized learning? It's a pressing question for 21st-century learning—more so in rural areas where interdisciplinary attempts can create holistic and connected learning for the learners—but the literature fails to guide systematically, apart from rendering systematic solutions that rely only on tacit, non-explicit, technical interventions. Therefore this research contributes a systematic intervention that combines a Plithogenic Offset—neutrosophic attempts to neutralize the uncertainty of responses—with AI effort rendered that the AI's involvement is simplistic without programming—to assess endeavors that are dynamically responsive to need and culture. The open-ended responses suggest that such alignment increases motivation and engagement and interdisciplinary cooperation, improving formative assessment. Thus, the research presents a systematized contribution to the body of knowledge that expands education from practically from AI and neutrosophic integration for dynamic assessment of what's possible within educated, accessible resources for those educators able and positioned to provide consistent feedback integrated with reality on the ground.