Article’s

Reimagining Educational Assessment through Human–AI Collaborative Intelligence

Ritu Singh

(07 – 2026)

DOI: 10.5281/zenodo.21272788

 

Abstract The evolving educational landscape demands assessment systems that transcend traditional measures of academic achievement and actively contribute to improving learning outcomes. Despite sustained curriculum reforms, a significant proportion of learners continue to progress through school without mastering foundational competencies, resulting in cumulative learning deficits that impede higher-order thinking and problem-solving abilities. Diagnostic assessment, integrated with systematic remediation, offers a learner-centred approach that identifies individual learning gaps and enables targeted instructional interventions. This paper examines the conceptual underpinnings, design, implementation, and educational implications of a comprehensive diagnostic assessment framework developed through collaborative efforts involving curriculum experts, psychometricians, technology specialists, and educators. Drawing upon implementation experiences and contemporary educational research, the paper discusses how diagnostic assessment supports competency-based education, aligns with the vision of India’s National Education Policy (NEP) 2020, and contributes to preparing learners for the demands of the twenty-first century. The paper also analyses implementation challenges, including teacher readiness, educational change management, and post-pandemic learning recovery, while proposing future directions for data-informed personalized learning. Keywords: Diagnostic assessment, remediation, competency-based education, psychometrics, formative assessment, NEP 2020, future-ready learners.

 

 

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