<![CDATA[This research was conducted to produce a diagnostic assessment instrument using an EWS (Early Warning System) approach that is able to detect early learning problems in students accurately and comprehensively and to assess their impact on the academic performance of elementary school students. The research method used is research and development (R&D) using the ADDIE (Analysis, Design, Development, Implementation, Evaluation) model. The research subjects were fifth-grade students in three elementary schools in Bima City. Data were collected using cognitive and non-cognitive diagnostic assessment instruments based on an EWS approach as well as student academic performance assessment instruments. Research data analysis was carried out by testing the validity of the diagnostic assessment model using descriptive statistics and multiple regression tests to determine the effect of the assessment model with the help of Jamovi software. The results of the validity test showed that the EWS-based diagnostic assessment model was found to be very feasible based on the analysis by two validators (learning evaluation experts and elementary education experts) with the characteristics of the assessment model, namely comprehensive, preventive, and solution-oriented. The implementation of this assessment facilitates teachers in making informed decisions regarding learning strategies and specific interventions needed by students based on the results of cognitive and non-cognitive diagnoses. Statistical test results showed a significance value (p-value) <0.001, indicating a significant effect of the EWS-based diagnostic assessment model on student academic performance, with an effect size (R2) of 63.7% of the variation in student academic performance scores.]]>
