<b>EXPLORING THE IMPACT OF GENERATIVE AI ON ASSESSMENT AS LEARNING (AaL), ASSESSMENT OF LEARNING (AoL), AND ASSESSMENT FOR LEARNING (AfL) IN HIGH SCHOOL</b>

<b>Abstract</b>This research explores the transformative potential of generative Artificial Intelligence (AI) in high school educational assessments, focusing on three key paradigms: Assessment as Learning (AaL), Assessment of Learning (AoL), and Assessment for Learning (AfL). Through applied research questions, this study examines how AI influences self-assessment and metacognitive processes, enhances the reliability and fairness of summative assessments, and contributes to feedback mechanisms in formative assessments. Data collection involves self-assessment questionnaires, reflective journals, standardised tests, and surveys conducted in a high school setting. Findings indicate that AI significantly improves personalised feedback, fostering greater student autonomy and reflective thinking. Moreover, AI enhances the consistency and fairness of summative assessments by reducing human biases. Real-time feedback provided by AI in formative assessments accelerates learning processes, increasing student engagement and understanding. However, the integration of AI raises ethical concerns, including data privacy and algorithmic transparency, necessitating careful implementation and ongoing research. This study provides empirical evidence supporting the use of AI in educational assessments, informing policy decisions and educational practices to ensure AI enhances student learning experiences and outcomes while addressing ethical and practical challenges.<b>Keywords:</b> Generative AI, Assessment as Learning (AaL), Assessment of Learning (AoL), Assessment for Learning (AfL), Real-Time Feedback.<br>