Abstract:
In the contemporary landscape of education, the nexus of mathematics instruction and artificial intelligence (AI) offers a dynamic sphere of exploration. As technology increasingly influences education and society, it's crucial to scrutinize the role of assessment in mathematics education within the context of AI. This systematic review aims to explore assessment practices, revealing the diverse threats and opportunities arising from the intersection. This study utilized a systematic literature review method to synthesize existing literature concerning the threats and opportunities inherent in the assessment of mathematics education within the domain of Artificial Intelligence (AI). Results showed three (3) emerging threats, such as (1) Algorithmic Injustices and Equitable Results; (2) Standardization and Overemphasis on Procedural Knowledge; and (3) Data Security and Privacy Issues in Assessment. Another three (3) themes for emerging opportunities; namely: (1) Customized Learning and Flexible Assessments; (2) Real-Time Feedback and Formative Assessment Practices; and (3 Data-Driven Decision-Making and Educational Insights. It is recommended that mathematics educators and other concerned stakeholders may prioritize efforts to mitigate algorithmic biases, promote fairness, safeguard student privacy, and develop guidelines for responsible AI use in assessment. Investing in educator training is crucial to leverage AI effectively and ethically, fostering a culture of collaboration and innovation to enhance assessment practices and ensure equitable access to high-quality mathematics education.
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