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Concerns: Assessment & AI

While there are many potential benefits of using artificial intelligence (AI) in student learning assessment in higher education, there are also some concerns that need to be addressed.

One of the key concerns is the potential for AI-powered tools to perpetuate bias and discrimination.

One of the major concerns with using AI in student learning assessment is the potential for these tools to be biased against certain groups of students. For example, AI algorithms may be more likely to provide negative feedback to students from underrepresented groups, such as students of color or students


from low-income backgrounds. This could lead to these students being unfairly penalized or disadvantaged in their studies.


Another concern with using AI in student learning assessment is the potential for these tools to replace human educators. While AI-powered tools can provide valuable feedback and guidance to students, there is a danger that they could be used to replace human educators altogether. This could lead to a less personal and less effective learning experience for students, as well as potentially threaten the jobs of educators.


Additionally, there is a concern that the use of AI in student learning assessment could lead to a more standardized and less personalized learning experience. With the help of AI-powered tools, educators may be tempted to rely more heavily on standardized assessments and less on individualized feedback and guidance. This could lead to a less engaging and less effective learning experience for students.


While there are many potential benefits of using AI in student learning assessment in higher education, there are also some concerns that need to be addressed. It is important for educators and policymakers to carefully consider these concerns and take steps to mitigate any potential risks associated with the use of AI in student learning assessment. This could include implementing safeguards to prevent bias and discrimination, ensuring that AI-powered tools are used in a way that complements, rather than replaces, human educators, and focusing on personalized learning experiences that engage and motivate students.

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