Page 36 - CKA E- YEARBOOK 2024 NEW

The Profound Impact of Generative AI on Education (Cont’d)

The Role of Generative AI in Assessing Student Performance
Generative AI brings a new dimension to evaluating student achievements by leveraging its
capacity for comprehensive data analysis. This advanced technology goes beyond traditional
grading methods by interpreting intricate patterns of student interactions and outputs,
offering a nuanced view of learner competencies and areas for improvement. It automates the

generation of personalized assessments that challenge students appropriately based on their
unique learning curves, facilitating a more precise measurement of their progress over time.
Additionally, generative AI contributes to a holistic view of educational development,
identifying not only academic strengths but also soft skills like problem-solving and critical
thinking.

Challenges and Ethical Considerations of Generative AI in Education
The integration of generative AI into educational systems presents a complex array of
challenges and ethical dilemmas. Key among these concerns is the safeguarding of student
data. As this technology relies on extensive datasets to personalize learning experiences, the
risk of breaches and unauthorized access to sensitive information looms large. Moreover, the
inherent biases present in AI algorithms pose a significant challenge. If not carefully managed,
these biases could perpetuate inequality, providing skewed learning experiences that favor

certain demographics over others. There is also the issue of dependency, where an over-
reliance on AI-driven educational tools could diminish critical thinking and problem-solving
skills in students. Additionally, the potential for generative AI to generate misleading or
inaccurate information raises questions about content credibility and critical evaluation skills'
importance. To navigate these challenges, educators, developers, and policymakers must
collaborate closely to create robust frameworks that prioritize ethical considerations,
transparency, and accountability in the use of generative AI. This includes developing

standards for data protection, ensuring the diversity of training datasets to minimize bias, and
fostering an educational environment that balances technological innovation with the
development of essential human skills. Addressing these issues head-on is crucial to unlocking
the transformative potential of generative AI in education while safeguarding against its
potential pitfalls.

Conclusion
Generative AI is poised to revolutionize education by

enhancing learning experiences, supporting teachers,
and making education more personalized and accessible.

However, its implementation must be carefully managed
to address ethical concerns and ensure equitable
benefits for all learners.

By Mr. Adeyemi Okusanya Educator