Investigating the Strategies to Mitigate the Influence of AI Tools on Blackboard Evaluations

This study investigates strategies to mitigate the influence of AI tools on Blackboard evaluations. The hypothesis suggests that extensive use of AI in evaluations raises concerns about academic dishonesty and assessment reliability. Students may exploit AI to create answers, undermining the validity of their work. Furthermore, depending too much on AI for feedback and grading can generate biases and inaccuracies, reducing assessment reliability. The aim of the study is to provide practical ways for addressing these difficulties and ensuring that AI technologies improve, rather than subtract from, the educational experience. The researcher used a questionnaire to gather perspectives from students and English language instructors on the influence of AI tools on Blackboard evaluations. Key strategies include implementing advanced monitoring systems to detect and prevent academic dishonesty, combining AI tools with human oversight to balance feedback and grading, providing students with clear ethical guidelines for AI use, and updating AI algorithms on a regular basis to reduce biases and improve accuracy. Adopting these strategies allows educational institutions to benefit from AI tools in Blackboard evaluations while maintaining the integrity and reliability of assessments, leading to a more equitable and effective learning environment.