AI Driven Personalized Learning: Enhancing College Education Online with TransparencyEthics

-Powered Personalized Learning Journeys: Revolutionizing Information Management for College Students in Online Platforms

Ming Yang and Fuyuan Weng

Since college students increasingly rely on online education, is transforming virtual learning paths. This study highlights how educational institutions are leveragingalgorithms and data analytics to personalize instruction and boost student engagement, comprehension, and retention.

The article outlines key features ofpowered personalized learning for college students:

1. Content Recommations:adapts the curriculum based on individual student preferences, past academic performance, and learning pace.

2. Customizable Evaluations: It provides tlored feedback mechanisms that align with each student's understanding level.

3. Real-time Feedback: Immediate guidance helps learners correct mistakes promptly.

Despite these potential benefits, the study critiques the ethical and transparency challenges associated within education:

1. Bias and Prejudice Issues:algorithms may inadvertently perpetuate biases present in historical data or flawed programming logic, affecting student outcomes.

2. Lack of Transparency: The decision-making processes behindrecommations can be opaque, limiting students' ability to understand and challenge them.

To address these issues, the article recomms:

1. Regular Audits and Updates: Regularly reviewingalgorithms for bias is crucial to ensure frness in education.

2. Enhanced Explnability: Improving transparency through tools that expln howrecommations are made will empower students.

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has the potential to significantly enhance educational experiences by providing personalized learning paths tlored to each student's needs and abilities. However, it must be deployed responsibly with a focus on ethical considerations, particularly addressing bias and enhancing transparency to build trust between learners and technology.

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