Remove Fairness Remove Learning Disabilities Remove Learning Outcomes
article thumbnail

Five Tips for Writing Academic Integrity Statements in the Age of AI 

Faculty Focus

In a meta-analysis on the use of AI chatbots in education, Wu and Yu (2023) found that AI chatbots can significantly improve learning outcomes, specifically in the areas of learning performance, motivation, self-efficacy, interest, and perceived value of learning. This is not fair” (Syed, 2023). & Yu, Z.

article thumbnail

Five Tips for Writing Academic Integrity Statements in the Age of AI 

Faculty Focus

In a meta-analysis on the use of AI chatbots in education, Wu and Yu (2023) found that AI chatbots can significantly improve learning outcomes, specifically in the areas of learning performance, motivation, self-efficacy, interest, and perceived value of learning. This is not fair” (Syed, 2023). & Yu, Z.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Bridging the Gap: Overcoming Barriers in Higher Ed for Students with Disabilities including Neurodivergent Learners

Faculty Focus

of Australian undergraduate students reported having a learning disability. iii] [iv] ; furthermore, 19% of US undergraduate students reported having a disability, and of these, 35% reported a learning disability [v] for 2016 (the most current data we could find). For instance, in 2019, 6.2%

article thumbnail

Bridging the Gap: Overcoming Barriers in Higher Ed for Students with Disabilities including Neurodivergent Learners

Faculty Focus

of Australian undergraduate students reported having a learning disability. iii] [iv] ; furthermore, 19% of US undergraduate students reported having a disability, and of these, 35% reported a learning disability [v] for 2016 (the most current data we could find). For instance, in 2019, 6.2%

article thumbnail

AI in Education

eSchool News

AI also plays a role in the early identification of learning disabilities and special needs. AI systems rely on vast datasets, and if these datasets are biased or incomplete, the algorithms can reinforce existing disparities in educational outcomes. This raises concerns about fairness and equity in the learning process.

Ethics 130