Explore leading generative AI policies for higher education.

This resource is about page on a three part online program that teaches K-12 and higher-education educators on how they can use artificial intelligence to enhance their learning environments. This program aims to deepen educators' knowledge on artificial intelligence through four workshops, and then implement activities that utilize artificial intelligence with their students.

The use of generative AI technologies in student assessments requires thoughtful support and limitations to ensure responsible use, transparency, and adherence to academic integrity policies. Assessment tasks should be carefully designed or modified to align with the responsible use of AI, considering alternatives, open or collaborative processes, and higher-order thinking to effectively measure student learning. Additionally, the detection of AI-generated content raises privacy and equity concerns, and blocking or invigilation measures may not always be suitable, emphasizing the need for clear communication and continuous adaptation in the evolving landscape of AI and education.

This document talks about all the tools that AI gives us and how we should use them correctly so it will not cause you harm. It includes a very important topic that is communication. AI can improve communication through wireless by implementing learning algorithms to the wireless spectrum.

This document provides recommendations for instructors at the University of Oregon in regards to the use of Generative AI in education. This document states that faculty have flexibility for how they want to limit or enable the use of Generative AI. It also states that faculty should be transparent with their students about their policies. This document provides sample course policies and specific ways instructors can structure assignments to encourage the use of Generative AI.

To promote academic integrity and student learning, educators can implement strategies that align with the Honor Code. These strategies include clarifying Honor Code expectations, using frequent and low-stakes assessments, emphasizing assessments as learning opportunities, allowing exam or assignment resubmissions, and encouraging intrinsic motivation for learning. Additionally, considering alternative assessment methods, ensuring question clarity, and addressing potential cheating risks in remote exams are vital considerations for educators.

The article talks about the integration of AI tools in education, highlighting both the opportunities and challenges they present. Educators emphasize the potential of AI to forge content while also stressing the importance of digital and information literacy in the AI era.

This resource provides external links to online learning programs, videos, website about pages, and speaker events that all relate to generative AI training. Many of these links teach how to incorporate generative AI, like ChatGPT, in the classroom responsibly. This resource describes generative AI as an opportunity for learning innovation.

Academic dishonesty can be attributed to various factors, including peer pressure, performance anxiety, excuse-making, inability to manage the demands of student life, situations that encourage dishonesty, self-justification habits, unfamiliarity with academic dishonesty definitions, and a lack of understanding about consequences. Peer pressure, where students may pressure their peers to engage in dishonest practices, is one common cause. Some students may resort to cheating due to performance anxiety, inability to manage their academic workload, or a belief that unclear course policies and minimal penalties make cheating worthwhile. However, many students resist academic dishonesty due to moral values, a genuine interest in learning, fear of repercussions, respect for instructors and peers, effective time management, and religious beliefs.