Welcome to How AI is Changing Higher Education & Preliminary Syllabus
This is material related to my teaching about AI. For more, see AI Log teaches.
Welcome to How AI is Changing Higher Education
Hello!
If you receive this note, Pennβs course registration system believes you are registered for How AI is Changing Higher Education
Monday Classes are Weird
This class meets on Monday, so we meet for the FIRST time during the THIRD week of the semester. Classes start on a Tuesday, and then we have Labor Day off. So our first meeting is on Monday, September 8.
That may feel weird, but donβt worry. I have taught on Mondays before, and I like the late start.
Buy the physical books for the class
I have one thing to ask. Please buy a PHYSICAL COPY of the two required books from the Penn Bookstore or another bookseller and bring them to class on the first day.
The books are:
AI Snake Oil: What Artificial Intelligence Can Do, What It Canβt, and How to Tell the Difference by Arvind Narayanan and Sayash Kapoor
More Than Words: How to Think About Writing in the Age of AI by John Warner
Why do you need to get a PHYSICAL COPY of the book, not just use an e-version?
This class is different
The late start is not the only weird thing about this class. Here is a video that explains some of the ideas behind the course structure and what you should expect if you take it. The reason we need physical copies of the book is that we will be reading together in class, marking up passages, and showing them to each other.
In fact, Iβm hoping you will agree to a radical proposal I have about limiting our use of digital technology during class time while having no limits at all on using any technology you want, including AI, outside of class time. Again, watch the video learn more.
Meet with me to say βhiβ before the class starts?
I would like to meet with you before the class first meets to get to know you and answer any questions you have. Use this link <link removed> to schedule time with me to talk about the course How AI is Changing Higher Ed. If you donβt see a time that works for you, email me at erob <email link removed> with some times you are available the week of September 2-7. This is not required, but with the late start, it would be nice to say βhiβ and chat.
You should be able to see some of the weekly schedule and assignments in the Canvas site for the class, and below is a preliminary course syllabus for those who like to read, but I hope youβll watch the video introduction
Note: This preliminary syllabus is meant to give anyone else interested in a the course a sense of what weβll get up to. The Canvas course site had a lot more information, update regularly, about plans for each class meeting, assignment descriptions, deadlines, and guides.
Course Description
This course will explore how generative AI and other forms of artificial intelligence are changing higher education. Topics include ethical questions about AI, how academic writing and publishing are changing in response to AI, and the historical and social contexts for adopting new educational technology. Students will use large language models (LLMs) and other AI tools to prepare for class, assess the educational value of AI tools for higher education, and discuss questions about individual and institutional use of AI.
The class meetings will be organized using a structured, active, in-class learning or SAIL framework, so students will organize and lead many class activities.
Sharing experiences and ideas about using AI will be foundational to the course. Students will use JeepyTA, an LLM-based teaching tool created by the Penn Center for Learning Analytics, to aid their learning and to gain practical experience using a generative AI model. We will approach AI as a technology that has the potential to improve learning, but also ask critical questions about how it can be used to replace educational effort or simply complete assignments..
Norms and expectations for using generative AI tools and other digital technology will be determined collaboratively by the students and instructor during the first week of class and are subject to discussion and revision throughout the semester.
Course Objectives
Expand your understanding of how generative AI models work and how they are currently used in higher education.
Use cultural, historical, and social analysis to understand how generative and other forms of AI are changing educational and administrative practices in colleges and universities.
Explore ethical and political dimensions of AI-related change in academic integrity, scholarly publishing, instructional technology, and educational assessment.
Improve your writing and communication skills by completing short writing assignments, presenting individually and in groups during class meetings, and participating in peer-review evaluations of classmates' writing and presentations.
Consider how generative AI has shaped and will continue to shape your experience as a student.
Course Format
The course will meet in person on a weekly basis. Students will be responsible for preparing for class meetings on their own schedule, but group meetings outside class may be necessary to complete some assignments. Each week, students will watch pre-recorded lectures, read assigned pages from the books, and prepare for class activities and discussion.
Core Texts
AI Snake Oil by Arvind Narayanan and Sayash Kapoor provides a historical account of the development of AI technologies and a critical analysis of how technology companies rely on hype and fraud to market AI products. The authors offer an array of videos and learning aids with the book, making it an ideal foundation for class activities, especially those organized by students.
More Than Words: How to Think About Writing in the Age of AI by John Warner continues the authorβs argument in βChatGPT Canβt Kill Anything Worth Saving,β published just after the AI chatbot debuted in November of 2022. For Warner, the fact that generative AI can now produce text indistinguishable from text written by humans is a reason to abandon formulaic writing pedagogy.
Course Assignments and Grading
Active learning means students take responsibility for the class through activities such as group presentations and group writing exercises aimed at exploring ethical and social questions. The class will culminate in a student-led workshop.
Collaborative engagement with the ideas of your classmates and the course materials is fundamental to success in the class and will be the basis for grading. Individual and group presentations, participation in class activities, and providing constructive feedback on classmates' work are required class activities.
Missing more than one or two class meetings may make it challenging to receive an A. Missing more than three classes will make it difficult to complete the class successfully.
Grading will be based on the successful completion of required activities as tracked by the instructor in Canvas, and each studentβs self-assessment of how well they met the course objectives as reviewed by the instructor. Half the grade is based on completing six short essays, and half the grade is based on making meaningful contributions toward a student-led workshop in December.
Accommodations for students with disabilities
The University of Pennsylvania provides reasonable accommodations to students with disabilities who have self-identified and been approved by Student Disabilities Services (SDS). If you have not yet contacted SDS and would like to request accommodations or have questions, you can make an appointment by calling SDS at 215-573-9235. The office is in the Weingarten Learning Resources Center at Stouffer Commons 3702 Spruce Street, Suite 300. All services are confidential.
Academic Integrity
This course requires honesty, responsibility, and doing your own work. All students should read and understand the Code of Academic Integrity. Taking ideas or words from others is plagiarism and will result in a referral to the Office of Community Standards. Academic integrity questions about the use of AI tools will be discussed throughout the course. Norms and expectations for using generative AI tools will be determined collaboratively by the students and instructor during the first week of class and are subject to discussion and revision throughout the semester.
Class Attendance
Students are expected to attend all class meetings. Please contact the instructor if you need to miss class or are having challenges attending.
Contacting the Instructor
The best way to contact the instructor for routine matters is through the courseβs Canvas site or by email.
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