AI in Teaching Symposium - Friday May 31 at 1PM
12/04/24 11:24
The DePaul AI Institute and the DePaul Center for Teaching and Learning are embarking on a series of signature events and collaborative resources that strategically and pragmatically integrate artificial intelligence into academic activities that promote student learning and enhance critical thinking skills.
The AI in Teaching Symposiums are opportunities for DePaul faculty and staff to share and see how their colleagues have successfully utilized an AI activity or assignment into their teaching. Quick, simple, direct demonstrations that can be easily adopted in other courses at the university.
We are soliciting proposals from interested faculty members who would like to develop a brief presentation (along with accompanying resources) and present to the university community at the first AI in Teaching Symposium on Friday May 31 at 1PM. For the first Symposium, up to 4 faculty members will be selected to present. Other proposals will be considered for future Symposia in the next academic year.
Here are the guidelines for the presentations:
Presenters will be awarded a $500 honorarium.
The Symposium will be offered in a Flex format. The sessions will be recorded, but the recording will be only shared with DePaul faculty and staff in a password protected streamed format.
If you are interested in submitting a proposal, please complete and submit the Qualtrics survey by April 26.
You can register to attend the Symposium here.
The AI in Teaching Symposiums are opportunities for DePaul faculty and staff to share and see how their colleagues have successfully utilized an AI activity or assignment into their teaching. Quick, simple, direct demonstrations that can be easily adopted in other courses at the university.
We are soliciting proposals from interested faculty members who would like to develop a brief presentation (along with accompanying resources) and present to the university community at the first AI in Teaching Symposium on Friday May 31 at 1PM. For the first Symposium, up to 4 faculty members will be selected to present. Other proposals will be considered for future Symposia in the next academic year.
Here are the guidelines for the presentations:
- No more than ten minutes to present an AI assignment, practice, or concept that can be implemented in other courses taught at DePaul.
- No more than five minutes for Q&A.
- Written resources (overview, recommendations, links, etc.) must accompany each presentation. These will be shared on the web.
- Presenting faculty will attend the symposium at the DePaul Center to engage in a discussion and Q&A.
Presenters will be awarded a $500 honorarium.
The Symposium will be offered in a Flex format. The sessions will be recorded, but the recording will be only shared with DePaul faculty and staff in a password protected streamed format.
If you are interested in submitting a proposal, please complete and submit the Qualtrics survey by April 26.
You can register to attend the Symposium here.
Tech Tuesdays: Microsoft Copilot
08/03/24 16:22
When it comes to Large Language Models (LLMs), there is a bewildering myriad of models to choose from. What are the best models for DePaul faculty, students, and staff to use in work and research?
In this engaging and productive session, we will focus on “Microsoft Copilot.” Copilot is the term that Microsoft uses for its AI tools and services. This can be a little confusing, given the various Microsoft products using similar names (Microsoft Copilot, Copilot for Microsoft 365, Github Copilot, Copilot for Sales, etc.). Microsoft Copilot is a free service that provides access to GPT 4 and DALL-E 3.
Microsoft Copilot, when used with DePaul credentials, provides you with important protections and safeguards that you may not find when using other free generative AI services, including:
- Chat data is not saved.
- Chat data is not used to train AI models.
- Citations accompany generated textual content.
Topics covered:
- Ethics.
- Conversational styles (Creative, Balanced, Precise).
- GPT 4 access.
- Generative imagery (DALL-E 3).
- Data protection.
- Differences and similarities between Github Copilot, Microsoft Copilot, Copilot for Microsoft 365.
- Document summarization and analysis.
- Prompt engineering techniques.
- Suggested classroom use.
- Hallucinations.
- Context windows and character limits.
- Future developments.
- Competing LLMs for consideration.
- And more…
This will be a Flex session. You are welcome to attend in person or virtually via Zoom. The session will be recorded (streamed recording available upon request).
- Date: Tuesday April 30.
- Time: 12-00 - 1:00 PM.
- Location: Flex - Zoom or Lewis 1002 (10th floor of the Lewis Center - connected to the DPC 8th floor via the skybridge).
DePaul faculty and staff can register here.
4th Annual Marketing Tricks And Treats Event
18/10/23 11:31
The 4th Annual Marketing Tricks And Treats Event will be in DPC 7500 on Wednesday October 26 from 3:00 - 5:00 p.m.
AI Syllabus Statement
21/06/23 11:26
Here is the AI Syllabus Statement I am currently using in my courses. This may change, but thirds what works for me at the moment:
Work done for this course must adhere to the University Academic Integrity Policy, which you can review in the Student Handbook or by visiting Academic Integrity at DePaul University.
However, this is a course in which you are allowed to use generative AI (Artificial Intelligence) in your assignments – in some assignments I will require that you use generative AI. Please note that other courses at DePaul may not allow use of generative AI – always ask your professor in writing if you are unsure of what the academic integrity policies are for your course.
In this course we will demonstrate that generative AI will confidently fabricate information. This process is known as “AI hallucinating.” Be aware that AI-generated content may contain untruths. Large Language Models (LLMs) respond and write like humans, but importantly they do not know empirically what is false or true - just a plausible narrative written probabilistically. Crucially, a LLM may not understand the difference between an important error and an unimportant error.
Thus, I would like you to cite your use of generative AI when you submit your assignments. You can do this by creating an appendix and noting the prompts that you used with a particular LLM and the responses your received.
The process of citing generative AI is evolving. Please look at these three sources for guidance:
Work done for this course must adhere to the University Academic Integrity Policy, which you can review in the Student Handbook or by visiting Academic Integrity at DePaul University.
However, this is a course in which you are allowed to use generative AI (Artificial Intelligence) in your assignments – in some assignments I will require that you use generative AI. Please note that other courses at DePaul may not allow use of generative AI – always ask your professor in writing if you are unsure of what the academic integrity policies are for your course.
In this course we will demonstrate that generative AI will confidently fabricate information. This process is known as “AI hallucinating.” Be aware that AI-generated content may contain untruths. Large Language Models (LLMs) respond and write like humans, but importantly they do not know empirically what is false or true - just a plausible narrative written probabilistically. Crucially, a LLM may not understand the difference between an important error and an unimportant error.
Thus, I would like you to cite your use of generative AI when you submit your assignments. You can do this by creating an appendix and noting the prompts that you used with a particular LLM and the responses your received.
The process of citing generative AI is evolving. Please look at these three sources for guidance: