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I recently had a birthday. Maybe I am getting wistful, but this Inside Higher Ed article by Kenneth McNay had some solid advice for those of us who have been here a while. In particular, it made me think about how I can explore innovation and risk-taking, that I should try to facilitate knowledge sharing, and finally, to redefine my research productivity metrics to encourage me to explore those high-risk, innovative areas. |
Teaching, Tech, and Tidbits Digest
The posts below are from a bi-weekly digest that encapsulates a range of evidence-based best practices and cutting-edge insights on innovative teaching strategies, effective use of technology, student engagement techniques, and effective assessment, to name a few. The content, diligently curated or crafted by the director Dr. Lew Ludwig, is grounded in robust research and drawn from a wide array of innovative articles, books, and online resources. The goal is to support timely, ongoing faculty development with the most current and impactful knowledge in the field.
Teaching and AI: Why Professors are Polarized on AI
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| It is safe to say I have tumbled way down the AI rabbit hole. Since January, I have developed and led 15 workshops locally, regionally, and nationally. However, I still don’t know where our faculty at Denison stands concerning AI.
To be clear, the CfLT and ETS have run a series of workshops around AI. The attendees were very engaged but few in number. |
Teaching: How to Motivate and Engage the Whole Class
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Teaching: From the teaching archive- Midterm Course Evaluations
As we near the halfway mark, consider getting mid-semester feedback from your students. Mid-semester evaluations:
- If necessary, provide a chance to correct student misconceptions or make changes to the course schedule, activities, etc.
- Allow students to reflect on their expectations, efforts, and learning.
- Let students know you care about their input.
Here are some sample mid-semester evaluations you can use or adapt for your course:
- This check-off format from Seattle University makes it easy for your students to provide specific feedback and some open-ended questions.
Tech: A picture tells a thousand words- unique images for your course
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Tidbit: But What if You Can’t Quit Your ‘Dead-End Job’?
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In my role as director, I subscribe to a large number of newsletters, listservs, and blogs. So, my inbox sees a lot of traffic. One article titled But What if You Can’t Quit Your ‘Dead-End Job’? recently stood out. It brought to mind a note I received from a senior colleague soon after I secured tenure back in 2007. |
Tidbit: A note from Megan Threlkeld on AI in her W101
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Like many of us, I spent a lot of time over the summer reading and thinking about generative AI chatbots and what they might mean for my teaching, especially since most of my courses involve a lot of writing. Could ChatGPT answer my prompts? Did my assignments encourage students to put in thought and effort, or was I making it easy for them to farm out their work to a bot? |
Tech: Utilizing the Canvas Calendar
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| Students gave us positive feedback on the Canvas calendar last spring! As an instructor, you are able to add events that will appear on your students’ calendars and “to do” lists. This is a great way to communicate and remind students of important events and deadlines! These guides will quickly walk you through adding an event and adding an assignment on your course calendars. |
Teaching: Do my learning outcomes meet the needs of my students these days?
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This question, posed during a recent session on AI and assessment, really resonated with me. The rising attention (or, should we say, hysteria?) surrounding AI has prompted me to reflect on what I expect my students to learn and how I choose to assess that learning. While I’m still grappling with a definitive answer, two insightful articles this week prodded me to reconsider my teaching approach as we enter this new era of AI. |
Tidbit- To understand AI, you need to engage with AI
I recently facilitated an AI-focused session for the GLCA (resources, including the recording, can be found here). Out of nearly 300 registrants, about 60% reported being very familiar or somewhat familiar when asked to rate their knowledge of generative AI based on exposure through reading, podcasts, webinars, etc. Interestingly, 63% of registrants reported no experience or limited experience using generative AI such as ChatGPT, Bing, or Bard.