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.
Did you know that Denison offers access to LinkedIn Learning? Encourage your students to explore thousands of engaging video courses covering technology, creativity, business, and beyond! It’s a great way to enhance classroom learning, support your course objectives, and empower students to build valuable skills.
Lately, I’ve been saying that keeping up with AI feels a bit like being stuck on a treadmill that only speeds up. Just when I think I’m catching my breath, something new barrels in. In the past few weeks alone, I’ve heard about “vibecoding”—the emerging ability to speak complex code into existence like some kind of techno-conjuring spell—and OpenAI’s latest image tools, which have taken deepfakes from disconcerting to downright uncanny. |
 |
||
|
 |
||
|
In a CfLT-sponsored webinar on assessment and gen-AI on March 3, Leon Furze (longtime educator, education administrator, and now Ph.D. candidate working on a dissertation on AI in writing instruction) shared an academic article, “Validity Matters More than Cheating,” which argues that academic integrity needs to focus on “assessment validity” rather than “cheating.” Cheating is a question of moral integrity, whereas validity is a process by which educators ensure that students have met learning outcomes.
 |
| We’re at that critical midpoint, and it’s all too easy to coast (or crash) until finals. But midterm is our golden chance to step back and see if we’re still on the path we laid out at the start. A few small tweaks now can save us—and our students—a heap of stress when crunch time rolls around. |
I’ve been in education long enough to recognize this as a familiar faculty lament. Over the years, I’ve heard numerous concerns:
You see the pattern. It seems that the longer we teach, the more likely we are to encounter this sentiment.
 |
||
|
Despite Sydney Green’s proficiency with AI prompting, she often finds extracting specific tasks from advanced models like ChatGPT or Gemini to be time-consuming and sometimes unproductive. To address this, she turned to Magic School AI, a platform offering over 80 AI-powered tools designed to assist educators with lesson planning, assignment creation, and material generation. It’s user-friendly, click-based interface allows users to interact without the need for specialized prompts.
My approach to AI in my writing courses is primarily to teach students how to make informed decisions about when it is appropriate and inappropriate to use AI. Part of this involves helping them understand what they do and don’t learn when they use AI. To that end, I include an AI policy statement on every assignment as well as a table that identifies what students learn if they use AI for some tasks vs.
