Creating a Feedback Loop with Students

When I first started teaching online back in 2017, the course evaluation process bothered me. Initially, I was excited to get feedback from my students about their learning experience. Then I saw the survey questions. Even though there were about 15 of them, none actually helped me improve the course. They were all extremely generic and left me scratching my head, unsure of what to do with the information. It’s not like I could ask follow-up questions or suggest improvements to the survey itself. Understandably, the institution used these evaluations for its own data points, and there wasn’t much chance of me influencing that process. So, I decided to take a different approach. What if I created my own informal course evaluations that were completely optional? In this survey, I could ask course-specific and teaching-style questions to figure out how to improve the course before the next run started. After several revisions, I came up with these questions: - Overall course rating (1–5 stars) - What was your favorite part (if any) of this course? - What did you find the least helpful (if any) during this course? - Please rate the relevancy of the learning materials (readings and videos) to your academic journey, career, or instructional design journey. (1 = not relevant at all, 10 = extremely relevant) - Please rate the relevancy of the learning activities and assessments to your academic journey, career, or instructional design journey. (1 = not relevant at all, 10 = extremely relevant) - Did you find my teaching style and feedback helpful for your assignments? - What suggestions do you have for improving the course (if any)? - Are there any other comments you'd like to share with me? I was—and still am—pleasantly surprised at how many students complete both the optional course survey and the official one. If you're looking for more meaningful feedback about your courses, I recommend giving this a try! This process has really helped me improve my learning experiences over time.

One of the ways I'm incorporating #AI in the feedback loop for students in my writing class is to use it as a guide for talking points when they go to the language lab for support. I told students I would be using Brisk Teaching for round 1 (maintaining transparency about when I'm using AI and hopefully leading by example), where it creates feedback points based on my rubric and inserts them in a table at the top of their essay. Using Google Docs, I converted the bullet points to checkboxes (though it would be nice if Brisk did this part automatically), so students can go through point by point and show me that they're at the very least looking at the feedback before the next round of writing. Next, I asked students to highlight one point from each category and use the comment feature to speak to it. This could be any variation of responses: 🔦 Spotlighting an issue that they know they need to work on and how they're dealing with it in this paper 🙅♀️ Disagreeing with the AI and explaining why they don't want to make the change it's suggesting ❓ Asking for clarification on how to respond to a point ➕ Etc. Next, when they go to the lab to get help, these highlights and the changes they made will form the foundation for the talking points when they work with the professor. One of the biggest problems when students go to a lab for support is always training them to be prepared instead of going in and saying "please check my paper" rather than empowered with a specific learning goal in mind. So the goal here is to have them go in with 5 already acted upon (or at least considered) points to discuss in order to make a more productive lab time. The screenshot is a sample that I sent to my students to understand the concept. I'm sure there will be some fine-tuning, but already many of them are interacting more with their early drafts and even coming to me to make sure that they're building good responses to talk to the professor in the lab about. I'll need more exploration, but to me this is a good way to take advantage of the strengths of AI, continue to challenge students to think critically about what it generates, and wrap it all in a human-centered approach focused on student learning rather than just using a shiny toy for the sake of it. #AIinESL #ArtificialIntelligence #TESOL #TESL #TESOL #ELT #LanguageLearning #Composition #StudentSuccess

Feedback is a loop, but we often keep it open-ended. Closing the loop is more than a simple "thank you for giving me the feedback." That's merely a dead end. Feedback isn't an event, it should be an ongoing partnership for growth. How do you make that happen? By applying feedback and following up with this three step process: Step 1: Change the way you ask for feedback. Instead of simply asking "what feedback do you have," get more specific in what you're asking for up front, so you can focus the other person's attention to what you need (e.g. I'd really like your feedback on the overall flow of that presentation and what made it easy or difficult to absorb). Then look for the one thing you can take and apply. This approach makes it easier to get valuable, actionable feedback, even if there are elements you disagree with. Step 2: Proactively set a date to action on the feedback and even follow up. When can you implement a first step? How will you re-connect to provide an update? Discuss that plan with the other person. Step 3: When that date hits, share the following: "Because of your feedback, I did x, and this is what I've observed as a result. What have you noticed?" We leave conversations unfinished and open-ended every single day, like strands of string dangling everywhere. It's time to start creating loops - professionally and personally. #ignitedbyjordana #feedback #leadership #communication #closetheloop

Too often, offering students feedback is an exercise in compliance. The professor offers feedback, and expects the students to incorporate all of it. (It’s like the professor is giving items on a checklist. The subtext: “do these things and I’ll give you an A.”) But I want my students to think about feedback differently. I want them to be able to cut between different sets of feedback, connecting them to each other and linking them back to their own understanding. With that in mind… Here’s the feedback cycle I’ve designed for my Comp II students at Berkeley. 1️⃣ Self-Assessment Students use their own self-designed rubric to evaluate their own performance. 2️⃣ Peer Assessment Students get feedback and assessment from other students. 3️⃣ Instructor Assessment I’ll offer feedback on the assignment. 4️⃣ AI Assessment Students get feedback from a custom chatbot. I will be incorporating some of Anna Mills’s prompts for the PAIRR framework. 5️⃣ Assessment Assessment (or Reflection) Students apply the different assessments to their own self-assessment. They defend their ultimate edits within the context of their Self-Empowering Writing Process (SEWP).