Providing Developmental Feedback | Origin: ED163
This is a general discussion forum for the following learning topic:
AI in Assessment and Feedback --> Providing Developmental Feedback
Post what you've learned about this topic and how you intend to apply it. Feel free to post questions and comments too.
This module showed me that effective feedback should be timely, focused, and manageable. Giving students ten corrections at once can overwhelm them, so feedback should prioritize two or three improvements related to safety, professional competency, and the next logical skill. At Decolovers Institute, I intend to group students by common performance patterns and use AI to help draft consistent feedback, which our instructors will review and personalize. I also want to incorporate self-assessment checklists so students can identify strengths and errors in their balloon projects before submitting them, helping them develop greater independence and professional judgment.
I intend to utilize feedback characteristics such as acknowledging strengths, providing action plans to focus on, be specific. Do not need to overload with comment and feedback.
I learned AI can improve the delivery of developmental feedback
I found it interesting that AI can help instructors identify patterns in student work that might lead to more effective feedback and help students understand the underlying concepts of each topic or assignment.
Always start with the rubric when introducing a written task; but I can always run this by AI first and see what the tool suggests as well.
La retroalimentación con IA ayuda mucho a los docentes para brindar recomendaciones mas detalladas sobre los temas que los estudiantes necesitan reforzar.
One thing I learned about providing developmental feedback with AI is that AI can help instructors create more timely, detailed, and growth-focused feedback that encourages students to improve rather than simply focusing on grades. The timing of feedback is also especially important.
