Enhancing Student Feedback with Tech Solutions

In 2022, two professors were drowning in 8,224 student questions. Instead of hiring more staff, they built an AI that's changing elite education forever. When Kevin Bryan and Joshua Gans got tired of answering the same MBA student questions repeatedly, they didn't just complain. They built. All Day TA—an AI assistant trained on their actual course materials—became their solution to an age-old academic problem. The results have been nothing short of amazing. In one course with 250 students, their AI handled 8,224 questions—over 30 interactions per student—with projections hitting 50 by semester's end. This isn't theoretical conjecture or wishful thinking. This is real classroom data from the University of Toronto, where innovation meets necessity. Students could ask questions anytime, whether it's during 2am cramming sessions, moments before class, or while puzzling through feedback. No more waiting for office hours or hoping for an email response in time. The system knew its limits, too. When questions ventured beyond its scope, it gracefully escalated to professors without guessing or overreaching. No hallucinations. Just intelligent guardrails respecting human judgment. Student feedback revealed something powerful: they felt more confident asking questions. The AI eliminated that familiar "am I bothering the professor?" hesitation we've all felt when our hand hovers over the send button. Impact breakdown: • Faster responses • Fewer repeat questions • More consistent answers • Less teaching fatigue Now MIT, Berkeley, Princeton, UCLA, and others have piloted All Day TA, or they are implementing similar systems, recognizing the potential for transformation. This isn't about replacing professors with robots. It's about liberation. By eliminating the mental load that silently drains teaching energy, professors can teach once, then let technology handle the repetitive inquiries that consume precious time. They protect their energy for what truly matters: deeper connections, complex concepts, and the meaningful mentorship that machines can never provide. The schools leading the future won't just have smarter students. They'll have freed-up faculty with bandwidth for what matters. And that changes everything for everyone involved in education.

𝐓𝐡𝐞 #𝐆𝐞𝐧𝐀𝐈 𝐡𝐲𝐩𝐞 𝐢𝐧 𝐞𝐝𝐮𝐜𝐚𝐭𝐢𝐨𝐧: 𝐀𝐫𝐞 𝐰𝐞 𝐦𝐢𝐬𝐬𝐢𝐧𝐠 𝐭𝐡𝐞 𝐩𝐨𝐢𝐧𝐭? 🧐 Many #EdTech companies are marketing AI tools to educators with a focus on "speed" and "efficiency." But as an educator, I have to ask: 𝑾𝒉𝒆𝒏 𝒅𝒊𝒅 𝒆𝒇𝒇𝒊𝒄𝒊𝒆𝒏𝒄𝒚 𝒃𝒆𝒄𝒐𝒎𝒆 𝒐𝒖𝒓 𝒑𝒓𝒊𝒎𝒂𝒓𝒚 𝒈𝒐𝒂𝒍? In my experience, the true potential of AI in education lies not in saving time, but in enhancing learning outcomes. Let me share an example: Over the past three semesters, I have implemented AI-powered formative feedback tools in my courses. These tools use my assignment rubrics to provide feedback to student before they submit their final work for grading. The goal? Not to cut my grading time, but to empower students to: · Identify strengths and areas for improvement · Attempt to close knowledge gaps independently · Enhance the quality of their work before submission Since using these AI tools for formative feedback, I've noticed that my students plan ahead to allow time for revision and approach me with targeted questions about their work. As a result, I can spend time on more advanced discussions rather than basic corrections of their work. What are your thoughts on the role of AI in education? Are we too focused on efficiency at the expense of effectiveness? #AIinEducation #TeachingInnovation #HigherEd #EdTechTrends

Many teachers are skeptical about the utility of AI... Here the #UK Department for Education documented Use Cases for #GenAI in #Education - #User #Research Report The report examines the collaboration between educational institutions and the UK Department for Education to assess the use of GenAI in automating routine educational tasks. Several innovative use cases for generative AI (GenAI) in education that were explored during the hackathons and proof-of-concept (PoC) development. a) #LessonPlan or activity adaptor: A tool that can adapt existing lesson plans and tailor lesson activities to the specific context and needs of individual classes or students. b) #Feedback and revision activity generator: The PoC tool developed in this project focused on reviewing student work, providing personalized feedback, and generating tailored revision activities based on the individual student's errors and areas for improvement. c) #QuestionGenerator: A tool that can automatically generate graded, lesson plan-aligned questions based on information from sources such as lesson plans, objectives, and curriculum materials. d) #Disabilities #SupportTool: A tool designed to assist teachers in adapting lesson content to meet the specific needs of students with Special Educational Needs and Disabilities (SEND). e) #Parent and carer communications tool: A tool that can generate communications with parents and carers, such as school newsletters or emails about upcoming events. f) #PolicyGenerator: A tool that can support the generation of school policies based on submitted school characteristics, existing policy documents, and national legislation or guidance. Three Challenges Identified: - ⚠️Model capabilities and limitations: While GenAI models showed potential in certain tasks like generating lesson plans or activities, there were significant limitations in more complex tasks, such as accurately marking student work or generating comprehensive feedback. - 🚨User trust and acceptance: Many teachers expressed concerns about trusting GenAI tools for tasks like providing feedback, and some were worried about becoming overly reliant on these tools. - ⏰Need for training and guidance: Teachers reported a need for time, training, funding, and expert support to increase their knowledge and skills in using GenAI tools in their practice, as well as guidance on how to use AI safely and effectively. Five aspects to improve: i) #DataPrivacy and safety ii) #Adoption #Reluctance iii) #Lack of #Personalization iv) #Accuracy of #AI v) #Implementation #Barriers via Martin Ebers https://lnkd.in/ekbHKxyS Source: Faculty AI, National Institute of Teaching, ImpactEd Group, & Department for Education. (2024). Use Cases for Generative AI in Education: User Research Report. UK Government