Student Feedback Analysis

Power shapes candor. Even when we think we’ve flattened hierarchy, others still feel its weight. For years, when I was a full professor, I believed I had created environments of psychological safety and candor. That was particularly important to me, since I collaborated with many people. I cared deeply about these values and thought those around me felt safe enough to tell me, with candor, when something wasn’t working. But after getting fired, I learned that wasn’t always true. Not long after, a former collaborator—a junior colleague—wrote me a note. We had worked together on several projects, and I had always found our relationship positive, even energizing. The note said otherwise. Here’s part of it: “I am sorry that these things are painful to hear, but unfortunately they reflect how I and others have felt about working with you for many years. The hierarchical nature of academia certainly contributes to everyone’s unwillingness to stand up for themselves and say something. I am not saying this to beat on you when you are down, but to make it clear that my earlier message was not just me losing my temper. It was me saying what I have felt for years and never had the courage to say…” She wanted me removed from a paper I felt I had contributed to, and made the case that I was overestimating the value I added to collaborations. She acknowledged that I brought important positive qualities—like enthusiasm for ideas others dismissed—but that I regularly frustrated her by not being more available and by taking too long to respond. It was painful to read, especially because I had seen our work together as creative, collaborative, and warm. And it was painful to realize that her honesty had been withheld for years because of hierarchy and fear. This experience taught me how easily we, as leaders, can misjudge the climates we’ve created. We assume that because we invite openness, people feel safe to be open. But power distorts feedback loops. It’s not enough to say once, “I welcome candor.” This needs to be said repeatedly—and backed with humility and behavior that proves it’s real. Since then, I’ve been trying to live differently. I’m practicing regularly asking questions like: (1) “What’s something I’m doing that makes it harder for you to be fully honest with me?” (2) “What could I do to be a better collaborator, partner, or friend?” (3) “We can only get better if we help each other improve. What’s one thing I’m doing well—and what’s one I need to improve on?” Sometimes the answers sting. But I’ve learned that the moment after you hear something hard is the moment psychological safety is actually built, if you can stay curious and open instead of defensive. I share this story because many leaders I meet believe, as I once did, that they’ve created environments of candor and psychological safety. But most of us haven’t... not fully. And we can’t fix what we can’t see, unless someone trusts us enough to tell us the truth. #candor #learning

Getting the right feedback will transform your job as a PM. More scalability, better user engagement, and growth. But most PMs don’t know how to do it right. Here’s the Feedback Engine I’ve used to ship highly engaging products at unicorns & large organizations: — Right feedback can literally transform your product and company. At Apollo, we launched a contact enrichment feature. Feedback showed users loved its accuracy, but... They needed bulk processing. We shipped it and had a 40% increase in user engagement. Here’s how to get it right: — 𝗦𝘁𝗮𝗴𝗲 𝟭: 𝗖𝗼𝗹𝗹𝗲𝗰𝘁 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 Most PMs get this wrong. They collect feedback randomly with no system or strategy. But remember: your output is only as good as your input. And if your input is messy, it will only lead you astray. Here’s how to collect feedback strategically: → Diversify your sources: customer interviews, support tickets, sales calls, social media & community forums, etc. → Be systematic: track feedback across channels consistently. → Close the loop: confirm your understanding with users to avoid misinterpretation. — 𝗦𝘁𝗮𝗴𝗲 𝟮: 𝗔𝗻𝗮𝗹𝘆𝘇𝗲 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 Analyzing feedback is like building the foundation of a skyscraper. If it’s shaky, your decisions will crumble. So don’t rush through it. Dive deep to identify patterns that will guide your actions in the right direction. Here’s how: Aggregate feedback → pull data from all sources into one place. Spot themes → look for recurring pain points, feature requests, or frustrations. Quantify impact → how often does an issue occur? Map risks → classify issues by severity and potential business impact. — 𝗦𝘁𝗮𝗴𝗲 𝟯: 𝗔𝗰𝘁 𝗼𝗻 𝗖𝗵𝗮𝗻𝗴𝗲𝘀 Now comes the exciting part: turning insights into action. Execution here can make or break everything. Do it right, and you’ll ship features users love. Mess it up, and you’ll waste time, effort, and resources. Here’s how to execute effectively: Prioritize ruthlessly → focus on high-impact, low-effort changes first. Assign ownership → make sure every action has a responsible owner. Set validation loops → build mechanisms to test and validate changes. Stay agile → be ready to pivot if feedback reveals new priorities. — 𝗦𝘁𝗮𝗴𝗲 𝟰: 𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝗜𝗺𝗽𝗮𝗰𝘁 What can’t be measured, can’t be improved. If your metrics don’t move, something went wrong. Either the feedback was flawed, or your solution didn’t land. Here’s how to measure: → Set KPIs for success, like user engagement, adoption rates, or risk reduction. → Track metrics post-launch to catch issues early. → Iterate quickly and keep on improving on feedback. — In a nutshell... It creates a cycle that drives growth and reduces risk: → Collect feedback strategically. → Analyze it deeply for actionable insights. → Act on it with precision. → Measure its impact and iterate. — P.S. How do you collect and implement feedback?

During our last Inner Circle call, we spent almost half the session not on methods, not on journals, but on… confidence. The research novelty was strong. The research design was solid. But the real friction was internal: “Some days I’m sure journals will be interested in this. Other days I’m convinced no one will care and it’s already outdated.” If that sounds familiar, you’re not alone. A few patterns keep coming up with PhD students and early‑career researchers: - “No novelty” from reviewers often means the gap and contribution aren’t visible enough, not that they don’t exist. - International/visiting scholars carry an extra “Who am I to publish on this?” when their context isn’t the “usual” one. - We quickly forget our small wins and treat a single rejection as a referendum on our entire career. Here are three shifts that helped the person on that call – and might help you too: 1. Keep a “wins log” Every week, write down specific wins: a clear paragraph, constructive feedback, a good question you answered at a seminar, a supervisor saying “this is promising”. On the bad days, you have evidence that you’re not standing still. 2. Treat confidence as a practice, not a personality trait Confidence is not “I always know the answer”. Confidence is “I’m willing to show my work, listen, and improve.” Every time you send a draft, ask a question, or present unfinished work, you’re doing a rep in the confidence gym. 3. Separate your value from reviewer decisions In many fields, 10–20% acceptance rates are normal. Rejection is the default outcome, even for very good work. The useful question is not “Am I good enough?” but “What is this decision telling me about how to sharpen my problem, gap, and contribution?” On that call, once we normalised the imposter feelings and anchored back to actual evidence of progress, you could feel the shift: from “Maybe I shouldn’t be doing this” to “Okay, how do we get this paper out?” In my Inner Circle, this is exactly the mix we work on every week: – the technical side (structure, methods, responses to reviewers) and – the human side (confidence, mindset, navigating rejection without burning out). If you’d like a small, focused space where you can bring both your drafts and your doubts, send me a message and I’ll share how it works. #scientist #research #phd #professor #science #thesis #publishing #career

The fastest way to make feedback ineffective? Turn it into a monologue. In RA/QA, I see this all the time.
Leaders really care about their teams. They want to be supportive. They want to give context.
So they turn a simple piece of feedback into a long explanation… and the core message gets lost. The intention is there, but the result is the opposite of what they hoped for.
People walk away unsure what actually needs to change. Long feedback creates confusion.
Short, factual, future-focused feedback creates improvement. We spoke about this on our recent episode of future leaders - link in comments. Here’s a structure that works in under 30 seconds - and actually lands: 1. Here’s what I saw Keep it factual. No assumptions. No emotion. “Hey, I noticed in today’s meeting you asked questions that were already covered in the preread sent yesterday.” This is just the observation.
Not a character judgement.
Not a story.
Just: here’s what happened. 2. Here’s why it matters People need to understand the impact of their behaviour. “It gave the impression you weren’t fully up to date, and we spent time repeating information instead of moving the discussion forward.” Impact gives the feedback meaning.
It connects the moment to the bigger picture - team time, decisions, trust, efficiency. 3. Here’s what to do next time Make the path forward simple and achievable. “Next time, please take a moment to go through the preread so we can use our time together more effectively.” This is what effective feedback sounds like.
Not dramatic. Not heavy. Not personal.
Just clarity. Short feedback doesn’t minimise the issue - it removes the confusion.
And when people know exactly what’s expected, they adjust faster and perform better. Most performance issues don’t require a 10-minute monologue.
They require a 30-second conversation delivered with intention. These insights are backed by the expert panel in our latest Future Leaders Session, Mastering Performance. You can watch the full session here: https://lnkd.in/dtEHMta2 And if you want to deepen your leadership capability in 2026, join the next Future Leaders Session: here > https://luma.com/oemwy59f See you there!

During my formative years, I followed the traditional feedback formula: begin with compliments, provide criticism, and conclude with support. However, I left behind this "feedback sandwich" (or compliment cushioning) method many years ago. The issue? This method weakens significant messages. When encased in praise, constructive criticism diminishes its effectiveness. Even more troubling, team members come to expect criticism whenever you begin with compliments("Here comes the 'but'..."). An improved approach: Be straightforward and precise: I begin with the specific action or result that requires attention. There is no introduction, only clarity. Emphasise effect: I describe how the particular behaviour influences results, team dynamics, or business performance. Present as growth: I view feedback as a chance for progress instead of a personal critique. Collaborate actively: I inquire about their viewpoint and collectively explore solutions. My perspective may overlook something. Separate praise entirely. I offer genuine praise independently. My constructive feedback stands on its merit—never as a softening prelude to criticism.

Ensuring Students Act on Feedback Feedback is only as valuable as the action students take in response to it. Too often, feedback becomes a passive exchange,teachers give comments, students glance at them, and then move on to the next task without making meaningful improvements. To truly accelerate progress, we need to create structures that ensure feedback leads to independent development. Here’s how: 1. Build Dedicated Feedback Lessons into Your Scheme of Work If feedback is to be effective, there must be time for students to engage with it properly. This means moving beyond a quick ‘read your comments’ approach and embedding dedicated feedback lessons into the scheme of work. By protecting this time within the curriculum, feedback becomes a continuous, structured process rather than an afterthought. 2. Use Targeted and Specific Feedback Vague comments like ‘be more analytical’ or ‘develop your explanation’ don’t give students a clear direction. Instead, feedback should be precise and actionable. For example: • Before: ‘Your analysis is weak.’ • After: ‘To strengthen your analysis, explain why this event was significant and link it to a wider consequence.’ Or Pose questions to help students develop their answer or guide them to the correct knowledge. Pairing feedback with examples or sentence starters can help students apply improvements more effectively. 3. Teach Students How to Use Feedback Students need to be explicitly taught how to engage with feedback. This includes: • Modelling the process – Show students how to act on feedback by walking them through a worked example. • Guiding self-reflection – Use prompts like, ‘How does my answer compare to the model? Where can I improve?’ • Encouraging peer support – Structured peer review can help students identify strengths and areas for development before teacher intervention. I often like to highlight a weak paragraph in a green box so students know what area to precisely improve/re-write, as you can see below. 4. Use Feedback Trackers to Monitor Progress Instead of feedback disappearing into exercise books, encourage students to keep a feedback tracker where they record teacher comments and their own reflections. They can then set targets for the next piece of work and review previous feedback to ensure they’re improving over time. Feedback is most powerful when it becomes part of the learning process, not just an add-on. By allocating time in the curriculum for feedback lessons, making guidance explicit, and encouraging students to take ownership, we can transform feedback from words on a page into meaningful improvement. The ultimate goal? Students who no longer just receive feedback, but actively use it to progress.

I watched a teacher with a group of leaders the other day give nearly every student feedback as she circulated. Eager to see how much better students’ writing was going to be after all that feedback, we walked around the room expecting to see big improvements. From student to student, their work looked exactly the same as it had before the feedback. What gives? So we listened more closely to the feedback she was giving: “You’re missing key details. Go back and revise.” We watched as a confused 7th grader flipped back through the text, unsure where to start. So we helped in the moment by having the teacher adjust her feedback: “You’ve written strong topic sentences for your two body paragraphs—nice work. Your second paragraph is missing two key details, like we named in the criteria for success. Re-read page 71 and find at least one detail to add. I’ll come back in five minutes to check the detail you added.” What happened next? Students’ writing actually improved, and here's the added bonus: so did their connection with the teacher. Instead of feeling frustrated or stuck, they were eager to show her their revisions. That formula — affirm the effort, name the gap, name the fix, and plan the follow-up — is one worth practicing, especially if you have 32 other students you need to give feedback to like she did. When teachers use it, student work gets better, and so do relationships.

𝐖𝐡𝐞𝐧 𝐀𝐈 𝐠𝐢𝐯𝐞𝐬 𝐬𝐭𝐮𝐝𝐞𝐧𝐭𝐬 𝐟𝐞𝐞𝐝𝐛𝐚𝐜𝐤, 𝐬𝐡𝐨𝐮𝐥𝐝 𝐢𝐭 𝐩𝐫𝐨𝐯𝐢𝐝𝐞 𝐝𝐢𝐫𝐞𝐜𝐭 𝐜𝐨𝐫𝐫𝐞𝐜𝐭𝐢𝐨𝐧𝐬 𝐨𝐫 𝐞𝐧𝐜𝐨𝐮𝐫𝐚𝐠𝐞 𝐫𝐞𝐟𝐥𝐞𝐜𝐭𝐢𝐨𝐧? Delighted to share that our latest paper — the third in our trilogy of empirical studies examining the role of generative AI feedback in learning environments, “𝐃𝐢𝐫𝐞𝐜𝐭𝐢𝐯𝐞, 𝐦𝐞𝐭𝐚𝐜𝐨𝐠𝐧𝐢𝐭𝐢𝐯𝐞, 𝐨𝐫 𝐚 𝐛𝐥𝐞𝐧𝐝 𝐨𝐟 𝐛𝐨𝐭𝐡? 𝐀 𝐜𝐨𝐦𝐩𝐚𝐫𝐢𝐬𝐨𝐧 𝐨𝐟 𝐀𝐈-𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐞𝐝 𝐟𝐞𝐞𝐝𝐛𝐚𝐜𝐤 𝐭𝐲𝐩𝐞𝐬 𝐨𝐧 𝐬𝐭𝐮𝐝𝐞𝐧𝐭 𝐞𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭, 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞, 𝐚𝐧𝐝 𝐨𝐮𝐭𝐜𝐨𝐦𝐞𝐬” has recently been published in Computers & Education: Artificial Intelligence. Fantastic work by our talented PhD student Omar Alsaiari in leading this study, and sincere thanks to colleagues Nilufar Baghaei, Jason M. Lodge, Marie Boden, Omid Noroozi, and Dragan Gasevic for their valuable contributions. 🔗 Link to the article https://lnkd.in/gR2yf33g Links to posts about the other two papers in the series are included in the comments. 𝐓𝐡𝐞 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧 A major challenge in designing feedback is balancing clear guidance with opportunities for reflection. 𝐃𝐢𝐫𝐞𝐜𝐭𝐢𝐯𝐞 𝐟𝐞𝐞𝐝𝐛𝐚𝐜𝐤 gives explicit corrections that reduce cognitive load and accelerate early performance. 𝐌𝐞𝐭𝐚𝐜𝐨𝐠𝐧𝐢𝐭𝐢𝐯𝐞 𝐟𝐞𝐞𝐝𝐛𝐚𝐜𝐤 prompts students to plan, monitor, and evaluate their work, supporting self-regulated learning. Both approaches have strong theoretical foundations, but how do they actually influence student behaviour? 𝐌𝐞𝐭𝐡𝐨𝐝 We conducted a 𝐬𝐞𝐦𝐞𝐬𝐭𝐞𝐫-𝐥𝐨𝐧𝐠 𝐫𝐚𝐧𝐝𝐨𝐦𝐢𝐬𝐞𝐝 𝐜𝐨𝐧𝐭𝐫𝐨𝐥𝐥𝐞𝐝 𝐭𝐫𝐢𝐚𝐥 𝐰𝐢𝐭𝐡 329 𝐬𝐭𝐮𝐝𝐞𝐧𝐭𝐬. Students received one of three types of AI-generated feedback: • Directive – clear, step-by-step recommendations • Metacognitive – reflective prompts encouraging self-evaluation • Hybrid – a combination of directive guidance and reflective prompts 𝐑𝐞𝐬𝐮𝐥𝐭𝐬 ➡️ The three feedback types were linguistically and structurally distinct, confirming that prompt design can intentionally produce different pedagogical feedback styles. ➡️ Hybrid feedback prompted the most revisions, followed by directive feedback, while metacognitive feedback led to the lowest revision rates. ➡️ Engagement time, confidence, and final work quality were similar across groups, suggesting that different feedback styles influence how students engage rather than the final outcomes. 𝐈𝐦𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 ➡️ Generative AI provides a powerful and scalable testbed for studying feedback design. ➡️ Blending directive and metacognitive feedback may be particularly promising, combining clear, supporting both immediate revisions and deeper learning processes.

One of the most defining moments in my leadership journey came from a simple realization: Our students were seeking more spaces to feel seen, heard, and celebrated. At 21, returning from NYU, I reflected on our convocation ceremony at Manav Rachna—an event rooted in pride and tradition. While it carried the weight of legacy, I saw an opportunity to make it more student-focused and emotionally resonant. That moment sparked a shift in how I approached leadership—not by choosing between tradition and transformation, but by blending both. 1️⃣ The Convocation Celebration Inspired by NYU’s vibrant format, I proposed some unconventional changes. What I found was incredible support from our leadership, grounded in data and driven by a shared desire to honour our students more meaningfully. The outcome? A 300% increase in graduation attendance and moments that lived on through proud social media shares. 2️⃣ The Internship Evolution There were initial concerns that interdisciplinary programs might affect academic depth. But when engineering students returned from marketing internships with sharper problem-solving skills, the results spoke for themselves. Today, 78% of participants outperform peers in innovation challenges. 3️⃣ The Feedback Framework We introduced “Reverse Office Hours,” a space for students to offer structured feedback to faculty. What began as an experiment has grown into a valued tool for refining curriculum and enhancing classroom engagement. The Lesson? Great institutions thrive not by preserving legacy alone, but by embracing student voices as catalysts for growth. At Manav Rachna, it’s not about tradition versus change—it’s about evolving together. So, when I’m at a crossroads, I ask: •⁠ ⁠Are we doing this because it truly serves our students or simply because it’s always been done? •⁠ ⁠Can this policy stand up to the thoughtful feedback of a 19-year-old learner? The real magic begins when we stop viewing “student-centric” and “senior-led” as opposing forces—and start seeing them as partners in progress. #education #innovation #students #convocation #graduation

All the scholarship on assessment and feedback means little if we cannot translate it into practice. This week I am teaching a course in the Graduate Certificate in University Teaching, where I introduce academics to some amazing scholars who help us think more expansively about how feedback and assessment supports learning goals for students. First, I translate scholarship into principles: 1. Feedback is relational practice Elizabeth Molloy shows how trust, dialogue and psychological safety shape whether feedback becomes usable. 2. Feedback is cultural practice David Boud and Joanna Tai highlight how assessment and program cultures build students’ capacity for future learning (sustainable assessment) and evaluative judgement. 3. Feedback is learning practice Naomi Winstone and David Carless demonstrate that students need structured opportunities to interpret and apply feedback (feedback literacies), not just receive it. 4. Feedback is emotional and identity practice Rebecca Olson and Rola Ajjawi show how belonging, vulnerability and identity shape how students respond to feedback (and how feedback shapes identities). Then I translate these principles into my teaching practice: – Embed dialogue and collaboration (professional learning communities model) across the course – Create feedback conversations in class before assessment is due – Add ‘changes I made because of peer feedback’ as part of the graded assessment task – Integrate self-assessment to build evaluative judgement and use this in marking and written feedback process – Dedicate class time to address all assessment questions throughout the semester – Link earlier feedback to later tasks so students can act on it (scaffold assessment tasks) In my Grad Cert class, academics then apply this work to a subject or supervision context they teach. They identify the explicit role feedback will play and design three or four feedback activities to embed across pedagogy and assessment. This is scholarly teaching: translating theory into practice. It is how we unlock the creativity and academic rigour of university teaching. And it is fun!