UX Design In Education Technology

Accessibility in eLearning and beyond. I’ve learned a huge amount from Esi Hardy over the years. That’s why it was such a privilege to join her to reflect on over eight years of focused work in eLearning accessibility in her latest podcast episode. I love Esi’s podcast because it genuinely represents the accessibility community. Alongside Esi, it brings together impactful voices such as Max Horton, Teresa Joy Mack, Isaac Harvey MBE and Joe Collett. It also models good practice. Each episode includes a clear summary and a full transcript that not only includes people with a range of access needs but is also great for SEO - demonstrating perfectly how accessibility and quality content go hand in hand. Here are my five key takeaways from our conversation: • We need to stop debating about whether accessible learning is possible and start acting as if it is expected. The question is how we do it, not if we should. • Standards do help. WCAG can feel complex, but it gives you a practical starting point. Without a baseline, it is very hard to make consistent progress. • Accessibility and inclusion are not the same. Something can meet requirements and still feel excluding. Inclusive learning is about the experience, not just passing technical standards. • Change happens when accessibility stops being theoretical and becomes personal. Understanding the real effect of barriers on confidence, engagement and outcomes is what makes the case compelling. • We need to move from 'advocacy to architecture'. Accessible learning is not an optional 'nice to have'. It's part of excellent learning design. You can access the full episode here. https://lnkd.in/exA9m5Du #eLearningAccessibility #DigitalInclusion #DigitalAccessibility (Episode artwork featuring Esi and Susi side by side, alongside the podcast title “Accessibility Beyond The E-Learning Content” from The Equality Edit. The page includes an audio player, a written episode summary outlining themes of accessibility and learning design, and the opening section of the full transcript.)

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.

User experience surveys are often underestimated. Too many teams reduce them to a checkbox exercise - a few questions thrown in post-launch, a quick look at average scores, and then back to development. But that approach leaves immense value on the table. A UX survey is not just a feedback form; it’s a structured method for learning what users think, feel, and need at scale- a design artifact in its own right. Designing an effective UX survey starts with a deeper commitment to methodology. Every question must serve a specific purpose aligned with research and product objectives. This means writing questions with cognitive clarity and neutrality, minimizing effort while maximizing insight. Whether you’re measuring satisfaction, engagement, feature prioritization, or behavioral intent, the wording, order, and format of your questions matter. Even small design choices, like using semantic differential scales instead of Likert items, can significantly reduce bias and enhance the authenticity of user responses. When we ask users, "How satisfied are you with this feature?" we might assume we're getting a clear answer. But subtle framing, mode of delivery, and even time of day can skew responses. Research shows that midweek deployment, especially on Wednesdays and Thursdays, significantly boosts both response rate and data quality. In-app micro-surveys work best for contextual feedback after specific actions, while email campaigns are better for longer, reflective questions-if properly timed and personalized. Sampling and segmentation are not just statistical details-they’re strategy. Voluntary surveys often over-represent highly engaged users, so proactively reaching less vocal segments is crucial. Carefully designed incentive structures (that don't distort motivation) and multi-modal distribution (like combining in-product, email, and social channels) offer more balanced and complete data. Survey analysis should also go beyond averages. Tracking distributions over time, comparing segments, and integrating open-ended insights lets you uncover both patterns and outliers that drive deeper understanding. One-off surveys are helpful, but longitudinal tracking and transactional pulse surveys provide trend data that allows teams to act on real user sentiment changes over time. The richest insights emerge when we synthesize qualitative and quantitative data. An open comment field that surfaces friction points, layered with behavioral analytics and sentiment analysis, can highlight not just what users feel, but why. Done well, UX surveys are not a support function - they are core to user-centered design. They can help prioritize features, flag usability breakdowns, and measure engagement in a way that's scalable and repeatable. But this only works when we elevate surveys from a technical task to a strategic discipline.

Inclusive design is not just about the font you choose. It is about how your content behaves when it meets a different nervous system. Last week, we pruned your typography. This week, we are looking at the soil. We are auditing your media and structure. In our rush for "engagement," corporate communications often rely on visual shortcuts like flashing GIFs, color-coded alerts, and walls of emojis. Marketing calls these "hacks." I call them Barriers. When you rely on a color change to signal "danger," you lock out the colorblind. When you replace words with a string of emojis, you create chaos for a screen reader user (hearing "Face with tears of joy" five times in a row). When you post a video without captions, you tell the Deaf and Auditory Processing communities that they are not your audience. Accessibility is not a "feature" for a minority group. It is an indicator of Organizational Health. If your content requires perfect vision, perfect hearing, and neurotypical processing speed to understand... your content is flawed. Below is The Inclusive Content Audit (Part 2). We moved beyond fonts to look at media, structure, and interaction. Here are 9 Ways to Operationalize Inclusion in your content: 1. The Emoji Restraint ❌ Barrier: Emojis read aloud via screen readers as clunky descriptions. ✅ Fix: Use clear words to convey tone. Keep emojis at the end of sentences rather than in the middle. 2. The Caption Mandate ❌ Barrier: Audio/Video posted "naked." ✅ Fix: Burned-in open captions. (This helps ADHD brains like mine focus just as much as it helps Deaf users). 3. The Contrast Rule ❌ Barrier: Text over busy, semi-transparent backgrounds. ✅ Fix: Solid color backgrounds behind text blocks to reduce visual noise. 4. The "Color + Shape" Rule ❌ Barrier: Using only color to convey meaning (e.g., Red = Error). ✅ Fix: Pair color with a distinct shape or icon label. 5. The Alt-Text Discipline ❌ Barrier: Images with file names like "IMG_5920.jpg". ✅ Fix: Descriptive, concise Alternative Text. 6. The Header Hierarchy ❌ Barrier: Manually bolding text to look like a header. ✅ Fix: Using actual "Heading Styles" (H1, H2) so screen readers can navigate the structure. 7. The Motion Control ❌ Barrier: Auto-playing GIFs or flashing content. ✅ Fix: Static images or user-controlled "Play" buttons. (Protect your team from vestibular triggers). 8. The Data Summary ❌ Barrier: Complex charts with no text explanation. ✅ Fix: A simple text summary beneath the visual. 9. The Permanent Label ❌ Barrier: Form field labels that disappear once you start typing. ✅ Fix: Labels that remain visible above the field. (Reduces cognitive load and working memory strain). The Verdict: Low-friction content is high-impact content. Stop making your audience fight your design to get to your message. #Accessibility #InclusiveDesign #WCAG #Neurodiversity #Leadership #ClinicalStrategy

🎯 Monitoring & Feedback: The Heart of Effective Classroom Interaction In every successful classroom, two powerful teaching tools quietly shape learning: monitoring and feedback. They may look simple , walking around the classroom, asking questions, writing on the board but when used purposefully, they transform learning. 👀 What is Monitoring? Monitoring is more than just observing. It means: 🔎 Watching and listening carefully while learners work 🚶 Moving around instead of staying at the front 🎯 Identifying difficulties and common errors 📊 Tracking learners’ progress 🤝 Showing learners you are present and interested When teachers move among learners, they create a more dynamic learning environment not a static one. Sensitive monitoring makes teachers appear more approachable, supportive, and engaged. 🌱 Why Monitoring Matters Effective monitoring: ✨ Builds rapport ✨ Keeps learners on task ✨ Increases engagement ✨ Provides individual attention ✨ Prepares the teacher for meaningful feedback Learners feel supported when they know their teacher is actively interested in their work. 💬 Giving Feedback: More Than Correction Monitoring and feedback go hand in hand. What we observe during monitoring guides the type of feedback we give. Here are six powerful feedback techniques: 1️⃣ 🤝 Peer Correction ✔ Encourages collaboration ✔ Develops critical thinking ⚠ Needs training to avoid over-criticism 2️⃣ 🔁 Learner Review (Self-Review) ✔ Promotes autonomy ✔ Reduces teacher workload ⚠ Requires clear guidance and criteria 3️⃣ 🧍 Individual Language Feedback ✔ Provides direction ✔ Personalised support ⚠ Challenging in large classes 4️⃣ 🏫 Class Language Feedback ✔ Quick and efficient ✔ Highlights common errors ⚠ May not apply to everyone 5️⃣ 🔎 Self-Correction ✔ Builds independence ✔ Deepens learning ⚠ Must be checked 6️⃣ 💡 Feedback on Content ✔ Values creativity ✔ Builds confidence 🔑 Key rule: Always comment on content first, then language. 🧩 Staging Feedback for Greater Impact Effective feedback is not random. It follows clear micro-stages: 1️⃣ Recap the previous activity 2️⃣ Ask specific questions 3️⃣ Write key answers on the board 4️⃣ Elicit a model sentence 5️⃣ Set up the next task Breaking feedback into smaller stages makes it: ✔ Clearer ✔ More constructive ✔ Less overwhelming ✔ More motivating 🏆 What Strong Teachers Do During Feedback ✔ Keep a brisk pace ✔ Don’t always ask the same learners ✔ Highlight good examples ✔ Correct common errors ✔ Praise effort and improvement ✔ Ask for personal responses Feedback isn’t just about mistakes — it’s about growth. 🌟 Final Reflection Monitoring is not simply walking around. Feedback is not simply correcting. When done intentionally, they: ✨ Build confidence ✨ Encourage autonomy ✨ Strengthen classroom culture ✨ Support meaningful learning #ClassroomInteraction #TeachingStrategies #PrimaryEducation #ELT #TeacherDevelopment #AssessmentForLearning #StudentEngagement #EducationLeadership

Can students judge like experts? New research challenges assumptions about AI feedback in education. A new large scale study (Nazaretsky, Gabbay & Käser 2026) compared AI-generated and human-crafted feedback for 472 STEM students. Here is what they found: 📊 Quality is comparable. AI-generated feedback matched human-authored feedback in pedagogical quality. Both had strengths, and both had gaps, particularly around metacognitive guidance. 🧠 Perception ≠ reality. Students' evaluations of feedback quality were driven more by who they thought provided it than by the feedback's actual merit. This held across academic levels, genders and fields of study. 📋 A new standard emerges. The researchers introduced a structured rubric for assessing formative feedback quality, addressing a real gap in how we evaluate AI tools in education. ⚡ Key reflection. We need to help students become better evaluators of the feedback they receive regardless of its source. Feedback is only as effective as a learner's ability to use it. So how do we do that? Here are some ideas: ➜ Demonstrate the different levels feedback can operate at. Show them: task-level feedback says "this is wrong." Process-level feedback says "your approach broke down here, try this strategy." Self-regulation feedback says "before starting problems like this, estimate the answer first to catch errors early.” ➜ Encourage and scaffold structured self-questioning when students are in the planning and process phases of completing tasks. ➜ Have students rate feedback on metacognitive criteria. Don't ask "was this helpful?" Ask: Did it help me understand why I made the error?” ➜ Compare feedback examples. Show two pieces of feedback on the same work: one purely corrective, one with metacognitive guidance. ➜ Model metacognitive evaluation out loud. Teachers modelling their own thinking and self-talk to demonstrate metacognitive strategies helps students see how to evaluate feedback critically. Any other suggestions?

Practical design tips for cognitive & mental-health accessibility What can we actually do, in practice, to make digital experiences calmer, safer, and easier to use? Here are some techniques that go beyond WCAG checklists, drawn from real accessibility work and user feedback: 1. Reduce cognitive load → simplify tasks Use plain language, short sentences, chunked steps. Example: GOV.UK consistently ranks as one of the best models for cognitive clarity: https://lnkd.in/eNc-Cbwx 2. Support emotional safety → avoid stress-inducing patterns Remove manipulative patterns, rushed steps, or overwhelming UI. Study: Digital design influencing emotional distress - “Digital Health Risks & Social Isolation”: https://lnkd.in/eXQSbUCz 3. Give users control over pace, motion & interruptions Provide pause/stop controls, reduce auto-refresh, allow more time. Study: Digital mental-health accessibility and processing time needs: https://lnkd.in/e_R33qZF 4. Create highly predictable navigation Users with anxiety or executive dysfunction rely on consistency. Study: “Improving Cognitive Web Accessibility” - predictability reduces cognitive strain: https://lnkd.in/e2rrKC5N 5. Allow personalisation & adaptive modes Let users reduce clutter, choose simpler layouts, alter colours or spacing. Research: Neurodivergent-inclusive design & adaptive interfaces: https://lnkd.in/eJcWnxuV 6. Support focus → minimise distractions Avoid auto-playing video, flashing banners, notification loops. Example: “Reader Mode” in Firefox & Safari is a real-world model of reducing distractions: https://lnkd.in/er8UsxDw 7. Provide emotional reassurance in UI Use confirming messages, check-ins, progress indicators, and reduced ambiguity. 8. Use multimodal presentation → support different processing styles Provide text + visuals + examples; avoid relying on one cognitive channel. Cognitive accessibility by W3C WAI: https://lnkd.in/enTWiJdJ 9. Avoid memory-heavy interfaces Don’t force users to remember steps, data, or locations → keep key actions visible. Principle: Recognition over recall, supported by decades of UX & cognitive psychology: https://lnkd.in/eGsr_9bi 10. Test with diverse minds, not only sensory disabilities Include people with ADHD, PTSD, anxiety, dyslexia, brain fog, burnout. Study: UX design for mental-health needs, comparing typical vs. cognitive users: https://lnkd.in/eZ_7mmE6 Which of these do you already apply in your design or development process? And what other good strategies have you seen that support mental wellbeing online? #WebAccessibility #InclusiveDesign #CognitiveAccessibility #MentalHealth #A11y #DesignForGood #EmpathyInDesign #UXDesign #DigitalWellbeing #AccessibilityMatters

Read our latest research article, "Enhancing Peer Feedback Provision Through User Interface Scaffolding: A Comparative Examination of Scripting and Self-Monitoring Techniques," published in Computers & Education! 🔗 Read the full paper: https://lnkd.in/ecz3ZhZc 🎉 Special thanks to Hatim Lahza and Hassan Khosravi for their significant contributions and leadership and also for involving me in this exciting research! Also, many thanks to the other co-authors (Gianluca Demartini, Dragan Gasevic, Shazia Sadiq) for their valuable inputs and contributions. 📌 Key Findings: 🔹 Scripting-based scaffolding significantly improved the depth and specificity of peer feedback compared to students in the self-monitoring condition. 🔹 Students in the self-monitoring condition provided more lenient, high-quality ratings, while those in the scripting condition were more cautious and exhibited lower confidence. 🔹 Scripting scaffolds are associated with more critical evaluative judgement outcomes. 🔍 Key Contributions: ✅ Expanding the empirical foundation of educational design principles in peer feedback provision by deepening our understanding of the individual effects of scaffolding tools—scripting and self-monitoring. This lays the groundwork for future research into optimal application strategies. ✅ Advancing theory-based digital learning environments, contributing to the ongoing efforts to develop more effective, research-driven educational technologies for enhanced learning experiences. ✅ Providing practical insights for educators and instructional designers, demonstrating how adaptive user interface scaffolding can enhance peer learning and feedback practices in higher education. #Peerfeedback #Peerlearning #Peerreview #Feedback #Scripting #Scaffolding #Selfregulation #LearningAnalytics #Selfmonitoring

In my online course this semester, I wanted to rethink how we give feedback, not replace it with AI, but reimagine it through a human–AI hybrid lens. Each week, my graduate students wrote a 300-word reflection in response to three prompts. For the first three weeks, I told them I’d experiment with a new feedback model: something between human/instructor/expert insight and AI precision. I wrote about this online course before. I utilized a research-backed online course model (more details to follow) that enables graduate students to practice AI for their assignments, based on @Mike Perkins et al.'s (2024) AIAS framework. This is the 2nd semester I am piloting it (this reminds me a new post about it!) Inspired by S. Kazem Banihashem et al.'s (2025) pedagogical model for hybrid-intelligent feedback, here’s how I approached it: 1️⃣ I read each reflection carefully and took personal notes (my initial thoughts, questions, and highlights etc.) 2️⃣ I trained ChatGPT using the course overview, assignment instructions, and my feedback tone from previous semesters. 3️⃣ I fed it anonymized notes for three students and received AI-generated first drafts. 4️⃣ I revised them for tone, accuracy, and depth to ensure warmth and critique balanced each other. 5️⃣ I re-trained my chatbot, guided by Timperley et al. (2007) on effective feedback, so it could “learn” what high-quality, evidence-based feedback looks like. The results? Surprisingly good! The final feedback felt genuine, efficient, and nuanced! (For step 4️⃣, the hardest part was that ChatGPT's outputs were always positive, even though the reflection missed a very important aspect or missed a response to one of the prompts.). In the Human–AI feedback spectrum (pictured below), I’d say I’m on the human-led, AI-supported side. My human input added emotion and context; AI refined language, consistency, and conciseness. I didn’t follow Dr. Banihashem's framework exactly (pictured below), but you’ll see my Napkin-generated illustration in the document. (Still need some work) And yes! I also collected some informal data: a 6-item Likert scale + one open-ended question about students’ perceptions. I’ll share those findings in my next post.

Effective feedback relies on students knowing what to do with it. It's not enough to just give students hopefully useful information, we also need to create the conditions where they can make the most of it. And part of that includes helping develop students as expert and agentic feedback users. Now, it probably surprises nobody that to develop that capability, we need to do more than just tell students what to do in feedback. We need to get students to practice doing good things with feedback. But after you have that realisation, the question becomes: what, exactly, do we get them to do? Enter: Feedback emPower Tools, from three of the world's leading feedback experts: Kieran Balloo PhD SFHEA, Rob Nash and Naomi Winstone. There's video, text, guidance etc on there but most importantly some activities you can download in H5P and embed directly on a LMS subject page etc. All grouped into addressing the real challenges students face in feedback. You could just put in whichever ones you want in a course, but I reckon the best approach would be to look across a whole degree program and embed one of them per unit/subject/module, carefully placed in the assessment sequence so it's relevant at that moment. https://lnkd.in/emhRTGyQ