User Experience Case Studies In Education Platforms

Recently, I conducted user testing for some exciting projects at Stanford, and decided to share some insights. This post feels especially personal because it’s not just about design—it’s about my journey as both a student and a designer. When I first came to Stanford as an international student, I struggled with navigating its complex academic systems. It was frustrating, and I remember wishing for tools that could make things simpler and more intuitive. Fast forward to today, and I have the incredible opportunity to work on improving those very systems—side by side with current students. Listening to their frustrations during user testing brings back so many of my own memories. It’s a full-circle moment, where my past experiences fuel my passion to make these tools better for everyone. Here are some interesting insights: • 𝗠𝗲𝗻𝘁𝗮𝗹 𝗠𝗼𝗱𝗲𝗹𝘀 𝗮𝗻𝗱 𝗠𝗶𝘀𝗮𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁: Users often approach academic tools with mental models shaped by other apps or systems they use. Identifying and aligning with these expectations can significantly reduce confusion and improve engagement. • 𝗦𝘁𝗿𝗲𝘀𝘀 𝗮𝘀 𝗮 𝗗𝗲𝘀𝗶𝗴𝗻 𝗙𝗮𝗰𝘁𝗼𝗿: Academic tools are often used in high-pressure moments (e.g., enrollment deadlines). Testing revealed that reducing friction in the interface during these times significantly improves the overall experience. • 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗘𝘅𝗽𝗲𝗰𝘁𝗮𝘁𝗶𝗼𝗻𝘀: Today’s students expect tools to adapt to their preferences, like saving search filters or suggesting classes based on their academic history. • 𝗗𝗮𝘁𝗮 𝗩𝗶𝘀𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝗖𝗹𝗮𝗿𝗶𝘁𝘆: Students value clear, visual representations of information, such as progress bars for degree completion or graphs showing their weekly workload distribution. • 𝗜𝗻𝗰𝗹𝘂𝘀𝗶𝘃𝗶𝘁𝘆 𝗕𝗲𝘆𝗼𝗻𝗱 𝗔𝗰𝗰𝗲𝘀𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆: Designing for inclusivity means accounting for diverse backgrounds, from non-traditional students to those who are the first in their family to attend college. • 𝗜𝘁𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 𝗶𝘀 𝗚𝗼𝗹𝗱: Even after a design seems polished, user testing consistently uncovers areas for refinement, proving that the design process is never truly finished. User testing can be really challenging but truly rewarding in the end. I decided to share these moments to contribute to a community that’s all about learning and growing together. If you’ve got user testing stories or tips, I’d love to hear them—let’s inspire each other! #UXDesign #UIDesign #UserTesting #HumanCenteredDesign #DesignForEducation

Looking for a new way to incorporate AI into lessons after half term? An article in The Wall Street Journal caught my attention recently because it highlights one of the simplest but most powerful ways AI can be used in education: to create interactive case studies for students. At Northwestern’s Kellogg School of Management, students now use AI not to make their work easier but to think more deeply. Instead of working through pages of documentation and producing written summaries, they interact with an AI version of the case, asking questions, testing ideas and developing strategies. It turns the traditional business-school case study into a live conversation that encourages deeper reasoning. If you are a teacher who is becoming more confident with AI and looking for something new to try after half term, I would really recommend experimenting with this approach. It can be adapted to almost any subject. In essence, you create a fictional case study or scenario for students to explore through AI. The AI can either be projected on a classroom screen or used by students individually. I have used versions of this in History and Politics and written before about how these activities can transform class discussion. In History, my students have taken on the roles of decision makers during major crises such as the Cuban Missile Crisis or the growing tensions in Northern Ireland in the 1960s. They analyse context, weigh options and agree on next steps before seeing how the AI responds. In Politics, I have designed fictional nations facing complex issues such as economic inequality or constitutional reform. Students act as advisers and propose policy solutions, which we then debate and refine as a class. Students have actually fed back that these sessions have often been among the most demanding lessons they have experienced. As well as modelling the effective use of AI itself, this approach can develop problem solving skills, strategic thinking, teamwork, and help consolidate understanding at the end of a learning sequence. The AI case study approach reminds us that AI, far from being a shortcut, can create rich opportunities for students to think and engage. (Links in comments to the WSJ article and to some of my earlier write-ups showing examples of these AI case studies in practice.)

The Impact of Khan Academy Learning Platform on Mathematics Achievement in Primary School 4th-Grade Students The study conducted at Bartın Üniversitesi (Bartın University) in #Turkey assessed the impact of the Khan Academy learning platform on fourth-grade primary school students' mathematics achievement. Utilizing a pre-test post-test control group design, the research involved 60 students divided into an experimental group using Khan Academy and a control group receiving traditional instruction through the Education Informatics Network (EBA). Key Findings: 1. Enhanced Learning Outcomes: Khan Academy significantly improved students' mathematics achievement compared to traditional methods. 2. Adoption of Technology: The positive results suggest integrating digital platforms like Khan Academy into teaching strategies to enhance learning and provide personalized educational experiences. 3. Support for Differentiated Instruction: Digital platforms facilitate differentiated instruction, benefiting mixed-ability classrooms by tailoring teaching to diverse student needs. 4. Data-Driven Decision Making: Pre-test and post-test data are crucial for adjusting teaching methods to address student difficulties. 5. Encouragement for Further Research: Additional research is needed to evaluate the effectiveness of various educational technologies to make informed choices about classroom tools. Risks and Limitations: 1. Limited Sample Size: The small sample size of 60 students limits the generalizability of the findings. 2. Focus on a Single Unit: The study’s focus on one mathematical unit may not reflect the effectiveness of Khan Academy across various topics or grade levels. 3. Variability in Engagement: Differences in student engagement with the platform could lead to varied outcomes. 4. Dependence on Technology Access: Limited access to technology can impact the effectiveness of online learning platforms. 5. Need for Teacher Training: Effective use of technology requires adequate teacher training; without it, the benefits may be diminished. 6. Potential for Over-Reliance: There is a risk of over-reliance on digital platforms, necessitating a balance with traditional teaching methods. [Citation: Ulum, H. (2023). Khan Academy Öğrenme Platformunun İlkokul 4. Sınıf Öğrencilerinin Matematik Başarısı Üzerindeki Etkisi. Necatibey Faculty of Education, Electronic Journal of Science and Mathematics Education, 13(1), 533-547.  ] https://lnkd.in/eN5SJ7Qs