research

Learn About the Users

During the research phase, we wanted to learn about Gen Z’s learning behaviors with various platforms and creators motivation to create content and reasons they would stay at a platform. We started by asking these preliminary research questions:

Research Methods

To gain more insights we used four different research methods, and here are the rationales for each method we chose:

Interviews

For our research, we designed two distinct discussion guides tailored for Gen-Z learners and content creators. Out of the 9 interviewees, I recruited four participants, and moderated each interview session. Prior to the interviews, we developed essential preparatory materials, including a screening survey, introduction document, and consent form.

Co-Design

I advocated for bringing together Gen-Z learners and creators in a 90 minute in-person co-design session, creating a collaborative space for mutual learning where participants engaged in brainstorming and co-design activities. I took charge of planning and moderating the session, scripting both questions and four activities, while also curating the environment with drawing materials and catering. The insights gathered not only supplemented our interview findings but also provided valuable guidance to enhance our upcoming design work.

Results Analysis

We analyzed the data collected from all of our research methods using affinity diagramming. Below is the learners' analysis, shown as an example.

Key findings

Through meticulous triangulation and synthesis, we distilled our research into 17 key findings, categorized into the perspectives of both learners and creators. Due to project constraints, our focus predominantly honed in on the insights derived from the learners. The following represent the most pivotal findings, serving as our guiding principles throughout the design process.

Heuristic Evaluation

As we delved into our findings, we felt it's also important to assess the current state of Microsoft Learn. The platform has excellent resources for learning Microsoft products, accompanied by a lively community of creators producing high-quality content. However, we did spot a gap – there's plenty of written material and forums, but not as many of those quick, bite-sized videos that Gen-Z tends to prefer.

Areas of Improvement

Based on our understanding of Gen Z, here are some areas for improvement:

Pivot to AI

As our team invested considerable time brainstorming possible directions, a sudden wave of groundbreaking news in the AI landscape, including Microsoft's unveiling of the new Bing and Copilot, prompted a reevaluation. While sticking with our initial plan appeared logical from a timeline perspective, I championed agility, seizing the opportunity to create something more intricate and cutting-edge.

Exploring the capabilities of AI, especially its efficiency in learning processes, we recognized its potential to elevate our solution beyond traditional platforms. In discussions with the client, we discovered that this direction also aligns with Microsoft's forward-looking strategy. This realization led us to make the strategic decision to pivot, with the integration of AI becoming our new focus, a move aimed at delivering a more powerful and forward-thinking experience for our users.

How Can AI Elevate User’s Learning Path?

Drawing from our insights into Gen Z and our exploration of AI capabilities, including personalization, adaptive learning paths, interactive engagement, and real-time feedback, here are key areas where we believe AI can enhance our users' learning journey:

Design Requirements

Before diving into a new round of brainstorming session for solutions, we established some design requirements to serve as guiding principles throughout the design process.

Key Features for the AI-powered Learning Hub

After many brainstorming sessions, we narrowed down our focus to three key AI features for our product.

Brainstorming

Next, we engaged in a range of generative design activities to generate creative concepts and innovative solutions. These activities included brainstorming sessions and collaborative idea generation exercises. Through these ideation activities, we explored various possibilities for our personalized learning platform. We then settled on five main concepts:

Wireframe & Prototype

The other designer on the team and I initiated the process of mapping out potential screen wireframes to illustrate the functionality of each AI feature. Wireframing plays a foundational role in our design journey, providing a visual representation of the overall structure and layout of our product. This skeletal framework not only helps in early identification and resolution of potential design challenges through usability testing but also facilitates seamless collaboration and alignment on design concepts with our client.

Usability Testing

By presenting participants with mid-fidelity static mocks at an early stage of the design process, we evaluated their understanding, expectations, and interactions with the interface. This allowed us to identify potential usability issues, gather user preferences, and make informed design decisions before investing resources into high-fidelity prototypes or development.

Key Testing Results

We analyzed the data collected from our research findings using affinity diagramming. Based on our synthesis, we developed the following key findings. The feedback gathered helped us to further refine our design in order to create a product that meets the needs and expectations of our target audience.

Design Improvements

Based on the findings from usability testing, we made significant design improvements to enhance the onboarding process and improve the overall product experience.  

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