Engageli Studio AI-Powered Course Builder
- Company
- Engageli
- My role
- Head of Product Design
- Team
- A team of 4 I hired
- Timeline
- 2022 – present
- The challenge
- Turn passive video lectures into interactive, self-paced courses — without adding work for instructors. Studio is one part of the Engageli virtual-classroom platform, which I redesigned from zero.
- What I did
- Set the design vision, led research with K-12, higher-ed and corporate instructors, and drove the AI-first authoring experience from concept to launch.
- Outcome
- ~75% less time to update a course · 92% of instructors saw higher engagement · 94% of pilot users preferred Studio — from beta and pilot surveys
Starting point
“Online courses shouldn’t feel like staring at a TV screen.”
Students tune out of passive video lectures. Engageli Studio turns those lectures into interactive, self-paced courses. As Head of Product Design, I set the design vision and led a team of researchers, designers and writers. AI handles the tedious parts — cutting the video and drafting quizzes — so instructors can focus on teaching, not tooling.
See the full design process Research, personas, flows and prototypes
Discovery & Research
We interviewed instructors across K-12, higher education and corporate training. Two needs stood out: creating content had to be simple, and learners had to stay engaged. That set the priorities — AI video chunking, a quick quiz-and-poll creator, and built-in analytics. (Engageli’s research data later showed pilots achieved a 75% reduction in update time and that 94% of pilot users preferred Studio.)
Personas & Journeys
- Instructor Persona (Educator) – e.g. a university professor, corporate trainer or K-12 teacher (Engageli specifically targets “corporate training, higher education, and K-12” instructors). Goals: Quickly turn recorded lectures into an interactive course, engage students, reduce prep time. Frictions: Existing tools are fragmented or complex; editing videos and quizzes by hand eats hours.
- Learner Persona (Student) – e.g. a busy online student. Goals: Learn at own pace, get immediate feedback, stay motivated. Frictions: Passive videos and static slides lead to boredom; questions go unanswered unless the instructor is live. They value features like the AI tutor (Engageli’s Learning Pal) for on-demand help.
Each journey was mapped from these personas’ perspectives. For instructors, the flow begins with content upload and ends with publishing a finished course. For learners, the journey goes from discovering the course to actively answering embedded questions and receiving AI support. Our personas helped us prioritize usability for both sides: an educator-friendly authoring flow, and a learner-friendly engagement experience.
User flows
- Create Module: Instructor logs in to Engageli Studio and starts a new module, naming it (e.g. “Intro to Computer Science”). They upload source materials – an MP4 lecture or slide deck.
- AI Analysis: Studio’s AI processes the content. It auto-chunks the video into micro-lessons (scene breaks or topic shifts) and flags natural pause points. Meanwhile, it suggests adding polls/quizzes at logical spots.
- Add Engagement: The user reviews the automated outline. Using the Activities sidebar, they drag and drop or click to insert interactive elements (quiz questions, polls, documents) onto the timeline. A quick editor pops up to customize each question and answer.
- Review & Publish: The instructor previews the course in Review mode (mimicking the learner view, complete with “Learning Pal” assistance). They make final tweaks, then publish the module. The content is now a self-paced course accessible to students.
Each step flows naturally from the last. We designed clear affordances (buttons like “Add quiz”, drag-and-drop modules, etc.) so users always know what to do next. This flow was refined iteratively: wireframes and prototypes were reviewed with real educators to ensure the journey felt logical at each stage.
Wireframing & Prototyping
We started with pencil sketches and low-fidelity mockups to explore the layout. Early wireframes placed a video preview at center, a timeline underneath, and an “Add Activity” panel on the side. In these sketches (see image), we prototyped different approaches: should the timeline show thumbnails or dots? How many clicks to insert a poll? Using paper prototypes and digital mockups (Figma), we tested these questions.
Feedback drove major iterations. For example, one round of testing revealed that instructors struggled to understand how AI-suggested segments worked. We simplified by adding an explicit “Chunk Content” step. Another insight: users wanted to quickly change question order, so we added drag handles in the quiz editor. By the third sprint, we had high-fidelity interactive prototypes simulating the real flow. These were invaluable for catching issues early – for instance, adjusting button labels and increasing contrast for accessibility. Throughout prototyping, we kept designs simple and consistent, using Engageli’s purple-highlight theme and familiar iconography.
From upload to a ready module
Processing a long lecture takes time, so the flow never makes the instructor wait. The file uploads and processes in the background, the instructor gets an email when it’s ready, and the builder switches over on its own. The AI splits the video into parts and drafts polls for each one — and nothing goes live until the instructor reviews it.
Final UI
The final interface is clean, intuitive, and designed to scale with future product growth. At the center sits the video player, acting as the primary workspace anchor. Directly beneath it is a dynamic timeline with subtle, color-coded markers that indicate where engagement activities have been added. As the video plays, prompts appear in sync with the timeline, creating a seamless connection between content and interaction.
On the right, the Activities Panel presents a clear, scrollable list of engagement tools. When the user clicks “Add Activity,” a focused modal appears, offering a range of content types — from AI-generated podcast segments and polls to YouTube links, PDFs, PowerPoint slides, instructor self-recordings, etc. Each type is visually distinct and easily previewed.
Activities can be generated in real-time or attached to specific moments in the video. Once selected, a simple “Add” action places the activity on the timeline with immediate visual confirmation. The interaction flow is designed to feel effortless, combining clarity with creative control — enabling instructors to build rich, engaging lessons with minimal friction.
Signature feature
An AI summary for every module
Once learners go through a module, the instructor sees who finished it, where they stopped and how long it took.
The AI reads the same data and says it in plain words: which activity caused a drop-off, and what to change, like simplifying that activity or adding progress checks. The instructor gets a clear next step instead of a dashboard to decode.
Designing for AIHow we made the AI understandable and trustworthy
AI suggests, the instructor decides
Studio proposes chapter breaks and quiz spots, but nothing is published until the instructor reviews it. We added an explicit “Chunk Content” step after testing showed people didn’t trust silent automation.
Show where the AI acted
AI-created segments and activities are marked on the timeline, so instructors always see what was generated and can edit or remove it in one click.
Help on demand, not in the way
Learning Pal, the AI tutor, sits beside every lesson but only answers when a learner asks — support without interrupting the content.
Design system
The Studio component library: video player, timeline markers, activities and AI cards, built so design and engineering work from one source. Click any board to see it full size.
Take Interactive TourImpact
- Content Creation Speed: In beta trials, instructors reported a ~75% reduction in course update time (e.g. refreshing lecture modules that used to take hours now takes minutes).
- Student Engagement: 92% of instructors said students were more engaged when videos included Studio’s quizzes and polls.
- Platform Preference: 94% of pilot users preferred Engageli Studio.
What I learned
This project underscored the power of empathetic design and cross-functional collaboration. Working closely with product, engineering, and real educators taught me to prioritize features that solve genuine pain points. For example, learning that students often get stuck after videos led us to integrate the Learning Pal AI tutor – now on every lesson page, the “on-demand support” is just a click away.
I also learned to handle complexity gracefully: enabling AI-driven content generation could have overwhelmed users, but by iterating on prototypes we ensured the interface remained simple. Balancing fast innovation (AI analysis of videos) with UX clarity (straightforward timeline and activity controls) was a key challenge. In future iterations, we’ll build on these lessons by deepening user feedback loops (perhaps adding in-app tips or walkthroughs) and expanding features (like more activity types).
What I’d do differently now
I would put real lectures through the AI chunking much earlier. Our first prototypes used clean sample videos, and it took real, messy classroom recordings to show us where instructors lost trust. Today, with stronger models, I would also flip the flow: let the AI draft a complete first module, and make the instructor’s job reviewing and refining it — while keeping every AI decision visible and easy to undo.
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