AI-Powered User Research for EdTech: Learners, Educators, and Administrators

AI-Powered User Research for EdTech: Learners, Educators, and Administrators

The short answer: EdTech user research has a unique challenge — you have at least three distinct user types, each with different goals and constraints. AI interview platforms like Koji let EdTech teams run parallel research streams with all three audiences simultaneously, without scheduling headaches or research team scale limitations.

---

The EdTech Research Challenge

Educational technology sits at the intersection of consumer product design and institutional purchasing decisions. This creates research complexity that other software categories do not face:

Multiple stakeholders with conflicting priorities:

• Learners want engaging, flexible, low-friction experiences
• Educators want control, curriculum alignment, and evidence of outcomes
• Administrators want compliance, cost justification, and easy rollout

A product that perfectly serves learners may still fail because administrators cannot justify the purchase or educators cannot integrate it into their workflow.

Sensitive participant populations: Research with minors requires GDPR- and COPPA-compliant consent processes. Even adult learners studying sensitive topics (mental health, career transitions, personal finance) require careful ethical framing.

Geographic and language diversity: EdTech often operates across regions with different curricula, learning cultures, and language requirements. Research that captures this diversity requires multi-language capability.

Evidence-based purchasing decisions: Unlike consumer software, educational tools are often purchased based on evidence of efficacy. Administrators and district buyers want research data — which means EdTech companies need robust research programs just to support sales.

Koji addresses all of these challenges: GDPR-compliant interview design, multi-language support (60+ languages), async format that removes scheduling barriers, and automated report generation for efficacy documentation.

---

Three Research Streams EdTech Teams Must Run

Stream 1: Learner Research

Learner research focuses on the actual experience of using your platform. The goal is to understand motivation, engagement, barriers, and learning outcomes — from the learner's perspective.

Key research questions:

• What motivates them to use your platform vs. alternatives?
• Where do they drop off, and why?
• What does success feel like to them? (Often different from platform-defined completion metrics)
• What barriers exist to continued learning?

Koji setup for learner research:

• Use hybrid interview mode to mix structured progress tracking (scale questions) with open-ended experience capture
• Set interview duration to 8–10 minutes to respect learner time
• Use multilingual settings if your learner base is diverse
• Enable voice interviews for learners more comfortable speaking than typing

Sample question set for learner research:

1. Open-ended: "Tell me about the last time you used [platform]. What were you trying to accomplish?"
2. Scale (1–5): "How motivated do you feel to use [platform] regularly?" (1 = Not at all, 5 = Highly motivated)
3. Open-ended: "What is the hardest part about sticking with your learning goals?"
4. Single choice: "When you stop mid-lesson, what is usually the reason?" [Too long / Too hard / Got distracted / Finished what I needed]
5. Open-ended: "What would make you more likely to complete lessons you have started?"
6. Yes/No: "Do you feel like you are actually learning when you use [platform]?"
7. Open-ended (probed): "Tell me more about that — what gives you that impression?"

---

Stream 2: Educator Research

Educator research is often the most neglected stream — and the most consequential for retention. Educators are the primary decision-influencers for institutional renewals and the primary source of organic adoption within schools.

Key research questions:

• How does your platform fit (or not fit) into their existing curriculum?
• What is the overhead of integrating your tool into their workflow?
• How do they measure whether students are benefiting?
• What would make them recommend your tool to colleagues?

Koji setup for educator research:

• Use the company context feature to give the AI interviewer background on educational standards relevant to your platform
• Apply jobs-to-be-done methodology — educators hire EdTech tools to do specific jobs (save planning time, improve engagement, demonstrate outcomes)
• Use structured questions to benchmark NPS, ease of use, and curriculum alignment scores

Sample question set for educator research:

1. Open-ended: "Walk me through how you typically incorporate [platform] into your teaching."
2. Scale (1–5): "How easy is it to align [platform] content with your curriculum requirements?"
3. Open-ended: "What would need to change about [platform] for you to use it more frequently?"
4. Yes/No: "Have you recommended [platform] to a colleague in the past year?"
5. Open-ended: "What would make you more confident recommending it?"
6. Multiple choice: "Which of these would most improve [platform] for your classroom?" [Offline access / Better reporting / More curriculum alignment / Easier assignment integration / More student engagement features]

---

Stream 3: Administrator and Buyer Research

Administrators — department heads, curriculum directors, district IT — control purchasing decisions and renewals. Research with this group is essentially buyer research within an educational context.

Key research questions:

• How do they evaluate EdTech purchases?
• What evidence of efficacy do they need to justify renewal?
• What are the compliance and privacy requirements they are evaluating?
• What implementation support do they need?

Koji setup for administrator research:

• Use customer discovery methodology to understand the buying process
• Focus on structured questions that capture decision criteria and competitive alternatives
• Include questions about data privacy and compliance (a critical EdTech buying criterion)

Sample question set for administrator research:

1. Open-ended: "Take me through how your institution typically evaluates and decides on EdTech tools."
2. Single choice: "What is the primary factor in your renewal decision for a platform like this?" [Student outcomes / Ease of implementation / Teacher adoption / Cost / Data privacy compliance]
3. Open-ended: "What would you need to see from [platform] to justify another year of investment?"
4. Scale (1–10): "How confident are you in [platform] data privacy and compliance posture?" (1 = Not confident, 10 = Completely confident)
5. Open-ended: "What is the biggest implementation or rollout challenge you have faced with EdTech tools?"
6. Yes/No: "Do you currently have clear metrics for measuring the ROI of [platform]?"
7. Open-ended: "What metrics would be most meaningful to you?"

---

Running Parallel Research Across All Three Groups

One of Koji's core advantages for EdTech research is the ability to run three simultaneous studies — one per stakeholder group — and compare the findings.

How to set it up:

1. Create three separate Koji studies with the same research question but tailored question sets
2. Use the insights chat on each study to answer cross-study questions
3. Export data from each study for cross-group comparison
4. Look for misalignment between groups — this is where your biggest product risks live

What misalignment looks like in practice:

• Learners love the flexibility of your platform; educators say it is too unstructured for classroom use → You need a classroom mode
• Administrators cite strong data privacy posture; teachers cannot get individual student data without admin credentials → Permission model needs rework
• Learners report high satisfaction; educators do not see evidence of learning → In-platform progress metrics are not reaching the right audience

---

Sensitive Research: Ethical Considerations for EdTech

Research with minors: Koji's intake form supports consent collection. For research involving learners under 18, require parental consent before the interview begins by adding a consent checkbox to the intake form.

Topic sensitivity: Learning struggles, academic failure, and educational anxiety are sensitive topics. Frame questions carefully: "Tell me about a time when learning felt challenging" rather than "Tell me about times you have failed."

FERPA compliance: When conducting research with US institutional customers, be clear that you are collecting research data (not student educational records) and that participation is voluntary and anonymous.

Data minimization: Collect only what you need. Configure the intake form to ask only for the identifying information required for your research, and clearly explain why.

---

Using AI Research to Build the EdTech Evidence Base

A unique benefit of Koji for EdTech companies: your research doubles as product evidence. The reports Koji generates can be used in:

• Sales conversations: "Here is what 47 educators told us about how they use [platform] in their classrooms."
• Grant applications: Qualitative evidence of learner impact alongside quantitative metrics
• PR and content marketing: Anonymized quotes and themes from learner research
• Board reporting: Evidence of user satisfaction and stakeholder alignment

Koji's report publishing feature lets you create a public or password-protected URL for your research findings — making it easy to share with buyers, partners, or funders without giving them raw data access.

---

Structured Questions That Work Especially Well for EdTech

Koji's six question types map naturally to EdTech research needs:

See the structured questions guide for full setup details including how to configure scale labels and choice options.

---

EdTech Research Calendar

A systematic EdTech research calendar:

With traditional research methods, this calendar would require a full-time research team. With Koji, a solo researcher or PM can execute it sustainably.

---

Setting Up Your EdTech Research Program

Step 1: Create a study for each stakeholder group with custom question sets and interview modes as described above.

Step 2: Use the company context feature to upload your curriculum standards, product overview, and learning methodology — this helps the AI interviewer ask more relevant follow-up questions.

Step 3: Configure intake forms to collect segment data (educator level, subject area, grade level) without collecting personally identifying information unnecessarily.

Step 4: Set language preferences for international learner research — Koji supports 60+ languages for both voice and text interviews. See the multilingual research guide for setup.

Step 5: Build a participant panel from your existing user base. Use CRM import to bring in email lists segmented by user type (learner, educator, admin) for targeted outreach.

Step 6: Generate and publish reports after each research round. Koji's auto-generated reports include themes, sentiment, quotes, and individual insights — all shareable via URL.

---

Related Resources

• Structured Questions in AI Interviews
• Multi-Language User Research: How to Interview Participants in Any Language
• How to Customize Your Research Study: Branding, Landing Pages, and Intake Forms
• Company Context: How to Make Your AI Interviewer a Domain Expert
• How to Set Up AI Voice Interviews: A Researcher's Complete Guide
• Research Participant Incentives: How Much to Pay and What to Offer