When you think of inclusivity in EdTech product design, your mind probably jumps to accessible design principles. But truly inclusive design starts long before UX designers put pixels to prototypes. In fact, the seeds of inclusivity are planted in the earliest UX research stages. And it all begins with how you recruit and relate to test users.
Race, gender, and socioeconomic status are just a few factors that inform how users participate in your research initiative — if they participate at all. If participants feel put off by an insensitive word choice or a lack of recognition or empathy, you’re not going to get the feedback necessary to create a design that meets the needs of all of your users. And the very last thing you want is to alienate a group of users before they even engage with your product.
5 Inclusive Practices to Incorporate in Your Design Research
You need accurate and in-depth findings — findings that reflect the full spectrum of users your product is intended to serve. That’s the kind of research that lays the foundation for an essential and widely-adopted EdTech product. Here’s how to get started.
1. Be mindful of unconscious bias
You are an expert in EdTech, not other people’s experiences. The first step in conducting research responsibly is to uncover the inherent limitations of your perspective. Be honest about the biases you bring to the table. Generally, you want to avoid prescribing problems or using your participants to validate what you assume to be their experience. The more you can approach participants with an open, neutral curiosity, the less likely you are to “fill in the blanks” with your own assumptions and expectations. No research is without bias, but by bringing in multiple perspectives to examine your plans, scripts and findings, you have a better chance of identifying existing biases so they may be mitigated.
Racial bias
The first step in addressing racial bias in your work is to recognize that Black, Latine, and Indigenous populations are pressured to norm toward white hegemonic standards to succeed. The field of higher education is no exception. The history of racist practices in the US education system only amplifies the mistrust and antipathy BIPOC communities may feel toward predominantly white higher ed institutions.
If you’re a mostly white EdTech organization entering a mostly BIPOC space, keep this in mind. Any initial skepticism a BIPOC user base may feel toward you is rooted in their experience, and it’s up to you to build trust through transparency.
2. Make accommodations for low-income participants
As much as race and gender should be a consideration in the discovery phase of design, your participants’ socioeconomic status should be, too. If you decide to compensate participants for their feedback, make sure their compensation is fair. You must also make sure that their time commitment does not result in financial insecurity.
For instance, not all parents can carve out an hour of their working day to participate in a study or a survey. You also can’t assume they can travel to connect with your team, either. Parents who can participate during working hours likely have the privilege of a flexible work schedule and/or a salaried income. If you only incorporate feedback from this privileged niche group, your EdTech design won’t serve a diverse user base.
You have to meet your participants where they are (sometimes literally) for accurate data.
Bridging the digital divide
You may remember in the early days of the pandemic, students with limited Wi-Fi access had to drive to restaurant parking lots to attend their virtual classes. That experience underscored the importance of families’ access to tech resources. When conducting surveys or user testing, consider that lower-income students and parents may not have the resources or web access required to participate.
Here are some options to support those with limited access to tech:
- Phone calls
- Digital calls with or without video
- Asynchronous feedback with activities that could be downloaded or saved offline
3. Refrain from language that alienates your user base
Language that doesn’t consider your users’ lived experiences can inhibit honest feedback. Worse, it could dissuade participation altogether. One way to guarantee you’re not alienating users is to adopt an asset-based mindset rather than a deficit-based mindset.
Deficit-based thinking focuses on problems without context. A good example would be describing an individual as “homeless” (deficit-based) instead of “someone experiencing homelessness” (asset-based). “Homeless” puts the onus on the individual for their circumstances as opposed to the systems in place that led them to experience homelessness (e.g., housing costs, lack of mental health resources, etc.). An asset-based mindset takes into account the complexity of one’s experience.
Don’t “talk shop”
There may be certain idioms, jargon, or acronyms that are commonplace in your profession (or culture). But using them outside that context can be confusing for others. In research initiatives, using unfamiliar language can create walls that discourage participants from opening up. If you think your questions make you sound like a “Silicon Valley bro,” you’re probably not off-base.
Screen your questions for any words or terminology that may be incomprehensible or off-putting to the average user.
Avoid triggers
Consider all potential triggers that might affect your user base. This includes external, internal, trauma, and symptom triggers. Not everyone is going to feel comfortable sharing their experience, particularly if it’s very personal or traumatic.
One example: Openfield ran a project to support underserved students and reduce dropout rates. The reasons a student drops out of high school tend to be wholly personal. The causes range from a lack of financial resources, to a family tragedy, to learning differences.
As researchers, it’s our job to press until we get the answers we need to understand the heart of the problem. But if you force a participant to share very personal and sometimes upsetting information, they’re more likely to shut down or abandon the process altogether. If you have questions that require very personal information from your participants, communicate about it beforehand. You can give them the freedom to opt out or skip questions if they aren’t comfortable answering them. And always make sure that if you’re asking such personal questions, the answers are likely to have a direct impact on your final design direction. Make sure you can easily explain why their answers matter and will impact the work you’ve set out to do.
Another option is to phrase questions so that participants can share their stories under the guise of a third party. For example, say you want to know what a student’s challenges are in the classroom. You might phrase your question: “Please reflect on your personal lived experience or that of your friends to help us identify the top 3 most prevalent challenges.” This way, the participant doesn’t have to divulge whether it’s their experience or someone else’s.
4. Don’t confine participants to a single label on a multiple choice list
Multi-select questions are better than single-select when asking about a participant’s identity. This is to prevent one from feeling forced to choose one option that doesn’t quite fit. Multi-select is particularly helpful when asking about one’s race, ethnicity, or gender identity in a survey. Just make sure your multi-select answers cover a broad range of identities so participants don’t feel “erased.” You may also want to give users the option to sidestep identity-related questions if they prefer not to disclose certain demographic details.
Here’s an example of a multi-select question:
What best describes you? (Select all that apply)
- White
- Black or African American
- Hispanic or Latine
- East Asian (China, Japan, South Korea, Vietnam, Thailand, etc.)/East Asian American
- South Asian (India, Pakistan, Bangladesh, Sri Lanka, etc.)/ South Asian American
- Native American or Pacific Islander
- I prefer to self describe: _______________________
A note on gender identity
As a reminder, biological sex (male, female) is different from how a person chooses to identify regarding their gender. And because gender identities are varied, it’s important to include multiple options (e.g., male, female, trans, nonbinary, intersex). You should also present the option for your participants to self-describe. Phrases like “nonbinary” or “prefer to self-describe” are inclusive. You shouldn’t use the word “other” as an option as it can read as, well, othering.
5. Be transparent
When it comes down to it, transparency is key to creating trust between your UX researchers and your users. Without it, you won’t even get past the discovery phase of design. Be clear with stakeholders and users about how you plan to use their feedback. While it may be customary to hide who will be listening on calls or to BCC on emails, your participants should know who is receiving their information (and if it’s being shared). Being transparent with your user base will encourage more users to participate, especially as word of mouth can encourage a larger, more diverse audience to participate.
Inclusive Research Practices Are Worth the Discomfort
It’s understandable to feel some trepidation as you’re soliciting feedback from someone with a background vastly different from yours. This is where you can lean on user feedback and co-creation sessions to make sure they are included in the process and informing your research initiatives. Empower users to speak up at any part of the process, too. When they do speak up, repeat to them what they have shared to confirm that you interpreted their feedback correctly.
You will inevitably make mistakes as you go. You will feel uncomfortable about those mistakes. Education is full of “life-long learners,” and that goes for EdTech UX, too. If you can push through the discomfort enough to listen, learn, and adjust, it will speak volumes to your user base in the form of an inclusive product that makes users — all of them — feel seen and supported.
