We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today!
This is a guest post by professor, Reynol Junco
We’re in the middle of an Educational Technology (“ed-tech”) startup boom.
Research by GSV Advisors shows a sharp increase in investments in education companies almost doubling between 2007 and 2011 to $930 million. Data from the National Venture Capital Association shows that investment in ed-tech companies has almost tripled between 2002 and 2011.
It’s no surprise that the number of ed-tech startup companies has grown exponentially and will continue to do so into the foreseeable future.
The market is flooded with these startups and clearly, there is a great deal of interest from venture capital firms.
Many ed-tech startups typically build their product because one of the founders had a particular issue in college that they think can be addressed with a new technology or by building an education version of an existing technology.
For instance, a founder might think “I used to forget to bring my chemistry book to class so why don’t I develop a cool app that automatically texts students right before a class where they need a book?” (Please note that I did not base this example on a real startup; however, I wouldn’t be surprised if such a product existed). Other ed-tech startups have an idea they think should result in improved student outcomes and they run with it.
I hate to break it to you…
This may come as a surprise to ed-tech companies, but you’re not going to invent the next big thing by shooting in the dark. Without knowing the research on how students learn and develop as well as the literature on how technology affects student outcomes, the chances of your startup magically creating student success are almost nonexistent.
Indeed, it’s not the technology that generates learning, but the ways in which the technology are used.
Ed-tech startups rarely, if ever, talk with educators about designing their product. You’d be surprised at the number of emails I get asking me to comment on a product after it has been conceptualized, built, and tested. I have dubbed these messages “tell us how cool our product is” emails.
Startups in other fields don’t behave this way. Imagine a genomics startup that didn’t talk to medical researchers and/or didn’t base their products on research in the biotech field. Such a company would never exist, let alone be funded by a venture capital firm.
Yet, in this new boom investors are more than happy to fund an ed-tech startup whose employees have never bothered to read a single piece of educational research. My fellow academic rebel Audrey Watters famously commented about a $2.5 million investment in Codecademy, “Wow, bullshit badging and shitty pedagogy wins the day in ed-tech investing.”
Educators and researchers who know about how students learn know that there is nothing special about Codecademy. The flashing lights and pretty buttons fool the venture capital firms and foundations that invest in these kinds of startups. Since funders also know next to nothing about how students learn, of course these ideas sound amazing.
Where’s the data?
Lastly, there is the issue of adoption of new technologies by educational institutions. Higher education faculty and administrators are already distrustful of startups because there is inherent skepticism about for-profit ventures. Ed-Tech companies have no data showing that their product does what they say it does. Indeed, in their Unleashing the Potential of Educational Technology report the U.S.’s Council of Economic Advisers politely wrote, “It is difficult for producers of these technologies to demonstrate the effectiveness of their products.”
It’s actually not that difficult to demonstrate effectiveness, it’s just that startups have been unwilling and/or do not have the expertise to do so. Having evidence is crucial in convincing educators to adopt a new technology — don’t tell them that your new technology is effective in improving student learning, show them.
Here are some suggestions for getting it right:
- Collaborate with an academic when developing your product. You don’t have to have an educator or a researcher directing what you do, but at least get some input so that you know you are building a product that might have some utility.
- Assess your outcomes. In business-speak this usually means “provide financial figures to show you are being successful;” however, what you must provide to educators are data that show that using your product does what you say it does. Did you develop an app that’s supposed to increase student lecture attendance? Then design a study with your academic collaborator to evaluate differences in attendance rates between app users and nonusers. Remember, data are the lingua franca of academic circles.
- Refine your technology based on assessment data. This goes beyond bug fixes and UI design. In collaboration with your academic collaborator, you’ll likely discover ways to make your product more robust in doing what you want it to do. Recently, my colleagues and I published a paper showing that using Twitter to continue discussions outside of class was positively related to student engagement and learning; however, using Twitter as a back channel for in-class discussions was not. If your outcome studies don’t yield a positive effect, at least you’ll have some great data with which to refine your product.
- Publish what you find. No matter what you believe about the current academic publishing process, the academic culture values results presented through peer-reviewed academic publications more than blog posts, presentations, and “white papers” (a phrase I absolutely despise, but that’s a topic for another day). Not only will you have clout in academic circles when you publish data, your academic collaborator will have an additional benefit of working with you (another publication) that will help them in their tenure and promotion process.
- Learn about the culture of academia and help academia learn about the culture of startups. This will help you understand institutional resistance to new technologies in education as well as help you understand how to best approach your new academic partners.
Reynol Junco is a Faculty Associate at the Berkman Center for Internet & Society at Harvard University. He researches the impact of social technologies on college students. Follow Rey on Twitter and read about his research on his blog.
The opinions expressed in this article are those of the author, and they do not reflect in any way those of the institutions to which he is affiliated.
[Top image credit: wavebreakmedia ltd/Shutterstock]
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Learn more about membership.