How ed tech marketers are bad for higher education

A lot of ed tech marketers are really bad. They are probably not bad at their ‘jobs’ — they may or may not be bad at generating leads, creating well-designed sales material, creating brand visibility. But they are bad for higher education and student success.

Bad ed tech marketers are noisy. They use the same message as the ‘competition.’ They hollow out language through the use and abuse of buzz words. They praise product features as if they were innovative when everyone else is selling products that are basically the same. They take credit for the success of ‘mutant’ customers who — because they have the right people and processes in place — would have been successful regardless of their technology investments. Bad marketers make purchasing decisions complex, and they obscure the fact that no product is a magic bullet. They pretend that their tool will catalyze and align the people and processes necessary to make an impact. Bad marketers encourage institutions to think about product first, and to defer important conversations about institutional goals, priorities, values, governance, and process. Bad marketers are bad for institutions of higher education. Bad marketers are bad for students.

Good marketing in educational technology is about telling stories worth spreading. A familiar mantra. But what is a story worth spreading? It is a story that is honest, and told with the desire to make higher education better. It is NOT about selling product. I strongly ascribe to the stoic view that if you do the right thing, rewards will naturally follow. If you focus on short-term rewards, you will not be successful, especially not in the long run.

Here are three characteristics of educational technology stories worth telling:

  1. Giving credit where credit is due – it is wrong for an educational technology company (or funder, or association, or government) to take credit for the success of an institution. Case studies should always be created with a view to accurately documenting the steps taken by an institution to see results. This story might feature a particular product as a necessary condition of success, but it should also highlight those high impact practices that could be replicated, adapted, and scaled in other contexts regardless of the technology used. It is the task of the marketer to make higher education better by acting as a servant in promoting the people and institutions that are making a real impact.
  2. Refusing to lie with numbers – there was a time in the not-so-distant past when educational technology companies suffered from the irony of selling analytics products without any evidence of their impact. Today, those same companies suffer from another terrible irony: using bad data science to sell data products. Good data science doesn’t always result in the sexiest stories, even it it’s results are significant. It is a lazy marketer who twists the numbers to make headlines. It is the task of a good marketer to understand and communicate the significance of small victories, to popularize the insights that make data scientists excited, but that might sound trivial and obscure to the general public without the right perspective..
  3. Expressing the possible – A good marketer should know their products, and they should know their users. They should be empathetic in appreciating the challenges facing students, instructors, and administrators and work tirelessly as a partner in change. A good marketer does not stand at the periphery.  They get involved because they ARE involved.  A good marketer moves beyond product features and competitive positioning, and toward the articulation of concrete and specific ways of using a technology to meet the needs of students, teachers, and administrators a constantly changing world.

Suffice it to say, good marketing is hard to do. It requires domain expertise and empathy. It is not formulaic. Good educational technology marketing involves telling authentic stories that make education better. It is about telling stories that NEED to be told.

If a marketer can’t say something IMPORTANT, they shouldn’t say anything at all.

Using Analytics to Meet the Needs of Students in the 21st Century

Below is excerpted from a keynote address that I delivered on November 8, 2016 at Texas A&M at Texarkana for its National Distance Education Week Mini-Conference


Right now in the US, nearly a quarter of all undergraduate students — 4.5 million — are both first generation and low income.

Of these students, only 11% earn a bachelors degree in under 6 years. That’s compared to the rest of the population, which sees students graduate at a national rate of 55%. What this means is that 89% of first generation, low income students stop out, perpetuating a widespread pattern of socio-economic inequality.

Since 1970, bachelors degree attainment among those in the top income quartile in the US has steadily increased from 40.2% to 82.4 in 2009. By contrast, those in the bottom two income quartiles have seen only slight improvements: under an 8 point increase for the bottom two quartiles combined. In the US, a bachelors degree means a difference in lifetime earnings of more than 66% compared to those with only high school. Read more

Product as Praxis: How Learning Analytics tools are ACTUALLY Differentiated

I’ve been thinking a lot recently about product as praxis. Without putting too much conceptual weight behind the term ‘praxis,’ what I mean is merely that educational technologies are not just developed in order to change behavior. Ed tech embodies values and beliefs (often latent) about what humans are and should be, about what teaching and learning are, and about the role that institutions should play in guiding the development of subjectivity. As valued, educational technology also has the power to shape, not just our practices, but also how we think.

When thought of as praxis, product development carries with it a huge burden. Acknowledging that technology has the power (and the intention) to shape thought and action, the task of creating an academic technology becomes a fundamentally ethical exercise.

Vendors are not merely responsible for meeting the demands of the market. ‘The market’ is famously bad at understanding what is best for it. Instead, vendors are responsible for meeting the needs of educators. It is important for vendors to think carefully about their own pedagogical assumptions. It is important for them to be explicit about how those assumptions shape product development. The product team at Blackboard (of which I am a part), for example, is committed to values like transparency and interoperability. We are committed to an approach to learning analytics that seeks to amplify the power existing human capabilities rather than exclude them from the process (the value of augmentation over automation). These values are not shared by everyone in educational technology. They are audacious in that they fly in the face of some taken-for-granted assumptions about what constitute good business models in higher education.

Business models should not determine pedagogy. It is the task of vendors in the educational technology space to begin with strong commitments to a set of well-defined values about education, and to ensure that business models are consistent with those fundamental beliefs. It will always be a challenge to develop sustainable business models that do not conflict with core values. But that’s not a bad thing.

When it comes to the market for data in eduction, let’s face it: analytics are a commodity. Every analytics vendor is applying the same basic set of proven techniques to the same kinds of data. In this, it is silly (and even dangerous) to talk about proprietary algorithms. Data science is not a market differentiator.

What DOES differentiate products are the ways in which information is exposed. It is easy to forget that analytics is a rhetorical activity. The visual display of information is an important interpretive layer. The decisions that product designers make about WHAT and HOW information is displayed prompt different ranges of interpretation and nudge people to take different types of action. Dashboards are the front line between information and practice. It is here where values become most apparent, and it is here where products are truly differentiated.