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

Twitter, Smug Intellectualism, Trolls, and Philosophical Charity

Yesterday, I witnessed an exchange on Twitter that continues to bother me.

In the interest of citing sources and providing evidence, my first inclination is to embed the public conversation here. But, especially in this current climate, citing a personality in association with a controversial piece of content frequently serves to distract from the specific issues at hand. It is also not my intention to ‘call out’ any particular individual, but rather to use the situation as an opportunity to think through some issues related to philosophical charity, social media, and anti-intellectualism. Read more

Death is a Fact of Life

“Phamous is dead”

Those were the first words I heard my wife say as she entered the house after morning chores. She had obviously been crying.

It had been a tragic accident, most details of which are still a mystery. Strong and magnificent though they may be, horses are also surprisingly delicate. Like gigantic toddlers, horses also have an uncanny ability to get themselves into trouble and in the most unusual ways.

This was not the first time I have been exposed to equine death. A year or so ago, I witnessed an accident during an event on cross country.  I was called to assist in restraining the horse as veterinarians were faced with no other humane alternative than to give it the ‘pink juice.’ It was hard. I cried. Read more

Please stop putting images in your email signature

This is something that has bothered me for a long time. It’s time I spoke up about it.

I like email signatures. I like having a person’s contact information and title at the ready. But email signatures should be simple. There are three reasons why no one should ever put images in their email signature, no matter how tempting it might be:

  1. It’s Wasteful – images are attachments. No matter how cute and insignificant they may look in a single email, they still serve to unnecessarily bloat the size of your message. Even as the cost of disk storage continues to decrease according to Kryder’s Law, that’s no excuse to unnecessarily inflate the size of your email message, as well as the size of every subsequent forward and reply.
  2. It’s Ineffective – I have yet to see any evidence that images in email signatures ‘work.’ If they contain text, they are unsearchable. Within an organization, it might be tempting for marketing departments to encourage employees to use branded image to promote a product or event, but individual employees have a tendency to poorly execute marketing’s best intentions. Worse yet, people don’t tend to touch their email signatures for a long time, which means that signature images are frequently off brand and out of date. The result is not an effective marketing strategy. To the contrary, the results are often quite embarrassing.
  3. It’s Inefficient – for me, this is really the crux of the matter. It goes back to the fact that images are attachments. How often have I searched for an email from someone in order to find a particular attachment, only to find that EVERY message from that person contains an attachment? In the absence of being able to use ‘attachment/no-attachment’ as a search criterion, I have to either build a more complex query (based on attachment size, for example), or else go through individual emails one by one within a large search domain. Either way, the process of simply finding an email becomes an ordeal. It unnecessarily wastes my time, and results in a non-trivial amount of resentment.

The temptation to put an image (or several images) in your email signature can be great. We want our social media links to ‘pop.’ we want to highlight our personal or corporate identity by including a logo. But a signature is not a marketing tool. It is not a business card. It is powerful in its simplicity.

When crafting your signature, think about the information that would be inconvenient for your recipient NOT to have, and include that. Next time you’re tempted to fancify your signature with wiz bang graphics, don’t.

Does Student Success start with Diversity in Higher Ed Administration?

Twitter has finally begun to add tools to mitigate harassment.

Harassment on Twitter has been a huge problem in recent years, and the amount of poor citizenship on the platform has only increased post-election. Why has it taken so long to respond? On the one hand, it is a very hard technical problem: how can users benefit from radical openness at the same time as they are protected from personal harm? In certain respects, this is a problem with free speech in general, but the problem is even greater for Twitter as it looks to grow its user base and prepare for sale. On the other hand, Twitter insiders have said that dealing with harassment has simply not been a priority for the mostly white male leadership team. Diversity is famously bad at Twitter. A lack of diversity within an organization leads to a lack of empathy for the concerns of ‘others.’ It leads to gaps in an organization’s field of vision, since we as people naturally pursue goals that are important to us, and what is important to us is naturally a product of our own experience. Values create culture. And culture determines what is included and excluded (both people and perspectives). 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.

Five Must-See Analytics Sessions at EDUCAUSE 2016

EDUCAUSE is big.  Really big. With so much to take in, conference-goers (myself included) are easily faced with the paradox of choice: a sense of paralysis in the face of too many options.  To help myself and others, I have scanned this year’s conference agenda and selected five presentations that I think will be individually strong, and that as a group offer a good overview of the themes, issues, and state of analytics in higher education today.

Learning at Scale with Analytics: Findings from the Field and Open Questions

Wednesday, October 26, 2016 | 3:40 PM – 4:30 PM | Meeting Room 204B

Moderated by Michael Feldstein (e-Literate), and featuring John Whitmer (Blackboard), Russ Little (PAR), and Jeff Gold (California State University), and Avi Yashchin (IBM), this session promises to provide an engaging and insightful overview of why analytics are important for higher education, the biggest challenges currently facing the field, and opportunities for the future.  Although most of the speakers are strongly affiliated with vendors in the analytics space, they are strong data scientists in their own right and have demonstrated time and time again that they do not shy from critical honesty.  Attend this session for a raw glimpse into what analytics mean for higher education today.

Deploying Open Learning Analytics at National Scale: Lessons from the Real World

Thursday, October 27 | 8:00am – 8:50am | Ballroom A, Level Three

Jisc is a non-profit company that aims to create and maintain a set of shared services in support of higher education in the UK.  The Effective Learning Analytics project that Michael Webb will discuss in this session has aimed to provide a centralized learning analytics solution in addition to a library of shared resources.  The outputs of this project to date have valuable resources  to the international educational analytics community in general, including Code of practice for learning analytics and Learning Analytics in Higher Education.  Jisc’s work is being watched carefully by governments and non-governmental organizations worldwide and represents an approach that we may wish to consider emulating in the US (current laws notwithstanding).  Attend this session to learn about the costs and opportunities involved in the development of a centralized approach to collecting and distributing educational data.

Founding a Data Democracy: How Ivy Tech is Leading a Revolution in Higher Education

Thursday, October 27 | 1:30pm – 2:20pm | Meeting Room 202A/B, Level Two

The higher education community is abuzz with talk of how data and analytics can improve student success.  But data and analytics are worthless unless they are put in the hands of the right people and in the right ways.  I am really interested to see how Ivy Tech has worked to successfully democratize access to information, and also about the ways that access to data has driven the kind of institutional and cultural change necessary to see the most significant results from data-driven initiatives.

Analytics and Student Success: Research and Benchmarking

Thursday, October 27 | 8:00am – 8:50am | Meeting Room 304A/B, Level Three

Everyone’s talking about analytics, and every institution seemingly has the will to invest.  Attention paid to analytics in media and by vendors can lead to the impression that everybody’s doing it, and that everyone who’s doing it is seeing great results.  But the truth is far from the case.

I’m not the greatest fan of benchmarking in general.  Too often, benchmarking is productized by vendors and sold to universities despite providing very little actionable value.  Worse yet, they can exacerbate feelings of institutional insecurity and drive imprudent investments.  But when it comes to analytics, benchmarking done right can provide important evidence to counteract misperceptions about the general state of analytics in the US, and provide institutions with valuable information to inform prudent investment, planning, and policy decisions.  In this presentation, I look forward to hearing Christopher Brooks and Jeffery Pomerantz from EDUCAUSE discuss their work on the analytics and student success benchmarking tools.

Building with LEGOs: Leveraging Open Standards for Learning Analytics Data

Friday, October 28 | 8:00am – 8:50am | Meeting Room 304C/D, Level Three

I am a huge advocate of open standards in learning analytics.  Open standards mean greater amounts of higher quality data.  They mean that vendors and data scientists can spend more time innovating and less time just trying to get plumbing to work.  In this interactive presentation, Malcolm Brown (EDUCAUSE), Jenn Stringer (University of California, Berkeley), Sean DeMonner (University of Michigan-Ann Arbor), and Virginia Lacefield (University of Kentucky) talk about how open learning standards like IMS Caliper and xAPI are creating the foundation for the emergence of next generation learning environments.