Are We There Yet? Impactful Technologies and The Power to Influence Change
A Q&A with Ellen Wagner
Learning analytics, augmented reality, artificial intelligence, and other new and emerging technologies seem poised to change the business of higher education — yet, we often hear comments like "We're just not there yet…" or "This is a technology that is just too slow to adoption…" or other observations that make it clear that many people — including those with a high level of expertise in education technology — are thinking that the promise is not yet fulfilled. Here, CT talks with veteran education technology leader Ellen Wagner, to ask for her perspectives on the adoption of impactful technologies — in particular the factors in our leadership and development communities that have the power to influence change.
"It becomes harder and harder to justify not being interested in putting data back to work to answer questions in support of the success of the enterprise." — Ellen Wagner
Mary Grush: What do you find, when you look at the adoption of new and emerging technologies — particularly those that reputedly have the potential to create the biggest changes at our institutions? What factors influence acceptance and adoption on our campuses and within our development communities?
Ellen Wagner: Digital learning professionals working across the full array of institutions, enterprises, and agencies that make up the learning and development ecosystem know how important it is to stay ahead of the curve on trends likely to influence the industry as a whole. This is especially true about staying abreast of new competencies and skills that will likely be needed to keep up with the capabilities that new digital tech tools enable. In the current era, some learning professionals are beginning to speak of artificial intelligence as the next big thing in our organizations; others of us are just beginning to make peace with the idea that our futures will demand that we develop more than a passing familiarity with analytics dashboards and evaluation methods. I expect that more than a few of us will become increasingly conversant with techniques of data-driven decision making. But so far, the current bubbling angst about changes on the horizon bears many similarities to prior periods of bubbling angst that eventually calm down after a few incremental changes appear in the workplace.
Grush: Let's look at one specific example. Let's take a big one: learning analytics. What should we be asking ourselves?
Wagner: After 10 years of significant interest in learning analytics, commercial product development in student success software products, in foundation initiatives exploring various dimensions of student success, intervention measurement, college completion, retention and persistence studies, why do you suppose learning analytics have not lived up to all of its expectations?
I personally think it has a lot to do with overselling and underdelivering on technology as the innovation — rather than as the solution to a problem. It's too much touting of innovation wrapped up in the tools, rather than in what people are doing with the tools. This is not to say that software isn't innovative. But with education technology, it's easy to forget that the software is the means to the end. It is what we use to solve our problems at hand. This is just one of the issues we should be thinking about.
Grush: What is one of the key things we should be considering when we look at how we are using our data in higher education? What's the opportunity we may be missing? Of course there are many things you could point to… but what would you pick to make people aware of?
Wagner: Today, data are both stored and generated by use in learning technology tools and resources. Efforts are increasingly going toward collecting and actively using those data in real time to improve user results and system throughput.
The current shift in expectations around future skills development is emerging from scientific disciplines rather from learning and development disciplines. This is likely to spark more new, and different learning technology solution conversations than have been sparked in the past. For example: how to take learning data from our users, on a continuous basis, to evaluate our work formatively while we are doing it.
Grush: Let's look a little harder at the realm of digital learning or eLearning professionals. How are these professional positions changing, and could we expect change that will create a professional environment that's better suited for technology adoption?
Wagner: It used to be that the people interested in eLearning typically came to their eLearning jobs from other learning organizations — training departments, corporate universities, on-boarding centers, compliance centers, colleges or universities, or counseling and testing centers. eLearning positions typically called for experience in training, teaching, and curriculum design, with degrees in education, psychology, HR, ID, training, and communications. Graduate degrees in education technology and instructional design provided the experience with theoretical knowledge and research methods. The ability to add certifications and credentials from professional associations and from technology companies themselves helped expand technical knowledge of an ever-evolving field.
However, as the Web increasingly became the preferred medium of expression, especially for eLearning, online learning, and digital learning, more and more User Experience (UX) Designers found their way into instructional design studios, creating rich, engaging instructional teaching, training, and learning resources, environments, and assets. "Accidental" instructional designers found their way into the craft of ID by coming from sales organizations and product organizations. Accidental IDs studied ID models and methods through self-help curricula and online courses, and through the use of rapid authoring tools as well as through the support and encouragement of professional communities including the eLearning Guild communities, Articulate's eLearning Heroes, AECT, EDUCAUSE, and the Online Learning Consortium, to name just a very few examples. Other "accidental" IDs joined the learning and development professional ranks after shifting from academic, instructional, and information technology-focused positions in institutions, agencies, and enterprises to jobs that focused more on the users, and less on the platforms. They, too, often found their ID-specific skills being augmented by short courses, workshops, and Web casts from associations, communities of practice, and from commercial providers of professional development resources.
Grush: But what is happening now?
Wagner: These days, with data from organizational transactions, platforms, assessments, engagements, and interactions surrounding us, people from across lines of business are increasingly interested in taking a look at these data, in conjunction with other organizational performance data, to seek ways to improve enterprise performance. What if we could compare investments in learning experiences and interventions used in the workplace, training, product development, and even experimental testing settings with other measures, such as sales performance, product rollouts, or employee retention? It becomes harder and harder to justify not being interested in putting data back to work to answer questions in support of the success of the enterprise. In doing so, it becomes harder and harder to separate learning functions from the rest of the enterprise. This is a significant shift in the role that learning enterprises can play in today's enterprises.
Grush: So is the interest in more of a scientific, "learning engineering" approach coming from the instructional design community? Or are IDs maybe even just feeling themselves swept along — which is of course a potential recipe for negativity.
Wagner: Today's rising interest in learning engineering is not necessarily coming from learning professions themselves. Some of the biggest growth in interest is coming from professionals working in hard sciences — including computer science and data science, to name two important examples. These are all environments where interest in using emerging new media such as augmented and virtual reality is high, and comfort in dealing with large experiments is significant. Perhaps even more important, there is willingness to engage in large-scale research that is pushing data analysis and evaluation comfort levels past where traditional providers of ID products and services are willing to go. Big data research methods, coming from computer science and data science, are starting to challenge education researchers to reconsider their entire approach toward social science research modeling.
Grush: It sounds like the professionals covering instructional design and the learning sciences are dealing with a complex set of issues that could impact technology adoption and application.
Wagner: Welcome to the flexible, frustrating ambiguity of the field of instructional design, sometimes called instructional systems design, sometimes called learning design — which is now also featuring branches of learning experience design — with instructional and education technology, and on rare occasion, with human performance technology thrown in for good measure.
Grush: I know there are no quick fixes, but is there something relatively simple that could be done to move traditional ID more towards the learning sciences?
Wagner: Well, it could be that one of the fruitful avenues for exploration is for instructional designers to revisit the literature and practices of learning sciences, and to reclaim them for the practice of ID. There is a rich body of ID literature that is available to be shared with those coming from the learning sciences.
Grush: Circling back to data, what is important to do in higher education to use our data well?
Wagner: As data makes its way into our decision making paradigms, and as we have technology platforms available in workplaces and on campuses to link learners with assets and experiences, we need to consider what it takes to ensure that those platforms link learners to the learning experiences that they desire to achieve their goals and for enterprises to realize a return on investment.
[Editor's note: Ellen Wagner is the founder and general manager of North Coast Eduvisory LLC. She can be contacted at [email protected]]