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— by mindflash
I recently attended the American Society for Training and Development’s 2012 TechKnowledge conference, where over 1,200 attendees and 70 exhibitors got together in Las Vegas to talk about training, do some networking, and discuss the future of learning and technology.
One theme that resonated most for me was the increased emphasis on data and data analysis — or what’s being called Big Data. This isn’t the traditional, Kirkpatrick-style learning data most people think about, like post-workshop evaluations and test scores. Big Data is a term that you may not of heard of before but will hear a great deal of in the near future. In his recent New York Times piece, “The Age of Big Data,” Steve Lohr explains Big Data this way: “What is Big Data? A meme and a marketing term, for sure, but also shorthand for advancing trends in technology that open the door to a new approach to understanding the world and making decisions. There is a lot more data, all the time, growing at 50 percent a year, or more than doubling every two years, estimates IDC, a technology research firm.”
Big data doesn’t just describe the volume of data being collected, though that is part of the equation. It refers to brand-new types of data being collected that were previously unavailable, but that can now be analyzed thanks to rapid advancements in computer processing power, providing us with new answers to questions about how people learn and digest information.
Consider many of the automobiles you now see on the road. Years ago, when I would get my car serviced, it was often a manual — and time-consuming — process for the mechanic just to determine what was wrong with the engine. The last time I took my car to the mechanic, however, he was able to access the computer in the car and generate a report collected from data that hundreds of sensors throughout the vehicle picked up. That data enabled him to quickly determine the problem, and offered a solution.
The data collected by a car’s computer also provides a good example of how Big Data can impact an area that’s near and dear to the heart of learning professionals: performance support. For instance, I’m fairly skilled at parallel parking, but when a space is really small, I’ll likely call upon “performance support” to assist me with the task (in this case, my wife, who steps outside and lets me know how much room I have).
In my father-in-law’s car, though, the moment the car’s put in reverse, the dashboard shows a wide-angle video display of the rear of the car. Overlayed on the video image is a green/yellow/red distance guide that lets me know how close I am to the car behind me. The computers and sensors collecting data and responding to it in real time weren’t available even a few years ago. But now, they provide a great example of performance support, generated by Big Data.
Many of these technological advances have not yet reached the learning field, but that parking example very well represents the change Big Data will have on the industry. My wife stepping out of the car to assist me with parking is metaphorically what we have now — a need for performance support, which is where the learning and performance professional comes in. The problem right now is that by the time we develop and provide the tools to help our learners, it’s often too late to help them solve their immediate problems. Further, the support we provide often involves a stoppage of work.
Now imagine a workplace system in which computers could analyze every action a worker makes, and respond in real-time, sensing when a worker required support and identifying the appropriate support tool right away, within the task’s workflow. Big Data could make that possible.
In addition to providing work-based performance support, Big Data will also enhance our formal learning programs. New data analysis systems will be able to better track the user experience so that we’re not just measuring if someone selected the right answers at the end of a module. We’ll instead be able to track the journey the employee took during the learning experience, seeing where they might have gotten stuck, where things might have been too easy, and how effectively they are able to apply a skill.
It’s not science fiction; it’s actually happening today. Just this month, a report from the WICHE Cooperative for Educational Technologies suggested that new students are more likely to drop out of online colleges if they take full course loads than if they enroll part time. This finding, which challenges long-term assumptions about college drop-outs, was only possible because of a research project using Big Data analysis.
That report shows that the impact of Big Data has already arrived in academic education, so it’s arrival in corporate education cannot be far behind.
David Kelly is the director of training at Carver Federal Savings Bank and ember of the ASTD National Advisors for Chapters. He is also the author of the blog Misadventures in Learning, where he discusses the future of the learning field and curates the backchannel of learning conferences.
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