What parts of your training program are the most or least effective? When are your employees really engaged and when are they daydreaming? What training units / simulations / assessments / employee actions are most associated with learning? How does training influence the success of your employees and your organization? Would you like to be able to answer these questions? According to the ASTD 2012 State of the Industry Report, in 2011 U.S. organizations spent more than $156 billion on training, averaging just under $1200 per employee. For that kind of dough, companies want to see some results.
MOOCs (massive open online courses) are currently redesigning the educational and training landscape. In January 2013, the Harvard Business Review blog called “the advent of massively open online classes… the single most important technological development of the millennium so far.” Did you get that? The single most important technological development of the millennium so far.
Why are they making such a huge impact? The reasons are many and growing. Not only do they offer unprecedented scalability and access and challenge the long-held notion that content is king, but they can provide large amounts of user data. We’re not talking just how long people engage in a particular task or who got what question right; we’re talking the ability to track and analyze every aspect of the learner experience.
The current model in training analytics is “small data” – data based on reports, assessments, and so on from small numbers of learners. But MOOCs can provide data from millions of people and the data are collected at many different levels: the keystroke level, the question level, the learner level, the instructor level, the program level, and even the organizational level. This “big data” can be used to model learner and organizational characteristics and outcomes and, most importantly, to predict future trends and patterns. It can help organizations identify which programs are working and which are not, where additional training is required, and the best way to deliver that training.
In a 2012 report on educational data mining and learning analytics, the U.S. Department of Education’s Office of Educational Technology identified several questions that big data can help educators answer. Here are a few of them:
- What sequence of topics is most effective for a specific learner? When are learners ready to move to the next topic?
- What learner actions are associated with more learning? What actions indicate satisfaction, engagement, learning progress, etc.?
- What features of an online learning environment lead to better learning? What will predict learner success?
- When is intervention required?
When the entire learning process takes place online, the entire learning process can be tracked and analyzed, and the data generated goes far beyond what is available in a classroom. Students in MOOCs don’t just watch videos and answer questions – they interact with each other and with the instructor through discussion forums, social networks, blogs, and many other streams, leaving long and rich trails of digital data. These data can reveal trends and patterns that can’t be detected in traditional formats, and they allow us to move beyond what people are learning to how they are learning. As Coursera co-founder Daphne Koller said: “The availability of these really large amounts of data provides us with insights into how people learn, what they understand, what they don’t understand, what are the factors that cause some students to get it and others not that is unprecedented, I think, in the realm of education.”
This knowledge can be used to improve both instructor-led training (ILT) and online learning. Here are a few major areas where big data from MOOCs can inform training practice:
- Improving results. This is the obvious one. Of course the goal of all training is to increase employees’ skills and effectiveness. MOOC data can be analyzed on both micro and macro levels to improve individual and organizational results.
- Clustering and relationship mining. These two concepts have to do with discovering relationships between variables. The data can be used in many ways, such as for organizing employees with complementary skills into teams and work groups.
- Customizing programs on a large scale. MOOCs started out as a one-size-fits-all solution, but they are rapidly evolving into adaptive learning environments tailored to individual learners. In the near future, the learning experience will be optimized individually and in real time.
- Predicting future trends. What will the return on investment (ROI) be for your training program? Big data will help organizations predict the impact of training programs on individual, business-unit, and organizational success.
Businesses already use big data to make decisions about sales, financial services, advertising, risk management, pricing, supply chain management – you name it. But until MOOCs came on the scene, most organizations could not amass enough data to inform decisions about their training programs. Now data is being collected from millions of learners in virtual educational and corporate classrooms all over the Internet.
The field is very new and educators are just starting to realize the power of having this data available. In a first attempt to quantify this learning experience, Duke recently released a report on its first MOOC. The results provide insights not only into student achievements, but into their activities and outcomes, motivations and attitudes, and the factors that both promote and provide obstacles to learning. As more organizations collect, analyze, and (in true MOOC spirit) share their data, we will begin to develop new models to increase instructional efficiency and effectiveness. Smart companies will use that data to make sure they are getting the best possible return on investment in their training programs so they will have something to show for that $156 billion.
So, now you are convinced that the learning-framework is the way to go and that big data will transform your approach to training, but you don’t know where to start with the implementation? No worries – there’s a MOOC for that!
Source by Bryant Nielson
