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MOOC Analytics: What Corporate Training Can Learn From Big Data

MOOC Analytics: What Corporate Training Can Learn From Big Data

What parts of your training program are most or least effective? When are your employees really engaged and when are they daydreaming? What training units / simulations / evaluations / 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 ASTD’s 2012 State of Industry Report, in 2011 American organizations spent more than $ 156 billion on training, averaging just under $ 1200 per employee. For that type 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 most important technological development of the millennium so far.” Did you get it? The most important technological development of the millennium so far.

Why are they having such a big 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, they can also provide large amounts of user data. We are not talking about how much time people spend on a particular task or who answered the question well; we are talking about the ability to track and analyze all aspects of the student experience.

The current model of training analysis is “small data”: data based on reports, assessments, and so on. of a small number of students. But MOOCs can provide data from millions of people, and the data is collected at many different levels: the keystroke level, the question level, the student level, the instructor level, the program level, and even the level. organizational. This “big data” can be used to model the characteristics and results of the learner and the organization and, more 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 US Department of Education’s Office of Educational Technology identified several questions that big data can help educators answer. Here are some of them:

  • Which sequence of topics is most effective for a specific student? When are students ready to move on to the next topic?
  • What student actions are associated with increased learning? What actions indicate satisfaction, commitment, progress in learning, etc.?
  • What characteristics of an online learning environment lead to better learning? What will predict student 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. MOOC students not only watch videos and answer questions, but interact with each other and with the instructor through discussion forums, social media, blogs, and many other streams, leaving long and rich traces of digital data. This data can reveal trends and patterns that cannot be detected in traditional formats and allows us to go beyond what people are learning to how they are learning. As Coursera co-founder Daphne Koller put it: “The availability of these really huge amounts of data gives us information about how people learn, what they understand, what they don’t understand, what are the factors that cause some students to get it and others that they are unprecedented, I think, in the field of education. “

This knowledge can be used to enhance both instructor-led training (ILT) and online learning. Here are some important areas where MOOC big data can inform training practice:

  • Improving the results. This is the obvious one. Of course, the goal of all training is to increase the skills and effectiveness of the employees. MOOC data can be analyzed at both the micro and macro levels to improve individual and organizational outcomes.
  • Clustering and Relationship Mining. These two concepts have to do with the discovery of relationships between variables. Data can be used in many ways, such as organizing employees with complementary skills into teams and workgroups.
  • Large-scale program customization. MOOCs started out as a one-size-fits-all solution, but are rapidly evolving into adaptable learning environments designed for individual learners. In the near future, the learning experience will be optimized individually and in real time.
  • Predicting future trends. What will be the return on investment (ROI) of 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 appeared on the scene, most organizations couldn’t accumulate enough data to inform decisions about their training programs. Data is now collected from millions of students in educational and corporate virtual classrooms on the Internet.

The field is very new and educators are beginning to realize the power of having this data available. In a first attempt to quantify this learning experience, Duke recently published a report on its first MOOC. The results provide information not only on the achievements of the students, but also on their activities and results, motivations and attitudes, and the factors that promote and hinder learning. As more organizations collect, analyze and (in true MOOC spirit) share their data, we will begin to develop new models to increase the efficiency and effectiveness of instruction. Smart companies will use that data to make sure they are getting the best possible ROI on their training programs so they 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 implementation? Don’t worry, there is a MOOC for that!

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