When learners interact with content in your course, they leave behind ‘digital breadcrumbs,’ so to speak, which offer clues about the learning process. We’re now able to collect and track this data through learning management systems (LMSs), social networks, and other media that measure how students interpret, consider, and arrive at conclusions about course material.
The good news is that this information–called Big Data–can do wonders for personalized instruction, especially within the e-learning industry. The not-so-good news is that the rise of Big Data brings with it many risks and ethical dilemmas, all of which need to be addressed before we move forward with this new approach.
The following are a few ways Big Data is expected to help education in the near future:
1. Feedback: Big learning data can be informative from a feedback and context perspective. Because somebody often might fail at a topic but not know why he is failing, it becomes interesting when the learner can look not just at himself, but at other people who have had the same experience. He may certainly get an insight either that would explain it so he is not frustrated or that he could use to correct it so that he could succeed again.
2. Motivation: If you implemented big data in a comprehensive way, learners potentially become invested in inputting data to the process because they see the impact of how it works.
3. Personalization: Big Data will change the way we approach e-learning design by enabling developers to personalize courses to fit their learners’ individual needs. This will allow e-learning professionals to continue to raise the standard for effective and exceptional e-learning courses.
4. Efficiency: Big Data can save us hours upon hours of time and effort when it comes to realizing our goals and the strategies we need to achieve them. Say someone wants to take job B, having done job A for a year. Big data would indicate, first of all, the number of people who did job A and who then got to job B. Of the people who got job B, what preparation did they have? It also would indicate which learning programs were most effective, and what the timing was for when they attempted to change to job B.
5. Collaboration: More often than not, specialists from multiple departments must come together to keep a Learning Management System functioning at its best. This encourages cooperation, collaboration, and interdisciplinary thought processes.
6. Tracking: Big Data can help us understand the real patterns of our learners more effectively by allowing us to track a learner’s experience in an e-learning course. In examining the digital footprints or ‘breadcrumbs’ learners leave behind, we’re able to track their journey throughout the entire learning experience.
7. Understanding the learning process: By tracking Big Data in e-learning, we can see which parts of an assignment or exam were too easy and which parts were so difficult that the student got stuck. Other parts of the journey we can now track and analyze include pages revisited often, sections recommended to peers, preferred learning styles, and the time of day when learning operates at its best.
Still, when discussing Big Learning Data, we must honestly consider the risks that it raises, which in some cases may outweigh the rewards.