E-learning has become a near standard in todays technological and educational landscapes. With courses available on anything from carpentry to algorithm design, people are turning to the internet to self-educate on topics that they would otherwise not have access to. As the population of e-learners grows, so does the opportunity to utilize the power of Big Data and improve e-learning programs by learning about the behavior and interests of their users.
To understand how Big Data can move e-learning forward, we must first understand what Big Data really is. With traditional means of data storage and analysis, there were computational restraints on how much information could be processed. While websites were possibly able to track simple things such as user location and languages, more complex and detailed information was often unavailable. However, as technology improved, the amount of information that could be processed and analyzed improved by leaps and bounds. This gave rise to the concept of what has come to be called Big Data, digital breadcrumbs that are left behind when users engage with the internet.
The depth and complexity of Big Data is sometimes difficult to comprehend. Instead of the limited information that is available from registration details, Big Data is able to analyze behavior patterns and the popularity and quality of digital content. By tracking information such as time spent on an individual page, pages that are often revisited, page popularity by geolocation, and more, services are now able to better tailor their content for their users.
Now, while this information is obviously beneficial in certain fields such as marketing and medical research, the impact it can have on e-learning is remarkable as well. By tracking how users interact with available content, courses and learning programs can be tailored and tweaked to the target demographic.
For example, Big Data can assist in identifying inconsistencies in a courses difficulty curve, pointing out parts of a curriculum that were too simple for most users, and parts that seemed to stall progress due to a level of difficulty above the students level.
Another powerful example is how Big Data can be analyzed to track sharing across social media. This can help identify subjects that are in high demand across a target demographic and help developers provide increased high quality content on these subjects.
As the demand for e-learning increases, the need to continuously improve the quality of online educational programs increases as well. Until recently the best way to discover the habits of online users were surveys and polls and while they did their part in improving content, the amount of additional information that can be gained in this manner has begun to plateau.
The power of Big Data lies not only in the staggering amount of data that can be collected and processed but also how hands-off this approach to data analysis is. The need to manually investigate and enter data has decreased exponentially, while the quality and volume of this data increases at an incredible rate.
One more thing to take into account is how painlessly Big Data integrates with the majority of e-learning platforms. By their very nature, e-learning platforms are multi-dimensional, rarely tied to a specific device or location. The fact that an e-learning course can be accessed by anyone, anytime, and anyplace means that Big Data is quite possibly one of the most important tools to improving the user experience.
Learning management tools (LMSs) such as Moodle or BISTrainer allow e-learning platforms to take full advantage of the digital breadcrumbs left behind by users and provide easy-to-use tools to utilize the information gleaned from Big Data.
