Large companies and multinationals are starting to implement Data-driven Learning Analytics (DDLA) in their businesses. This learning system consists of ability of companies to analyze information provided by workers about their capabilitiesand thus be able to facilitate training based on this knowledge in order to make decisions for the personalization and adaptation of learning that depends on each type of need and user.
This is why DDLA refers to the willingness of companies to align their business objectives and connect it to the development and learning of your workers take advantage of the traces left by the user to know them better and be able to develop and design learning experiences according to their needs.
Therefore, it is essential take into account the four dimensions which should be given special attention when designing a learning experience, namely: concern, opportunity, inquiry and community.
Piece by piece, Concern arises due to data growth. This concern is linked to lack of privacy and ethics, lack of knowledge about data ownership, fairness and usability.
Concerning the opportunity variable, Companies that manage to analyze data perfectly manage to replace decisions based on intuition with those based on data.. But to do this, they must conduct a research process that allows them to know how people interact with machines in the learning process, in order to find a solution. To do this, it is essential to know the community around you and how they are able to interact with each other.
Apply “data driver”
To know how the DDLA method is applied, you need to know how a project of this type is built in a company. Everything goes through set the goal what you want to achieve with the selected learning method, understand the problem you are starting from and identify the relationship between the data and the learning characteristics. Afterwards, it is essential prepare the data those available in the project, which is the most important task and with which it is necessary to have greater precision, since they are rarely directly available for use and it is necessary to apply processing techniques that allow them to be adjusted and leave ready to be used during their analysis. design learning methods. In this step, all current regulations must be taken into account so that the analysis process is as useful as possible.
Afterwards, it is necessary create the model from which you wish to work. In this process, one of the premises is not only to measure the activity, but also to evaluate the complete interpretation of the learning on how the employee developed it.
When the field work has been carried out and all the processes have been correctly defined, it is finally necessary define what decisions are made based on the results obtained when applying the “Data Driven Learning Analytics” learning system.
Consequences of the method
The DDLA method stands out among large companies for the benefits it brings when it comes to knowing the behavior of workers, because it allows us to make better decisions that directly affect their status.
One of the groups that has already applied this apprenticeship model, Grupo Éxito, did so because it was aware that the development of workers is a differential factor in the market. Thanks to DDLA, they were able to identify the variables that measure the impact of learning actions on one of the most important indicators of the company, the “Net Promoter Score”, NPS, which helps them measure the level of customer satisfaction and it also helps them generate personalized recommendations and action plans.
Again, It is essential that companies have methods that improve the efficiency of their workers.since they will directly influence the economic results of the year.
