learning analytics

How learning analytics must be collected and analyzed? 

E-learning data analysis can have several problems. The creator has to see that these mistakes are avoided.

Learning analytics is the process of collecting data about the learners so that changes can be made to the learning process. This helps in a better learning process for the organization. When learning analytics are collected, the performance of the employees certainly improves. It’s because whatever the eLearning lacks is analyzed and corrected. When the right information is collected, the L&D activities are improved.

Different kinds of data can be collected for learning analytics. The following is the information:

  • How much time do employees expend on the program and each module?
  • Employee satisfaction levels with the program can be gauged through interviews
  • Different grades or score levels in the test

How can biases occur in analyzing data?

The sample is chosen for learning analytics from a population of a certain size. If a minimal sample, is selected, it does not lead to clear results. The results can be biased or skewed in favor of those who have been included.

The biggest bias can occur when samples have not been drawn carefully. This kind of bias is called the selection bias. In this case, the sample does not reflect all the groups that are part of the population. Selection bias can cause the subjects from some groups not to be included in the sample, or people from some groups to be included in excessive quantities.

Survivor bias can also be a part of the conclusion. In this, only those subjects are chosen who have cleared the tests, but those who have failed the tests are ignored. Hence, it does not lead to a clear conclusion being drawn.

There can also be problems with conclusions drawn from the data. This is called confirmation bias. In this, it can happen that we have already drawn conclusions in the mind and are looking for information to prove it. This happens when the L&D professional has a prejudice and believes in it. However, it’s important to look at the analytical result of the data rather than confirming such bias.

Also, sometimes companies just rely on historical conclusions drawn from the data in the past.

When L&D professionals suffer from this bias, they tend to ignore information that does not conform to their beliefs. There can be an error in the conclusion due to historical bias. These are further problems that can occur in collecting and analyzing data:

  • Lack of employee views:

In learning analytics, sometimes data is not the only answer before the researchers.

The learning data may not represent the whole story. It can be incomplete and not true. Apart from data, human judgment about the matter is also important. The organization must have a balance between the data and the human intuition to get the reality of the picture. It gives a proper answer as to why the learning process is not yielding results as it should.

  • Lack of data:

The lack of data sources is a reason why the conclusion might not be right. It’s because sometimes, the companies look no further than the test scores. Such data can be easily provided by the LMS admin. They don’t ask employees at all about their viewpoints regarding the LMS. Also, sometimes, the number of employees who have failed the tests needs to be taken into consideration. Then only you can get a real conclusion whether the e-learning needs improvement or not. You can only get an answer to whether there has been any improvement after e-learning through several data sources. 

Importance of learning analytics:

Learning analytics are very important for any organization that has implemented an eLearning program. It’s because they help them detect those areas where the learners are facing problems. The problems can also be caused because the students are leaving the course in between due to the issues from the course. When such analytics are evaluated, the L&D head can see what the difficulties are. They can work on the course itself or even ensure that there is blended learning in which learners attend classes to sort out their difficulties.

Challenges of learning analytics:

Learning analytics provide data about the employees in an organization. But this data has to be protected. The company should be extremely careful about the data getting leaked. It’s because it can affect an employee’s career when his learning progress is in the hands of nefarious sources. Hence, all kinds of unauthorized access must be regulated.

Most often, the L&D professionals are happy in their own space and don’t want to bring any change. But they have to focus on the impact of their learning activities too. L&D Professionals need to learn too because that can improve their performance.

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