Tag: learning analytics

07 Mar 2024
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.

09 Jun 2022
learning analytics

Measure whether your employees have become better through learning analytics 

Learning analytics can now ensure that the elearning content gets used by learners. So the people should be helped to increase their skills for retaining them in the company. But some problems arise in collecting such analytics.

Why is learning analytics needed?

Every job has a key performance indicator(KPI), and the training aims to ensure that these parameters related to a job improve. But, unfortunately, if they didn’t improve, the training didn’t impact them.

The KPIs are measured in terms of job functions and include whether the employee grasped the working of new software and used it successfully to handle clients. It could also be related to meeting new revenue goals for an employee. Hence the major targets of an elearning program are these KPIs. Every training program aims to improve the performance of employees in terms of KPIs so that they become worthy of appraisals.

And the targets of a training program help a company know what learning analytics should be captured for it. For example, if they are a part of a desk-based job and need better retention of hard skills related to software, the employees must score more than 80% in all elearning tests. This should be the key learning analytics measured for them. But are the test scores enough? Read more…

Learning analytics are useful for a business because there is a need for employee participation for L&D to be successful.

The elearning team has to check the completion rates, but the learners might not have learnt any skills from the course despite completing it. Moreover, the learners might be scoring high on tests, but the course might not affect their job performance.

Hence, companies must know which data to collect and measure for their learning program to be effective.

    • Test results might not reveal the truth.

The businesses need expert LMS admins to extract the data related to a training program. It’s not easy because the admin might not know when to collect the data.

The LMS admins have to get learning analytics even after a program has finished.

Companies need to analyze the elearning test results once the employees fail to perform well post-training. The LMS admin can ensure scheduled reporting so that the intended test result report is delivered one month after the data is captured. Through the scheduled reporting, the crucial reports are sent frequently and automatically to the stakeholders through the LMS. Employees clear assessments by learning everything in an elearning course, but if they fail to apply skills, it’s useless in their jobs.

Hence, after 1 month, if problems are discovered in employees’ behaviour regarding implementing knowledge of a completed course, the course must be modified.

Cramming theoretical knowledge is not a way to impart practical skills to employees; instead, memory association games are needed, making employees apply such knowledge in real life.

    • Ask employees and managers about their training feedback.

Apart from checking employees for their knowledge retention by getting reports 1 month after the test scores, the LMS admin can also get information about whether employees liked the elearning or not. The employees can be sent surveys through Google Forms sometimes after the course. It might be true that although employees are employing the new skills at the workplace, they are not yielding the relevant results.

If they are facing any problems in using the skills imbibed through the elearning course, a review session can be arranged for them so that any doubts are clarified.

If employees cannot be contacted for any feedback about the training, managers can be asked for their post-training feedback. Some employees might have trouble applying new skills because they cannot synthesize knowledge. In the case of hard skills, this is an important step.

  • Inability to synthesize knowledge.

The learners need to be able to arrange the theoretical knowledge taught to them in a practical way which is possible when they are asked to construct a flowchart based on the skills of a procedure.

But if this step is missing, some learners might have trouble applying the skills. Hence, they should be asked for feedback after assuring them that it will be confidential, so they don’t become objects of ridicule. Getting feedback from the employees must be a constructive process because if training needs improvement, it does. Employees must not be blamed for their lack of understanding.

The aim of the HR that is collecting the learning analytics is to make employees better at their jobs and improve the ROI of the company. Hence it should encourage employees for their feedback.

 

 

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