Category: eLearning

12 Apr 2024
Extended enterprise training

How is extended enterprise training useful?

Training is an important component of every company’s operations today. They train employees to get the maximum benefit from themselves. Learning and development are very crucial for companies today because they increase the skills of employees. When a company decides to train every one associated with the company, be it external or internal, it is known as extended employee training. This kind of training involves everyone in the company i.e., customers, distributors, partners, and suppliers. Training all these stakeholders means empowering everyone to ensure that they can contribute to the business.

The extended enterprise training should be made accessible to the various stakeholders.

A company should invest in various platforms such as webinars or mobile apps to convey the necessary information to the partners. The external partners of the company should be allowed access to the LMS of the company for the training material. 

  • Sellers:

When employees are trained to do sales, they can improve their service. It’s important to deal with customers positively because then only they can convert to a sale. Sometimes, the customers might not be in a mood to buy, but any positive interaction with the CSR makes sure that they return to the store when they have a need. The various stakeholders for which a company needs to impart training are:

  • Partners (Vendors):

Partners also play a crucial role in the success of a business. Vendors are one kind of suppliers who provide raw materials or services necessary for an organization’s operations. Distributors are also partners who make sure that the organization is able to expand its operations in different areas. So, an organization can sell services/products anywhere, thanks to these people. 

When these partners help a business build its business in various geographic territories, they also have to be trained in how to convey the brand image of the company. They must be trained in the sales pitch, about the product features, and taking the company’s brand name forward through the franchisee. Partners with better networks can also help a business reach and get sales in new markets. 

Partnerships can help businesses in entering new markets, which is helpful, but there can be regulatory changes. A partner can help a company follow all the new regulatory rules and not lose any money due to compliance fines. There can also be market fluctuations due to new competitors entering different regions. Since the partners are completely acquainted with the market, they can help a business reduce the competition by changing their policies. These could be reducing the prices or finding new raw material suppliers.

A company must diversify these days because any market can stop giving returns in the long run like in the pandemic, the hotels had to shift to the QSR model because people stopped dining outside. Businesses can also attain flexibility, which is the need for today’s times because the customers’ demands have increased. They want sellers who sell everything, rather than going from store-to-store to meet individual needs. But partners must be trained to be alert of all changes and inform the company of the same. 

  • Strategic partners:

When a company has strategic partners, who can help it in distributing freebies with its goods, it can offer better products to its customers, such freebies can increase the value of goods for the customers and ensure that new customers can be won. 

  • Technical partners:

There are technology partners also, which help a company sell its software products because these partners provide complementary products like software or hardware. For example, a mobile company can gain more sales if a technology partner provides headphones with cell phones. 

Technical partners can also be of use to the same. Sometimes, the business does not have competent staff to ensure that the new software is implemented carefully. But when it has technology partners, it can implement all these changes and become efficient in its operations. Today, every business has partnered with cloud-based solutions. Sometimes, businesses need service vendors or contractors to supply external labor to finish a contract for which internal talent is not enough. They can hire someone on a project basis rather than losing the project. Today, the business can’t be dependent on just the market because it can enter into a recession, rather it needs to enter different markets to make the best use of its capacities. This is only possible by tapping into the know-how of partners and imparting extended enterprise training. A company needs to train all these partners so that they provide perfect services to the customers. 

08 Apr 2024
upskilling through competency modelling

How can upskilling be done through competency modeling?

Companies today are working hard to ensure that they can meet their productivity goals. Therefore, they are training the workers based on competency models. Those are the models that help a company determine the competencies needed for a person to be successful in his/her job. These models help a company in setting parameters for training.

The concept of the competency model emerged from the job analytic process, which breaks a job into tasks depending upon the job description. When the tasks underlying a job have been defined, they are mapped onto the knowledge required to perform them.

How to build a competency model?

It’s not always easy to come up with a competency model. It can be a tough task even for skilled managers. The first step is to do a job analysis for upskilling. It helps in detecting the tasks. The first people to answer this question are the stakeholders. These stakeholders are those who perform this function regularly and know the tasks required. They can consist of HR managers and ultimately the employees at the executive level.

How to create a proficiency model?

The competency model decides how much training is required for upskilling.

Then, you can get feedback from all the managers on whether the competency model is correct. Subject-matter experts can also validate the model by checking it. The company can then segregate the required competencies into different sections, like technical and leadership competencies. When you have the proficiency levels designed, you can get the training levels. There should be proficiency levels defined for each competency to decide how much training is required by employees.

Update the competency model when required:

Once the company’s L&D team has got the necessary validation for the competency model, they can begin the training processes. This competency model needs to be changed quite often so that it stays pertinent. If it’s not relevant anymore, ask the managers where it can be improved.

Regularly review and update the competency model to ensure its relevance and effectiveness in meeting the evolving needs of the organization and its workforce. Solicit feedback from users and stakeholders to identify areas for improvement. There is also one more way to detect competencies required for a role. It’s through observing the way people do their job. This can help you detect what tasks are required to perform a role. Although interviews can be used to detect the competencies required for a job, they cannot be used for all job roles because that would require a massive effort.

An AI tool can also be used for finding the competencies needed for a job. When such a loss has been generated, it can checked by the managers and the SMEs to see whether it’s perfect.

Challenges in creating a competency model

  • The requirement of different jobs:

The competency model is not required by a company for every job, rather it is required for every strategic job. The company should do competency modeling for jobs that are highly critical for it. Such jobs would require upskilling for the needed skills so that the company continues to run in the same manner in the future.

  • Future possibilities for a competency model:

The competency model should also take the future requirements of a job for upskilling. It’s because a job does not require some skills now, but it might require some skills in the future, like AI. A stakeholder needs to check which skills will be needed in a job 5 years from now.

To do an analysis of skills required for the jobs in the future, it’s better to understand the environment. Then envision what sort of changes can happen in the future in terms of technologies and trends. There can also be disruptions like the pandemic and shifts in the economic conditions of people caused by urbanization, leading to better demand for a company’s products. These kinds of possibilities can also be envisaged by a company when it takes interviews of experts in the industry. They have much more knowledge about what can affect an industry in the future, like how artificial intelligence can take over all the work. So, this can affect the tasks required to be done for a job, changing its competencies.

Apart from competency modeling, there are some general competencies that will be required in the future in all kinds of jobs. These competencies are digital literacy and cybersecurity. All employees need to have such competencies and should be taught tasks related to them because they will be needed in the future.

22 Mar 2024
STEM based authoring tools

What features should STEM-based authoring tools contain?

The education landscape has changed today. The students want to learn through the modern means.

There are new opportunities set forth by digital means. STEM subjects like science, technology, engineering, and mathematics are better understood with digital tools. Students can have problems understanding mathematics. But when eLearning is used to teach them these subjects, their lives become easier. The teachers must know how to use these tools so that they create effective eLearning materials with their aid.  

But the first question is how to choose these eLearning authoring tools. There must be some features present mandatorily in such tools:

  • Diagrams:

Such tools must be able to create effective diagrams for, e.g., the teachers can create a Milky Way galaxy through them. Then there can be a drag-and-drop functionality designed around the galaxy so that the students can understand the names of the planets and their satellites.

The authoring tool must allow the inclusion of all kinds of scientific data into the eLearning module. You must be able to display the data just like you want.

Interactive elements are a crucial part of STEM education. Students must be taught through quizzes which help them retain information better. So, a STEM authoring tool must have the feature to build quizzes.

  • Equation editor:

There must be an equation editor built into such tools. An equation editor helps the students to edit the equations for their font size, color, and alignment. There should be a feature to write long numbers that are generated through satellite-based observations like the distance of the Earth from the Sun.

There must be equation editors that allow printing of matrices, integers, fractions, and summations through the authoring tools. Having these features is integral to an authoring tool so that students can learn advanced mathematical concepts through them.

Equation editors should also be compatible with other tools. This way you can save equations and use them in other tools, exporting them through the authoring tools to other tools. The scientific data can be about planets. It refers to the data that has been aggregated and not tampered with at all, called observational data.

  • Huge Vector library:

Such data can be in fields such as anthropology, which refers to the advancement of human beings. So, when explaining how human beings evolved at all, including various shapes of human beings is necessary, such as how they walked like animals. Such data can also be about astronomy, which includes the position of planets and stars at various times of the year. So, the STEM authoring tool must be able to exhibit all such data.

Ecological data is also a kind of observational data. This data shows how the ecosystem is balanced through different organisms. Hence, the authoring tool must contain the feature to draw organisms and show their movements, like predators running after their prey. Cell diagrams should also be present in the vector library so that students can learn about them through drag-and-drop functionality. This goes for other body parts, such as the eyes. So, there should be a comprehensive vector library that includes various kinds of animals and as many shapes, numbers, and equation signs as possible.

Experimental data also needs to be stored in an authoring tool and shown to students. Such data can be in the form of chemical equations and hence the authoring tool must have the feature to write such data. Such data can be generated after doing experiments like mixing two compounds together. There should be vector shapes like test tubes present in the authoring tool to depict an experiment. There can be prebuilt animation to show when the two compounds are mixed. Either the animation should be a part of the module, or the teacher should be able to create it without having an extensive knowledge of coding. The two test tubes should move away to show the result that occurs when the first two are combined.

  • Curriculum-based templates:

Authoring tools should have various templates available so that STEM education can be easily imparted.

A tool that has many templates can make it simple for the teachers to add content. They just need to edit the template and show the template to students. Such templates must be in sync with the subject curriculum you are trying to teach. For example, there can be a template about the food chain so that you can just change the animals in it. There must be templates that pertain to a grade level in a school. The most important aspect of eLearning is that the students need to have fun while browsing the modules created through such authoring tools.

In the end, the teachers should be given training to use such tools. When they know how to use such tools, they can easily implement their creative ideas.

15 Mar 2024
Online learning

How is online learning affecting education?

Modern classrooms have changed so much. From chalk-and-blackboard classrooms, we are now living in an age where digital classrooms (online learning) have taken over the world. Now, the students listen to their teachers talking through a Zoom screen. The world has changed a lot significantly due to the pandemic, which has brought so much modification into our lives.

Pitfalls of a conventional classroom:

In a conventional classroom, the students don’t get all the attention from the teacher. There is practically no interaction between the teacher and the students. Some of the students are not able to understand the teacher but can’t question them at the same time while they are delivering the lecture. So, these students are unable to perform because they have not understood anything.

Often, a lack of attention is also caused due to seating arrangements. Some of the students are sitting in the front rows, others in the middle, and some are backbenchers who find it tough to maintain attention. Whatever the number of students in a classroom also determines the understanding level of students.

  • Disadvantages of large class sizes:

Studies have proved that with a smaller number of students in the class, they tend to score better, and it’s also easier for teachers to manage the class. When class size is small, teachers can talk to students individually about their problems. This is not possible with a large class size because too many students can’t be talked to at once.

With large class sizes, the use of technology is limited. This is due to the ability of students not able to see the projector. This is not beneficial for students because they can’t hone their digital abilities. They have no technical skills, which can prove to be detrimental in the later stages of their lives.

Using technology in class proves to be useful for students because it is required in corporate careers these days. When students are taught through technology like tablets, they become more adept at using them than those who are not.

Use of technology in education:

This transition from textbooks to modern-day gadgets happened because of the invention of the internet. Now instead of cumbersome books, education is available at the fingertips of every human being due to the internet. Due to this, students found it easy to access information and understand it. So, teachers started teaching students through virtual classrooms. But with technology, Learning Management Systems (LMSs) were invented where students could easily be transferred lessons, and they could study from them. They were handed over the entire lessons online, where they could study the material and try the quizzes also.

Technology has also changed a lot in recent years. With smartphones, students can browse through information at any time.

Students benefit from the flexibility offered by online learning.

When the material is available to them 24/7, they can browse through it at night or in the morning. They don’t have to follow a packed schedule like in the case of traditional classrooms where they have to be in the class at a certain time.

  • Use of LMSs:

LMS is getting used in virtual classrooms, due to which content availability is omnipresent. The LMS also provides analytics that are not present in a conventional classroom. The students might not understand something, but the teacher does not know about it. It’s because the student does not finish a lesson if they are unable to understand it. So, their LMS analytics show a lesser time spent on a lesson that they didn’t understand. The teachers can make sure that the students can have personal online learning paths, due to which they can spend more time on lessons incomprehensible to them. It’s not like they are supposed to spend a fixed time on a lesson.

  • Use of AR:

The technology is advancing like never before. Now, AR (Augmented Reality) is also being used in teaching students via online learning. With objects drawn along with real-life objects, students can see the latter from a better perspective. This is very useful in medical and manufacturing industries where everything can’t be explained with examples. So, a patient’s vitals can be shown and what is to be done in the situation through AR-based objects and headsets. Traditional classroom-based learning will not stay any longer, because students can’t focus when anything lifelike is not shown to them, only possible through technology. When they are transferred to different situations in online learning through this technology, they tend to understand information better.

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.

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