Benefits Of Learning Analytics In enhancing Corporate Learning

Learning Analytics

Learning Analytics can be defined as “the collection, analysis, assessing and reporting of data about the learners  in specific contexts, for better understanding and optimizing the learning environments in which it occurs”.  Learning Analytics and a proper custom learning management system in Bangalore can provide the methods and tools to collect Learner data during the delivery of a lesson in order to comprehend and update individual student profiles. The types of student data used belong to the ‘Dynamic Student Data’ category and may include (a) Performance in assessment activities, Engagement in learning activities, (c) Interaction with Digital Educational Resources and/ or Tools and (d) Behavioral data.  This further helps to analyze and report on the data to facilitate personalized interventions (e.g., feedback and scaffolding).

 Learning Analytics has been buzzing around in the L&D circles for a few years now. But, What values does it actually hold for your organization? Businesses now prefer to provide comprehensive training programs with the help from the best educational portal development in India to their employees to ensure higher income without formalized training. Enterprises seem to earn profit and success with increased productivity and improved ROI as compared to those Corporates that do not provide any employee skill training courses. Several eLearning analytics metrics and any leading educational portal development company in Bangalore, India help to create personalized training programs and thereby track the effectiveness of a business. In this blog, we tried to jot down the benefits of the Learning analytics metrics and the impact of corporate training on your business in an enhanced  way that can pave the way for creating effective training thus revolutionizing the general perception of the corporate training.

Benefits of learning analytics program in corporate training

Benefits of Learning Analytics Program in Corporate training

Are the training programs worth the money invested?

How beneficial are these e-learning activities and programs for an organization’s workforce? 

There is an increasing number of organizations preferring to opt for e-learning programs as a part of their corporate training schedules and Lms development in Bangalore . Recent technological advances have been able to measure the training effectiveness and performance level of each employee for every course that they go through. Read on next to comprehend more on various methods in which the learning analytics has impacted corporate training programs for success.

  • Aids in defining your learning strategy
  • Identifies specific learning difficulties if any
  • Senior management buy-in and support
  • Predictive for future performance
  • Improved content retention by the learners
  • Provision for long-term cost savings along with improved efficacies

Aspects that influence Corporate Training and its improved productivity

1. Personalized Learning Modules:

Personalized learning experiences are an efficient way to implement personalized training programs. These are incorporated to meet the learning preferences of individual learners and/ or groups of learners. This is accomplished through thorough data analysis on different functional units, roles and learning preferences of employees within an organization.

2. Individual Employee Performance Analysis: 

Most of the e-training programs have an evaluation or assessment process at the end of the module that helps to track the learners’ understanding of the content. The data related to employee performance can be used to predict his performance/ engagement level in a respective course and thereby can further be used to implement new strategies to improve the overall performance ensuring efficiency.

3.Increased Learner Retention:

Learning analytics proves to be extremely helpful in monitoring individual learners’ progress and thus track successful completion as in some cases  learners fail to complete the compliance training programs. In these cases, the corporates face circumstances resulting in the ineffectiveness of the e-learning course which clearly indicates a less qualified workforce.

4. Effective e-Training Programs:

Learning analytics enables tracking of the activities, understanding their individualized potentials and thus helping employee engagement accordingly. Each learner is basically assessed based on the time spent on each module of the e-learning course, or the  learning activities, content, assessments of that module. A thorough analysis is carried out after each course/module that checks for the feedback from the employees in order to reveal on-point strategies for further modifications.

5. Cost-effective Method:

Businesses offer several courses for their employees but they fail to access most of them successfully. Where every course may not have the desired reach, a proper data analysis regarding the course access, completion, and/ or assessment scores reveals the actual outcome of training programs. Also organizations prefer to invest in courses that ensure a pre-assessment to check the skill of their employees and not the basic soft skills.

Types/ Strands Of Learning Analytics

Today’s world is undoubtedly driven by data, and corporate training is no exception.  Learning Analytics empowers the organizations to make informed and relevant L&D decisions. On the contrary, in the absence of data- L&D decisions are mostly taken on the basis of educated guesses, hunches, opinions, and previous patterns that probably  provide no guaranteed effective training or create the desired business impact. Here’s where the learning analytics works as the lens thus enabling the organizations to view and implement improved changes at the course or strategy level.

Getting started with proper learning analytics can be challenging. For example, it can be difficult to figure out where to begin, or how to coordinate with different functions such as IT,thereby  ensuring expertise in eLearning, and /or Instructional Design, LMS, analytics, and so on. Nevertheless, the effort will definitely prove to be fruitful as leveraging learning analytics in e-Learning comes with several benefits.

 Learning Analytics can be classified into four  main strands, which exploit the same learner data types, however aim to achieve different outcomes. Below are mentioned a few benefits from the perspective of 4 different types of learning analytics.

1. Descriptive Analytics

Descriptive analytics  aims to analyze the  data and create dashboards that depict meaningful patterns or insights emerging from these analyses. It enables collating the data from multiple sources to provide insights into the  past performance. This data can further be used to make better informed decisions that will impact the future training programs for an employee. Thus, Descriptive analytics typically will present you answers to questions regarding what has already happened.

For example, a healthcare provider can check on the number of patients admitted in a week on average and a retailer can know about the average monthly sales. Similarly, with eLearning, it is also possible to find the number of course enrollments, pass percentages, assessment scores etc.

If the data shows increasing dropout rates, you might need to take steps to improve the training content or probably think of switching towards a better engaging learning strategy. These discoveries will surely allow you to enhance the training programs and eliminate those courses that are not worth the organization’s money and resources.

Descriptive analytics, though, are limited to indicating that something has occurred, without properly explaining why. Therefore, in case your organization is looking for in-depth insights, it is better to combine descriptive analytics with other types.  Examples of Descriptive Learning Analytics include the SmartKlass and the Learning Analytics Enhanced Rubric, which are the plugins for the Moodle Learning Management System.

2. Diagnostic Analytics

Diagnostic analytics can be used to scrutinize and ask questions about the reason as to why something happened.

The relevant elements can easily be figured out and the patterns can be identified as well to get insights into a particular opportunity. For example, data from diagnostic analytics might provide information on an eLearning course on customer service that experienced low completion rates by the senior executives while the new hires found it to be more effective. Further diagnosis revealed that the course content was relatively basic for the senior executives, thereby suggesting that the organization needs to roll out an advanced and improved level of customer service course for them.

In a way, the detailed analysis highlighted the need to cater to the specific needs of individual learners and offer a better personalized learning experience that would help ensure that the training program is not redundant and is able to impact all learners’ performance positively.

3. Predictive Analytics

As the name suggests, predictive analytics  focuses to predict the future trends in course  progress and is typically used to identify learners who might become “at-risk” in terms of low engagement or low performance.

It presents what is likely to happen and it is related to “Predict Future Trends in Progress”. It takes into account the findings of the existing data to predict the future. However, it should be noted that predictions are just an estimate, and the accuracy depends highly on the quality of data and stability of the related situations. Predictive analytics can help to identify the probable difficulties that the learners might face during a learning course. This allows the superiors to create opportunities that can provide early intervention and targeted support. Additionally, predictive analytics can be used to improve the quality of training and enhance the engagement ratio.

For example, let’s assume that data from a post-course survey revealed that some of the learners did not prefer accessing the e-program from a desktop. Rather most of them prefer accessing the e-training program anytime, anywhere on their mobile devices. In this case, the learner profiles and the predictive analytics can assist you offering solutions in microlearning formats that should be able to meet individual needs.  Examples of Predictive Learning Analytics tools include Early Warning System  that  is a plugin for the BrightBytes Clarity Learning Management System, and  Engagement Analytics tool, that  is a plugin for the Moodle Learning Management System.

4. Prescriptive Analytics

The purpose of prescriptive analytics is to generate recommendations for further teaching and learning actions, that is to  suggest alternative educational resources or tools. It is more related to “Recommend Teaching and Learning Actions” way. Prescriptive analytics help you strategically plan for training interventions. Let’s take an example of a curriculum of eLearning courses which needs to be rolled out to employees in the manufacturing industry. Surveys on courses that were conducted in the past revealed 2 aspects. A. The courses excel theoretically; but, it would be more beneficial if learners could learn how to apply this to their work.

In this scenario, simulations can be delivered to progressively help learners to apply their learning in a simulated environment which in turn, will increase the value and the impact of the training program. Examples of Prescriptive Learning Analytics tools include the LearnSmart tool, that has been developed by McGraw-Hill Education, and Adaptive Quiz tool, which is a plugin for the Moodle Learning Management System.

Discover More With Learning Analytics

Personalized Learning is a key challenge in global education as at its core remains the need for an accurate and meaningful student profile. However, the effort to populate and update accurate student profiles manually is usually restrictive which brings up the need for a good e learning management system in Bangalore. To overcome this hurdle, specific Analytics technologies have been proposed that use Learning Analytics. In today’s data driven world, Learning analytics offer a deep insight into the way corporate training programs are aligned with organizational goals and the individual learning needs. There is an excellent opportunity for L&D leaders, as well as their stakeholders to make data-driven decisions and to use learning analytics. Therefore, if your organization hasn’t yet started using learning analytics to improve the quality and the ROI of the training programs, it’s time to think on implementing learning analytics to maximize Training Effectiveness.

Why wait, opt for eLearning analytics with us…

Learning Analytics assists the educators and trainers to provide personalized support to each employee by collecting, processing and reporting on various data to track and thereby visualize each learner’s performance. As per organizations, this tool enables data-driven decision- making with skilled and trained employees. Learning Analytics ensures long-term content retention by the learners thereby contributing to business development. It enables an organization to provide its training team with a great opportunity to identify the recent trends and patterns in courses, upgraded learning methods and training contents. This data must be used to have broad implications that pave way for targeted improvement in the business.

The eLearning analytics has successfully opened up the channel for effective corporate training in the aspects of extensive training requirements, employee productivity and LMS performance tracking, that yields increased revenue in a desired period of time. There are numerous efficient LMS providers with great expertise in custom corporate educational portal development in India that compete to provide the best e-learning analytics for corporate training.

 

 

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