How To evaluate Your e-Learning Experiences
When companies invest in digital training, e-learning platform and development for their employees, they expect to see results that indicate the digital training process was successful.
Unfortunately, these organizations don't have the right e-learning tools or practices to measure the effectiveness of these digital training programs other than the typical traditional metrics such as e-learning course completion and score.
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While it is understandable that some e-learning systems and technology have been designed that way, these metrics do not in any way provide any meaningful insight into e-learner competency, behavioral changes in learners, or the organizational impact of the e-learning training.
Students may complete a e-learning course, but it can be hard to tell if the digital training resulted in the desired behavioral change, which should be the goal of the e-learning experience.
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Successful e-learning experiences should lead to improved skills and higher productivity, which typically translates to decreased expenses, increased revenue, and an improved brand.
It is all about e-learning objectives!
Mere e-learning course completion and the ability of learners to answer a few random questions are unlikely to lead to these outcomes.
So how can instructors and organizations know when the required learning has taken place? To answer this question, we will need to take into cognizance the principles of monitoring and evaluation as well as a few other tried and tested learning evaluation models.
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Monitoring and Evaluation
Monitoring and evaluation are processes that involve the collection, analysis, and use of information to track the effectiveness of a program or initiative toward reaching its goal. The idea behind this approach is to improve a program for maximum impact. It helps to reveal to what extent a project has (or not) met its e-learning objectives. The principles of monitoring and evaluation are suitable for a wide range of applications and, in this instance, the effectiveness of learning experiences. Here are some ways to leverage the principles of M&E to learning:
Define objectives: Before anything else, set goals to spell out what you intend to achieve at the end of digital training. To do this, you will need to answer three vital questions:
What problem is the program trying to solve?
What steps are being taken to solve that problem?
How can stakeholders know when the program has been successful in reaching the problem?
These questions will help in defining the goals of the program and will help both learners and stakeholders know whether or not it worked.
Collect data:
Data collection should commence right from the beginning of the program implementation and then continue throughout the duration of the program. This will help determine the progress of the e-learning program.
Analyze data:
Next, the data collected at every stage of the program must be analyzed and used to modify the program as necessary. Analyzing the data and making the needed changes can help improve the overall impact of the program.
Review the program:
At the end of the e-learning course, compare the data collected at the beginning of the program to determine whether or not there are behavioral changes or improved competencies and what can be improved going forward.
What is e-learning evaluation?
e-Learning evaluation refers to the systematic process of analyzing and evaluating the results of digital training and educational programs. The overarching idea is to determine the extent to which defined objectives are realized and the effectiveness of the e-learning experience.
Different e-learning evaluation models have been developed by e-learning and development theorists, which suggest key evaluation criteria relating to the micro-level (the e-learning experience itself) as well as the macro-level (its impact on the organization.)
Examples of these models include the Kirkpatrick learning evaluation model, Philips's model, cathy Moore and Anderson's model for e-learning evaluation, etc.
The Kirkpatrick model is one of the most popular methods of learning evaluation, and it details the criteria for evaluating learning experiences to four levels: reaction, learning, behavior, and results. Roger Kaufman expanded on the Kirkpatrick model to include societal impact.
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What metrics do you evaluate?
While the criteria above help to provide insights into how to gauge learning effectiveness, there is still the need to pay attention to a couple of other metrics as they often indicate the success (or otherwise) of a e-learning experience.
If you've developed goals from the onset of the e-learning design process, you should have no trouble determining whether the program lived up to its expectations. Other metrics to take into consideration include:
Conduct assessments:
Assess the capabilities of learners at the beginning of the digital training and compare it at the end of the training by designing simple baseline surveys and knowledge checks to see if there's been any improvement.
Track engagements:
How well has the learner participated in the training program? Take a look at e-learning course completion; grades achieved, engagement rates (through clicks, time spent, and contribution to discussion forums.)
Measure results:
Observe the increase and decrease in scores of learners at different stages of the digital training to gauge their understanding of the e-learning course. Also, look out for higher productivity and improved skills as evidenced by faster turnaround times and higher quality of work delivery.
Analyze data:
All the data collected from the leaderboards, as well as the e-learning course levels, badges, and rewards achieved, also counts in evaluating the success of a e-learning experience.
It might help to use Next Generation e-learning Platform Like TheLearning LAB and technologiy as xAPI.
The digital data obtained using xAPI shows how learners interact with a program and other platforms in the organization. It can track and capture everything about the activities of learners related to your course, including how they viewed the course, clicks, how much time was spent, what was revisited, etc.
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Conclusion
Rather than assume that a e-learning program is successful, proving the effectiveness can help reveal how well a course performed and how it can be improved for maximum impact. This will, in turn, lead to bigger returns on investment for organizations and better e-learning experiences for learners.