The concept of confidence-based assessments plays a decisive role in making microlearning truly adaptive. The other two concepts that are equally important are spaced repetition and retrieval practice. An understanding of these 3 core concepts is a must to get the most out of your microlearning initiatives!
In this article, let’s focus on ‘confidence-based assessments’- the backbone of an adaptive microlearning approach.
James E Bruno refined this concept and showed us how we can measure the extent to which a learner has gained mastery over what’s learned.
The problem learners using guesswork
We know how learners use guesswork to score high in learning assessments after an eLearning or microlearning module. Cracking multiple choice questions code comes easy to many using guesswork. The problem is that guesswork doesn’t work when your learner/employee is faced with real-world challenges. There are no multiple choices at work for your learner.
The concept of confidence-based assessments targets the ills of this guesswork where real competency is not built. After all, the goal of any assessment is to build real competencies, and not just churn out meaningless scores.
What you are actually interested in is to know what your learner really needs. You need to know your learners’ weaknesses, opportunity areas, doubts, fears, apprehensions and lack-of-confidence. Only then can you help them overcome these gaps!
This is where the concept of ‘confidence-based assessments’ comes-in to weed out this element of guesswork. It makes gaining mastery and knowing areas of opportunity the real purpose.
What are a ‘Confidence-based Assessments’?
At the end of each eLearning or microlearning lesson, you ask questions to check for recall, and your learner gets a score. But, many learners end-up passing a test, but are not able to apply what’s learned at work. It indicates lack of knowledge and skill. Now, that’s useless and completely defeats the purpose of an assessment!
Confidence-based assessments cater to two things:
- First- a leaner’s response to a query or question
- Second (most important)- a learner’s confidence level on that response
The element of confidence is more important. Without confidence, a skill or a competency is meaningless!
Bruno came-up a 4-blocker grid that measure 2 things:
- The knowledge- correct or incorrect
- The level of confidence- 100% confident or being unsure
While seeking an answer to a multiple-choice question, we simultaneously ask the learner to declare whether or not she/he is sure (confident) of the response being chosen.
The 4-blocker grid gives you knowledge quadrants. Each quadrant depicts a certain knowledge profile of a learner about the lessons learned.
Quadrant I- Misinformation- Incorrect Knowledge, High Confidence
- Incorrect knowledge confidently believed to be correct by a learner
- Result- learner makes mistakes on the job, high-risk, disastrous
Quadrat II- Mastery— Correct Knowledge, High Confidence
- Correct knowledge confidently believed to be correct by a learner
- 100% correct, 100% confident
- Result- learner correctly applies knowledge and skill in practice, high degree of confidence, productive, fewer mistakes
Quadrant III- Doubt— Correct Knowledge, Low Confidence
- Correct knowledge with an element of doubt that exists in a learner
- Result- learner may not act on the knowledge, or act with hesitation
Quadrant IV- Uninformed— Incorrect Knowledge, Low Confidence
- Knowledge not acquired by learner yet
- Result- uninformed learner is unlikely to act, a state of inaction/paralysis
Let’s take another example in a microlearning lesson-
After each response to a question chosen, you can ask a learner ‘How confident are you about your answer?- High, Medium, Low’. This is a simple confidence rating system to check what your learner thinks she/he knows, and what she/he actually knows. The more sure your learner is about the answers chosen, the quicker, more confident, and more reliable she/he will be at work.
This way you get to test, score and interpret how confident a learner is about the correctness of one’s answer.
So, while giving assessment questions, the focus is on the knowledge quality, NOT the score.
Confidence-based Assessments and Microlearning
Confidence-based assessments capability in a microlearning platform makes it truly adaptive. By using both logical and emotional senses, you can ask relevant questions to create the knowledge profile of each learner.
This concept helps you measure baseline learning needs, capabilities and knowledge levels of each learner. Knowledge profile in turn is used by an AI-enabled microlearning platform to optimize individual performance and results by using algorithms. This is how an adaptive microlearning experience is made possible.
To conclude, the concept of confidence-based assessments helps you work through each lesson until your learner achieves proficiency. You can shorten the time to achieve work-related competency by using an adaptive microlearning approach.
Most of all, the path from Uninformed to Mastery becomes clearer, shorter and achievable!
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