What are adaptive-learning and micro-learning?
Adaptive-learning
We call adaptive learning educational processes that adapt to each learner, to his personal progress, his cognitive workings and, possibly, his preferences and choices.
Micro-learning
Micro-learning consists of brief but repeated cognitive requests, each requiring reduced effort, but building solid progressive learning. Thus, learning moments can take place in the interstices of a day, ultimately like natural learning in working conditions. Micro-learning is not an alternative to more concentrated training; it is a valuable complement, and, in certain cases, an extension. Micro-learning must also be adaptive, so that each request is truly useful, at a perfectly adapted level, well in line with the learner's progress.
Let's see how ExperQuiz chose to implement and combine these two approaches in order to increase the performance of training.
Analysis and decision
Fundamentally, adaptive-learning consists, at each stage of a learning journey, of making decisions about the most relevant continuation for optimal learning.
These decisions involve rules that are based on data collected relating to the learner. The positioning test is typically a source of data allowing you to decide: identify the subjects to be reinforced, go back on certain concepts, skip a step, offer more suitable content. To do this, it is essential that each assessment not only produces a score, but provides the multidimensional analysis essential for sophisticated and relevant decision-making.
The bases of the assessment
ExperQuiz is an LMS designed to support the most advanced assessment strategies, starting with the development of evaluation questionnaires: possibilities to create question bases thanks to an advanced question authoring tool offering a wide range of models, integrating various medias (images, videos, audios, pdf, documents, etc.).
The questionnaires come next, as support for different assessments. A questionnaire is defined by a selection of questions and by the different ways in which they are administered: will the questions be mixed? How will time be checked? How will the score be calculated? What feedback will be given after each question? 25 parameters enable us to define a test for each use case (positioning, formative, certification assessments, etc.). Some questionnaires correspond to a fixed set of questions, others to questions dynamically selected from the database, partly at random, but respecting certain criteria (level of difficulty, coverage of themes).
Scheduling of micro-learning events
The implementation of micro-learning will include the notion of cycle, a scenario which programs different requests over time. For example, a cycle will send a questionnaire to a group of learners once a week, every Monday morning, or daily, for 90 days, etc.
Those registered for a cycle of this type (learners or employees) automatically receive an email or SMS request at each scheduled deadline: they are invited to participate in a short exercise (typically 3-5 questions, or sometimes just one). At 30 seconds per question, or a few minutes at most, the event has a fun dimension, the satisfaction of receiving your little daily challenge, and seeing your score progress!
A personalized selection of questions
The questionnaire used in a micro-learning cycle is dynamic: it mobilizes questions selected on a case-by-case basis. The process is adaptive: the choice of questions, each day, comes from different rules aimed at optimizing learning in a personalized way, based on the answers already given by the learner.
Three types of rules come into play
- First, to “vary the pleasures”, the repetition of the same questions must be avoided; from a base of around a hundred questions, for example, we will choose new questions to gradually complete the coverage of the subject.
- Then, you must identify the concepts that are insufficiently mastered and come back to them, but not too quickly; the algorithm, which has identified knowledge to be consolidated, will allow a period of a few days to pass before returning to this notion.
- Finally, if knowledge has been confirmed by several correct answers, there is no point in returning to it. The intelligent and personalized choice of questions for each request improves anchoring and the learning curve; it stimulates the learner without weariness. Also affected are soft-skills: adaptive learning allows their assessment via specific questions, to integrate their development into an adaptive-learning or micro-learning course.
By combining the adaptive and personalized selection of questions asked and the flexible programming of regular requests, it is possible to launch a micro and adaptive-learning approach.
Vary the approaches and tools
Other tools offered by ExperQuiz make it possible to adapt and personalize learning approaches.
With each assessment, personalized consequences : for example, the tool allows you to define the consequences of an evaluation. Different actions will be carried out following an assessment, according to the analysis of the results of the learner — an analysis which is based on the overall score and on all the scores associated with the different areas covered in the theme, as well.
We will use this technique to identify weaknesses in an area and program actions accordingly (submission of another questionnaire, easier or more targeted to the area to be strengthened, registration to an e-learning module, or assignment to a specific group, etc.).
When it comes to learning, it is essential to be able to vary approaches, to target the same learning from different angles and with different tools, different paces.