In past, I considered adaptive learning a computer learning feature. The program responds to the learner’s actions and responses. I now think of personalized and adaptive as similar and part of the learning environment. The path is often automated in response to the learner’s actions, but also may be determined in part by the instructor, a success coach or an advisor. A goal of adaptive learning is to not waste learner’s time and to motivate learners. You provide them with just-in-time materials and paths to achieve the course outcomes. I see adaptive learning in the following ways. The pre-test and post-test (course and modules) not only measure learner progress to accomplishing outcomes but may be used to deliver a personalized journey.
The Canvas Learning Management System (LMS) uses Mastery Paths for both choice and personalized learning pathways. That is not to be confused with Learning Mastery. You may view my and Dr. Amanda Rosenzweig’s Mastery Path presentation from 2018 (InstructureCon). The more your learning materials can be customized, offer differentiation, and offer choice, the easier it is to create personal learning experiences. In addition, data-driven teaching can help you personalize learning. Just as a pre-test can indicate whether the learner requires lesson pre-work (remediation) it also can indicate whether the lesson may be skipped or enhanced for the learner. A challenge is in writing a pre-test that can differentiate between topics to properly prescribe a path. That is yet one more reason why I embrace microlearning. It is easier to map the journey. Diagnostic tests are also a great way to identify what learners know and do not know, making next steps easier to identify. I create Excel tests that offer diagnostic feedback based on the N-RET design.
https://community.canvaslms.com/docs/DOC-26297-how-do-i-add-requirements-to-a-moduleThe Analytics do not just show who is missing work or late with work and therefore at risk, but how often they log in, what they look at and do when they log in is helpful. Is the learner stuck? Where and what can you do to help the learner get back on track? Some see adaptive release as a feature of personalized learning. I do not. Often adaptive release becomes a barrier for weaker students. Adaptive release is when a module opens once criteria in preceding modules have been met. I prefer to use (in Canvas) module requirements.
Adaptive learning does not have to create more work for the faculty member. As online learning shifts where and when you spend time, so does an adaptive learning environment. Using a mix of LMS (system) graded activities and assessments and those you grade manually lowers the workload increased by grading different assignments each week. It is easy to set and forget assignments that are auto-graded. Therefore, I recommend that you remember to review the assignment statistics, item analysis for quizzes, and in Canvas, the New Analytics to gauge how individuals and the class as a whole are performing. The results can drive topics for your next lecture or an added lectures or resources as needed. Any application that uses branch logic can be used to create a personalized learning experience, for example, Microsoft PowerPoint or Adobe Captivate.
Educause provides a 2-page adaptive learning brief titled, 7 Things You Should Know about Adaptive Learning. The brief classifies adaptive learning as a “technique for providing personalized learning”.