Simply, this is a sub-genre of data-driven, AI learning technologies that respond to student inputs, and can adapt the trajectory of the presented material based on the student's competency or proficiency in the subject.
Brightspace LeaP course building tool that builds learner paths based on individual student driven data. It considers factors such as learner confidence, self-assessments, time to finish exercises, performance of specific objectives and the mastery level of past objectives. Course content can be resequenced or skipped based on student performance, enabling them to move at a pace best suited for them.
Knewton is a learning platform that adapts with every interaction the student has. Every exercise builds on the learner profile to determine the best mode of concept delivery for that specific student. It automatically scaffolds information and assessment at intricate levels, taking into account student strengths and weaknesses. Through multiple paths each student can end up achieving the course objectives.
Dreambox is an elementary focussed math platform that measures how students are thinking within the lessons. The program is said to collect, analyze and respond to over 800 data points about the individual student and how they learn. The delivery of concepts is adjusted based on this to personalize the experience and give students greater chances of success.