What are Adaptive Learning Technologies?


Adaptive learning technologies refer to software and online platforms that adjust to individual students’ needs as they learn. According to a paper commissioned by the Bill and Melinda Gates Foundation and authored by Education Growth Advisors, adaptive learning is a “sophisticated, data-driven, and in some cases, nonlinear approach to instruction and remediation, adjusting to a learner's interactions and demonstrated performance level, and subsequently anticipating what types of content and resources learners need at a specific point in time to make progress." In this sense, contemporary educational tools are now capable of learning the way people learn; enabled by machine learning technologies, they can adapt to each student’s progress and adjust content in real-time or provide customized exercises when they need it. In higher education, many faculty envision these adaptive platforms as new, patient tutors that can provide personalized instruction on a large scale. There are two levels to adaptive learning technologies — the first platform reacts to individual user data and adapts instructional material accordingly, while the second leverages aggregated data across a large sample of users for insights into the design and adaptation of curricula.

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(1) How might this technology be relevant to the educational sector you know best?
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(3) What do you see as the potential impact of this technology on teaching, learning, or creative inquiry?
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