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?

  • As more and more courses adopt technology-delivered learning (video, LMS, structured lessons, online quiz) it seems apparent that the next logical step will be to tailor learning. Good teachers have probably always done this, but with decreasing teacher-student contact time, adaptive learning systems could become powerful tools for education. - s.diener s.diener Feb 9, 2015

  • After a long gestation, these technologies are beginning to show some of the potential that has long been ascribed to them. With students in higher education wanting more flexible and personalised learning, these sorts of adaptive technologies are likely to have a significant impact on higher education over the next few years. - jason.lodge jason.lodge Feb 26, 2015

  • This technology has the potential for significant disruption to the current higher education model that links time, place, learning and assessment. As much as we like to think that our institutions have become more flexible, we still have term times and assessments are still due on specific days. Once data about a learner is truly integrated into the learning and assessment environment we will need to rethink what time and place means for the learner, teacher and institution. Adaptive learning is where true flexibility begins to become a reality. - geoffrey.crisp geoffrey.crisp Feb 27, 2015

(2) What themes are missing from the above description that you think are important?

  • TIME. Adaptive learning technologies can focus on mastery learning, but our culture of constructing the perfect 3-credit course for delivery in a perfect organized semester may need review. Learners learn at different paces, so what needs to be added to this description is the factor of time. Learners need adaptive time.- s.diener s.diener Feb 9, 2015

  • One aspect that is impacting on how useful these technologies will be is that the most recent advances are enabling these technologies to respond to student emotions. If students get frustrated or confused, the technology can adapt accordingly. - jason.lodge jason.lodge Feb 26, 2015

  • Intelligent Autonomous Educational Delivery Systems While there have been numerous "intelligent delivery" systems around for maybe a decade they have tended to be simple approaches structured around AI pattern responses generated from an LMS or associated product. For example where an LMS generates tailored assessment tasks based on programmed metrics or an early Google tool assisting students with content production. However progress in AI and modelling of pedagogical frameworks suggests that the future of a true multi-agent and autonomous engagement paradigm between students and teachers with active system participation is not far away. This will further challenge the concept of the role of the teacher - amongst other things. - philcounty philcounty Feb 26, 2015 This would coalesce some of the topics such as Machine Learning, Virtual Assistant and Affective Computing into a single theme. - philcounty philcounty Feb 26, 2015 Phill I came to add this topic to the page, and you have summed it up well. On the Online Learning topic page I noted that for online learning to scale up it needs to be more than a content delivery system with peer support. In order to provide more of what a traditional face to face course offers there must be both engagement of students (online learning has a massive drop out rate) and support to fill gaps in knowledge through discussions and answering questions (like what traditional Tutors who work in small groups and help guide learners. I assume that any good course (online or not) already contains the great questions around which learning occurs. My father (an ex proff of Ed and now Dir at ACER) has always maintained that real learning only occurs around questions where the answer is "it depends". So given that the online course contains the content, questions and assessments the missing bit is the direct support and activities to engage students to help stay in the course. Currently Unis have the role "digital learning assistants" who are people who's role is to stimulate and engage students to watch out for those who a disengaging, for those that a struggling and to be an online couch. (They are not often content experts as well). I therefore conclude that there is market for such a role to be digitally enhanced, initially as enabling the Digital learning assistance role to be more effective, however longer term and at its logical conclusion, be able to act as that assistant. However as you point out the real impact on learning will come come if this engagement service was truly content smart and could answer the questions students have like a human tutor. That also feeds into my other contention - that there will only be a handful of LMS's in the world in 5 years time(could be 10 based on the adoption rate in education), however for corporates it will happen faster). I dont mean versions of software, I mean a handful of cloud based platforms used by every Uni in the world. This is because the big data required to provide these massive cost savings to supporting courses which are becoming commodities can only be done in systems with huge scale.- daniel.ingvarson daniel.ingvarson Mar 1, 2015 [Editor's Note: Added here from RQ2.]

(3) What do you see as the potential impact of this technology on teaching, learning, or creative inquiry?

  • Potentially, this technology could not only provide personalized learning at scale, but also can assist teachers by objectively showing weakness in their teaching or curriculum. Bayesian modeling and IRT can both be surfaced in ways that are not overwhelming, and can be used to inform teaching (particularly around assessment validity). Using the wisdom of the teacher (prior probabilities in the model) this could lead to fairly rapid and creative changes. - s.diener s.diener Feb 9, 2015 I agree - the ability to identify areas of teaching weakness or curriculum gaps could be significant, in addition to the benefits for the students in guiding them more carefully through their learning - jwilliams jwilliams Feb 15, 2015

  • The points made above capture the potential impact nicely. - jason.lodge jason.lodge Feb 26, 2015

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(4) Do you have or know of a project working in this area?

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