Adaptive Learning (AL) refers to responsive learning environments that make use of technology to track every aspect of learner interaction or the “micro-steps of the learning process” (Cope and Kalantzis 2016). "This often takes place in real-time, is often automated and driven by technology" (Osmosis.org). Through the use of technology - algorithms are able to customise learning pathways for each individual learner. AL environments are focused on gaining a deepened understanding of the individual learner’s needs through identifying gaps, learning styles and preferences subsequently content is changed or ‘adapted’ based on learner performance and recurring learner interactions.

Adaptive Learning Process for Medical Students' Application

Adaptive learning systems encompasses three broad education paradigms of behaviourism, cognitivism and constructivism (Sonwalkar Youtube). From these paradigmatic positions came the work of Skinner in the 1950’s on operant conditioning and stimulus-response theorising; and also Cronbach, Bloom, and more recently Pasher - underpinning Adaptive Learning Theory (Murray and Perez, 2015). These theoretical positions have informed the notions of individualisation (pace and path of learning), differentiating (changes in content delivery and methods) as well as personalisation (tailoring all facets of the learning experience to learner needs) (Means and Anderson 2013). This personalisation is driven by the iterative use of algorithms, feedback, assessment, instructor adjustments and various media as the system “learns” about the learner so as to personalise the learning (Moskal, et al. 2017).

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Exploring further into the research that drives AL systems and environments, we find learning approaches associated with Mastery Learning (Bloom), Intelligent Tutoring Systems, Deliberate Practice, Metacognition and Ebbinghaus’ Forgetting Curve (Unlocking Potential - McGraw Hill Education). Tasks are repeated as practice within certain timeframes over a period that would eventually lead to mastery and deeper learning as any number of pathways are chosen based on the learners needs. Indeed this process of remediation and repetition in terms of knowledge gains and outcomes is synonymous with AL assoicted with special needs education over the last few decades. Where individual learners could not be accommodated in mainstream classes of 20-30-40 learners. Learning needed to be paced, navigated, customised and adapted to the learners’ needs, personality, interest and learning styles and preferences - a time consuming task - let alone to do it for every child in the class. This is simplified and do-able with technologies in 21st century digital learning environments, and do-able with a vast number of learners.

Many AL providers offer large claims about the efficiency and the benefit of their products. Little research related to discernible outcomes is currently backing the application of these environments and its prized significance that it could offer. What is known is that increased motivation and engagement is taking place in the learning process. Similar to Murray and Perez (2015) raised questions around the quality of AL systems at scale and suggested that pedagogy drive the evolution of AL systems. In a snapshot study of AL (2013 - 2015) The Bill and Melinda Gates Foundation requested that AL products be put to the test in US colleges and universities. https://www.sri.com/sites/default/files/brochures/almap_final_report.pdf

The SRI Report makes it clear that the learning outcomes of learner progress and development is contingent on a number of factors and cannot be left solely to rely on the AL system i.e. student characteristics, specifics of AL system use, as well as aspects of the course beyond the digital domain.

AL is not a magic pill - but perhaps one part of the solution of education in a plagued society stretching forward towards inevitable beckoning of the leaps in our minds but still plagued and hindered by consciousness of recent history and mechanics of industrialisation.

The Khan Academy a free online education organisation who adopted an Adaptive Learning technology in 2013. From watching the video you can see many of the concepts associated with AL in terms of the design, workflow and engine - obviously the engine room of any AL system is an exciting and indeed complex space that has requires a great amount of collective intelligence in design and modification.

https://www.youtube.com/watch?v=jQQjbq0gMmE

RESOURCES:

https://learn.mheducation.com/rs/303-FKF-702/images/eBook_TOFU_Unlocking-Potential-eBook_2017.pdf?_ga=2.251841289.1061788640.1524949070-775864742.1524949070 (Unlocking Potential - McGraw Hill education ebook)

https://library.educause.edu/~/media/files/library/2017/1/eli7140.pdf (Educause Learning Initiative)

VIDEOS

https://www.youtube.com/watch?v=RmQX-lajdOI (Osmosis.org)

REFERENCES:

Cope, B. and Kalantzis, M. eds., 2017. E-Learning ecologies: principles for new learning and assessment. Taylor & Francis.

Means, B. and Anderson, K., 2013. Expanding Evidence Approaches for Learning in a Digital World. Office of Educational Technology, US Department of Education.

Murray, M. C., & Pérez, J. (2015). Informing and performing: A study comparing adaptive learning to traditional learning. Informing Science: the International Journal of an Emerging Transdiscipline, 18, 111-125. Retrieved from http://www.inform.nu/Articles/Vol18/ISJv18p111-125Murray1572.pdf

Moskal, P., Carter, D., Johnson, D. (Jan 4. 2017). “7 Things You Should Know About Adaptive Learning”. Educause Library. Retrieved Apr 26, 2018