Mobile Technology and Adaptive Learning

The concepts underlying adaptive technology are nothing new. It has long been recognized that different people learn in different ways. We all have different learning styles and preferences, different levels of skills and prior knowledge, different interest levels and attitudes, different learning goals and purposes. Accommodating these differences has long been the aim of differentiated classroom instruction, in which teachers tailor content, learning activities, assignments, and assessments to meet individual needs. Adaptive learning is essentially differentiated instruction delivered and supported by intelligent digital technology.

Beyond the Classroom

The advent of smart phones and other mobile devices has made it possible to individualize instruction and learning in a way that can’t be achieved within the confines of a classroom or corporate training venue. Technology can eliminate the need for the physical presence of a teacher or instructor to make the decisions involved in teaching the right content in the right way to meet the individual needs of learners. In adaptive learning, that role is played by the algorithms built into a learning management system (LMS) or the instructional modules or apps accessed through an LMS.

An Evolving Technology

Adaptive mobile learning is still an emerging science. Examples range from simple using computer-based pre-testing to determine which course or program a given learner should take to more sophisticated models employing artificial intelligence to build learner profiles that support a greater degree of adaptation to the needs of a given learner. Over time, as a learner interacts with an intelligent, adaptive LMS and the various instructional programs accessed through it, the system acquires and analyzes data regarding the individual’s:

  • Motivation level (reluctant, determined, etc.)
  • Learning style (e.g., visual, auditory, experiential, etc.)
  • Materials preferences (e.g., text, images, audio, video, etc.)
  • Knowledge level (e.g., beginner, medium, advanced, expert)
  • Achievement (based on test results)

This degree of sophistication in learner profiling maximizes student engagement, which is essential to effective learning. It ensures that learners are presented material at a customized difficulty level that will neither bore them nor frustrate and discourage them. Instruction that hits this “sweet spot” between too easy and too difficult (the Zone of Proximal Development, or ZPD), encourages creative problem-solving that carries over into the real world.

Benefits of Mobile Adaptive Learning

Mobile adaptive learning yields proven benefits in both K-12 and higher education and employee training. The business impact for companies that successfully adopt mobile adaptive learning can be substantial.

Mobile adaptive learning increases training effectiveness, as seen in the improved learner retention of newly acquired knowledge that results from a high degree of learner engagement. Adult learners are particularly averse to engaging with training that is not relevant to their immediate earning needs. In self-instructional situations they tend to focus on what they need to know but blast through or over everything else. With an LMS that delivers mobile adaptive learning, employees get exactly the information they need, when and where they need it.

Mobile adaptive learning also increases efficiency in the use of training resources – namely time, money, and materials. It holds great promise for the large-scale reskilling of workers in industries undergoing rapid technological transformation.

The Future of Mobile Adaptive Learning

In short, mobile adaptive learning has the potential to reshape education and training in a wide variety of organizations. Embedded analytics that allow the continuous collection of data can provide the basis for in-depth profiling of LMS users. More sophisticated algorithms and smarter AI tools can enable an LMS not only to maximize the differentiation of instruction but also to provide individualized insights, feedback, error correction, and enrichment to learners. While some view mobile adaptive learning as the current instructional fad “de jour,” enthusiasts envision a scalable cloud-based architecture capable of providing unique learning experiences and real-time feedback simultaneously to vast numbers of users—potentially millions. What do you think?

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