Flexible & Adaptive Learning

Summary

The diversity of contemporary online learning cohorts requires learning experiences that are designed for high engagement but are flexible and adaptive to the needs of autonomous learners. Adaptivity in learning design, online teaching and student support has been made possible by technologies providing timely data on learners’ knowledge, perceptions and study behaviour. Alongside this, flexibility in the timing and mode of engagement with teachers, peers and learning content, and data driven feedback on study approaches can promote agile and personalised learning experiences. This element supports enhanced learner-content, learner-learner, learner-teacher and learner-institutional engagement.

Rationale

The diversity of contemporary online learning cohorts requires learning experiences that are designed for high engagement but are flexible and adaptive to the needs of autonomous learners.

Adaptivity in learning design, online teaching and student support has been made possible by technologies providing timely data on learners’ knowledge, perceptions and study behaviour. The use of learning analytics and adaptive learning technologies can be key enabling elements for the provision of a tailored learning experience for students (Siemens & Long, 2011). Learning analytics enable personalised support from teachers and learning support staff which recognises students as individuals and ensures that problems encountered are headed off quickly. Another tool available to personalise the learning experience is the use of adaptive technologies that allow students to progress through a course at their own pace with quizzes and other online assessment techniques providing feedback and guidance to allow them to skip over material they have already mastered or engage more deeply with components where they need additional help (Irwin, Hepplestone, Holden, Parkin, & Thorpe, 2013).

Alongside this, flexibility in the timing and mode of engagement with teachers, peers and learning content, and data driven feedback on study approaches can promote agile and personalised learning experiences. Conole (2009) provides a sophisticated interpretation of personalised learning, citing the aspiration of a range of international governing bodies to move beyond a one-size-fits-all view of education. She highlights a focus on the Personal Learning Environments of individuals who learn through social engagement using a range of loosely coupled tools in their unique environments. She points to the changing educational context of open content and open courses and argues that in our increasingly connected society we need to capitalize on the affordances of all of the resources available to us to enable our learners to be part of a global, connected distributed intelligence (Conole, 2009, p. 3). This may eventually require a rethinking of course structures and credit and credentialing processes as we explore the affordances of strategies like the modularisation of content and badging of learning achievements (Gibson, Ostashewski, Flintoff, Grant, & Knight, 2013).

Strategies

Data informed course and subject design - Subject and course learning designs informed by data drawn from student and peer feedback, research and learning analytics can ensure a strong fit with learner needs and learning preferences.

Adaptive teaching - Data-informed during session adaptation of teaching strategies and resources can be undertaken based on evidence about students’ characteristics, knowledge and learning behaviours.

Data informed student support recommendations - Personalised support can be provided through use of data to inform decisions to help connect students with university support services.

Student dashboards informing self-regulation - Personalised support can be provided through dashboards providing feedback to students on their learning strategies and behaviours to inform their study decisions and approaches.

Flexible learning designs - Personalised learning journeys can be provided through flexible or adaptive lessons and resources that provide individualised pathways through content based on student knowledge, behaviours and special needs. Alternatively flexible and adaptive course designs can allow students to proceed at their own pace through differentiated or individualised pathways based on their demonstration of knowledge and competency.

Flexible assessment - Personalised learning can be supported through flexibility in assessment to provide opportunities for students to draw on personal/professional interests or expertise as part of a common task.

References