By Louis Major & Gill A. Francis
With schools around the world closed to prevent the spread of COVID-19, we have been undertaking a series of ‘rapid evidence reviews’ to help education decision-makers respond effectively. These reviews aim to provide evidence-based summaries on specific areas of EdTech. In this post, we look at the role of technology in supporting personalised learning.
What do we mean by personalised learning?
As with so many concepts in education, there is no universal definition of ‘personalised learning’. In our rapid evidence review we define this as “the ways in which technology enables or supports learning based upon particular characteristics of relevance or importance to learners”.
Personalising education by adapting learning opportunities and teaching to the needs of individual students has always been an aim of educators. Everyday practice in schools around the world typically involves some personalisation. For example, when walking around a classroom, teachers usually personalise their teaching by giving extra support to those who are struggling, while challenging further those who are making good progress (Holmes et al., 2018). The idea of personalised learning is therefore not new. There are, however, considerable variations in how personalisation happens in practice.
Research on technology’s role in enabling personalised learning can be traced back many years, for instance, to groundbreaking work on ‘teaching machines’ in the 1920s and 1950s. EdTech visionary Seymour Papert also once wrote that because computers can take on “a thousand forms and can serve a thousand functions, [they] can appeal to a thousand tastes” (Papert, 1980, p. viii).
With increasing availability and sophistication of technology, the adaptive and personalisable features of EdTech have been suggested as offering a powerful means for addressing important educational challenges. This includes a potentially pivotal role in tackling one of the greatest disruptions to education in our time — an effective response to ongoing school closures.
A growing body of research demonstrates how technology-supported personalised learning can allow different kinds of content to reflect learners’ own preferences and cultural context, in addition to automatically capturing and responding to students’ learning patterns with data. It can also enable the pace of learning to be adjusted in a way that empowers learners to choose how and when they learn.
Such capabilities of EdTech potentially allow new scalable opportunities for greater personalisation that adjust the learning experience based on age, ability, prior knowledge and personal relevance (FitzGerald et al., 2018). In low- and middle-income countries in particular, technology-supported personalised learning carries significant promise to improve education. For instance, by increasing access to education, enabling teaching at the ‘right’ level and reducing the negative effects of high pupil–teacher ratios.
What did our research find?
Our work involved a systematic search for evidence to answer “What is known about personalised learning through using technology that can be of value in responding effectively to mass school shutdowns in low- and middle-income countries?”. After a screening process, 24 studies undertaken in 12 countries since 2006 were analysed. You can read our full report and more about the methodology here.
On the whole, technology-supported personalised learning is reported to have an encouraging and positive impact. Our work shows there is a growing base of strong evidence on how technology-supported personalised learning can improve learning outcomes.
- Technology-supported personalised learning appears to offer significant promise to improve learning outcomes, including potentially for ‘out-of-class’ and ‘out-of-school’ learning. Further research is, however, needed and it is important to remember that most existing research conducted ‘out-of-school’ has been in classroom-type settings with support from facilitators. It is also unclear how long any learning gains persist over time.
- The adaptive nature of technology-supported personalised learning to ‘teach at the right level’ is key as it lets students learn at their own pace and level. It can also adaptively respond to learner’s inputs to deliver individually customised resources and activities for all students regardless of the extent of heterogeneity in learning levels in the class.
- Technology-supported personalised learning may be most beneficial in closing educational gaps for lower attaining students, potentially including those returning to school after an absence. This is particularly significant in the context of mass school shutdowns. Much of the evidence points to it being an effective avenue for supporting remedial instruction in mathematics and science. Note, ‘personalised learning’ does not necessarily mean ‘individualised learning’; it can include groups and some research indicates the beneficial nature of student collaboration in this context (as in many others).
- Any introduction of personalised learning technology should not be interpreted as decreasing the importance of the teacher, but rather enhancing it. Technology-supported personalised learning approaches also appear to have some promise in helping teachers improve their own subject and conceptual knowledge.
- The implications for cost and infrastructure are also unclear as is whether the ‘added value’ of technology-supported approaches are cost-effective. When reviewing these findings we must remember the body of evidence is still quite limited. More research is needed to learn about the benefits of using technology to support personalised learning, particularly in low- and middle-income countries.
Nonetheless, one of the key recommendations is that technology-supported approaches to personalised learning warrant serious consideration by education decision-makers interested in using EdTech to respond to the current crisis. Beyond the crisis too, EdTech offers one potential way to “build back better” in the post-COVID world.
Technology-supported personalised learning approaches that complement teaching or are integrated into the teaching and learning process may aid in this process. New personalised models of technology-supported education will, therefore, likely form an increasingly important part of the educational landscape moving forwards. Researching how technology can adapt to the diverse needs of marginalised learners will be one area of interest for the EdTech Hub as we work to accelerate progress toward ending the global learning crisis by increasing the use of evidence to inform decision-making about education technology.
We would like to thank all those colleagues who kindly reviewed drafts of the rapid evidence review. Your constructive advice was invaluable in improving the quality of the final work. All the reviews are available here.
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