Technology-mediated personalised learning for younger learners: Concepts, design, methods and practice

INTRODUCTION Technology-mediated personalised learning has a rich history (Reich, 2020). In the late 2000s, the concept of ‘personalised learning’ was introduced to refer to learning that happens less face-to-face and through whole-class instruction with more time for the individual to work with adaptive learning tools that address individual needs by providing tailored support (Fitzgerald et al., 2018). Personalised learning has been defined in many different ways but recurring elements within definitions are the characteristics of the learner that are taken into account (eg, prior knowledge, interests, preferences), design components that enable personalisation during learning (eg, pace, sequence, technology, choice) and the learner outcomes that are targeted (eg, agency, motivation, performance) (Bernacki et al., 2021). It has been argued that if we consider children's differences when we develop learning environments, children will benefit in terms of learning outcomes, learning experience and attitudes towards particular subjects (Reynvoet et al., 2021). Nowadays teachers have access to digital technologies, which have accelerated the movement towards personalised learning environments (Plass & Pawar, 2020). The increased popularity of digital personalised learning environments can be seen across multiple domains such as educational public policy decisions (financing projects which promote digital technologies), personalised learning platforms promoted by private EdTech companies and academic research investigating the concept. The use of digital learning technologies has facilitated many opportunities to personalise the learning environment. A systematic review by Griffith et al. (2020) on the factors that influence learning when young children use interactive apps showed that children benefit from interactive and game-like activities, adaptive learning technologies and immediate, individual feedback, which promote repeated and varied practice of academic skills. Teachers, on the other hand, benefit from actionable data and learner feedback (Fitzgerald et al., 2018). Intelligent tutoring systems and exploratory learning environments are two examples through which technology-mediated personalised learning can be established (Holmes et al., 2018). Lately, the optimisation and personalisation of learning environments was further boosted with the increasing use of learning analytics in which the analysis of large data sets is central (Gašević et al., 2016). Furthermore, in the light of the widespread disruption to young children's education due to the global pandemic, the interest in technology-mediated personalised learning has particularly become a pertinent and beneficial topic for research to enable remote teaching (Major et al., 2021)