2.2.2 The Affordances of Technology for Differentiated Instruction

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As Stanford et al. (2010) point out, technology could help teachers to “think and work ‘smarter’ … rather than trying to work harder” when catering for individual needs (p. 2). ICT is believed to offer various ‘smart’ features that could be helpful in supporting differentiation efforts.

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Firstly, technology can facilitate self-paced learning by allowing students to proceed at their own speed, and thus to have more control over their learning process (Anderson, 2008; Larsen-Freeman & Anderson, 2011; Valiande & Tarman, 2011; Zeng, 2020). There are several applications (apps) which adapt to the individual readiness levels of learners by analysing their input and providing customised feedback and practice tailored to their proficiency (Larsen-Freeman & Anderson, 2011; Renandya et al., 2023; Zeng, 2020). By using such tools “students can explore, investigate and present their work with support when needed at their own pace” (Primary Professional Development Service, n.d., p. 19) and “make choices of when, what, and how to learn based on their own proficiency levels, goals and learning styles” with the “affordance of the time to think and the possibility for feedback” (Zeng, 2020, p. 26). As student choice is a central aspect of DI (Tennant, 2017), the support ICT tools can provide in this respect seems to be especially important.

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Secondly, ICT tools can cater for students’ different learning profiles by allowing for auditory, visual and social learning (Stanford et al., 2010; Richards, 2015). As Benjamin (2014) formulates, “the interplay and possibilities of learning through words, images, and sounds, as well as the availability of review, make computers extremely effective as learning tools” (p. 6). Smith and Throne (2007) posit a similar view by stating that “technology easily complements activities based on multiple intelligences and allows teachers to support students with distinct learning profiles” through the use of a wide range of choices including “web research, databases, spreadsheets, software (such as interactive, drill and practice, group decision or collaborative, movie-making, robotics, multimedia, and concept mapping), handheld computers, and WebQuests” (p. 70) .

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Besides, many ICT tools offer an element of gaming, either through gamification, i.e., by using “game design elements in non-game context” (Deterding et al., 2011, p. 9) or through game-based learning, i.e., by integrating the learning process into actual games (Dimitra et al., 2020). Both approaches can enhance DI by offering varied challenges, instant feedback, customised rewards, while also fostering community through transparent class rules and flexible grouping (Barbarics, 2023; Dimitra et al., 2020; Moyle, 2012; Wiggins, 2016). Besides, game-based learning allows for task-based, authentic learning by providing students with meaningful and contextualised input (Lajtai, 2022), which is another important component of differentiated learning (Blaz, 2016; Tomlinson & Imbeau, 2023).

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Finally, ICT-supported learning environments are often associated with increased student motivation and engagement (Benjamin, 2014; Dóczi, 2024; Larsen-Freeman & Anderson, 2011), which is an additional affordance worth considering. As Benjamin (2014) argues, DI is often project-based, “favouring authentic, constructivist activities” (p. 6), which are supported by a wide range of ICT tools that not only boost motivation but also make learning more relevant and meaningful by connecting it to real-life contexts.

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The abovementioned characteristics of ICT offer promising opportunities for the enhancement of DI. However, as Benjamin (2014) points out, when using technology for DI, the importance of a solid pedagogical basis cannot be overlooked: “When it comes to DI, we don’t want to put kids on computers just to keep them occupied while we work with other groups. We want computers to enhance instruction, not just parallel it” (p. 4). She argues that TEDI needs to be rooted in the Piagetian and Vygotskian basis of DI and focus on “uses of technology that are truly constructivist, where students engage in higher level thinking, meaningful communication, creation of original work, and problem solving in nonlinear ways” (p. 4). By referring to the Bloomian categories (1956) of higher-level thinking, Benjamin (2014) contends that cognitively challenging tasks play a crucial role in supporting learners’ active engagement in meaning-making. The following section offers an overview of empirical studies that investigated such meaningful applications of TEDI in ELT.
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