Another quasi-experiment was conducted by Meşe and Mede (2022). The authors examined the effects of DI on the speaking proficiency and self-regulated learning (SRL) of EFL students in an online learning environment at a private Turkish university. The study involved an experimental group of 16 students and a control group of 15 students, and data were collected with the help of a speaking proficiency test and an online self-regulation questionnaire, as well as through a focus group interview with six students. The digital tools used during the intervention were GoFormative (for pre-assessments, formative assessments, and individualised feedback), Google Docs (for the assignment of tiered tasks), and Zoom (for breakout room activities, one-to-one check-in meetings, and speaking clubs). The authors found that the intervention, which differentiated the process, product, and learning environment based on students’ readiness levels and interests, led to significant improvements in the speaking proficiency of the experimental group. While there was no difference in the overall SRL of the two groups, students of the experimental group did report on improvements in their use of target setting, help seeking, and self-assessment strategies.

A qualitative action research study carried out by Vargas-Parra et al. (2018) analysed how the implementation of DI in Moodle, a virtual learning environment (VLE) affected EFL students’ learning process. The participants were a group of 29 10th-grade students studying at a private school in Colombia. Before the intervention, students were asked to complete an interest and a learning style inventory, a survey on their digital competences and two English diagnostic tests. The intervention was based on the results of these pre-intervention inquiries and included four EFL lessons mediated in Moodle, which offered students various learning choices. Data were collected through lesson observations, reflective journals written by the participating teachers and a focus group interview with the students, and then analysed through content analysis. Findings suggested that the use of DI in Moodle increased students’ motivation, engagement, and self-efficacy.

Another qualitative action research study by Güvenç (2021) examined the integration of TEDI activities in an English preparatory course at a private university in Turkey. The study investigated the students’ and the teacher-researcher’s perceptions of DI in online teaching and collected data through student questionnaires and teacher reflection notes, over a period of 13 weeks and with the participation of 12 students. Two ICT tools were used in the intervention: Rewordify, which was used for adapting reading materials to different comprehension levels, and ThingLink, which helped create interactive 3D environments. The study revealed that these tools facilitated the personalisation of the online learning experience by addressing the needs and preferences of the learners. The DI practices were seen by students as more entertaining, engaging, effective, and collaborative than conventional methods, and were also found by the teacher-researcher to increase learner agency.

The Tablio project (Hustinx et al., 2019) analysed good practices of tablet use for DI purposes in primary and secondary school classes in various subjects, including EFL. Funded by the Commission of the European Union, the project recruited teacher participants from Italy, Northern Ireland, Belgium, Slovenia, Turkey, and the Netherlands with experience in using tablets for DI. Data was collected through interviews in which participants described their practices in detail and provided visual documentation such as photographs and screenshots. The data was analysed using a theoretical framework based on Tomlinson’s (1999, 2014) model of DI to reveal what elements of DI the practices attended to. As for the subject of EFL, several good practices were identified, such as the creation of digital student portfolios on Padlet and SeeSaw for formative assessment, the inclusion of Edpuzzle for self-paced listening comprehension exercises, and the use of ThingLink, a picture and video annotation app, which can serve as a presentation tool for visual and auditory learners. These practices were found to be suitable for attending to various elements of Tomlinson’s (1999, 2014) DI model, and the teachers using these apps reported high levels of student motivation, engagement, and self-efficacy. Although the outcome of the project may be considered more of a descriptive list of good practices than an in-depth analysis, its merits of identifying innovative solutions for TEDI are beyond dispute.

An overview of these studies, briefly summarised in Table 3, suggests two points to note. Firstly, despite the differences in research methodology, research contexts, and the specific digital devices used for DI, a common theme across these studies is the reported development in learning outcomes (Rapti, 2018; Meşe & Mede, 2022) or an improvement in cognitive and affective variables such as student motivation, engagement, and self-efficacy (Güvenç, 2021; Hustinx et al., 2019; Vargas-Parra et al., 2018) (a brief discussion of the definitions of these variables is provided in Section 2.2.3.3).

 

Moreover, the TPACK framework may not only help conceptualise the building blocks of TEDI, but, as Koehler et al. (2013) point out, it can also serve “as a theoretical and a conceptual lens for researchers and educators to measure preservice and in-service teachers’ readiness to teach effectively with technology” (p. 4). This is especially important because knowing how to use digital tools (i.e., technological knowledge) does not automatically result in effective subject-specific teaching. For this to happen, the tools must be purposefully selected and used with a clear focus on achieving pedagogical aims (i.e., technological pedagogical content knowledge). In the words of Koehler et al. (2013), “good teaching with technology … cannot be achieved by simply adding a new piece of technology upon existing structures. Good teaching, with technology, requires a shift in existing pedagogical and content domains” (p. 3). In order to understand if and to what extent such shifts take place, looking at perceived and actual teaching practices is particularly important. Teachers may believe they are effectively differentiating instruction through technology, yet their use of digital tools may remain passive and reinforce teacher-centred approaches rather than promoting active, learner-centred engagement. Research on TEDI in TEFL is still limited in examining how teachers manage this shift, but such studies would be essential to understand whether the integration of technology truly enhances differentiation or simply reproduces traditional teaching methods in digital formats.

In the past few decades, a rich body of literature has emerged around the concepts of both foreign language learning motivation (Csizér, 2020; Ushioda, 2019) and self-efficacy beliefs (Mills, 2014), as well as the possible interplay between these variables (e.g., Csizér et al., 2021; Khoadad & Kaur, 2016; Linnenbrink & Pintrich, 2002; Piniel & Csizér, 2013).

Students’ motivated learning behaviour is regarded as one of the most important individual difference variables leading to the success of foreign language learning (Piniel & Csizér, 2013), and one that has been generally understood as “students’ effort that they are willing to invest into foreign language learning” (Csizér et al., 2021, p. 4). Out of the variables traditionally investigated in relation to motivated learning behaviour, most often as a predictor variable of motivated learning behaviour (Csizér & Kormos, 2009; Islam et al., 2013; Kormos & Csizér, 2008; Taguchi et al., 2009) and also one that is frequently mentioned as a variable increasing as a result of differentiation, is language learning experience, which may be defined as “the perceived quality of the learners’ engagement with various aspects of the language learning process” (Dörnyei, 2019, p. 19). As Dörnyei (2019) points out, this notion has mostly been operationalised as an affective construct, referring to how students emotionally relate to the learning experience. However, Dörnyei argues that if the construct is to be understood as students’ engagement with learning, then it should be seen as a more complex construct, encompassing behavioural, cognitive, affective, and social dimensions. Within this interpretation, the behavioural dimension refers to “actual learning behaviors a student displays through their observable actions”, while the cognitive and affective dimensions pertain to internal aspects such as “the learners’ cognitive and emotional participation (i.e., genuine personal identification with the learning process)” (p. 24).

With this more complex understanding of language learning experience/engagement, the constructs of motivated learning behaviour and the behavioural dimension of language learning experience/engagement become closely intertwined. In fact, as Henry and Thorsen (2018) argue, “since motivation rarely flows completely unhindered into action, it is the behavioral outworkings of various motivational sources that are captured in the engagement construct” (p. 3). Philp and Duchesne (2016) argue in a similar way when, citing multiple authors (Ainley, 2012; Cleary & Zimmerman, 2012; Martin, 2012; Reeve, 2012), they state that engagement “is described by some as the visible manifestation or ‘descriptor’ of motivation” (p. 52). As a result, in recent observational research, it is not uncommon to treat these constructs together under measurable terms such as interest, concentration, effort, active participation, and emotional responsiveness (Philp & Duchesne, 2016).

Another construct often examined within the context of DI and TEDI is self-efficacy, which originates from Bandura’s social cognitive theory (1986), and in the context of FL learning it refers to learners’ beliefs about their capabilities “to successfully learn a foreign language in the school context and to complete particular language-learning tasks” (Csizér et al., 2021, p. 5). According to Bandura (1997), learners’ self-efficacy beliefs are influenced by their experiences of success (mastery experiences), the comparison of their achievements to those of their peers (vicarious experiences), the feedback they receive from their teachers (verbal persuasion), and the emotions experienced while learning (emotional indicators). Since the goal of readiness-based DI is to provide students with an appropriate level of challenge, which in turn is to generate feelings of genuine success (Tomlinson, 2017), the concept of differentiation seems to be closely linked with self-efficacy, and more specifically, with mastery experiences, which, according to Bandura (1997), are the most influential sources of self-efficacy. This link has been addressed in theory (e.g., Tomlinson, 2017) as well as in some studies on the differentiated teaching of various subjects (e.g., Hood, 2012; Lai et al., 2020); however, to the best of the author’s knowledge, in the context of TEFL the relationship between readiness-based DI and self-efficacy beliefs has yet to be confirmed statistically.

In examining the affective and cognitive variables that TEDI is believed to foster, and when evaluating the effectiveness of TEDI practices more generally, it is important to consider whether students’ motivation and self-efficacy are primarily driven by the technological medium itself or by the instructional content it supports. The mere entertainment value of technology should not be mistaken for meaningful educational engagement; ideally, such positive effects should stem from the learning process facilitated by technology, rather than from its pure entertaining features (Blaz, 2016).

As such, when assessing these practices, content- and modality-oriented motivation and self-efficacy do not necessarily need to be viewed as mutually exclusive; rather, they could be regarded as interacting factors that may jointly enhance learning. This perspective is supported by Keller’s (1984, 2012) ARCS model of instructional design, which identifies four components of effective learning experiences: attention (A), relevance (R), confidence (C), and satisfaction (S). According to this model, motivation is attained by capturing learners’ attention—something technology can often facilitate—but it is also important for the content to be relevant to their interests and needs, which differentiation can help achieve. Moreover, fostering learners’ confidence by strengthening their beliefs in their ability to succeed, which ultimately leads to satisfaction, is also of utmost importance. Thus, according to this model, the modality and the educational content can operate in an interconnected manner: when integrated meaningfully, technology can promote deeper engagement with the content, rather than functioning merely as a source of entertainment. As such, a purposeful combination of content and modality can create a new quality of learning experience that enhances both motivation and self-efficacy.

To date, research on how this balance can be effectively attained within TEDI in the context of TEFL remains scarce; the studies that were reviewed in Section 2.2.3.1 include no explicit discussion of this question. What can be established based on the overview is that some of the tools used in these studies, such as EdPuzzle (Hustinx et al., 2019) or GoFormative (Meşe & Mede, 2022), have the potential to support learner-centred teaching, as they enable self-paced learning and self-differentiation, and offer various options for content, process, and product differentiation. However, it would be important for future research to critically examine how technology can be harnessed as a tool for enhancing differentiation through the meaningful combination of content and modality.