The development of digital literacy (DL) is essential for individuals to navigate and excel in digitally mediated environments effectively. Concurrently, self-regulated learning (SRL) is a fundamental competence in the face of challenges (Morris & König, 2020; Morris & Rohs, 2021). Although proficiency in DL is widely acknowledged as a prerequisite for effective self-regulated learning (), it is evident that people require self-regulation capacity to assist their digital learning (Anthonysamy, 2022; Johnson et al., 2014). However, the interconnection between SRL and DL as competencies remains a largely uncharted territory.

DL is a multidimensional construct that includes information and data literacy, communication and collaboration, media literacy, digital content creation, security, intellectual property issues, problem solving and critical thinking (Publications Office of the European Union, 2018; Godaert et al., 2022). SRL remains a critical skill in lifelong learning, facilitating individuals’ ability to set goals, exhibit motivation, and adapt to challenges (Pintrich, 1995; Carver & Scheier, 2000). In recent years, increasing attention has been paid to the role of SRL in digital learning environments, where learners are required to manage their own learning processes in often less structured and more autonomous settings (e.g., Gambo & Shakir, 2021; Morris & Rohs, 2023). For instance, SRL can be effectively fostered in digital learning contexts through the provision of interactive features, timely feedback, and tools that support self-monitoring and self-assessment (Steffens, 2006).

Importantly, digital learning is not limited to fully virtual settings; rather, it encompasses a spectrum of technology-enhanced learning environments. Within these environments, DL represents a foundational competence that enables learners to navigate, evaluate, and engage with digital content and tools effectively. Thus, DL not only supports technical engagement with digital platforms but also facilitates metacognitive processes that are central to SRL. Understanding the relationship between DL and SRL is essential, as this interdependence underpins students’ ability to learn effectively and autonomously in today’s technology-rich educational landscape. A clearer understanding of this association can inform the design of digital learning environments and interventions aimed at enhancing both digital and self-regulatory competencies. Therefore, the first research question of this study aims to provide a quantitative understanding of the overall relationship between SRL and digital literacy DL, which serves as a foundation for conducting more fine-grained analyses in the subsequent stages of the study:

RQ1

What is the overall association between digital literacy (DL) and self-regulated learning (SRL)?

Theoretically, both of DL and SRL are predicated on an individual’s active agency. Wolf (2007) pointed out that the convergence of SRL and DL underscores both shared principles and distinctions (see Fig. 1). Specifically, both emphasize task-specific regulatory processes, such as monitoring and self-reflection – for instance, self-regulated learners monitor their progress (Winne, 1995), while DL involves self-evaluation (i.e., evaluating information sources, Eisenberg & Berkowitz, 1992). SRL focuses on subject-specific metacognition and motivation (Boekaerts & Niemivirta, 2000), whereas DL is oriented towards problem-solving tasks (Abilock, 2004; Eisenberg, 2008). Additionally, both DL and SRL involve the accumulation of behavioral, cognitive, and emotional experiences to build expertise and prepare for future challenges (Wolf, 2007).

Willem et al. (2006) adapted the SRL cycle—comprising planning and analysis, monitoring and reflection, and evaluation and application—to the context of media literacy. They aligned each phase of SRL with key media literacy competencies, including media access, message analysis, message evaluation, and content creation. This alignment offers a comprehensive framework that underscores the cognitive and metacognitive skills essential for media literacy.

Despite such conceptual overlaps, an important theoretical issue remains insufficiently addressed: the degree to which empirical studies examining the relationship between DL and SRL explicitly adopt and integrate established theoretical frameworks. Furthermore, it is unclear whether the theoretical models employed across studies exhibit consistency or instead reflect conceptual fragmentation. Clarifying these issues is essential, as theoretical inconsistencies may hinder the accumulation of coherent knowledge and obscure the underlying mechanisms that link DL and SRL.

In terms of theoretical frameworks, a wide range of SRL models have been proposed from diverse perspectives (Panadero, 2017). These include the socio-cognitive perspective, exemplified by Zimmerman’s (2000) cyclical phases model; the emotional perspective, as reflected in Boekaerts’ (2000) dual processing model; the metacognitive perspective, as captured in Winne’s (2017) model of SRL; the motivational perspective, illustrated by Pintrich et al.’s (1991, 1993) SRL model; and the collaborative learning perspective, represented by the socially shared regulation of learning model (Hadwin et al., 2011).

With regard to DL frameworks, four major conceptual perspectives can be identified based on their underlying emphasis. First, the competency-based perspective operationalizes DL into measurable skills and performance levels (e.g., DigComp; Vuorikari et al., 2022). Second, the cognitive-developmental perspective emphasizes the role of cognitive processes in digital literacy (e.g., Eshet, 2004 cognitive model). Third, the sociocultural perspective views DL as socially situated practices shaped by context, power relations, and identity (e.g., Lankshear & Knobel, 2008). Finally, the holistic perspective integrates technical, cognitive, emotional, and social dimensions into a comprehensive framework (e.g., Ng’s (2012) tripartite model).

As Jones and Czerniewicz (2011) posit, the utilization of an explicit theoretical framework in empirical research can facilitate the generalization of findings across disparate contexts, thereby enabling researchers to advance their understanding collectively. Although previous scholars have explored the relationship between DL and SRL theoretically (Wolf, 2007), there is a paucity of evidence regarding how existing empirical studies have drawn upon these theoretical insights and the extent to which explicit theories have been systematically employed to guide research design, construct operationalization, and data interpretation. Therefore, this study aims to fill this gap by systematically analyzing the theoretical underpinnings of empirical studies on DL and SRL. Through this review, we seek to identify whether the current literature is grounded in coherent theoretical frameworks or marked by conceptual divergence, and what implications this has for theory development and practical application in digital learning. The second research question is:

RQ2

To what extent are existing empirical studies on DL and SRL theory-based, and what theoretical frameworks have been employed to guide their investigation?

The use of diverse theoretical frameworks and assumptions by different authors has led to the use of various concepts and measurement tools to assess SRL (Panadero, 2017) and DL (Law et al., 2018). As a result, the overall correlation between SRL and DL has yielded inconsistent findings. Such discrepancies may stem, in part, from differences in how these constructs are operationalized and measured across studies. For example, SRL may be assessed using metacognitive strategy use in one study and motivational regulation in another, while DL measures may range from basic technical skills to critical evaluation or content creation. These conceptual and methodological variations can affect the strength and direction of the observed relationships. To gain a deeper understanding of the DL–SRL relationship, this systematic review examines the specific dimensions of SRL and DL targeted by different measurement tools, as well as the extent to which these tools moderate the reported correlation.

This approach is theoretically grounded in the assumption that measurement instruments do not merely reflect constructs but also shape their empirical representation. Drawing from construct validity theory (Messick, 1995), inconsistencies in operational definitions may result in construct underrepresentation or contamination, thereby influencing observed associations. Therefore, the third research question is:

RQ3

What and how do different measurement instruments moderate the relationship between SRL and DL?

In addition, the capacity for SRL and DL exhibits considerable variability between individuals and across geographical locations (Hatlevik et al., 2018; Van Deursen & Van Dijk, 2014). These differences may reflect broader sociocultural, educational, and infrastructural contexts, which shape both the development and expression of SRL and DL. For example, ecological systems theory (Bronfenbrenner, 1994) and sociocultural learning theory suggest that learners’ cognitive and behavioral engagement with digital tools and self-regulatory strategies are embedded within specific cultural, institutional, and technological environments. Therefore, the context in which individuals reside may influence not only their levels of SRL and DL but also the strength of the relationship between them. Therefore, the fourth research question is:

RQ4

How do these research participants and geographical locations background moderate the relationship between SRL and DL?

Above all, a systematic review of this relationship would be beneficial for adapting education to the digital age, enhancing student outcomes, promoting equity, and contributing to the development of effective educational practices and policies.

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