This study contributes a replicable model of DigComp-aligned, student-facilitated PBL modules for Grades 2–4 and provides effect-size evidence from a quasi-experimental evaluation. The originality lies in operationalising university–school collaboration as a structured scaffolding mechanism for pupils’ digital competence development (rather than positioning pre-service students as researchers).

Although “digital competence” is widely used in education policy and research, it becomes analytically useful only when defined in ways that can be observed and assessed in age-appropriate tasks. The DigComp framework offers a structured model of digital competence through clearly defined domains and competence descriptors (Carretero et al., 2017; Vuorikari et al., 2022). Importantly, applying DigComp logic to Grades 2–4 does not imply expecting advanced technical proficiency. Instead, it supports a developmental interpretation of competence as purposeful, guided tool use in learning contexts.

In this study, digital skills are treated as task-level, procedural abilities (e.g., using basic functions of a platform or app), whereas digital competence refers to the integrated and meaningful use of those skills to accomplish learning goals under classroom conditions (Carretero et al., 2017; Vuorikari et al., 2022). For primary-aged learners, this distinction is essential: competence is demonstrated when pupils can (a) locate and select relevant information for a task, (b) communicate and collaborate within rule-governed digital routines, (c) create simple multimodal artefacts (posters, presentations, short digital stories), and (d) apply foundational safety practices (privacy awareness, respectful online behavior, and basic password routines). At the national level, Kazakhstan’s Digital Literacy Program for primary schooling reflects a policy intent to align local competencies with international frameworks (Ministry of Education and Science of the Republic of Kazakhstan [MES RK], 2021), while research continues to highlight implementation challenges related to teacher readiness and institutional capacity (Alférez-Pastor et al., 2023).

Project-based learning (PBL) is commonly grounded in experiential and sociocultural traditions that emphasise active learning through meaningful activity and social mediation (Dewey, 1938; Vygotsky, 1978). Kolb’s (1984) experiential learning cycle further clarifies how learning can be strengthened when action is coupled with reflection. In contemporary formulations, PBL is distinguished by sustained inquiry, authenticity, collaboration, and production of a tangible outcome, rather than by isolated “projects” as classroom events (Kokotsaki et al., 2016; Dias and Brantley-Dias, 2017).

This logic is directly relevant to digital competence because many digital behaviors in school are functional: pupils search, select, coordinate, create, revise, and present using digital tools. PBL makes these behaviors purposeful and socially distributed, thereby increasing opportunities for repeated enactment of target competencies. Empirical research in primary contexts supports the potential of well-structured PBL to foster broad competence indicators associated with twenty-first century skills, especially when projects are sequenced and guided (Rehman et al., 2023). For digital competence interventions, this literature also implies that domain-specific gains are likely to mirror task emphasis: domains repeatedly enacted in projects (often content creation and collaboration) may grow more strongly than those requiring routinised reinforcement (often safety), unless safety is systematically threaded through modules (Kokotsaki et al., 2016; Rehman et al., 2023).

A central debate in the PBL literature concerns the balance between learner autonomy and instructional guidance. From a cognitive load perspective, minimally guided approaches may be inefficient for novices because they can overload working memory and reduce learning effectiveness (Kirschner et al., 2006). In contrast, research on scaffolded inquiry argues that PBL and inquiry do not require the absence of guidance; rather, they depend on structured scaffolds (modeling, prompts, feedback, and staged task decomposition) that are gradually withdrawn as learners gain competence (Hmelo-Silver et al., 2007). This tension is particularly salient in early grades, where pupils typically require clear routines and close support to sustain collaborative work and regulate attention In the Kazakhstani primary-school context, Zhumabayeva et al. (2025) similarly foreground neuro-didactic principles in the design of learning content for younger pupils, reinforcing the argument that early-grade learning benefits from structured supports aligned with children’s attentional and self-regulation capacities.

Within this debate, student-facilitated PBL can be theoretically justified as a delivery model that increases the density and quality of scaffolding during project work (Dias and Brantley-Dias, 2017; Hmelo-Silver et al., 2007). However, the same literature implies a methodological requirement: studies must report implementation features (scaffolding routines, facilitator roles, and intervention dosage) clearly, because “PBL” as a label is not sufficient for replication or for interpreting outcome patterns (Kokotsaki et al., 2016).

Terminological precision is important for interpreting results and for formulating recommendations. In this paper, the digital divide refers to measurable disparities in access and immediate conditions of use (devices, connectivity, and opportunities to engage with digital tools in learning). Digital inequality is treated as a broader concept capturing the structural patterning of such disparities through socio-economic resources, parental support, and institutional capacity, including teacher training and school-level resourcing (Gottschalk and Weise, 2023). Equity-focused syntheses caution that technology can either narrow or widen educational gaps depending on how it is implemented, how teachers are supported, and whether pedagogical design reduces dependence on out-of-school resources (Gottschalk and Weise, 2023; UNESCO, 2023). For school-based PBL aimed at digital competence, this implies the need to specify minimum technological requirements per module, document baseline access conditions, and embed safety routines consistently—so that competence development is not contingent on home resources.

Taken together, the reviewed literature supports a focused logic for the present study. First, DigComp-informed work provides a coherent structure for defining digital competence and translating it into age-appropriate indicators for Grades 2–4, which directly informs instrument design and baseline profiling (Carretero et al., 2017; Vuorikari et al., 2022). Second, PBL research explains why sustained, product-oriented inquiry can generate meaningful opportunities to enact digital behaviors across information literacy, collaboration, and content creation (Kokotsaki et al., 2016; Rehman et al., 2023). Third, the autonomy–guidance debate clarifies that scaffolding is a necessary condition of effectiveness in early grades, motivating transparent reporting of facilitation routines and intervention dosage for replication (Hmelo-Silver et al., 2007; Kirschner et al., 2006). Finally, digital equity research frames contextual constraints that may shape feasibility and pacing of implementation, thereby informing replication recommendations for diverse school settings (Gottschalk and Weise, 2023; UNESCO, 2023).

This study adopted a quasi-experimental, non-equivalent control group pretest–posttest design. The approach was selected because the intervention had to be implemented in intact classroom conditions, making individual randomization impractical. Allocation to conditions was performed at the class level to minimize disruption to the school schedule; therefore, the study is classified as quasi-experimental even though groups were balanced by grade and baseline characteristics. Intervention effects were estimated by comparing (a) post-test outcomes and (b) gain scores (T1–T0) between the experimental and control groups. Statistical analyses relied on independent-samples t-tests (Welch’s t where assumptions were violated) and effect sizes (Cohen’s d), complemented by structured observations to triangulate behavioral indicators of competence. Importantly, teacher-education undergraduates acted only as trained classroom facilitators; study design, data collection, and data analysis were carried out by the research team.

The study involved 124 primary school students (Grades 2 to 4) from a single mainstream school. Classes were randomly assigned into two groups: the experimental group (n = 62), in which students engaged in project-based learning facilitated by pre-service teachers from a pedagogical university, and the control group (n = 62), which followed the standard curriculum without additional project assignments. To ensure comparability, a stratified random sampling method was applied. Within each grade level (2nd, 3rd, and 4th grades), students were randomly distributed across groups while controlling for gender and baseline digital competence levels. This stratification reduced the impact of age and academic differences and supported internal validity. The two groups were statistically equivalent in terms of gender, age (mean age = 9.1 years), and initial digital skill levels (p > 0.05), thereby allowing for the use of Student’s t-test to evaluate post-intervention differences. To implement the project modules, 24 fourth-year undergraduate students from the teacher training university were recruited. All participants had completed foundational coursework in pedagogy and underwent additional training in both project-based learning (PBL) methods and the use of digital educational tools prior to the intervention.

Within the quasi-experimental framework, the type of instruction served as the independent variable (traditional versus project-based with student-teacher involvement), while the dependent variable was the level of digital competence demonstrated by pupils. This competence was assessed across four core components of the DigComp 2.1 framework: information and data literacy, communication and collaboration, digital content creation, and digital safety. Changes in digital competence were measured before and after the intervention using a mixed-methods approach that included both a self-assessment scale and validated observational checklists. This dual strategy enabled a comprehensive evaluation of both quantitative progress and observational indicators in pupils’ digital skill development. The study was conducted in a mainstream public primary school in Kazakhstan (site de-identified) following the national curriculum, including regular age-appropriate digital literacy activities. Grades 2–4 were selected because pupils at this stage typically have sufficient reading/writing and self-regulation skills to complete structured project tasks and performance-based digital assessments. Pupils were not pre-screened by prior technology experience; baseline testing (Table 2) was used to capture initial variation in digital competence.

The intervention phase of the experiment spanned one academic semester (16 weeks). During this period, six project-based learning (PBL) modules were implemented in the experimental group. These modules were specifically designed to cultivate core components of digital competence, including the ability to search and critically evaluate information, use online resources safely, collaborate in digital environments, create original digital content, and solve practical problems using ICT tools.

Each module was grounded in the pedagogical principles of project-based learning and involved collaborative assignments such as creating multimedia narratives, designing presentations, and developing interactive educational materials using platforms like Padlet, Canva, and Google Classroom (see Table 7). The pre-service teachers acted as facilitators: they organized student groups, provided ongoing guidance, and demonstrated effective strategies for utilizing digital tools. Their role was not to instruct directly, but to scaffold the learning process and promote digital autonomy among the pupils.

In the control group, instruction followed the standard curriculum without the inclusion of any additional project-based components.

To assess the level of students’ digital skills, the following instruments were employed:

A DigComp-aligned diagnostic test of pupils’ digital competence, covering four core domains: information literacy, communication, digital content creation, and online safety. In this study, digital skills refer to task-level procedural abilities demonstrated in performance-based tasks (e.g., locating information, collaborating in a shared document, creating a simple digital artefact, applying basic safety routines). Digital competence is treated as the integrated, goal-directed use of these skills under classroom conditions and is operationalised through a DigComp-aligned diagnostic tool (Tables 1–5). Digital confidenceis reserved for pupils’ perceived capability and is measured separately via self-assessment (Table 6).

Observation checklists designed to capture students’ behavior and strategies while completing project tasks, allowing for structured monitoring of engagement and tool usage.

A self-assessment questionnaire, using a 5-point Likert scale, aimed at evaluating pupils’ digital confidence and perceived proficiency in using digital technologies.

Internal consistency of the diagnostic test was confirmed through the calculation of Cronbach’s alpha (α = 0.82), indicating high internal consistency. Content validity was ensured through expert review by three specialists in pedagogy and digital education.

At the outset of the study, baseline testing was conducted to assess the initial level of digital competence among primary school students. Upon completion of the project-based modules, both the control and experimental groups underwent post-intervention testing and repeated self-assessment. Quantitative data were processed using SPSS version 26.0. Missing observations were minimal and were handled using a complete-case approach; the effective sample size is reported for each analysis where applicable. To evaluate differences between the control and experimental groups, Student’s t-test for independent samples was employed, and Cohen’s d was calculated to determine the effect size. In addition to standardized testing, observation checklists based on the DigComp 2.1 framework were used to track students’ behavioral and practical demonstrations of digital skills during the project tasks. Each checklist comprised four domains aligned with digital competence (3–4 indicators per domain) and was filled in by student observers during group work sessions.

To ensure the reliability and validity of observations, inter-rater agreement procedures were implemented. This included pilot testing the observation instrument and conducting a calibration session involving 5 university instructors and 10 student observers. Inter-rater reliability was confirmed via Kendall’s coefficient of concordance (W = 0.84), indicating a high level of agreement. Before conducting comparative analysis, key statistical assumptions were verified. The Shapiro–Wilk test was used to assess the normality of distributions, and Levene’s test was applied to check the homogeneity of variances. In cases where assumptions were slightly violated, Welch’s t-test was used to allow robust interpretation under heteroscedastic conditions. The significance level was set at α = 0.05 (two-tailed), and Cohen’s d effect sizes with 95% confidence intervals were reported to assess the magnitude of differences. Qualitative responses from student reflections were analyzed using thematic analysis following the six-step procedure outlined by Braun and Clarke (2006). For transparency, an example of the coding logic was as follows: “For the first time, I felt like a real teacher” → code professional self-identification → theme emerging teacher identity. This included familiarization with the data, initial open coding, clustering codes into potential themes, refining thematic structures, and interpreting results in the context of pedagogical application. To enhance analytical rigor, codes were cross validated by two independent researchers.

The study adhered to ethical standards for research involving young children. Informed consent was obtained from parents and participating educators. Confidentiality and anonymity of all data were strictly maintained. The experimental protocol was formally approved by the Ethics Committee of Abai Kazakh National Pedagogical University.

To assess the digital competence of primary school students, a diagnostic test was developed based on the DigComp 2.1 framework (Carretero et al., 2017). The instrument included 20 tasks, evenly distributed across four core components of digital competence. Each component was operationalized through five items that targeted essential skills relevant to the primary education context. The structure and content of the instrument are presented in Table 1.

Hereafter, the DigComp-aligned diagnostic tool is used to operationalize pupils’ digital competence, while “digital skills” refers to task-level performance within the tool. The tool was specifically tailored to the developmental and cognitive characteristics of primary school students, ensuring age-appropriate language and context. It was administered in both paper and digital formats to accommodate different levels of digital access across the participating classes. Each domain was assessed using a five-point scale, where 1 indicated a minimal level of proficiency and 5 represented a high level of digital competence. The internal reliability of the instrument was confirmed by Cronbach’s alpha coefficient (α = 0.82), indicating a high degree of internal consistency across the diagnostic items. The diagnostic domains were aligned with the DigComp 2.1 framework (Carretero et al., 2017) and operationalised in age-appropriate tasks for Grades 2–4. This alignment should be interpreted as a pragmatic mapping of observable classroom actions to DigComp domains rather than a full psychometric validation of DigComp descriptors for this age group. For descriptive profiling, the 1–5 component scores were converted into three predefined proficiency levels: low (1.00–2.99), medium (3.00–4.49), and high (4.50–5.00). The same cut-offs were applied to all DigComp-aligned domains and to both measurement points.

The results of the baseline assessment confirmed that the digital competence levels of students in both the experimental and control groups were comparable and generally characterized as moderately low. A Student’s t-test revealed no statistically significant differences between the two groups at the pre-test stage (p > 0.05), supporting the conclusion that the initial conditions were equivalent across groups. A more detailed breakdown of performance by digital skill domain is provided in Table 2.

To illustrate the distribution of mean values across digital skill domains, Figure 1 presents a comparative diagram. As shown, the indicators for all four components - information literacy, communication, content creation, and digital safety range from 2.3 to 2.6 points and are nearly identical in both groups. This graphical representation confirms the data from Table 2 and clearly demonstrates the absence of statistically significant differences at the outset of the experiment.

The test results confirmed that the initial level of digital competence in both groups was equally low, with no statistically significant differences observed. This provided a reliable baseline for comparing the subsequent dynamics during the experiment and enabled the interpretation of any emerging differences as a consequence of implementing student-led project-based activities.

In addition, intra-group dynamics in the development of digital competencies were analyzed across the four dimensions of the DigComp framework. Students were classified according to predefined proficiency levels (low, medium, high) for each component, both before and after the intervention. A summary of the results for the experimental group is presented in Table 3:

Overall, more than 80% of students in the experimental group demonstrated improvement in at least one competency area, while approximately 60% showed progress across two or more dimensions. The most notable shifts were observed in the domains of digital content creation and digital safety (Figure 2).

The results of the student survey, conducted using a 5-point Likert scale, revealed a significant increase in the level of competence in using digital technologies among participants in the experimental group. The changes were statistically significant and accompanied by a strong Cohen’s effect size (d = 1.25), indicating not only a quantitative but also a qualitative improvement in students’ self-assessment of their digital skills. In contrast, although the control group also demonstrated some positive dynamics, the improvement was notably less pronounced. These findings confirm that participation in project-based activities fosters not only the development of specific skills but also the formation of a positive attitude toward digital engagement. Detailed results are presented in Table 6.

Figure 4 presents a comparison of post-test digital literacy scores between the experimental and control groups across four domains. In all categories, students who participated in project-based learning demonstrated a clear advantage. The most significant differences were observed in the areas of Content Creation and Information Literacy. These results confirm the effectiveness of the implemented methodology in developing digital skills among primary school students.

The diagram illustrates that students in the experimental group achieved higher results across all five dimensions of digital literacy compared to those in the control group. The most pronounced advantages were observed in the areas of digital content creation (1.76 vs. 0.67) and information literacy (1.37 vs. 0.65), indicating substantial development of key competencies. The overall composite index of digital competence was also significantly higher in the experimental group (1.38 vs. 0.58). These findings confirm the effectiveness of project-based learning as a method for developing digital skills among primary school students.

An analysis of students’ reflections who participated in the experiment was conducted following the thematic approach proposed by Braun and Clarke (2006). Four key themes emerged:

Students frequently mentioned digital tools such as Canva, Padlet, and Jamboard, indicating the development of practical EdTech skills relevant to contemporary classroom contexts.

Statements such as “It was exciting but interesting,” “I was scared but I managed,” and “I felt joy from interacting with children” reflect the deep emotional involvement students experienced during their teaching practice.

Representative quotes included: “At first, I did not know how to approach children with special needs,” “I learned to be patient,” “It’s important to see each child as a person.” These themes emphasize that participation in the experimental setting served as a space for developing metacompetencies, fostering pedagogical reflection, and shaping the professional identity of future educators. Thus, the experiment fulfilled a dual function: on the one hand, it supported younger students in developing their digital skills; on the other, it contributed significantly to the professional growth of the student-teachers, equipping them with metacognitive skills, critical reflection abilities, and readiness to work in digital and inclusive school environments. Overall, the project-based activities implemented by students at the pedagogical university had a notable impact on the digital competence of primary school learners. This impact was especially prominent in the components related to content creation, presentation, and digital communication as confirmed by both quantitative results and qualitative data from self-assessments and observational reports.

Self-assessment gains were consistent with the observed performance improvements, but they capture perceived confidence rather than objective competence. In contrast, the control group displayed only limited change. Between-group post-test and gain-score contrasts were statistically significant for several outcomes (Tables 4–5), with several effects in the medium range (Table 5). Importantly, descriptive shifts in proficiency bands (low/medium/high) should be interpreted with reference to the predefined thresholds reported in Table 3.

The data analysis suggests that the most significant dynamics were observed in the following areas:

Digital content creation: through the production of multimedia artifacts (e.g., presentations, digital stories, flashcards), pupils developed a sense of authorship and accountability. This finding aligns with Alférez-Pastor et al. (2023), who highlighted increased critical thinking and autonomy among learners engaged in project-based work. Digital communication and collaboration - These skills were developed through structured group activities using platforms such as Padlet, Jamboard, and Google Classroom. As noted by Alférez-Pastor et al. (2023), digital collaboration fosters social digital competence, including empathy and negotiation skills in virtual environments.

Information literacy: this component improved as students were required to search for relevant content, evaluate sources, and synthesize information into project outputs. Such tasks stimulated metacognitive processes, resonating with the conclusions of Mota et al. (2025), who argue that PBL enhances both information filtering and digital reasoning skills. The digital safety component showed more modest progress, which may reflect the comparatively smaller share of safety-focused tasks within the six-module sequence and the need for repeated, routine practice to consolidate safety behaviors in early grades. Nevertheless, gains were observed in areas related to privacy awareness and digital footprint, which were addressed through embedded scenarios (e.g., password routines and discussion of online behavior).

Several distinctive features affirm the overall effectiveness of the proposed intervention:

Positive gains were recorded across all subgroups of learners, regardless of their initial level, suggesting the universal applicability of the model.

The short-term format (only six modules over three months) proved sufficient to develop basic digital competencies, owing to the intensity and targeted design of the learning tasks.

Observation protocols recorded more frequent pupil-initiated actions and sustained engagement during project tasks (e.g., independent tool selection, peer coordination, and iterative refinement of products). These patterns are consistent with higher engagement; however, motivation was not measured as a separate psychological construct and should therefore be interpreted cautiously.

The project-based learning environment functioned as both an instructional and a developmental space. Interpreting these classroom behaviors through Self-Determination Theory (SDT; Ryan and Deci, 2000), the project format plausibly supported pupils’ sense of autonomy (choice within tasks), confidence (visible progress in products), and relatedness (collaborative routines). At the same time, SDT is used here as an interpretive lens rather than a directly tested mechanism, because need satisfaction was not measured explicitly.

The intervention was implemented under real-school conditions, where access to devices, connectivity stability, and adult support for technology use may vary across pupils. These contextual factors can shape both the pace of skill acquisition and the feasibility of certain digital tasks. For replication, we recommend (a) documenting baseline access conditions at the class level (devices/connectivity), (b) specifying a minimum technological set required for each module, and (c) providing brief facilitator training focused on scaffolding strategies rather than direct instruction. Future implementations may also benefit from explicitly integrating short safety routines into every module to strengthen gains in the digital safety component.

As supplementary process evidence (not a primary study outcome), we analysed facilitator reflections from the pre-service teachers who supported implementation of the model. Their participation was embedded within the broader action research framework and a mixed-methods design, enabling the collection of valuable qualitative data through reflective reports, feedback narratives, and structured observations.

A thematic analysis of students’ reflections (Braun and Clarke, 2006) revealed four dominant categories:

These thematic categories indicate the formation of key meta-competencies, including pedagogical reflection, digital maturity, and empathic capacity. Rather than functioning merely as teacher assistants, student participants acted as facilitators of the learning process, demonstrating the ability to respond flexibly to children’s behavior, manage group dynamics, and establish a psychologically safe and digitally enriched learning environment. The visualization of the pedagogical model developed during the study is presented in Table 8. This model maps the relationships between the components of project-based learning, the specific digital competencies fostered in primary school pupils, and the meta-competencies formed in student teachers. The model illustrates the integrative and bidirectional nature of the intervention, confirming its dual impact both on learners and on future educators.

The implemented model demonstrated dual effectiveness: it simultaneously fostered digital competencies in primary school pupils and contributed to the development of pedagogical and digital meta-competencies in student teachers. This dual-impact design underscores the potential of project-based learning as a promising pedagogical component in both initial teacher training and broader strategies of educational digital transformation.

Despite the positive results obtained, the present study has several limitations that should be considered when interpreting its findings.

First, the intervention was conducted over a relatively short period, which precludes conclusions about the long-term stability and retention of the digital skills developed among primary school students. Second, the sample was drawn from a single school, which limits the generalizability of the results to broader student populations and educational contexts. Third, although the observation protocols demonstrated a high level of inter-rater agreement (Kendall’s W = 0.84), the potential for subjective interpretations of student behavior remains, particularly in assessing less overt indicators of digital competence. Fourth, the level of student-teacher engagement in the project activities may have varied depending on individual motivation, which could have influenced the consistency and efficacy of pedagogical support provided. Finally, while the DigComp 2.1 framework was adapted to align with the developmental characteristics of younger learners, its formal validation for this specific age group was not undertaken within the scope of this study. This limits the precision with which the resulting data can be interpreted and underscores the need for further validation of the assessment instrument in early education settings.

Although the instrument demonstrated high internal consistency, the DigComp-aligned operationalisation was not formally validated for primary-aged learners through factorial validation or measurement invariance testing. Future work should validate the structure of the instrument (e.g., cognitive interviewing with pupils, confirmatory factor analysis, and invariance checks across grades and gender) before wider use. These limitations should be taken into account when considering the scalability of the proposed model to other educational contexts and in the design of future research.