INTRODUCTION

In the early 21st century, educators are faced with the crucial need to acquire skills that enable the seamless integration of digital technologies (DT) into the pedagogical process (Bond et al., 2018; Cabero-Almenara et al., 2021). This necessity is underscored by a paradigm shift in which higher education institutions are urged to transcend mere digitization and to instead aspire to genuine digital renewal. Such an endeavor aims to leverage the full spectrum of digital resource capabilities, thereby optimizing the educational potential of the academic landscape (García-Peñalvo et al., 2020).

The advent of the Internet and DT has ushered in an age of unlimited access to information and opportunities. Yet, disparities in individual capacities to harness these opportunities has given rise to a digital divide that has impeded inclusive development. This skills gap poses significant challenges, particularly for those lacking basic digital competence (DC), which affects their access to employment, education services, and civic engagement (Juárez Arall & Marqués Molías, 2019).

This contemporary challenge brings with it the need to encourage educators to deliberate, analyze, and comprehend the omnipresence of DT within the instructional milieu (Gallardo Echenique et al., 2011). It is therefore a challenge that can only be taken on by recognizing the importance of engaging in continual professional development processes aimed at enhancing teaching, research, and administrative competences in the use of digital tools (Cuadrado et al., 2020; Esteve-Mon et al., 2016; Silva Quiroz & Miranda Arredondo, 2020). The application of cooperative learning strategies in higher education, especially within the context of the training of future educators, has emerged as a critical endeavor. The integration of digital teaching skills is thus a pressing necessity, and the incorporation of digital tools (DTs) must be advocated for within higher education classrooms (Huertas Abril, 2018).

The symbiotic relationship between DC and teacher digital competence (TDC) is intricate and interconnected. DC encapsulates the range of skills and understanding required for the effective use of DT across diverse contexts, encompassing both personal and professional domains. Conversely, TDC accentuates the specific spectrum of DC that educators must cultivate to effectively integrate DT into their instructional practices and the teaching-learning process. DC lays the foundational bedrock for TDC, empowering educators to navigate technologies more adeptly in their classrooms. TDC thus includes the ability to use DTs, critically evaluate online resources, foster digital literacy among students, and adapt pedagogical strategies for the successful incorporation of technologies within the educational setting.

The centrality of TDC in embedding DT into teaching and learning processes cannot be overstated. The construct not only catalyzes the professional development of educators but also nurtures students’ digital literacy, thus fostering a digitally competent future workforce (Domingo-Coscollola et al., 2020). Institutions of higher education are advised to initiate and support instructional programs designed to furnish educators with the DC they require. These types of initiatives are fundamental in the process of equipping students with capabilities essential to success in both the academic and professional arenas (Gutiérrez-Castillo et al., 2017; Juárez Arall & Marqués Molías, 2019; Sánchez-Caballé et al., 2020). The formal acknowledgment and validation of these competences via certification processes are deemed crucial milestones in the continuum of teacher professional development (Verdú-Pina et al., 2023). Such certifications reflect educators’ adeptness in the integration of DT into their pedagogical practices, concurrently fostering a rise in educational quality benchmarks. Thus, systematically monitoring and critically assessing the relevance and applicability of these certifications is of paramount importance to ensure they are aligned with the evolving requirements of the digital educational landscape.

Within this dynamic and perpetually evolving educational landscape, myriad factors surface that are fundamentally linked to both DC and the overarching higher education ecosystem. This interconnection extends to scholarly research and the theoretical delineation of DC and TDC (Cisneros-Barahona et al., 2024). Furthermore, this complexity encompasses the methods employed in assessing the proficiency levels and developmental trajectories of these competences.

Study and conceptual basis

The academic discourse surrounding the conceptualization of digital skills is characterized by a rich tapestry of terminology (Biel & Ramos, 2019; Cateriano-Chávez et al., 2021; Gallardo Echenique, 2013). The interrelation between media literacy and digital media literacy is profound and encompasses the ability to navigate information across disparate modalities (Buckingham, 2007; Wilson et al., 2011).

Concurrently, multimodal literacy emphasizes the synergetic integration of various communicative modalities and cognitive processes, facilitating the discernment and interpretation of information presented in visual formats. This is juxtaposed with multiple literacies, which embodies a multimodal capacity including the creation of content using written, visual, auditory, gestural, or spatial approaches (Kress et al., 2014; Mills & Unsworth, 2017).

Computer literacy is defined as mastery of computer applications and the management of information (Buckingham, 2015; Poynton, 2005) and lays the groundwork for more nuanced competences such as informational literacy, ICT literacy, e-competences, and e-literacy. These competences are deeply entrenched in a critical perspective on DT, which advocates for ethical information management across diverse contexts (Oxbrow, 1998; Rockman, 2005; Schneckenberg & Wildt, 2006; Somerville et al., 2007).

The scholarly contribution of Spanish authors to the burgeoning corpus of literature on DC is noteworthy Cisneros-Barahona, Marqués Molías, Samaniego-Erazo, Uvidia-Fassler, De la Cruz-Fernández & Castro-Ortiz, 2023; Cisneros-Barahona, Marqués-Molías, Samaniego-Erazo, Uvidia-Fassler, Castro-Ortiz & Villa-Yánez, 2023). At the international level, digital literacy is the preferred nomenclature, while within the European discourse, it is synonymously employed with the concept of DC (Almås & Krumsvik, 2008). Digital literacy encapsulates the technical and procedural competence needed for the effective engagement with digital environments and includes the cognitive, motor, sociological, and emotional dimensions ( Aviram & Eshet-Alkalai, 2006; Eshet-Alkalai, 2009; Jones-Kavalier & Flannigan, 2006; Martin & Grudziecki, 2006; Rangel Baca & Peñalosa Castro, 2013).

Digital competence is described as a holistic amalgamation of values, beliefs, knowledge, skills, and attitudes across technological, informational, multimedia, and communicative domains. It manifests as a multifaceted competence that educators cultivate to integrate DT into their pedagogical praxis (Gisbert Cervera & Esteve Mon, 2011). Its essence lies in the effective management of information for the construction of knowledge (Gutiérrez, 2011), encompassing safe, critical, and responsible use of DT for educational, social, and interactive purposes. This competence includes information and data literacy, communication and collaboration, media literacy, digital content creation, online safety, intellectual property, problem solving, and critical thinking ( Council of the European Union, 2018).

The construct of TDC is presented as a composite competence comprising an array of capabilities, skills, and attitudes acquired through professional development (Lázaro-Cantabrana et al., 2019). It is further described as a set of competences required for 21st-century educators to expand their educational praxis and facilitate their own continuous professional growth (INTEF, 2017).

DC baseline perspectives

In the contemporary educational context, the emergence of an array of TDC reference frameworks, developed by diverse institutions, organizations, and academics in the European arena, reflects the substantive evolution of the domain of DC ( Cisneros-Barahona, Marqués Molías, Samaniego Erazo, Uvidia-Fassler & de la Cruz-Fernández, 2023; Cisneros-Barahona, Marqués-Molías, Samaniego-Erazo, Uvidia-Fassler, De la Cruz-Fernández & Castro-Ortiz, 2022). These frameworks have been instrumental in delineating conceptual models, essential dimensions, reference standards, key indicators, and pivotal components, thereby facilitating nuanced comprehension and fostering the propagation of TDC. The diversity inherent in these approaches is illustrated in Table 1, which summarizes some of the most significant contributions to this area of inquiry (Cabero-Almenara et al., 2020; Cisneros-Barahona, Marqués-Molías, Samaniego-Erazo, Uvidia-Fassler, Castro-Ortiz & Rosas-Chávez, 2022; Lázaro-Cantabrana et al., 2019; Palau et al., 2019; Pérez-Escoda et al., 2019). Each approach offers a distinctive and enriching perspective on the conceptualization and operationalization of TDC, allowing for the exploration of the multidimensional nature of these competences within education today.

Moreover, the acknowledgment of accreditations for the purpose of validating TDC has emerged as a pivotal factor within this discourse. In the Spanish context, some of the more notable certifications include ACTIC, CODIX, TuCertiCyL, and the DC Accreditation in Asturias. However, the prominence of international certifications such as the IC3 Digital Literacy Certification offered by Pearson and the I-SKILLS program developed by the Educational Testing Service (ETS) points to a distinct evaluative approach towards essential digital skills. Beyond these, the International Computer Driving License (ICDL) represents a flagship accreditation spanning a wide range of DC. The French context further introduces the Computer and Internet Certificate C2i, specifically targeting the accreditation of DC among students, thereby accentuating the global landscape of TDC validation efforts (Verdú-Pina et al., 2022).

Frame of reference: COMDID-A

The use of the COMDID-A questionnaire within the framework of this research is predicated on the need for an evaluative tool that has not only been customized for the nuanced appraisal of TDC, but that also reflects the specific requirements and the distinct contexts of the educational practitioners. The meticulous design and calibration of this instrument played an instrumental role in collecting data of profound relevance and significance with which to precisely address the objectives of the study.

The instrument’s intrinsic strengths, derived from its prior validation and its tailored adjustment to the Latin American educational landscape, confer upon the COMDID-A questionnaire a high degree of efficacy and applicability (Cisneros-Barahona, Marqués-Molías, Samaniego-Erazo, Mejía-Granizo & De la Cruz-Fernández, 2023; Lázaro-Cantabrana et al., 2018; Lázaro-Cantabrana & Gisbert-Cervera, 2015; Usart Rodríguez et al., 2020). This regional adaptation provides the instrument added value, ensuring its cultural relevance and alignment with the unique attributes of the educational context in Latin America.

Furthermore, the process of developing a rubric for the assessment of TDC was informed by an extensive review of the literature and existing theoretical constructs, as shown in Table 2. This endeavor has culminated in the formulation of a proposed rubric that encompasses foundational elements such as dimensions, scopes, and key concepts required for the establishment of indicators and the definition of development levels. These elements are described in Lázaro-Cantabrana et al. (2018) and Lázaro-Cantabrana and Gisbert-Cervera (2015), which provide a detailed, structured overview of the rubric’s critical components. It facilitates a deeper understanding of the rubric’s construction, ensuring its uniform interpretation and application by evaluators, thereby enhancing the integrity and consistency of the TDC assessment process.

The principal aim of this research is to quantify the extent of DC among the faculty members at UNACH, Ecuador, employing the COMDID-A theoretical framework (Lázaro-Cantabrana et al., 2018). The research seeks not only to gauge the degree of DC among the teaching staff, but also to determine its interrelations with a multiplicity of variables pertinent to academic personnel, including the domain of knowledge associated with both undergraduate and postgraduate qualifications, departmental affiliation, academic program, employment status, and the acquisition of doctoral credentials. The methodological approach adopted for this purpose is descriptive-correlational, encapsulated within a non-experimental, cross-sectional study design. The sample was selected through probabilistic means during the second academic term of 2022. To ensure the robustness and integrity of the construct under study, a series of factors were observed to guarantee methodological rigor, including the application of Cronbach’s alpha tests for reliability assessment and a confirmatory factor analysis (CFA) for validity verification. Spearman’s Rho was used as a statistical tool to explain correlations among the variables, and a bifactorial general linear model (ANOVA) was applied to explain the impacts of specific variables, namely employment relationship and academic program, on levels of TDC, thereby contributing to a nuanced understanding of the factors influencing digital proficiency within the academic sphere.

METHODS

Design

This research is based on a methodological framework that makes use of a descriptive-correlational approach underpinned by a non-experimental, cross-sectional study design (Bisquerra, 1989; Ramos-Galarza, 2020).

Population and sample

The study’s population consists of the professors at UNACH, totaling 690 faculty members during the academic term under study. A probabilistic sampling strategy was employed to ensure a representative cross-section of the population. The sample size exceeded the minimum threshold (452) (Badii et al., 2008), with 511 educators participating, surpassing the requisite ratio of 5 samples per item for confirmatory structural analysis. The study made use of the COMDID-A rubric, an instrument made up of 22 distinct items ( Hair JR et al., 2022).

The resulting sample represents 50 % of the targeted academic population, a figure supported by a statistical confidence level of 97 %. Participation rates and distribution are shown in Table 3.

Data collection instrument

The data was collected for this study by means of the administration of the COMDID-A questionnaire, an instrument carefully designed to assess the DC of in-service educators. It is a specialized analytical tool offering a nuanced and comprehensive exploration of the critical dimensions inherent to DC within the pedagogical domain. Figure 1 shows the structured composition of the COMDID-A questionnaire, illustrating the interconnected dimensions and indicators that underpin this evaluative framework (Lázaro-Cantabrana et al., 2018; Lázaro-Cantabrana & Gisbert-Cervera, 2015).

Source: ARGET Research Group, Universitat Rovira i Virgili

The questionnaire is based on an evaluative scale with five response options, reflected in a scoring continuum with gradations at 0, 25, 50, 75, and 100. This structured scale facilitates a nuanced appraisal of each indicator, calibrated against its developmental progression. Figure 2 shows an expanded description of this categorization framework and the operationalization of the evaluative scale.

Reliability and validation of the COMDID-A instrument

The instrument’s reliability was verified with Cronbach’s alpha coefficient (Cronbach, 1951). A factorial confirmatory analysis (FCA) was also applied in accordance with the methodological guidelines for its use (López-Aguado & Gutiérrez-Provecho, 2019).

Data analysis

Our data analysis process consisted of a two-pronged analytical approach that incorporated both descriptive and inferential statistical techniques performed with IBM SPSS statistics software (Version 28.0.1.1.15). The initial analytical phase attempted to detect central tendencies and dispersion metrics within the collected data, aiming to construct a foundational quantitative level of TDC among the faculty at UNACH in Ecuador. After the preliminary analysis, a phase of inferential statistical examination was begun using Spearman’s Rho as a pivotal tool to determine potential associative dynamics among the variables of interest: the domain of knowledge corresponding to the subjects’ undergraduate and graduate qualifications, their academic department affiliation, academic program, employment status, and the attainment of doctoral-level education. Throughout the analysis, a suite of statistical metrics including correlation coefficients, statistical significance (Sig.), effect size (p), and statistical power (1-β) were assessed using Gpower software (version 3.1.9.6) (Erdfelder et al., 1996; Faul et al., 2007).

To further examine the intricacies of TDC, a factor analysis was applied with two fixed components: employment relationship and academic program. This analytical stratagem was chosen to detect any substantive effects exerted by these variables on levels of TDC. To this end, we used a general linear model (ANOVA) with an F-statistic as a means of quantification (Garibaldi et al., 2019).

RESULTS

Instrument reliability and construct validity

The principal component analysis (PCA) showed that the sample exhibited optimal congruence with the Kaiser-Meyer-Olkin (KMO) metrics. Furthermore, the determination of four distinct factors, cumulatively accounting for 65 % of the variance, is consistent with the dimensions defined by the COMDID-A framework (Cisneros-Barahona, Marqués-Molías, Samaniego-Erazo, Mejía-Granizo & De la Cruz-Fernández, 2023). The computation of Cronbach’s alpha across the entirety of the instrument and its constituent dimensions revealed exemplary internal consistency, thereby confirming the robustness of the measuring tool (Figure 3).

Levels of TDC development

Figure 4 shows the TDC levels of the COMDID-A reference frame dimensions.

The representation of TDC levels, as framed by the COMDID-A reference structure, reveals a disparate distribution across the evaluated sample. Specifically, the “intermediate” and “expert” levels constitute approximately 49 % and 25 % of the sample, respectively, while the “beginner” and “transformer” levels are less prevalent, collectively representing about 13 %. Interestingly, there was a notable absence of educators within the “not initiated” category. Nevertheless, a nuanced examination across individual dimensions unveiled differing proficiency levels, signifying a diverse range of competences across the TDC spectrum.

Level of TDC development based on sample biodata.

TDC in relation to area of knowledge of graduate-level degree

Figure 5 shows the analytical outcomes concerning TDC levels and the correlation of the disciplinary domains and the graduate qualifications of the professors at UNACH (República del Ecuador, 2023). A pervasive “intermediate” level of competence was observed across a broad spectrum of disciplinary fields, with prevalence rates oscillating between 33.33 % and 70.37 %. This distribution suggests that the educators at this institution have cultivated a moderate degree of proficiency in digital competences across diverse knowledge areas.

Conversely, the “transformer” level of TDC was less common, with incidences ranging from zero to 27.59 %. These findings point to a more infrequent integration of innovative pedagogical practices and technological applications within these disciplines.

It is noteworthy that disciplines such as agriculture, forestry, fisheries and veterinary sciences and services exhibited lower propensities towards the “transformer” level, indicating potential avenues for the enhancement of sophisticated digital skills within these fields. In contrast, 27.59 % of the subjects in the information and communication technologies domain scored at the “transformer” level, indicating the widespread adoption of educational technology innovations in that field.

A crucial observation was the absence of educators classified as “not initiated” across all fields of knowledge, signifying a foundational digital competency baseline among the faculty members. This revelation points to the ubiquitous presence of basic TDC across the academic landscape, setting a foundational platform for the further development of digital skills.

TDC in relation to area of knowledge of undergraduate-level degree

Figure 6 delineates the progression of TDC in juxtaposition with the disciplinary specialization of undergraduate degrees among faculty members at UNACH (República del Ecuador, 2023).

The prevalence of the “intermediate” competency level across diverse academic spheres, with figures oscillating between 38.46 % and 66.67 %, underscores a consistent trend towards moderate digital proficiency. Notably, this trend exhibits a spike at the “intermediate” level with an associated reduction across other competence levels, suggesting the pervasive acquisition of intermediate digital skills among the faculty.

Prominently, the domains of information and communication technologies and engineering, industry, and construction were found to have high percentages of subjects at the “transformer” level, at 40.63 % and 17.81 % respectively, indicating a predilection towards innovative pedagogical and technological paradigms within these fields. Moreover, a significant contingent of educators within the fields of natural sciences, mathematics, and statistics (66.67 %) points to the overlapping relationship between these disciplines and the attainment of moderate DC.

Conversely, among subjects from the academic area of agriculture, forestry, fisheries, and veterinary sciences as well as from services, there was a conspicuous absence of scores at the “transformer” level, suggesting a potential gap in the advanced use of digital technologies. In this vein, strategies to foster a deeper integration of educational technologies within these sectors are imperative. Meanwhile, the information and communication technologies sector merge at the forefront, demonstrating a notable 40.63 % at the “transformer” level, indicative of its leadership in the adoption of cutting-edge DT in educational praxis.

The observation that no educators were categorized at the “not initiated” level across all disciplines is particularly salient, reflecting a universal baseline of digital competency among UNACH’s faculty.

TDC by department

Figure 7 shows the findings pertaining to the development of TDC by the specific academic departments to which the professors are affiliated.

At present, the organizational structure of UNACH encompasses four distinct academic departments:

1. 1. Department of Engineering (DE)
2. 2. Department of Educational, Human Sciences and Technologies (DEHS&T)
3. 3. Department of Health Sciences (DHS)
4. 4. Department of Political and Administrative Sciences (DP&AS)

The educators affiliated with DEHS&T were found to have a predominant “intermediate” level of DC, with 53.17 % of staff members falling into this category. This is juxtaposed with a notably lower percentage of subjects at the “transformer” level (12.70 %). Conversely, the DHS exhibits a heightened proportion of faculty members at the “beginner” level (15.25 %), with a lesser representation at the “transformer” level (11.30 %). The DE and the DP&AS were found to have a relatively equitable distribution of DC across varying proficiency levels. Notably, the categorization of faculty members within the “not initiated” level across these departments was conspicuously absent.

The “intermediate” level of DC proficiency was found to prevail across all departments, followed sequentially by the “expert,” “beginner,” and “transformer” levels. This distribution suggests an inverse correlation between the level of DC and the prevalence of faculty members at the “transformer” level within each department.

Strategically customizing training and professional development initiatives, attentively calibrated to department-specific, discipline-oriented, and educational level considerations, promises to enhance their effectiveness. By ensuring tailored adjustments to the distinct needs and attributes of educators across diverse academic landscapes, DC enhancement efforts can be optimized.

TDC in relation to employment status

Figure 8 shows the proportional distribution of TDC levels vis-à-vis the subjects’ employment status, namely part-time, full-time, and temporary. Notably, the “intermediate” level of DC emerges as the predominant category across all employment status brackets. Nonetheless, it is worth emphasizing that the temporary and part-time statuses manifest comparatively higher incidences at the “transformer” level, with 12 % and 7.46 % respectively. This is in stark contrast to the full-time faculty, of which 14.08 % were ranked at this level. Additionally, a pronounced representation of educators at the “beginner” level (24 %) was found among teachers with temporary status.

The temporary and part-time employment status classifications stand out as having a higher proportion of faculty members at the “transformer” level. This pattern suggests that the reduced workload inherent to these employment statuses may provide these teachers with enhanced flexibility, thereby facilitating the integration of innovative pedagogical methods and technological practices in their educational processes.

TDC in relation to employment relationship

Figure 9 shows the proportional distribution of TDC levels in relation to the employment status of the UNACH professors under study. Across the spectrum of employment categories, the “intermediate” level of TDC is consistently prominent, indicating a pervasive acquisition of DC within the academic context.

Particularly, we found a substantial number of professors with an “intermediate” level of TDC (50.24%) within the “full” (tenured) category. This prevalence suggests that tenured professors possess a foundational level of DC that is integral to their pedagogical functions. A similar trend was found among non-permanent teaching staff, with professors in the “adjunct” (non-permanent) employment category demonstrating a notable achievement of “intermediate” digital competences.

Overall, the “beginner” and “transformer” levels of TDC were found to be the least common, indicating a predilection for educators to attain either intermediate or advanced stages of DC.

TDC in relation to possession of a doctoral degree

Figure 10 shows the proportional distribution of TDC levels vis-à-vis the attainment of doctoral qualifications among the faculty members of UNACH.

The comparative analysis reveals a notable parity at the “expert” level of TDC between professors holding doctoral degrees (22.63 %) and those without such qualifications (26.47 %). Notwithstanding, a discernible disparity emerges at the “transformer” level of TDC, with 16.06 % of educators holding doctorates documented at that level compared to 12.03 % among their counterparts without doctoral degrees.

Correlational analysis

Given the non-normal distribution of the data pertinent to the variables examined, a non-parametric test was required for the correlation analyses. We chose the Spearman’s Rho coefficient as the statistical measure (Creswell, 2011) due to the ordinal/nominal nature of the categorical variables. The correlation coefficients, statistical significance (Sig.), effect size (p), and statistical power (1-β) were also evaluated at the same time (Erdfelder et al., 1996).

Table 4 shows the interrelations between TDC and a range of variables pertinent to the faculty at UNACH (Creswell, 2011). The correlations observed were predominantly of a low magnitude. The analyses did not reveal any statistically significant associations between the variables of employment status or the disciplinary field of undergraduate- or graduate-level degrees and the level of TDC development.

Conversely, statistically significant correlations were discerned regarding department affiliation and academic program academic program. These findings suggest the potential impact of these variables on the cultivation of TDC. Furthermore, notable correlations were identified in relation to the possession of doctoral degrees, indicating a potential variation in TDC levels contingent upon the doctoral qualifications attained by educators.

General linear model (ANOVA) between TDC and the fixed variables employment relationship and academic program

The modified Breusch-Pagan test (White’s test) detected a discernible level of significance, corroborating the presence of heteroscedasticity within the sample. This indicates that the variance of the residuals does not maintain constancy across the spectrum of the predictor variables, namely employment relationship and academic program. Furthermore, the application of the Kolmogorov-Smirnov test for independent samples yielded significances surpassing the .05 threshold, thereby justifying the use of a general linear ANOVA model to analyze TDC based on the fixed factors of employment relationship and academic program.

This analysis sought to determine the impact of the variables employment relationship and academic program on level of TDC, including their interaction effects. The null hypothesis posits equality among the mean values of the designated populations for each factor, excluding the presence of interaction effects. The F statistic served as the analytical tool (Garibaldi et al., 2019).

Table 5 shows the test of between-subject effects. The subsequent ANOVA revealed discernible differences between the variables employment relationship and academic program and TDC level, at a significance threshold of .05. Moreover, the interaction effects, along with the intersection and the corrected model, were found to be statistically significant.

The factor analysis, as illustrated in Figure 11, shows the marginal means of the levels of TDC in relation to the employment relationship of the educators studied and their respective academic programs within the university. Among the 31 academic programs examined, 23 exhibit statistically significant variances, revealing a perception of higher competence in adjunct professors compared to their tenured counterparts.

DISCUSSION AND CONCLUSIONS

The reliability of the instrument within the sampled demographic was confirmed by means of Cronbach’s alpha.

A confirmatory factor analysis (CFA) served to refine the precision and validity of the constructs delineated by the COMDID-A framework, which improved the quality and empirical credibility of the research outcomes. The alignment of the proposed structural construct with the sampled data validated the interrelation between the theoretical model and the empirical items. Moreover, the establishment of a coherent dimensional structure, characterized by substantial correlations among the dimensions, further corroborated the instrument’s internal consistency.

Understanding the interrelationships within the correlation matrix is instrumental in deciphering the complex dynamics of the COMDID-A model. The evidence of convergent validity improved the coherence among variables within identical dimensions, whereas discriminant validity distinctly separated the dimensions from one another. The Kaiser-Meyer-Olkin (KMO) measure and Bartlett’s test outcomes substantiate the CFA’s appropriateness, revealing a significant underlying structure within the data. The presence of moderately high communalities suggests that the derived factors are intimately linked to the observed variables, thereby reinforcing the model’s overarching validity.

Echoing prior research that made use of the COMDID-A rubric, in our study, Dimension 1 exhibited a more advanced level of development (Palau et al., 2019; Paz Saavedra & Gisbert Cervera, 2023). Conversely, while preceding studies have accentuated the integrity of Dimension 3 (Lázaro-Cantabrana et al., 2019; Silva et al., 2019), our research found a diminished mean rating within this domain. Variations such as these clearly reflect the contextual and demographic specificities inherent to the study.

The prevailing “intermediate” level of TDC across all evaluated dimensions is consistent with the corpus of existing literature (Santos et al., 2021). Nevertheless, the fact that not even 50 % of the subjects surpassed that competency level is noteworthy. Moreover, a minimal contingent of educators fell into the “not initiated” level within Dimension 3, and that lowest level was completely absent in Dimensions 1, 2, and 4. These patterns indicate that most teachers possess moderate digital skills, while drawing attention to a niche demographic yet to embark on their TDC development, particularly within Dimension 3. These results emphasize the importance of a call to action for intensified focus and investment in competence development initiatives aimed at elevating DT and DC mastery within academia.

In alignment with the overarching trends detected in relation to TDC levels, the “intermediate” level was found to be prevalent across most indicators within Dimension 1. Notably, the “not initiated” level was minimally represented across all indicators, suggesting an elemental familiarity amongst educators with DT and their pedagogical applications. Certain indicators, notably “1.1. Teacher planning and digital competence” and “1.3. Data processing and knowledge creation”, were found to have a significant contingent at the “expert” and “transformer” levels, indicative of advanced proficiencies in instructional planning and the use of digital information for knowledge generation. Conversely, the indicator “1.2. Digital technologies as facilitators of learning” showed a prevalence of “beginner” level scores, signifying potential areas for pedagogical enhancement. Furthermore, “1.3. Data processing and knowledge creation” and “1.4. Attention to diversity” within Dimension 1, when evaluated at the “expert” and “transformer” levels, underscore a symbiotic relationship between these domains and elevated levels of TDC. These observations are congruent with scholarly assertions advocating for comprehensive training in DT and curriculum integration, particularly emphasizing improved pedagogical competences which occasionally manifest suboptimal levels in contrast to other dimensions (Ayale-Pérez & Joo-Nagata, 2019; Lago Martínez et al., 2017).

The analysis of Dimension 2 revealed a pronounced proficiency at the “expert” and “transformer” levels within the “2.1 Learning environments” and “2.2 Managing digital technologies and programming” indicators, denoting advanced competences. Conversely, “2.3 Spaces with digital technologies of the educational center” exhibited a notable presence of “beginner” and “intermediate” level teachers, pointing to avenues for capacity development and reinforcement.

Dimension 3 consistently exhibited distributions across the “intermediate” and “beginner” levels, with “expert” and “transformer” levels also present, albeit less prominently. The “3.4 Digital content and the educational community” indicator is particularly noteworthy for its diverse distribution across the “beginner”, “intermediate”, and “expert” levels, highlighting a concerted focus on generating apt digital content. These parallel findings suggesting that ethical dimensions, such as “3.1 Ethics and safety”, are often documented at lower competency levels (Arango et al., 2020; Gallego-Arrufat et al., 2019).

Additionally, both “3.3 Communication, dissemination and transfer of knowledge” in Dimension 3, and “4.5 Personal learning environment (PLE)” in Dimension 4, were identified with diminished levels of TDC, which is consistent with the findings of other researchers (Basantes-Andrade et al., 2020; Biel & Ramos, 2019; Cabero-Almenara et al., 2021; Gutiérrez-Castillo et al., 2017). This accentuates the imperative for curating training modalities aimed at improving TDC levels, confronting the pedagogical exigencies emergent when DT and DC are not integrally woven into the teaching and learning (T-L) schema (Romero-Tena et al., 2020; Wu, 2014; Zhao et al., 2019).

Within Dimension 4, the indicators “4.3 Lifelong learning” and “4.5 Personal learning environment (PLE)” are notably distinguished by a pronounced prevalence of “intermediate” and “expert” levels. Specifically, “4.3 Lifelong learning” is characterized by elevated proportions of “experts” and “transformers”, reflecting a strategic emphasis on continuing professional development and the cultivation of personal learning environments at an institutional scale.

These findings are congruent with those in the published literature and underscore the nuanced variability of TDC across disparate cohorts of educational professionals (Zhao et al., 2021). Such distinctions are pivotal for contextualizing TDC evaluations amidst the evolving complexities and heterogeneity inherent to contemporary educational landscapes.

The marked disparities between groups highlights the instrumental role of DT in the configuration of educators’ DC (Guillén-Gámez et al., 2021), which strengthens the imperative to incorporate these factors into the framework of professional development initiatives aimed at improving TDC (Amhag et al., 2019; Nascimbeni, 2020). The tailoring and customization of these interventions are deemed crucial for bridging the competence gaps identified in this work and fostering the equitable ascension of DC within the educational community (Juárez Arall & Marqués Molías, 2019; Silva Quiroz, 2017).

The use of Spearman’s Rho to ascertain correlation coefficients brought to light significant positive correlations between TDC as a whole and its constituent dimensions (D1, D2, D3, D4), in agreement with prior research findings (Cabrera, 2009; Reguant-Álvarez et al., 2018). This interconnection reinforces the assertion that advancements within a singular dimension invariably precipitate beneficial impacts across the TDC spectrum, thereby fostering a multifaceted skills profile. Such a pattern of synergy and mutual reinforcement among the various facets of TDC aligns with other observations within the Latin American educational context (Paz Saavedra & Gisbert Cervera, 2023)

These interdimensional dynamics offer profound insight into the integrative essence of TDC (Gutiérrez-Castillo et al., 2017). Acknowledging that progression in one dimension catalyzes advancements in others underscores the need for holistic approaches in the design and execution of training and professional development programs (Garita-González et al., 2019). This comprehensive viewpoint is indispensable for navigating the intricacies of TDC and ensuring the balanced development of skills (Biel & Ramos, 2019; Vallejo & Aguayo, 2021).

The coherence observed amongst competency levels across dimensions indicates that the enhancement of digital skills transcends specific domains, fostering an effective interdimensional transfer and integration of DC. This pattern strengthens the argument for the holistic development of such competences (Romero-Tena et al., 2020), as the consistent skill levels across the diverse dimensions attest to the depth and scope of the DC profile cultivated within the subject group (Santos et al., 2021).

Exploring the diversity of correlations sheds light on the multifaceted nature of TDC and underscores its inherent complexity (Gisbert Cervera & Esteve Mon, 2011). The absence of definitive patterns in its development suggests the convergence of several subtly interacting factors, thus highlighting the intricate and individualized journey educators embark on in acquiring DC (Fernández Sánchez et al., 2016; Padilla-Hernández et al., 2020).

The negligible correlations with educators’ fields of study at both the undergraduate and graduate levels, as well as their employment relationship, suggest that these variables may not significantly sway TDC levels within this study’s context. Understanding these complex and indirect correlations is pivotal in formulating professional development strategies and educational policies, demonstrating the need for interventions tailored to educators’ unique contextual and educational requirements ( Cisneros-Barahona, Marqués-Molías, Samaniego-Erazo & Mejía-Granizo, 2023).

Notably, the discernible correlations with departmental affiliation and academic program underscore the impact of structured programs on the various levels of TDC observed (González et al., 2020). This finding accentuates the role of the academic context in shaping educators’ DC, emphasizing the importance of integrating these elements into the design of targeted training and intervention strategies.

Moreover, the correlation with doctoral qualifications underscores the critical role of academic attainment in TDC (Sarango Lapo, 2021). This correlation suggests a propensity among more highly educated educators towards advanced DC, thereby linking educational achievement with the acquisition of sophisticated digital skills and highlighting the value of promoting academic progression as part of TDC enhancement initiatives (Amhag et al., 2019; Gutiérrez-Castillo et al., 2017).

The linear factor analysis indicated statistically significant variances, revealing that adjunct professors are often perceived as more digitally competent than their tenured counterparts, a finding which diverges from other studies suggesting the opposite (Rodríguez Espinosa, 2016). This discrepancy invites further inquiry into training modalities, exposure to digital educational technologies, and opportunities for professional development, potentially elucidating the underlying causes for these observed differences.

These insights not only contribute to a nuanced understanding of TDC within the examined context but also establish a foundation for future research and informed educational policymaking. Recognizing variables associated with DT enhances the precision of TDC assessments and accentuates the need for strategic, personalized approaches to effectively improve DC among educators. Furthermore, employing advanced data analysis techniques (Cisneros-Barahona et al., 2021; Uvidia Fassler et al., 2017; Uvidia Fassler et al., 2018; Uvidia Fassler et al., 2019; Uvidia Fassler et al., 2020) to explore the reciprocal influences among competences across different dimensions could provide a more comprehensive understanding of the interrelations among skills, thereby enriching the overall conceptualization of TDC.

Data availability

The data used for the experimental replication is available at the following link: https://zenodo.org/doi/10.5281/zenodo.10655922

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