Assessing digital competences in higher education teachers: a case study

1 Introduction

Digital technologies are reshaping sustainable educational practices as they are adopted across all sectors of society and integrated into learning environments. Developing educators’ digital competencies is essential to enable education processes to leverage the opportunities offered by technological advancements and to design strategies that foster teachers’ professional development. Furthermore, teachers’ digital competencies are fundamental for empowering educators to enhance their students’ own digital competencies.

Educational institutions need to update the digital competencies of their faculty members as technological advances evolve. This involves the assessing teachers’ digital competencies. In this context, this research aims to address a timely question: How can higher education institutions systematically evaluate the digital competency levels of their teaching staff?

Once educators have been assessed, a second research question arises: how can assessment findings be translated into a continuous professional development framework to update and refine these competencies?

The primary objective of this study is to develop a baseline procedure as an institutional assessment model for higher education. Using a representative case study, the paper demonstrates how empirical data directly informs the design of a professional development program.

The authors adopted a mixed-methods case study design to conduct the research. A sequential explanatory approach was used to diagnose, interpret, and project actions to improve digital competencies in a specific higher education institution in Quito, Ecuador. The digital competency assessment combined a quantitative analysis with a qualitative approach, using standardized instruments and unstructured interviews conducted with selected institution personnel.

Several basic concepts underlie the aforementioned questions; they are required to construct a sound basis for comparison and reference. First, to evaluate a particular digital competence in a specific institutional setting, we must first define it. Consequently, the institution needs a digital competencies framework and an aligned methodology to assess faculty competencies.

Systematic reviews of digital competencies frameworks conducted by Sánchez et al. (2020), Zhao et al. (2021), Fernández-Batanero et al. (2021), Skantz-Åberg et al. (2022), Karimi and Khawaja (2025), Álvarez-Huari (2025) and Lachmann and Rücker, (2026) were used as the foundation for a Critical Interpretive Synthesis of the literature (Dixon et al., 2006). Based on these systematic review studies, the most relevant references for digital competencies frameworks were selected. For the instrument assessment, the systematic review conducted by García et al. (2023) and López et al. (2024) were examined.

As the main contribution of this research, we develop a baseline sequence of required actions—essentially a roadmap—that enables higher education institution to evaluate faculty digital readiness. To address the primary focus, a mixed-methods assessment framework, integrating both qualitative and quantitative approaches, was established. Furthermore, as a practical derived contribution, this study introduces the Digital Competencies Training Program (DCTP). This continuous professional development framework that combines initial diagnostic leveling with advanced professional growth through a seven-phase management model suggested for practical implementation.

2 Material and methods

The study employed a two-phase, mixed-methods explanatory sequential design. The first phase assessed the digital competencies of a faculty at a higher education institution. The second phase integrated and analyzed the quantitative and qualitative findings within the institutional context to develop a continuous improvement strategy for faculty professional development.

The DigEduComp Check-In questionnaire was administered in the quantitative phase. The findings served as the basis for the qualitative assessment, which comprises an institutional document analysis and semi-structured interviews with selected key informants. The combined information obtained for both phases allowed for a comprehensive analysis and an interpretation beyond the participants’ scores, contextualizing them within the institution’ s regulatory, pedagogical, and technological frameworks.

The methodological design provides an overview of educators’ digital competence levels, followed by an analysis of relevant institutional factors related to these results. The quantitative phase established a solid empirical foundation by identifying key trends, strengths, and areas needing development. These findings informed the qualitative phase, which aimed to explore participants’ experiences in depth and the institutional operational and conditional factors influencing the development of educators’ digital competencies.

The baseline assessment phase information was used to design a professional development program. This integration aligns with the methodology of explanatory sequential mixed-methods designs, where qualitative findings serve to explain, contextualize, and enrich the interpretation of quantitative results (Creswell and Plano Clark, 2018). The mixed-methods assessment and training framework serves as a preliminary, adaptable institutional model that requires further empirical validation and contextual adaptation across diverse higher education settings.

2.1 Case study method

The base case was a higher education institution evaluating the digital competency level of its faculty to define strategies for strengthening these skills within a continuous improvement framework. Accordingly, the study focused on assessing competency levels to inform the identification of strengths and weaknesses, thereby supporting the design of a continuous professional development program. The objective was to illustrate a preliminary baseline procedure that can serve as an adaptable reference model for similar institutions.

The case study design was selected to analyze the phenomenon within its real-world context, as it accounts for both the internal dynamics and the contextual conditions of a specific setting. This approach facilitates a comprehensive understanding of the phenomenon's distinctive characteristics and interactive complexity.

The research offers deep insight into digital competencies development within a university context. It investigates the relationship between the institution's pedagogical model, faculty professional needs, teaching practices, and available technological infrastructure. The analysis reveals the barriers and challenges educators face in updating, improving, and advancing their competencies. The primary unit of analysis was faculty digital competence within its institutional context.

2.2 Participants and context

The institution's total teaching staff consists of 56 faculty members. Of these, 48 (85.7%) educators participated in the questionnaire-based evaluation. This participation rate provided a robust source of evidence for the case study.

Regarding the sociodemographic profile of the participants, the majority fell within 40-to-50 age range, followed by the 31-to-39 range. Most had more than 15 years of teaching experience, and nearly all held postgraduate qualifications, including master's and doctoral degrees. The sample of participants offers a perspective for studying professionals with extensive experience, postgraduate academic training, and long-standing classroom practice in an educational environment influenced by dynamic technological advancements.

The qualitative phase of the evaluation process involved three key informants, chosen through purposive sampling based on their domain expertise, operational roles, and familiarity with the institution's pedagogical and technological dynamics. To capture different organizational perspectives, the selected profiles included:

Educational innovation specialist: Focuses on curriculum planning, active teaching methodologies, and faculty professional development.

Classroom educator: Offers insights into the day-to-day use of technology-mediated teaching practices, classroom interaction, and student engagement.

Director of educational technology: Provides structural data regarding technological infrastructure, Virtual Learning Environments (VLEs), technical support, and data security.

2.3 Quantitative phase

This phase was conducted using the DigCompEdu Check-In questionnaire, Spanish version (Cabero and Palacios, 2020). This instrument consists of 22 items corresponding to the six areas of the DigCompEdu framework (Redecker, 2017). Each item features five response options ordered by increasing levels of complexity regarding participants’ classroom practices and personal perspectives. Scores were derived using a 0-to-4point Likert scale, mapping each participant's score to a level of competence categorized by the instrument. The resulting data from this phase enabled the identification of the strengths and weaknesses in educators’ digital competencies. Data organization and statistical analysis were performed using spreadsheet software. The data file is available via the Data Availability Statement link.

2.4 Qualitative phase

This phase investigated the institutional pedagogical and technological conditions potentially linked to the quantitative findings. In line with the explanatory sequential design, interviews and documentary analysis enabled an in-depth examination of the quantitative results to identify key factors affecting the development of educators’ digital skills. The collected information revealed specific institutional characteristics and particular needs that were undetected by the quantitative assessment.

A systematic institutional documentary analysis was conducted to review institutional policies, the internal regulatory framework, and decision-making related to the case study (Bowen, 2009). Specifically, the Modelo Educativo y Pedagógico (Universidad Tecnológica Israel, 2025) was analyzed, as it sets the institutional guidelines and regulations for tertiary-level education.

This phase relied on two data sources: the institution's educational and pedagogical model (Universidad Tecnológica Israel, 2025), and qualitative data gathered during semi-structured, audio-recorded interviews with key informants, which lasted 45–60 min each. The documentary analysis identified the institutional principles, guidelines, and expectations regarding the educational application of technologies. Specifically, this involved reviewing institutional guidelines for assessment, feedback, technological infrastructure, and quality assurance processes. Complementing this, the interviews provided data on how these institutional principles translate into actual teaching practices. Integrating these reference elements allowed for the characterization of the institutional environmental conditions necessary to develop faculty members’ digital competencies.

The coding procedures were conducted manually and collaboratively by the research team to ensure analytical rigor and contextual authenticity. A hybrid deductive-inductive thematic analysis was executed: primary categories were deductively mapped to the DigCompEdu framework areas, while subcategories inductively emerged from the qualitative data. To establish trustworthiness and credibility (Lincoln and Guba, 1985), the team implemented researcher triangulation during codebook development. Transcript fidelity was confirmed with key informants, and code discrepancies were solved by team consensus.

The documentary review revealed that the institutional model's guidelines promote significant learning and active student engagement in self-managing learning processes, competency-based education, and curricular flexibility. A socio-critical and constructivist approach predominates in the institutional model with the integration of the Technological Pedagogical Content Model framework, TPACK (Mishra and Koehler, 2006), to incorporate the techno-pedagogical component. Furthermore, these guidelines promote the implementation of active learning methodologies such as the flipped classroom, project-based learning, gamification as a teaching strategy, Design Thinking, case-based learning, and problem-based simulation. Within this framework, faculty's digital competences extend beyond the technical application of tools and skills; technology participates within the pedagogical context as a mediator in the teaching-learning process.

The key informant interview guide was framed around the six competency areas of the DigCompEdu framework (Redecker, 2017) to maintain correspondence with the questionnaire's dimensions. The interviews provided insights that enriched the quantitative findings within the institutional context. The informants contributed their perspective on the use of virtual learning environments, content creation, digital resources, assessment practices, and formative feedback. Furthermore, the informants helped to examine additional aspects related to learning analytics, the ethical use of generative artificial intelligence and the institution's guidelines for the use of the technological resources. With the collected data was possible to identify institutional and pedagogical factors that either facilitate or hinder the integration of technology into the educational processes.

Thematic analysis, understood as a procedure for identifying, organizing, and interpreting patterns of meaning within textual data, was used to process the collected qualitative data (Braun and Clarke, 2006). A hybrid coding strategy was employed, combining predetermined categories with emergent themes derived from the data review. Initial deductive categories were established based on the DigCompEdu framework (Redecker, 2017), and the Modelo Educativo Institucional (Universidad Tecnológica Israel, 2025). Subsequently, these categories were expanded with emergent topics from the interview and documentary analysis. This approach aligned theoretical and institutional referents with contextual features such as technological infrastructure, the ethical use of technology, and the sustainability of change processes.

2.5 Procedure

The study primarily consisted of two phases plus an integration stage. The first phase was the quantitative diagnostic assessment. The data were analyzed using descriptive statistical techniques. The findings were used to identify competence areas that deserved a deeper examination in the qualitative phase.

In the second phase, the qualitative assessment, documentary analysis, and semi-structured interviews were conducted. The inputs obtained helped to interpret the results in detail and to identify institutional conditions for the development of digital competencies in teaching practice.

Finally, the results were integrated and synthesized using a joint display analysis to examine the relationships between the quantitative results, the educational model, and the interview information. The joint matrix facilitated the identification of common ground, differences, and the complementarity among the information sources.

2.6 Triangulation

Data and institutional documentary phases were contrasted through a triangulation strategy. Therefore, the phenomenon under study was examined from different perspectives, providing consistent support for the interpretation of results. Table 1 describes the criteria used for the analysis.

Table 1. Criteria and interpretation of findings triangulation.

Cross-referencing the qualitative and quantitative data highlighted three perspectives: the level of digital competence perceived by faculty, the institutional pedagogical policies, and the perspectives of stakeholders involved in academic management, educational innovation, and technological support. This synthesis yielded actionable criteria for designing an ICT training program aligned with the needs and conditions identified within the institution.

2.7 Definition of digital competence

The concept of digital competence is often used inconsistently throughout the literature, frequently as a synonym of digital literacy. Digital competence is regarded as an essential capability for educators, supporting the pedagogical, technological, and curricular dimensions of educational processes. Beyond the critical and responsible use of Information and Communication Technologies (ICT), teachers’ digital competence also includes assessment, collaboration, and feedback (Inamorato dos Santos et al. 2023).

Caviglia et al. (2026) describe digital competence as a teacher's capability to use of digital technologies in daily educational work. The concept has been associated with related terms such as digital literacy, information literacy, media literacy, and, digital skills (Sánchez et al., 2020). The literature also refers to related concepts, including ICT competencies, media competence, and computer competence (Skantz-Åberg et al., 2022).

Krumsvik et al. (2016) defined teachers’ digital competence at the individual level as the ability to use ICT, with sound pedagogical judgement while an understanding of the implications of technology for learning strategies and the integration of educational and digital knowledge in students learning.

Ferrari (2012) conceptualizes digital competence through several interrelated dimensions, namely learning domains, tools, competence modes, and purposes. In contrast, Ilomäki et al. (2016) describe the individual components that collectively constitute the concept of digital competence. Table 2 presents both proposed conceptualizations.

Table 2. Concepts of digital competence according to Ferrari (2012) and Ilomäki et al. (2016).

Both definitions share several core elements. They encompass the know how—including knowledge, abilities, and practical skills—applied to achieve specific objectives with a defined purpose in either a professional or everyday context. This conceptualization is reflected in digital competence frameworks such as DigCompEdu (Redecker, 2017) and the UNESCO ICT Competency framework for teachers (UNESCO, 2018).

2.8 Selection of the digital competence framework

At present, no single framework provides a universally accepted basis for comparing faculty development and evaluation programs within higher education institutions. Instead, different frameworks regarding teachers’ digital competencies in the techno-educational field share similarities, but consolidating them into a single overarching framework that encompasses all existing perspectives remains challenging (Lachmann and Rücker, 2026). For universities, the ideal situation would be to have an institution-specific framework, as in the case of the Universidad de Buenos Aires (2025).

For this study case addressed the conceptual structure proposed by Ferrari (2012) in Table 2 was adopted. Consequently, the reference framework must align with this concept, alongside appropriate assessment instruments.

As different terms are frequently used to conceptualize digital competence, the identification of an appropriate framework and corresponding assessment instruments does not constitute a linear process of gathering information. Rather, it requires a search based on the relevance and interpretive value of the available evidence. For this reason, the present study adopted the Critical Interpretive Synthesis (CIS), approach proposed by Dixon et al. (2006).

Systematic review regarding digital competencies frameworks conducted by Sánchez et al. (2020); Zhao et al. (2021), Fernández-Batanero et al. (2021); Skantz-Åberg et al. (2022); Karimi and Khawaja (2025); Álvarez-Huari (2025); Tiwari and Magre (2025); Lachmann and Rücker (2026), provided the foundation for the CIS undertaken in the research. These reviews serve as primary the references for selecting the most relevant frameworks. Regarding assessment instruments, systematic reviews conducted by García et al. (2023) and López et al. (2024) were selected.

The following competencies frameworks were selected: DigEduComp (Redecker, 2017), the UNESCO (2018), the Jisc Capabilities Framework (2024), the HeDiCom Framework (Tondeur et al., 2023), and the International Society for Technology in Education (ISTE)Standards, (2024).

The DigCompEdu framework (Redecker, 2017) is structured around three main domains: educators’ professional competences, educators’ pedagogical competencies, and the development of learners’ competencies. These three domains overarching six specific areas (see Table 3). Teachers’ digital competence is categorized through a six levels progression model designed to support educators in assessing and continuously developing their digital competence.

Table 3. Digcompedu framework (Redecker and Punie, 2017).

Competencies areas 2–5 represent the pedagogical core of the DigCompEdu framework (Redecker, 2017). Meanwhile, Competence 1, Professional Engagement, addresses the professional context of educators, specifically the use of digital technologies in professional interactions with colleagues and students, as well as for their own professional development. Finally, Competence 6 is dedicated to fostering learners’ digital competencies.

The UNESCO ICT Competence Framework for Teachers (UNESCO, 2018) organizes educators’ competencies into six aspects of professional practice, with three progression levels for the pedagogical use of ICT. Its underlying premise is that educators who are competent in integrating ICT into their educational practice will be better equipped to deliver high-quality education and thereby motivate and guide the development of students’ own digital competencies. The UNESCO (2018) is aligned with Sustainable Development Goal 4 (Quality Education) of the United Nations’ 2030 Agenda. Table 4 summarizes the UNESCO (2018) aspects.

Table 4. UNESCO ICT-CFT (2018) framework.

The HeDiCom framework, developed by Tondeur et al. (2023) focuses on higher education and simplifies faculty competencies in four dimensions, summarized in Table 5.

Table 5. Hedicom framework.

The HeDiCom framework (Tondeur et al., 2023) seeks to provide a competency framework less complex than DigCompEdu (Redecker, 2017) or the UNESCO (2018), while preserving conceptual depth. The HeDiCom framework does not define progressive proficiency levels describing educators’ competency development.

The Jisc Digital Capabilities Framework (Jisc, 2024) focuses on the digital competencies required for professional practice in higher education. The framework has been mapped to the UK Professional Standards Framework (UKPSF). Rather than organizing competencies into developmental proficiency levels, Jisc structures digital capability around six interconnected elements, conceptualizing digital competence as a combination of technical skills, professional identity, digital wellbeing, research, and collaboration within institutional contexts. Table 6 summarizes elements, competencies, and tasks for the Jisc framework.

Table 6. Jisc Digital Capabilities Framework (2024).

The ISTE Standards for Educators (International Society for Technology in Education, 2024) provide a framework for transforming teaching and learning through the strategic and purposeful integration of technology. These guidelines prompt a paradigm shift from teacher-centered instruction toward student-centered learning, empowered by digital technologies within the context of a knowledge society.

The ISTE framework is organized around two overarching domains—Empowered Professional and Learning Catalyst—which together encompass seven professional roles. The Empowered Professional domain focuses on educators’ professional growth, equity, and ethical practice in digital environments. It encompasses the Learner, Leader, and Citizen roles. Within the teaching context, the Learning Catalyst domain addresses pedagogical interaction, learning environment design, and formative assessment, comprising Collaborator, Designer, Facilitator and Analyst roles.

Rather than defining discrete proficiency levels, the ISTE framework views educators’ digital competencies as evolving continuously. Table 7 summarizes the ISTE roles.

Table 7. ISTE framework: professional roles and competencies.

DigCompEdu (Redecker, 2017), UNESCO (2018), ISTE (2024), and the Jisc Digital Capabilities (2024) frameworks were included in the Cabero et al. (2020a) study. The authors concluded that all evaluated frameworks were highly relevant for both university and non-university educators.

2.9 Selection of the digital competence quantitative assessment instrument

For this case study, the selection of questionnaire was guided by the following inclusion criteria: alignment with at least one of the reviewed frameworks, demonstrated statistical validity and reliability, application in empirical studies between 2015 and 2026, and availability of a Spanish version.

The DigCompEdu framework (Redecker, 2017) includes a self-assessment tool, the DigCompEdu Check-In, developed by the Joint Research Center, JRC. Since its first version in the year 2018, the instrument has been reviewed and closely aligned with the core competence areas of DigCompEdu framework. The final version comprises 22 items, each featuring five response options measured on a Likert scale from 0 to 4 (Ghomi and Redecker, 2019). A Spanish version was developed and validated by Cabero and Palacios, (2020).

The DigCompEdu Check-In instrument has been used in various studies. For instance, Cabero et al. (2022), using a sample of 2,262 teachers, reported a McDonald's omega coefficient of 0.967, indicating a high level of reliability across the questionnaire dimensions. Similarly, Dias-Trindade and Moreira (2023) administered the instrument to a sample of 434 secondary teachers and 118 university educators. Furthermore, Fernández-Cruz et al. (2026), in a study with 655 non-university educators, reported a Cronbach's alpha of 0.941, confirming the high reliability of the questionnaire.

The questionnaire developed by Agreda et al.(2016), titled “Competencia digital del profesorado universitario de las Facultades de Ciencias de la Educación Española”, followed a four-stages methodology: dimension identification, item construction, questionnaire revision, and administration. The final version comprises four dimensions and 112 items. Expert judgement was used to validate the instrument. Internal consistency was confirmed with a sample of 1,145 participants, yielding a Cronbach's alfa of 0.92.

Lázaro et al. (2018) propose a four-dimensional rubric structured around the following indicators: (1) didactic, curricular, and methodological competence; (2) planning, organization, and management of technological spaces and resources; (3) relational, ethical, and security competence; and (4) personal and professional dimension. Each dimension incorporates specific descriptors. Each descriptor which are categorized into four levels: beginner (N1), intermediate (N2), expert (N3), and transformer (N4).

Alternatively, Gutiérrez et al. (2022) developed an instrument based on the UNESCO (2018), integrating Information and Communication Technology (ICT) and Media and Information Literacy (MIL). This questionnaire comprises 23 items. It was administered to a sample of 402 in-service and pre-service teachers, yielding a Cronbach's alpha of 0.94 for internal consistency. Subsequently, an exploratory factor analysis confirmed sampling adequacy with a Kaiser-Meyer-Olkin with a value of 0.95, and revealed a statistically significant Bartlett's test of sphericity with a value of p < 0.001.

The DigCompEdu Check-In questionnaire stands out among the reviewed instruments due to its extensive application and validation across diverse geographic and sociodemographic contexts. For instance, Inamorato Dos Santos et al. (2023) conducted an extensive study sponsored by the Joint Research Center of the European Commission and Metared-Universia Foundation. This study encompasses universities across seven counties -Argentina, Brazil, Colombia, Chile, Peru, México and Portugal- and include a large sample of 30,407 participants. Its validation has been extensively documented in Inamorato Dos Santos et al. (2023), Ghomi and Redecker (2019), Cabero and Palacios (2020).

The reliability and validation of the DigCompEdu Check-In instrument was examined by Martín et al. (2022) through exploratory factor analysis (EFA), and confirmatory factor analysis (CFA) using a structural equations modeling approach. The analysis was performed in two stages: an initial EFA followed by a CFA within the structural equations model approach. The results, including a Cronbach's alpha of 0.95, confirmed both the high internal consistency and strong structural validity of the DigCompEdu Check-In questionnaire.

For this case study, the DigCompEdu Check-In questionnaire was administered to the institution's faculty. The instrument was selected due to its demonstrated consistency, reliability and validity, as well as its versatility in diverse sociodemographic and geographic contexts.

3 Results

This section presents the findings of the study, following the logic of an explanatory sequential mixed-methods design. Quantitative and qualitative datasets are reported and integrated through triangulation to identify specific training needs and to inform a professional development proposal for enhancing faculty members’ digital competencies. Subsections are sequentially organized to structure a baseline for the case study.

3.1 Administration of the DigCompEdu Check-In questionnaire

The DigCompEdu Check-In questionnaire, Spanish version (Cabero and Palacios, 2020) was applied to faculty members. Of the total institutional faculty (N = 56), n = 48 members (85.7%) completed the questionnaire. It represents a sufficient sample size to identify strengths, competency gaps, and professional development needs. Given that the sample constitutes a substantial fraction of the total population, the Finite Population Correction factor (FPC=0.381) was applied following Cochran (1977). Assuming a 95% confidence level and maximum variance (p = 0.5), this adjustment reduced the standard error, resulting in a margin of error of 5.39%.

The Spanish version of DigCompEdu Check-In (Cabero and Palacios, 2020) comprises 22 items distributed across the six competence areas of the DigCompEdu framework (Redecker, 2017): professional engagement (4), digital resources (3), teaching and learning (4), feedback and assessment (3), empowering learners (3), and facilitating learners’ digital competence (5). Each item features five response options rated on a Likert scale ranging from 0 to 4, yielding a maximum total score of 88 points. Each area is categorized using the sum of its item scores. Table 8 summarizes the levels.

Table 8. Competence levels thresholds for the DigCompEdu check-in (Cabero and Palacios, 2020).

The Cronbach's alpha obtained was 0.925. The original data file is available in the Data Availability Statement. The overall institutional score is 63.40 out of a maxim of 88, placing the digital teaching competence at the Expert (50–65 range). These results demonstrate that the institution possesses a teaching staff that is functionally proficient in the use of digital technologies. However, it is worth highlighting that the objective is not merely to integrate ICT, but rather to foster systematic, innovative, collaborative, and inclusive digital competence practice aimed at pedagogical transformation. The primary institutional challenge is determining how to progress evenly toward superior levels of competence. The overall institutional results across competency areas are shown in Table 9.

Table 9. Institutional global results across competency areas.

To design an effective strategy for upgrading, updating, and enhancing educators’ digital competence, it is essential to look beyond overall averages and examine the distribution of teachers’ proficiency level across the six areas. Table 10 summarizes the distribution of proficiency levels among participants across these areas of competence.

Table 10. Distribution of faculty members levels in the areas of competence.

M, mean; SD, standard deviation.

The bold numbers are the values for media and standard deviation.

In the Global Average, 87.5% of faculty members are positioned at the Expert level and above, but 12.5% of the educators fall below. Two areas display the highest educators’ proportion in the Integrator level: Assessment (35,42%) and Professional Engagement (33.34%). The distribution of proficiency levels extends toward Integrators and Explorers, with a minimal proportion of Newcomers. This distribution at different competence levels informed the design strategy for the professional development program. Initially, a leveling stage is required for educators across all fields to establish a uniform baseline before advancing to subsequent phases of updating, training, and professional development. The heterogeneity suggests the need for an institutional policy for the continuous strengthening of educators’ digital competence.

3.2 Qualitative findings

The qualitative phase was aligned with the explanatory sequential mixed-methods design. It aimed to examine, contextualize, and explain the quantitative diagnostic results within the institutional framework. The methodology comprised the analysis of three semi-structured interviews with key institutional informants and a documentary analysis. This analysis provided insights into how digital competencies are developed within educational processes, enabling a deeper understanding of the underlying pedagogical, technological, and institutional conditions behind the quantitative scores.

The data were analyzed following Braun and Clarke (2006) through a six-phases process.

In the first phase, data familiarization, the interview transcripts and institutional documents were reviewed to enable the identification of patterns of meaning related to the quantitative results and to the institution's pedagogical and technological conditions.

In the second phase, generating initial codes, a hybrid deductive-inductive coding strategy was employed. The initial deductive categories were derived from the DigCompEdu areas and relevant elements of the institution's Educational Model, while emerging codes were identified directly from the interview transcripts and documentary analysis.

In the third phase, searching for themes, codes were grouped according to their conceptual relationship and patterns of meaning. When the emerging codes represented the same dimension as an initial code, they were integrated into the corresponding category; otherwise, they were retained as a distinct emerging theme. This process resulted in a hybrid matrix linking primary categories, emerging themes, codes, information sources, and textual evidence.

In the fourth phase, reviewing themes, the thematic structure was evaluated by comparing the qualitative evidence from interviews and institutional documents, and by contrasting these qualitative findings with the quantitative scores. To assess the coherence of the themes across data sources, the organization, differentiation, or integration of codes were discussed among the research team until consensus was reached.

In the fifth phase, defining and naming themes, the themes were delineated according to the shared meaning of their associated codes and their alignment with deductive categories. The final thematic structure comprised: open educational resources production and licensing, active methodologies and pedagogical mediation, formative assessment and learning analytics, the digital divide and accessibility, the ethical integration of artificial intelligence, and institutional technological infrastructure and support.

In the sixth phase, producing the report, the consolidate themes were integrated in the Consolidated Qualitative Coding Matrix (Table 11). The Methodological Integration and Impact column of each finding establishes a link between the qualitative evidence, quantitative results, and the identified professional development needs.

Table 11. Consolidated qualitative coding matrix (hybrid deductive-inductive approach) reviewer 2, observation 4 reviewer 1, observation 5.

The matrix in Table 11 maps the deductive dimensions of the DigCompEdu framework with the inductive subcategories emerging from key informant interviews and the institutional educational model. It summarizes the contextual nuances of faculty digital competencies, thereby addressing the structural, pedagogical, and policy-driven conditions that underpin the quantitative baseline.

Participants agreed that the primary challenge lies in transforming the existing technological infrastructure into meaningful, systematic and assessable ICT- mediated pedagogical practices. Qualitative findings confirmed that the institution possesses a well-established technological infrastructure.

While the quantitative findings indicated robust digital competencies among faculty, the interviews underscored the need for systematic frameworking, ongoing technical support, deeper pedagogical alignment, and institutional coordination. The overarching institutional challenge is the integration of digital platforms, digital skills and tools to enhance their pedagogical, ethic, critical, and evaluative integration to the education processes.

Thus, the thematic analysis contributed to explaining and conceptualizing the findings of the quantitative diagnostic phase and provides the foundation for the development of the training program. Nevertheless, both sets of findings indicate the need for an initial leveling phase for educators with lower competence scores through training focused on fundamental digital competencies, followed by an advanced professional development program.

The study proceeded to the mixed-methods integration stage through a quantitative-qualitative triangulation. To operationalize this synthesis, a joint display matrix was developed (Table 12). This integration matrix contrasts the numerical proficiency scores from the quantitative evaluation with the qualitative evidence presented in Table 11. By aligning quantitative performance gaps with qualitative insights, Table 12 establishes the empirical and pedagogical justification for the modular structure, learning domains, and strategic orientations of the Digital Competencies Training Program (DCTP).

Table 12. Mixed-methods integration matrix.

3.3 Integrated interpretation of quantitative and qualitative findings

The interpretation of the faculty digital competencies through the integration of quantitative and qualitative findings provides deeper insights than the overall institutional score alone. This convergence is particularly informative regarding digital assessment.

Although overall quantitative results placed the institution at the “Expert” level (63.54/88) a substantial proportion of participants remained at Integrator level. Overall, 87.5% of participant qualified at the Expert level and above, while 12.5% remained below this threshold. The qualitative evidence helps explain this pattern. Informants reported that digital assessment practices were already supported by questionnaires, virtual learning environments, rubrics, and online assessment tools, while also identifying limitations in qualitative feedback, the systematic use of rubrics, and the development of formative assessment practices. Thus, the evidence suggests that the institutional challenge is the pedagogical refinement and systematization of these tools.

The varied distribution across competency areas demonstrates that the institutional average does not reflect homogeneous digital proficiency among faculty members. For example, the area Facilitating Learners’ Digital Competence, showed the highest standard deviation among the six competency areas (SD = 4.32). This is consistent with qualitative findings which highlight differences in students’ technology access, connectivity constraints, limited availability of equipment, and the absence of protocols for addressing digital access gap. Consequently, strengthening this competency area requires institutional measures related to accessibility and technical support.

Another example is illustrated by the Professional Engagement area. The participants’ distribution extends to Integrator and Explorer levels, even though the institution reached the Expert level. Qualitative findings highlighted the need for continuous professional development, sustained technical support, mentoring, and evaluation of training effects on teaching practice. The joint interpretation suggests that this area should be understood as an institutional process requiring opportunities for sustained professional learning besides continuity and technical support. These findings generate a meta-inference that would not be visible from either dataset considered independently. Although the quantitative evaluation reveals a baseline of institutional competence, the qualitative phase uncovers constraints regarding its uniformity, depth, and sustainability. The joint interpretation aims for consolidation and differentiation in the faculty competencies rather than a mere progression from lower to higher levels of competence. Faculty development should build on existing capabilities, while addressing specific areas of variability—such as formative assessment, inclusion, and pedagogical systematization—backed by sustained institutional support.

3.4 Institutional strengths

Based on the results presented above, the institutional strengths identified through the mixed- methods evaluation process were summarized in Table 13.

Table 13. Strengths of the institution's faculty.

These strengths indicate that the institution's teaching staff is receptive to the integration of ICT into their educational practice. Therefore, the professional development program should build upon this accumulated experience and promote progression toward higher levels of innovation, leadership, and pedagogical systematization, following an initial leveling process for educators with lower competencies scores.

3.5 Main training needs

The principal professional development needs were identified: These needs demonstrate that an ICT professional development program should be conceived as a continuous educational response, derived from the institutional diagnosis and from the constantly evolving nature of digital technologies.

• − Digital professional collaboration
• − Personalized learning
• − Advanced curation of digital resources
• − Data protection and digital security
• − Learning analytics
• − Design of advanced interactive digital resources

3.6 TPACK and digital teacher’s competencies

TPACK (Technological Pedagogical Content Knowledge) model (Mishra and Koehler, 2006), is an integration framework that identifies different forms of knowledge to meet the training needs (León et al., 2025; Ortiz et al., 2023). Furthermore, the TPACK model breaks this knowledge down into three domains: technological, pedagogical, and disciplinary content. The combination of these knowledge domains generates three areas of integration: Technological-Pedagogical (TP), Technological-Content (TC), and Pedagogical-Content (PC). Accordingly, teachers require an integrated knowledge base that combines content, pedagogy, and technology. Teaching cannot rely exclusively on disciplinary content; it requires pedagogical and technological mediation. The convergence of these domains creates opportunities for more effective learning. Figure 1 schematically presents the TPACK model (Mishra and Koehler, 2006).

The TPACK explicitly outlines the integration of three aspects in the teaching and learning process: pedagogy, technology, and content knowledge. Technology only gains pedagogical value when applied within an educational framework; it does not possess it inherently. The pedagogical framework depends on the teacher rather than on technology. The three areas of knowledge interact, forming the TP, TC, and PC dimensions, which indicate systemic functioning, especially if students can adapt technological tools to their learning styles and pace. Technology cannot be used as a pedagogical mediator without an evaluation process by the teacher (Aydemir and Babacan, 2025).

3.7 Digital competencies training program (DCTP)

Based on the findings, the second research question is addressed through the development of a comprehensive educator training, and professional development program for the university's academic staff. The authors developed an educator training program in digital competencies focused on the following elements: theoretical framework foundations, competency dimensions, progression levels, pedagogical applicability, and institutional relevance. This program would fill the need for a professional development program for teachers, a missing step in the reviewed literature.

The UNESCO ICT Competency Framework for Teachers version (UNESCO, 2018) serves as the primary theoretical anchor for developing the program. The UNESCO framework provides a practical and scalable progression (Acquisition, Deepening, and Creation) that has been widely adapted by educational authorities in Latin America. Examples include the national frameworks of Chile and Colombia, which have leveraged UNESCO's guidelines to harmonize teacher training with broader national digital transformation goals. In regions where digital infrastructure remains underdeveloped, such as certain rural areas in Latin America, UNESCO's flexible and scalable progression offers a pragmatic and viable pathway for the implementation of a professional development program.

Although the UNESCO framework is robust and encompasses a broad scope, its guidelines are predominantly descriptive. This framework is an initial reference document rather than a prescriptive mandate (UNESCO, 2018). Notably, the document lacks an operational roadmap to define objectives or structure execution for initiating and implementing teacher training. Effective institutional ICT integration should follow a strategy with clear intermediate milestones – an implementation dimension that the UNESCO framework does not fully address.

Initially, a qualitative analysis aligned with the UNESCO (2018) framework was carried out. For each aspect and its respective levels, competencies, objectives, and content were integrated into the technological training program: the Digital Competencies Training Program (DCTP). Figure 2 illustrates the structure of the program. Each aspect of teacher training evolves from Level I Acquisition, to Level II, Deepening, and culminates with Level III Knowledge Creation.

3.7.1 Competencies, learning objectives and basic content

The contents of the Digital Competencies Training Program (DCTP) were systematically derived from a mixed-methods integration process. The transition from empirical findings to curriculum design was implemented through a sequential mapping methodology linking Tables 11, 12.

The quantitative assessment established the baseline competence levels across the six DigCompEdu areas. Through thematic analysis of interviews and institutional documents (Universidad Tecnológica Israel, 2025), the quantitative results were contextualized and conceptualized in Tables 11, 12. Finally, specific operational needs were identified for each area, for instance, high quantitative performance in digital technology was qualified by qualitative data revealing a need for active learning strategies; similarly, an assessment gap led to the identification of needs in learning analytics and rubrics, while the inclusion gap addressed the need for Universal Design Learning.

The qualitative coding matrix, (Table 11) and the joint display integration (Table 12) identified key operational needs—such as active ICT—supported methodologies, formative assessment rubrics, learning analytics, Universal Design Learning (UDL), as well as accessibility protocols, Open Educational Resources (OER) production, and critical Artificial Intelligence literacy.

Tables 14–19 operationalize the competencies, learning objectives, and basic content for each aspect and respective levels that conform the basic knowledge unit—ensuring that every training objective addresses an empirical need.

Table 14. Aspect 1: understanding ICT in education.

Table 15. Aspect 2: curriculum and assessment.

Table 16. Aspect 3: pedagogy.

Table 17. Aspect 4: application of digital skills.

Table 18. Aspect 5: organization and administration.

Table 19. Aspect 6: teacher professional learning.

3.7.2 Management model for DTCP program

To operationalize the Digital Competencies Training Program (DCTP), it is necessary to construct a management architecture. The primary implementation challenge is organizational. It involves structuring the preparation phases, pedagogical sequences, content programming, initial diagnostic assessment. Additionally, it requires grouping participants according to similar ICT proficiency levels, planned study hours, formative assessment, and learning monitoring. To achieve this, a seven-phase management model has been developed as follows:

Phase 0: Diagnosis baseline and cohort formation.

This phase aims to identify teachers’ technical ICT skills, and establish a comprehensive diagnostic baseline that informs instructional design, mentoring, formative assessment, and the contextual adaptation of the program. The diagnostic process should combine self-assessment, practical evidence, pedagogical reflection, and institutional analysis.

Activities: Deliverable: A comprehensive diagnostic map including: teachers’ ICT competencies, pedagogical practices, beliefs about technology, TPACK integration levels, institutional conditions, organized learning groups, and a validated operational plan. This map will serve as the basis for instructional design, mentoring, formative assessment, and continuous improvement of the program

• Administration of validated self-assessment instrument to map baseline competencies.
• Analysis of pedagogical practices and teaching artifacts to identify pre-existing ICT integration into curriculum, assessment, and classroom activities.
• Exploration of teachers’ beliefs, attitudes, and perceived barriers regarding ICT integration.
• Identification of initial TPACK integration levels, across disciplinary areas.
• Audit of institutional infrastructure, connectivity bandwidth, digital resources, institutional culture, and available time.
• Cluster analysis of participants into homogenous learning groups according to diagnostic profiles with attention to both technical and pedagogical dimensions.
• Operational program's plan, including schedule, hybrid modality, tutor assignment, learning pathways, and formative assessment strategies.

Phase 1: Detailed instructional design.

This phase turns the diagnostic findings into a clear plan with practical learning steps: teaching sequences by level, formative assessment rubrics, and the design of integrative knowledge products.

Activities: Deliverable: A modular institutional ecosystem including: syllabi, learning sequences, rubrics, and digital learning environments.

• Curriculum blueprinting.
• Development of exemplary teaching sequences.
• Rubric architecture.
• Authentic artifact specification.
• Learning management system environment provisioning.

Phase 2: Implementation of participation modalities.

The pedagogical approach is blended: in-person sessions for collaborative work and collective learning with synchronous online support, in-depth asynchronous modules, and independent practical activities. Weekly hours are designated for each specific modality. For efficient and effective implementation, participants are organized into homogeneous proficiency levels, collaborative groups of 3–5 participants, and communities of practice by disciplinary areas.

Deliverable: Execution of scheduled hybrid training modules, including documented participant attendance and LMS analytics.

Phase 3: Support, mentoring, coaching, and instructional scaffolding.

To ensure continuous participation and knowledge transfer in the classroom, the following strategies are suggested: assigning a tutor to each homogeneous group, providing ongoing feedback, observing and guiding practical activities, and creating a forum for reflective discussions on completed activities.

Deliverable: Longitudinal coaching logs, qualitative feedbacks reports tracking participant progression and instructional adaptation.

Phase 4: Learning assessment: formative evaluation and competency validation.

Formative assessment is conducted continuously, is evidence-based, and aims to improve the learning process by providing ongoing feedback. The instruments designed include a digital portfolio for participants, a competency rubric, a learning diary, peer assessment, and practical observations. The formative cycle is implemented through activities, feedback, improvement suggestions, and new evidence of learning. A final assessment could be included: applied, contextual, and transferable, in one of the following forms: final integrative product, evidence of real-world practical application, or rubric assessment.

Deliverable: Evaluated teaching portfolios, completed competency rubrics, and individual competency growth records.

Phase 5: Program Closure, knowledge dissemination and escalation.

This phase synthesizes program outcomes, socialization of results, systematization of experiences, identification of ICT leaders, feedback for program improvement.

Activities: Deliverable: Publication in the institutional repository of the validated digital learning artifacts.

• Organizing institutional showcases.
• Documentation and archiving of high-quality artifacts into institutional repository.
• Identification and certification of advanced participants as future peer-mentors and digital leaders.

Phase 6: Institutionalization and governance integration.

Permanent learning communities should be established for the exchange and support of ICT learning among teachers to ensure the acquired training sustainability.

Activities: Deliverable: Formal institution policy document, updated faculty evaluation frameworks, and budget allocations.

• Institutional policy alignment: integrating competencies levels into formal faculty evaluation.
• Workload recognition: Accounting for training hours within faculty workloads allocation.
• Resource allocation.
• Quality assurance integration.

Phase 7: Institutionalization and sustainability.

DCTP program should be understood as an institutional strategy integrated into the regular functioning of educational institutions. The implementation of the program requires formal decision-making structures, clear responsibilities, resource allocation, workload recognition, monitoring procedures, and coordination among academic, administrative, and technical units. The sustainability of the DCTP depends on its articulation with institutional policies, career progression frameworks, incentive systems, quality assurance processes, and mechanisms for evaluating teaching innovation.

Teachers must be able to set their own goals, plan how to achieve them, and apply learning strategies as needed to support meaningful learning and continuous progress while managing “technology anxiety” (Dong and Abd Aziz, 2026):

3.7.3 Artificial intelligence (AI)

AI is profoundly reshaping all aspects of society, education, economy, and labor markets, and demands additional consideration (Boden, 2018; Torres, 2023). The exponential growth in the number of users has a significant social impact. Intuitive natural-language access and interaction elevated AI beyond being merely a technological tool (UNESCO, 2023b).

AI has emerged as a disruptive force in the educational process. Its integration into teachers’ practice raises epistemological, ethical, and pedagogical challenges regarding its operating principles and algorithms, scope, limitations, and risks (Holmes and Toumi, 2022; UNESCO, 2023a). The ethical use of AI in education is associated with the handling and security of personal data. The epistemological validity of AI-generated knowledge becomes relevant for the acceptance or rejection of a response generated by AI (Cuéllar, 2023). Accordingly, UNESCO has published several documents related exclusively to the inclusion and use of AI in education: UNESCO (2022, 2023, 2023a, 2023b, 2025, 2025a, 2025b). To integrate AI into teaching, faculty's AI literacy can be developed through the Project-Based Learning approach shown in Table 20. This project is structured around four sequential phases: institutional foundation and governance, instrumental and algorithmic immersion, epistemological reflections and ethical critique and curriculum integration. Table 20 summarizes each phase.

Table 20. AI project phases to integrate AI in teaching and learning process.

The project should prioritize formative assessment, characterized by: continuous feedback, iterative improvement cycles, evidence-based evaluation through proper instruments: digital teaching portfolio, rubric aligned with competencies, peer assessment, reflective diary, observation of teaching practices.

3.8 Baseline model for assessing faculty digital competencies

An institutional assessment baseline can be structured on the basis of the analysis performed in the aforementioned sections. Figure 3 illustrates the baseline model.

The baseline model is anchored to the institutional digital competence concept and digital competencies framework. The assessment stage must consist of both quantitative and qualitative assessment. Findings analysis should be able to establish cause-effects relationships between the results.

Finally, institution's policies must reflect the strategy for continuous improvement and professional development of teachers’ digital competencies. The cycle assessment-professional development must be included within as a current institution policy.

4 Discussions

The advancement of digital technology has transformed educational models, demanding constant renewal in teaching and learning strategies within higher education. Teacher training faces the challenge of responding to the demands of the digital era, with new cognitive, communicative, and cultural dynamics (Ally, 2019). Teachers are no longer conceived as transmitters of information, but as designers of learning experiences that integrate emerging technologies, active methodologies, and flexible resources oriented toward the development of 21st-century competencies.

Teacher training must respond to the needs of a generation of hyperconnected, mobile, and visually oriented students, whose interaction with knowledge occurs in brief, interactive, and personalized formats. The rapid pace of knowledge generation, together with the multiplicity of virtual environments, demands more agile, personalized, and sustainable training processes, capable of adapting to the emerging realities. The Literature review reports the need for continuous teacher training programs in digital competencies, framed with the Lifelong Learning paradigm. Consequently, the assessment reference framework and instrument must be aligned with educators’ digital competences and educational process context.

An institutional assessment process primarily must consider the concept of digital competence. This concept is elusive, and the literature often use terms such as digital literacy, media literacy, ICT skills, even though they are not synonymous (Sánchez et al., 2020). Various scholars have conceptualized teachers’ competencies [Caviglia et al., 2026; Skantz-Åberg et al., (2022); Krumsvik et al., 2016]. We adopted the concept proposed by Ferrari (2012).

Karimi and Khawaja (2025) reviewed 22 studies published between 2010 and 2023 covering various regions: Spain, China, Turkey y Latin America. The significant finding of this review is that 70% of studies report the absence of training programs and professional development opportunities to enhance teachers’ digital competencies.

Álvarez-Huari (2025) conducted a systematic review of 18 studies carried out at Latin American universities, between 2019 and 2024. Notably, fourteen of the reviewed studies concurred on the need to train teaching staff in ICT skills through continuous training programs. However, this remains an unfinished task. The effective implementation of these proposals requires institutional policies that foster a sustained commitment across the university ecosystem to achieve defined objectives

Inamorato Dos Santos et al. (2023). highlight that 6% of academics are classified as “Newcomer” or “Explorer”, emphasizing the importance of implementing training strategies for leveling these educators up for integrating them into the institution's ongoing professional development program

Martin et al. (2022). underscore the pursuit of a standardized digital competence framework for the institution, establishing proficiency levels to propose personalized training pathways. They conclude that educators must engage in reflective professional practice that enable them to create content, share learning experiences with colleagues, and how their disciplines are taught and learned.

Fernández-Batanero et al. (2021) examine the challenges teachers face in improving their competencies. They reviewed of twenty research studies were identified as primary barriers the lack of teacher training programs, educators’ attitude toward ICT, the lack of ICT experience and time availability.

There is a clear consensus on the need for continuous training programs in digital competencies for education as a core institutional policy. The dynamic development of technology requires periodic assessment of the teaching staff´s digital competencies through adequate an integrative process yielding both qualitative and quantitative insights.

The authors develop a baseline for the institutional faculty assessment in digital competencies, articulated with a six-dimension framework designed for teacher training to guide the practical development of the DCTP. However, this framework must be recognized as a preliminary model derived from a single institutional case. Its effective implementation and pedagogical efficacy remain subject to future empirical validation through pilot testing, rubric-based evaluation, and longitudinal impact studies.

Section 3.7.2, provides a practical roadmap for translating the evaluation process into institutional action. However, implementing this multi-phase management framework is not a one-size- fits-all solutions. Its success depends on the specific organizational readiness, available resources and governance structure of each institution. Therefore, the program's effectiveness relies on key human and material resources such as: technological infrastructure, connectivity, access to digital material, qualified facilitators, administrative support, allocated training time, workload recognition, and mechanisms for professional motivation and incentives. Teachers are recognized as learners and professionals operating within distinct institutional, organizational, and labor conditions.

Teacher training must be understood as a shared institutional responsibility, requiring organizational structures, technical teams, and clear policies that guarantee continuity, continuous improvement, and curricular coherence. Teacher autonomy is essential, but it is insufficient without an institutional environment that supports, values, and systematizes professional development.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2026.1985613/full#supplementary-material

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Footnotes

Edited by: Minela Kerla, The Association of Online Educators, Bosnia and Herzegovina

Reviewed by: Valentina Canese, National University of Asunción, Paraguay

Armando Sanchez-Macías, Autonomous University of San Luis Potosí, Mexico