A Diagnostic Study on the use of Generative Artificial Intelligence by Teachers at Armando Mestre Martínez Technical School

Introduction

The contemporary educational landscape is characterized by the accelerated incorporation of digital technologies, a phenomenon that brought about profound modifications to teaching-learning processes (Kong, Cheung & Tsang, 2024). In this scenario, generative artificial intelligence (GAI) emerged as one of the technological innovations with the greatest potential for educational systems at the global level (UNESCO, 2023). Its capacity to create original content, simulate complex scenarios, and personalize learning processes converted it into an invaluable tool for twenty-first century education. (Mariani et al., 2023)

In developing countries, such as Cuba, the integration of these advanced technologies faced multidimensional challenges (Fernández Hernández et al., 2024a and 2024b). Technical Professional Education (TPE) and especially polytechnic construction institutes (PCI), tasked with training the skilled workforce demanded by the country's economic and social development, required updating their pedagogical practices through the incorporation of emerging technologies (Fu et al., 2025).

Within this practice, lesson planning understood as the process of design, organization, and planning of teaching-learning activities (Monetti & Molina, 2024) constituted a privileged scenario for the utilization of GAI.

UNESCO (2023) highlighted that GAI offered innovative solutions to optimize lesson planning and adapt it to the specific needs of each group or student. Recent research (García-Peñalvo, 2023; Luckin et al., 2022; Tlili et al., 2023; Zawacki-Richter et al., 2019) documented its potential to personalize learning, generate educational materials, provide instant feedback, and create personalized learning environments.

The growing interest in GAI integration in education generated diverse empirical studies and systematic reviews at the international level (Díaz Vera et al., 2024; Jiménez Martínez et al., 2024; Marzano, 2025; Mercader-Juan et al., 2025); however, most of these investigations focused on Higher Education or contexts with advanced technological developments, which underscored the need for contextualized studies in Cuban vocational technical education.

The present investigation sought to contribute to meeting this need through a diagnosis of the current state of GAI use in lesson planning among teachers of technical education. The premise was that understanding the conceptions, levels of use, practical experiences, and attitudes of teachers constitutes an essential starting point for grounding proposals that respond to the real needs of educators.

Methods

The research was framed within a socio-critical paradigm with a mixed approach, as it combined quantitative and qualitative methods (Hernández-Sampieri & Mendoza, 2018) to achieve a comprehensive understanding of the phenomenon. A descriptive-diagnostic design was adopted that allowed characterizing the current state of the use of GAI in lesson planning.

The descriptive study—according to Hernández-Sampieri and Mendoza (2018, p. 108)—facilitated predicting a scientific fact which specifies that "there are gaps in knowledge about generative artificial intelligence, with a predominance of limited conceptions regarding its nature and pedagogical applications, evidenced by the limited experiences for its effective integration in the polytechnic, while the attitudinal dimension revealed conflicting perceptions ranging from lack of awareness to recognition of its transformative potential."

The study was structured around three dimensions: cognitive (knowledge), instrumental (practical skills), and attitudinal (disposition and interest), an approach that has been used by Báez Matos et al. (2024) and Pérez Díaz et al. (2024) in their respective studies. This three-dimensional framework guided the selection and construction of data collection instruments, as well as the subsequent analysis of the information.

Dimensions and indicators

I. Cognitive dimension:

This dimension took into account the foundational knowledge that IPC teachers should possess in relation to the use of GAI as support tools in lesson planning.

The dimension is evaluated as:
GOOD: If both indicators are evaluated as good.
FAIR: If one indicator is evaluated as fair and the other as good, it may have both as fair, but neither as poor.
POOR: If both indicators are evaluated as poor.

Indicator 1: Knowledge related to GAI.
This indicator was designed to evaluate the knowledge that teachers possess about GAI: concepts, basic characteristics, and educational potential.

For the evaluation of this indicator, the following scale was used:
GOOD: When they correctly identify and explain concepts related to GAI, its basic characteristics, and potential for the lesson planning process.
FAIR: When they partially recognize GAI concepts, but with inaccuracies in its characteristics and educational applications.
POOR: When they do not identify or explain the basic concepts of GAI.

Indicator 2: Knowledge related to the pedagogical application of GAI.
This indicator took into account verifying knowledge related to the pedagogical application of GAI in lesson planning for construction family specialties.

For the evaluation of this indicator, the following scale was used:
GOOD: If they know the specific pedagogical applications of GAI, integration strategies in the construction teaching process, and evaluation criteria adapted to these tools.
FAIR: If they moderately know the pedagogical applications of GAI, integration strategies, and evaluation criteria.
POOR: If they do not know the pedagogical applications of GAI, integration strategies, and evaluation criteria.

II. Instrumental dimension:

This dimension was designed to verify the professional performance of teachers translated into the planning and execution of learning activities using GAI tools.

The dimension is evaluated as:
GOOD: If both indicators are evaluated as good.
FAIR: If more than one indicator is evaluated as fair, it may have one as good.
POOR: If both indicators are evaluated as poor.

Indicator 1: Professional performance achieved in designing learning activities with GAI.
It took into account the professional performance of teachers in designing learning activities that integrate GAI pedagogically in the construction context.

For the evaluation of this indicator, the following scale was used:
GOOD: Demonstrates professional performance in designing creative and pertinent learning activities that integrate GAI effectively and contextually in construction specialties.
FAIR: Demonstrates some professional performance in designing learning activities that integrate GAI, with some limitations in creativity or contextual relevance.
POOR: Does not demonstrate professional performance in designing learning activities that integrate GAI.

Indicator 2: Professional performance achieved in implementing and evaluating activities with GAI tools.
It took into account the professional performance of teachers in the implementation and evaluation of learning activities with GAI tools.

For the evaluation of this indicator, the following scale was used:
GOOD: Demonstrates professional performance in implementing and critically evaluating learning activities with GAI, making pertinent adaptations and verifying the technical quality of the generated responses for construction content.
FAIR: Demonstrates some professional performance in implementing and evaluating learning activities with GAI, with difficulties in making necessary adaptations or verifying the technical quality of the responses.
POOR: Does not demonstrate professional performance in implementing and evaluating learning activities with GAI.

III. Attitudinal dimension:

This dimension was designed to verify the interest and disposition shown by teachers in innovation with GAI tools in the lesson planning process.

The dimension is evaluated as:
GOOD: If both indicators are evaluated as good.
FAIR: If more than one indicator is evaluated as fair, it may have one as good.
POOR: If both indicators are evaluated as poor.

Indicator 1: Interest shown in innovation with GAI tools.

For the evaluation of this indicator, the following scale was used:
GOOD: Shows constant interest in exploration and experimentation with GAI tools to improve the lesson planning process in construction specialties.
FAIR: Manifests some interest in exploration and experimentation with GAI tools to improve the lesson planning process in construction specialties, but with dependence on external guidance.
POOR: Shows little interest in exploration and experimentation with GAI tools to improve the lesson planning process in construction specialties.

Indicator 2: Disposition for continuous training and updating in GAI.

For the evaluation of this indicator, the following scale was used:
GOOD: Manifests permanent disposition for continuous training and updating in the use of GAI.
FAIR: Manifests little disposition for continuous training and updating in the use of GAI.
POOR: Does not manifest disposition for continuous training and updating in the use of GAI.

A system of theoretical, empirical, and statistical level methods was used, with a predominance of qualitative techniques complemented by descriptive quantitative analyses. To evaluate the reliability and internal consistency of the instrument, Cronbach's alpha coefficient was calculated, reaching a value of 0.91.

Information analysis was performed using descriptive statistics tools: SPSS and Microsoft Excel. Thanks to this, it was possible to detect trends and patterns in the responses, as well as to compare teachers' opinions regarding the use of GAI.

The study was conducted at the Armando Mestre Martínez IPC in the province of Camagüey, Cuba. The population consisted of all 87 teachers that made up the staff of the selected IPC. Intentional non-probabilistic sampling was used to select a sample of 23 teachers belonging to the Construction Department, representing 26% of the total.

The criteria for sample selection were:

1. Thematic relevance: Teachers from the Construction Department were selected, as they were the ones who planned and taught the basic and specific training subjects of the professional family, where GAI integration presented greater challenges and potential.
2. Accessibility and feasibility: The accessibility and logistical availability of the group were considered for the sequential application of diagnostic instruments and, in a later phase, for the possible development of a professional development program.
3. Homogeneity: Teachers were sought to present homogeneous professional characteristics regarding their direct connection with the Construction family specialties.

Data collection techniques and instruments

Questionnaire: It was designed and applied to the 23 teachers. It was organized into sections aligned with the three dimensions: cognitive, instrumental, and attitudinal. It included closed questions (Likert scales, multiple choice) for the quantification of trends and open-ended questions to collect qualitative explanations and nuances.

The questionnaire was subjected to a validation process through expert criteria and a preliminary pilot test to verify clarity, relevance, and reliability. The latter was guaranteed through content validity, ensuring that the items represented the theoretical dimensions constructed.

Interview: This qualitative method allowed exploring in greater depth the subjective perceptions, personal experiences, internal motivations, and contextual barriers that teachers faced or anticipated in the integration of GAI into their pedagogical practice. It investigated the "why" behind the attitudes measured in the questionnaire.

A flexible interview guide was used with open-ended questions organized around thematic axes: knowledge of tools, experiences of use, perceived obstacles, specific training needs, and vision of the impact of GAI on construction teaching.

The information from the interviews was triangulated with the questionnaire responses and observation records, which allowed validating findings and explaining apparent contradictions.

Observation: It was carried out systematically and directly, with the aim of capturing real teaching practice beyond what was self-reported. Twenty-three classes corresponding to different subjects of the Construction family specialties were observed. A structured observation guide was used that included observable indicators organized into categories such as: effective use of GAI tools, pedagogical strategies implemented, teacher-student interactions around technology, and technical quality of the generated or referenced content.

This method provided objective and contextual evidence on the gap between declared knowledge and effective practice, an aspect that was crucial to identify authentic and action-based professional development needs.

Documentary review: A documentary analysis was performed to frame the empirical findings within the normative, curricular, and institutional context of the IPC.

Documents analyzed:

1. Documentos normativos nacionales y ministeriales (Constitución de la República de Cuba, Resolución 140/2019 del MES sobre posgrado).
2. Documentos institucionales (planes de estudio, programas de asignaturas de las especialidades de construcción, proyectos educativos de grupo e institucional.
3. Registros metodológicos (actas de reuniones departamentales, planes de preparación metodológica, planes de clases).

This review allowed:

1. Understanding the legal and educational policy framework that supported or required the use of GAI in pedagogical practice.
2. Identifying the specific curricular demands of technical specialties that could be enhanced with GAI.
3. Contextualizing the practices observed in the classroom within the institutional guidelines and resources available.

Results

The results were organized according to the three dimensions: cognitive, instrumental, and attitudinal, which allowed characterizing the use of GAI in lesson planning.

Cognitive dimension

Only three teachers, representing 13% of the sample, accurately identified concepts related to GAI and mentioned its main characteristics, revealing a deep conceptual gap. The remaining 87% showed partial, outdated, or erroneous conceptions. The interviews deepened this finding; 70% of teachers (16 out of 23) associated GAI exclusively with "generic virtual assistants" (ChatGPT, Copilot) without understanding its potential for lesson planning in construction specialties. No teacher mentioned specific GAI applications for generating structural calculation problems, process simulation, or adaptation of technical material. The documentary analysis of planning corroborated this gap: in none of the 23 planning documents reviewed was there evidence of the intentional use of GAI for the design of objectives, content, or learning activities.

Instrumental dimension

Seventy-eight percent of teachers (18 out of 23) stated that they did not use GAI tools for lesson planning purposes. Nine percent (2 out of 23) reported having designed some learning activity supported by GAI, although in both cases these were isolated and unsystematic experiences. Sixty-five percent (15 out of 23) argued in interviews that they did not know how to integrate them into their pedagogical practices or did not know how to verify the technical quality of the information generated for construction content.

Documentary analysis corroborated this limitation; 100% of the planning documents reviewed relied exclusively on traditional methods (textbooks, technical manuals, printed guides). No written evidence was found of the intentional use of GAI for the design of objectives, content selection, activity development, or assessment design.

Attitudinal dimension

Contradictions were identified; 52% of teachers (12 out of 23) showed distrust towards GAI, considering it a tool that depersonalized technical teaching or a passing fad. However, in contrast to this stance, 82% (19 teachers) expressed high disposition to receive training on the subject, especially in specific applications for planning construction content.

The interviews revealed that this apparent contradiction responded to a tension between "fear of change" and "recognition of the need to update." Forty-three percent (10 teachers) explicitly expressed feeling "overwhelmed" by the speed of technological changes.

Identified strengths

• Disposition and interest in training in the use of GAI for lesson planning.
• Recognition of the need for technological updating.
• Relationship of GAI with real problems of lesson planning.
• Motivational base that combines skepticism with pedagogical curiosity, favorable for the training process.

Identified weaknesses

• Low level of conceptual knowledge about GAI.
• Null or sporadic use of GAI in lesson planning.
• Lack of knowledge of specific tools and strategies for designing effective prompts.
• Perception of threat to pedagogical authority and resistance to change.
• Absence of documented integration of GAI in planning documents.

Discussion

The results of this research reveal that the use of GAI in lesson planning by teachers at the Armando Mestre Martínez IPC is incipient, unsystematic, and marked by significant gaps in the cognitive, instrumental, and attitudinal dimensions. These findings are consistent with international studies that document slow and unequal adoption of GAI in educational contexts, particularly in technical education (García-Peñalvo, 2023; Zawacki-Richter et al., 2019).

In the cognitive dimension, the predominance of limited or erroneous conceptions about GAI is not an isolated phenomenon. It coincides with what authors such as Zawacki-Richter et al. (2019) point out: GAI in education is considered globally one of the emerging areas of educational technology that teachers still do not know how to take advantage of, because they are unaware of the significance and advantages of its application in lesson planning.

In this line, various international diagnostic studies have included specific dimensions on conceptual knowledge of GAI and recognize that measuring this variable is an indispensable previous step for any training intervention at a global level (Jiménez Martínez et al., 2024; Marzano, 2025; Mercader-Juan et al., 2025).

However, unlike these findings, studies in contexts with active institutional policies, such as that of Díaz Vera et al. (2024) in Ecuador, report that 68% of teachers received institutional training, evidencing that the cognitive gap is not inevitable but responds to the absence of systemic conditions. In the specific context of TVET, this situation is aggravated by the scarce presence of the topic in initial and continuing training programs.

In the instrumental dimension, the absence of consolidated experiences of using GAI for planning constitutes the most critical finding. It is not only that teachers do not use these tools, but that they have not had the opportunity to explore their pedagogical potential. As Terrazas (2023) warns, access to technology does not guarantee its educational integration; a process of appropriation is required that involves experimentation, reflection, and accompaniment. The fact that 65% of interviewees state that they do not know how to verify the technical quality of content generated by GAI evidences a specific and urgent training need, particularly in a field such as construction, where technical errors can have serious consequences.

This result contrasts with international studies that, while reporting incipient adoption, already document specific uses in the creation of didactic materials and content preparation (Díaz Vera et al., 2024). In the Ecuadorian study, for example, the results show that content preparation and didactic material development activities concentrated the highest levels of GAI use, while tasks such as feedback or evaluation showed significantly lower frequencies.

This pattern suggests that teachers tend to adopt GAI first in areas where they perceive less pedagogical risk, a finding that could explain why, in our context, where lack of knowledge is greater, use is almost non-existent. The documentary review of planning documents, which found no evidence of GAI integration, reinforces the thesis of Ratumanan and Krismiyati (2025) on the possible negative influence of rigid lesson planning frameworks on technological adoption.

In the attitudinal dimension, the coexistence of distrust and disposition to train reflects what Lim et al. (2023) call an "innovation paradox"; teachers recognize the need to change, but fear losing control over the processes they master. This ambivalence should not be interpreted as irrational resistance, but as an implicit demand for training that empowers, rather than replaces, pedagogical judgment. As Terwiesch (2023) points out, the role of teachers in teaching is even more vital, regardless of the educational level in which GAI is used in their pedagogical practices.

These data suggest that training not only reduces distrust but also allows a more nuanced perception of risks. Jiménez Martínez et al. (2024), for their part, designed a specific dimension on perception of potential benefit, methodologically validating the relevance of measuring these attitudes as a differentiated construct.

A relevant contribution of this diagnosis is the verification that the problem does not lie exclusively with the teaching staff, but also in the absence of institutional and systemic conditions; the documentary review evidenced that study plans, methodological guidelines, and normative documents of TVET do not contemplate GAI as content nor as a tool for lesson planning. This reflects what UNESCO (2023) pointed out: the successful integration of advanced technologies in education requires a favorable ecosystem that includes support policies, continuous professional development, and innovative institutional cultures.

The diagnosis carried out not only confirms the existence of significant gaps in the cognitive, instrumental, and attitudinal dimensions, but also provides empirical evidence that dialogues with the international literature. While studies such as that of Mercader-Juan et al., 2025, demonstrate that when facilitating conditions exist (training, access, institutional support) GAI can significantly improve student motivation and performance, this study evidences what occurs at the opposite end of the spectrum: the absence of these conditions perpetuates ignorance and non-use. This verification reinforces the need to design contextualized training interventions that jointly address the three diagnosed dimensions, as suggested by the most recent systematic reviews (Marzano, 2025) and the instrumental validation experiences in Latin America (Jiménez Martínez et al., 2024; Díaz Vera et al., 2024).

Conclusions

The diagnosis reveals that the use of GAI in lesson planning at the Armando Mestre Martínez IPC is incipient, with critical gaps in the cognitive, instrumental, and attitudinal dimensions. This finding constitutes a systematic approach to the phenomenon in Cuban TVET and evidences that GAI is not yet part of the tools that teachers consider when planning.

The high disposition of teachers towards training represents a strategic opportunity that must be taken advantage of through pertinent and contextualized interventions; it is not enough to transmit conceptual information or train in technical management; a training model is required that simultaneously addresses the three dimensions and accompanies the teacher in a process of critical reflection that allows them to integrate GAI into their pedagogical practice.

The study provides an empirical basis and a set of validated instruments, replicable in other TVET contexts, thus contributing a broader vision of the use of GAI in technical education and guiding future teacher professional development strategies that respond to the identified needs.

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