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STUDENT PERCEPTION OF ARTIFICIAL INTELLIGENCE IN EDUCATION  
PERCEPCIÓN DE LOS ESTUDIANTES SOBRE LA INTELIGENCIA  
ARTIFICIAL EN LA EDUCACIÓN  
Flores Zamorano Jesús Antonio  
National Technological Institute of Mexico/IT of Los Mochis  
https://orcid.org/0000-0003-0240-5434  
jesus_afz@hotmail.com  
Torres Medina José  
National Technological Institute of Mexico/IT of Los Mochis  
https://orcid.org/0009-0007-5915-613X  
josetorresitlm@gmail.com  
Ponce Martínez Tonantzin  
National Technological Institute of Mexico/IT of Milpa Alta II  
https://orcid.org/0009-0007-7986-167X  
tonantzin.itma2@gmail.com  
Álvarez Machado Ernesto Alonso  
National Technological Institute of Mexico/IT of Los Mochis  
https://orcid.org/0009-0004-9014-3263  
ernesto.am@mochis.tecnm.mx  
López Martínez Brenda  
National Technological Institute of Mexico  
https://orcid.org/0009-0008-2401-5078  
brelopez8405@gmail.com  
DOI: https://doi.org/10.61273/neyart.v3i3.155  
| Recibido: 03/11/2025 | Aceptado: 22/01/2026 | Publicado: 15/02/2026  
Esta obra está bajo  
una licencia internacional  
Creative Commons Atribución 4.0.  
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Abstract-- This study explores how first-semester Business Management Engineering students in  
Mexico perceive and use artificial intelligence in their daily academic lives. Researchers surveyed 31  
students between August and December 2025 to understand what they really think about tools such as  
ChatGPT and similar programs.  
The results are quite revealing: students are very enthusiastic about the potential of AI to improve their  
learning and even their quality of life. Although they feel comfortable using these tools, they recognize  
that they are not as easy to use as they seem. Most interestingly, they show surprising maturity in  
identifying the risks: they know that they can become dependent on them, that they could affect their  
critical thinking, and that they facilitate plagiarism.  
Keywords— Education, Students, Artificial Intelligence, Perception, Technology.  
Resumen-- Este estudio analiza las formas en que los estudiantes de primer año utilizan la inteligencia  
artificial en tareas cotidianas. Se encuestó a un total de 31 estudiantess. El estudio está enfocado en el  
uso práctico de tales herramientas como lo son: ChatGPT u otras herramientas de asistencia para la  
escritura.  
Los resultados son bastante obvios: los estudiantes están bastante entusiasmados con la posibilidad de la  
IA para mejorar su aprendizaje e incluso su calidad de vida. A pesar de que les resulta sencillo el uso de  
estas herramientas, admiten que no son tan sencillas de usar. La parte más llamativa es que, para su edad,  
son bastante maduros al momento de señalar los riesgos: son conscientes de la posible dependencia que  
puedan tener a estas herramientas, la afectación a la crítica, el plagio y la obra.  
Palabras clave – Educación, Estudiantes, Inteligencia artificial, Percepción, Tecnología.  
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INTRODUCTION  
Artificial intelligence has experienced unprecedented expansion in recent years, radically transforming  
various sectors of society, including education. Tools such as ChatGPT, Claude, Gemini, and other AI-  
based assistants have been progressively integrated into the academic practices of university students,  
generating both learning opportunities and debates about their impact on the development of professional  
skills.  
Higher education business programs in Mexico need to understand how students incorporate artificial  
intelligence into their learning. Business management engineering is no different. This degree integrates  
administration, finance, and operations with a considerable emphasis on technology.  
First-year students are of particular interest for this analysis because they are in the process of building  
their academic careers, in which they begin to develop work routines, research skills, and attitudes toward  
technology. In the literature, there are university students who make little or excessive use of artificial  
intelligence, a phenomenon that can be explained by the digital illiteracy gap, the perceived use of the  
tool in an academic setting, and institutional regulations on its use.  
Although artificial intelligence is gaining ground in Mexican classrooms, its actual use by business  
students remains largely unexplored territory. It is not enough to know that the technology is there. We  
need specific data on which tools they choose, how often they open them, and for which specific academic  
tasks they use them.  
BACKGROUND  
Latin Americans  
The results of Gago et al. (2025) show that 68% of respondents used ChatGPT to help them with their  
academic tasks, employing this tool to develop ideas and obtain information. Although the authors  
mention that students were aware of the advantages offered by Artificial Intelligence, there was concern  
about the dependence that the use of this technology can generate and the weakening of critical and  
analytical thinking.  
A. de la Torre and M. Baldeon (2024) studied the perception that business students in Brazil had about  
the use of generative artificial intelligence tools. An interesting paradox emerged from the study. Seventy-  
three percent of students believed that using the technology improved their academic performance.  
However, only 42% of students had received guidelines from the institution on the ethical use of  
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technology. The finding illustrates the growing disparity between technology and training in the  
responsible use of digital technology.  
In Colombia, Burbano & Ibarra (2024) analyzed the impact of AI on business students and documented  
that the most frequent users of ChatGPT, Google Bard, and other academic writing assistants. The  
researchers stated that AI was revolutionizing conventional study methodologies, but warned that the  
types of institutional regulations that were necessary needed to be established more clearly.  
Espinoza et al. (2024) studied the attitudes of university students in Chile toward the use of AI in  
education. They identified prior positive digital skills and perceptions of usefulness and ease of adoption  
as predictors of the use of such technologies. In the study, there were differences in the use of artificial  
intelligence as a learning tool, which were attributed to different generations.  
López and García (2023) state that, while conducting research in Mexico on the use of emerging  
technologies in higher education students, 81% of participants had experimented with some AI tools, of  
which only 35% understood their limitations and biases. The authors emphasize that the curriculum  
should include teaching something about AI.  
A comparative study by Davila et al. (2024) in Peruvian universities on the implementation of AI in  
business courses reported that first-year students, in the case of Davila et al. (2024), showed greater  
receptivity to such technologies than students in higher semesters. This suggests that the pre-university  
education of younger students includes more technological facilities.  
International  
The use of new types of artificial intelligence in universities has been studied in many parts of the world.  
For example, in the United States, Sullivan et al. (2023) studied 1,000 university students. Eighty-nine  
percent of respondents used some generative AI tool at least once in the semester , largely to write  
assignments and solve problems. The authors mention that, in the educational field, the use of these  
technologies has exceeded expectations, indicating the need for a review of academic policies.  
Within the European context, Kasneci et al. (2023) analyze the consequences of ChatGPT in higher  
education and argue that these tools can be tutors that accompany self-directed learning. The academics  
point out that, although AI offers significant changes for the personalization of education, it also entails  
problems regarding academic integrity and the possible impoverishment of critical thinking.  
Students at a UK university analyzed by Cotton et al. (2024) examine the educational potential of  
ChatGPT. In the study, 53% said that these types of tools help optimize the process of completing  
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activities. However, respondents expressed concern about the possibility of negative dependence on the  
tool in acquiring critical thinking and writing skills. This study highlights students' ambivalence about  
the incorporation of artificial intelligence technologies in education.  
Yuk and Hu (2023) studied AI among university students in business programs in Australia and found  
that most students used AI to summarize, generate ideas, and correct grammar. The authors say that AI  
can be used as a complement to increase students' abilities, as long as it is used responsibly and does not  
replace learning processes.  
Perkins et al. (2023) study the lack of clarity, from the perspective of defending academic integrity,  
regarding the use of AI and plagiarism, and the resulting confusion among American students. Sixty-eight  
percent of respondents are unaware of which institutional policies refer to the use of AI. These data reveal  
a lack of interest and/or inadequate education about the use of technologies (including tools) and the  
ethical education that should be included.  
Kit et al. (2021) analyzed the use of AI tools by engineering students in solving complex problems in the  
Asian context, more specifically in Singapore. One study showed that 76% of respondents felt more  
supported by AI, as AI explained difficult concepts in other ways, but they argued that some conceptual  
understanding should be built before resorting to these tools.  
Baidoo-Anu and Ansah (2023) examined the role of ChatGPT in higher education globally and argue that  
such technologies represent a disruptive innovation in the understanding of pedagogical practice. The  
authors assert that educational institutions need to shift from a restrictive to a more constructive use of  
artificial intelligence, critically and in a pedagogical sense.  
Dergaa et al. (2023) have conducted a systematic review of the use of ChatGPT and its impact on higher  
education globally. Although the research is still in its early stages, the authors argue that there are  
indications, albeit weak, that students will benefit from retention and motivation with the use of AI,  
provided that there is guidance from a teacher and an ethical framework that limits its use.  
METHODS  
Research paradigm  
The research was conducted under the positivist paradigm, which attempts to describe phenomena  
objectively and measurably using empirical data and statistical methods. This particular approach is well  
suited to the study, as it provides the means for a methodical and granular examination of the use and  
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perception of artificial intelligence by engineering students in telematics, and allows for the use of data  
that is quantifiable and verifiable.  
Level of research  
The study examined the use, perception, comfort, potential risks, challenges, and roles of teachers in  
relation to artificial intelligence. The study did not attempt to correlate any of the variables mentioned  
above. The academic level focused on outlining the phenomenon and framework, which provided relevant  
information on academic and curriculum planning.  
Procedure  
All parts of this process were carried out simultaneously. The first step was to create a data collection  
tool that he named the Artificial Intelligence Use Questionnaire (AIUQ). Once the first step was  
completed, the tool underwent a content validation process where it was validated by experts and a pilot  
test was conducted to evaluate the clarity, relevance, and reliability of the tool.  
Once the validation was complete, it was time to implement the plan. Surveys were sent to students  
through the institution's channels, including instructions and the purpose of the study. Responses were  
then obtained and this data was used for statistical analysis.  
Sample  
In total, 31 students from the Business Administration Engineering educational program participated in  
the study. With this type of sampling, all members of the population have an equal chance of being  
selected, which minimizes bias in the sample, thus legitimizing the findings.  
Data  
Descriptive statistics and SPSS software were used for data analysis. The quantification of the  
questionnaire data was merged into a single matrix for the calculation of frequency, mean, and mode for  
individual items and for the dimensions. Some graphs were created to facilitate the interpretation of the  
results. Cronbach's alpha was used to evaluate the questionnaires, and the score was 0.93. This indicates  
that the questionnaire is reliable.  
Privacy of information  
General data about the students was used. Responses were analyzed collectively. No personal information  
about the students was documented. The anonymity and rights of the participants were respected. Students  
were given sufficient information about the study to understand what was happening and give their  
consent.  
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Description of the instrument used  
An established questionnaire, the Questionnaire on the Use of Artificial Intelligence (CUIA), was used  
to collect most of the information. It was designed to focus specifically on students' use, perception, and  
propensity to use artificial intelligence in the education sector. This tool was created after reviewing some  
specialized literature and previous studies on the use of emerging technologies in the field of higher  
education in order to assess its theoretical and methodological validity.  
The main objective of the questionnaire is to identify the degree of familiarity of students with artificial  
intelligence tools, as well as to understand their perception of the usefulness, ease of use, comfort, privacy,  
security, risks, and challenges associated with these technologies. Likewise, the instrument allows us to  
explore students' opinions about the role that teachers should play in an educational environment that  
integrates artificial intelligence as a support for the teaching-learning process.  
The CUIA covers multiple dimensions, which structure the key areas of analysis in the study. These  
dimensions are: knowledge and willingness to adopt artificial intelligence; analysis of usefulness,  
comfort, and ease of use; concern and insecurity; and the use of artificial intelligence in the role of the  
teacher. Each dimension consists of a set of components that are formulated in a clear and direct manner,  
which helps to better understand students and obtain more consistent responses.  
The pollster often includes Likert scale questions so that respondents can express their degree of  
agreement and disagreement with different statements about the use of artificial intelligence technologies.  
Likert scales of this type can be used to capture respondents' suggestions and feelings, which can be  
examined statistically.  
In addition, the questionnaire was validated using the IVCUIA, which is an Artificial Intelligence Use  
Questionnaire Content Validation Instrument, and was developed with the collaboration of experts in the  
field. This procedure served to analyze the clarity, relevance, and consistency of the items, thereby  
providing greater certainty regarding the validity of the instrument and ensuring that the items did indeed  
adjust their criteria to the theoretical dimensions of the problem.  
RESULTS  
Figure 1 shows the gender distribution of the participants in the examination.  
Figure 1. Gender distribution.  
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Female  
Male  
Source: Own elaboration.  
The response rates by gender are almost equal, although slightly more responses came from women. Of  
the 31 responses, women were slightly more numerous with 16 (51.6%) compared to men with 15  
(48.4%). There is only a difference of one participant per gender.  
Figure 2 shows the results for the perception of AI usefulness.  
Figure 2. Results of the perception of AI usefulness.  
Perception of AI usefulness  
140  
120  
100  
80  
60  
40  
20  
0
Q2.  
Q3.  
P4.  
Perception of AI usefulness  
Source: Author's own work.  
The results reflect a strong belief, almost enthusiasm, on the part of learners regarding the practical use  
of AI in various contexts. P2 was concerned about the applicability of AI in education and vocational  
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fields. The highest possible score was 124, and considering that 31 respondents used a five-point Likert  
scale, this shows that respondents were very affirmative.  
Question P3, regarding AI's ability to solve problems adequately, received 93 points, which translates to  
3.0 on the Likert scale. This score is related to a more moderate stance, with participants falling on the  
scale between "undecided" and "agree." Although there is some acceptance of AI's capabilities, there is a  
certain mistrust or, perhaps, ignorance regarding the redefinition of complex problems that it may  
encounter.  
For its part, question P4 again received the maximum score of 124 points, showing absolute consensus  
that AI can contribute significantly to improving people's quality of life. This perception reflects an  
optimistic view of the social and humanistic impact of these technologies, beyond their purely technical  
or academic applications.  
Figure 3 shows the results for the comfort and ease of use of AI .  
Figure 3. Results for the comfort and ease of use of AI.  
Convenience and ease of use of AI  
140  
120  
100  
80  
60  
40  
20  
0
P5  
P6  
P7  
Convenience and ease of use of AI  
Source: Own elaboration.  
The responses show that adaptation to technology occurs at different levels among students.  
P5, which measures the amount of confidence in the use of AI in academic tasks, received a score of 124.  
This means that in the case of this participant, total dependence is based on the integration of AI into  
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educational processes. This demonstrates a very positive attitude and confidence in the use of AI in  
education.  
On the other hand, question P6 on the ease of use of AI tools scored 62 points, which is equal to 2.0, or  
"slightly disagree." This score shows that there is a division, as students do not believe these tools are  
easy to use. Perhaps this is due to the initial learning curve, the complexity of some platforms, or the lack  
of specific training.  
Question P7, regarding whether AI facilitates faster and more efficient learning, scored 93 points (average  
of 3.0), placing it in a neutral-positive position. Students show some indecision regarding the actual  
effectiveness of these tools in optimizing their learning processes, which could indicate mixed  
experiences or variable results depending on the context of application.  
Figure 4 shows the results for AI privacy and security.  
Figure 4. Results for AI privacy and security.  
AI privacy and security  
140  
120  
100  
80  
60  
40  
20  
0
Q8  
P9  
P10  
AI privacy and security  
Source: Own elaboration.  
This survey shed light on some risks associated with the use of artificial intelligence tools, where data  
use and privacy protection are of utmost importance. The results for question P8 on personal data  
protection were 62 points (average of 2.0), which shows that students have fairly low confidence in the  
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protections offered by artificial intelligence tools. This lack of confidence reflects students' concerns  
about the use of digital data and the loss of personal information.  
Question P9, which asks whether AI protects user privacy, scored 93 points (average of 3.0) and was  
rated as undecided. Students' lack of interest in privacy policy and the use of their data shows that they  
lack confidence. There is a need for AI developers and service providers to be clearer.  
The maximum score of 124 points for question P10 suggests 100% unanimous concern about the potential  
misuse of personal data. Here, the score is even more interesting, as it shows that, regardless of the tools  
used, students demonstrated a clear and thoughtful understanding of the threats that result from the  
processing of personal data.  
In question P10, the 124 points show that there was complete agreement about being more concerned  
about the loss of personal data. This is very interesting because it shows that even when students were  
using the tools, they remained cautious and critical about the risks of their personal information being  
used and abused in a digital environment.  
Figure 5 shows the results for the risks and challenges in the use of AI.  
Figure 5. Results of the risks and challenges in the use of AI.  
Risks and challenges in the use of AI  
140  
120  
100  
80  
60  
40  
20  
0
P11  
P12  
P13  
P14  
Risks and challenges in the use of AI  
Source: Own elaboration.  
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This dimension had fairly consistent results, with all questions achieving the highest score of 124. This  
reflects a consensus regarding the risks of AI in education. Question P11 shows that students strongly  
agree that excessive use of AI can lead to dependency, thus identifying the problem of uncritical adoption  
of these technologies.  
Question P12 reveals certain concerns about the possible positive impacts that Artificial Intelligence can  
have on the development of critical thinking. Students recognize that the automation of cognitive  
processes would be a disadvantage for the exercise of critical thinking.  
The unanimous agreement of participants on question P13 shows that AI can involve academic dishonesty  
(i.e., plagiarism or submission of AI-generated work without the author's consideration or contemplation).  
This demonstrates the ethical maturity of the participants.  
The responses to question P14 show that students are aware of the potential dangers of using AI in  
teaching and learning. This level of awareness suggests that a significant proportion of participants are  
aware of the risk on both sides of the argument.  
Figure 6 shows the results for the role of teachers in the use of AI.  
Figure 6. Results for the role of teachers in the use of AI.  
Role of teachers in the use of AI  
140  
120  
100  
80  
60  
40  
20  
0
P15  
P16  
P17  
P18  
Role of teachers in the use of AI  
Source: Own elaboration.  
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In this dimension, the results are very clear: all questions achieved the maximum score of 124, indicating  
absolute consensus on the importance of the mediator, in this case the teacher, in the use of artificial  
intelligence. Regarding P15, students highlight the importance of teachers limiting the use of these tools,  
which implied the need for pedagogical advice in the implementation of the technology.  
Question P16 shows that teachers are expected to use artificial intelligence as a resource that actively  
supports the teaching-learning process. Students not only embrace this technology, but also demand that  
their teachers use it intentionally and pedagogically in their teaching activities.  
In question 17, all students mention that the teacher sets certain limits on the use of AI and continues to  
emphasize the importance of establishing certain boundaries and guidelines. Teacher assistance means  
that students who are self-directed using tools may be ineffective.  
Question P18 confirms that students see teachers as key to promoting responsible and ethical use of AI  
by students. This finding shows that students consider the use of artificial intelligence to be something  
that is not free or self-governed and something that should be controlled and guided from a teaching,  
ethical, and professional perspective by teachers.  
DISCUSSION  
Students' perception of the use of AI in their academic and professional training, and its use to improve  
quality of life, is extremely positive. This result is consistent with that of A. de la Torre and M. Baldeon  
(2024) in Brazil, where 73% of business administration students considered that AI tools enhanced their  
academic productivity. It also coincides with the results obtained by Yuk and Hu (2023) in Australia,  
where students considered AI as a tool to improve their abilities and the performance of their cognitive  
processes.  
However, it is peculiar that question P3, which asks about AI's ability to solve complex problems,  
received the lowest number of points (93 points, average 3.0), remaining in the indecision zone. This  
reservation, compared to the general trend, indicates that although students appreciate the potential of AI,  
they remain skeptical about factors that have a high cognitive level. This type of encounter could be  
interpreted as a sign of true maturity, where subjects are able to discern the difference between a primary  
and a secondary, more sophisticated use of the technology.  
Artificial intelligence (AI) tools are simple and efficient; however, students report feeling paradoxically  
uncomfortable with their simplicity (P5: 124 points), but feel completely relaxed using them (P6: 62  
points). This contradiction stands out and requires further analysis. For example, Kasneci et al. (2023)  
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explain that acceptance of new technology is not always directly proportional to perceived simplicity.  
This implies that motivation, school stress, and/or work obligations may compel someone to use tools  
that are perceived as aggravatingly complicated.  
Espinoza et al. 2024 mentioned in their Chilean study that prior digital literacy and the perception of its  
usefulness significantly influence the adoption of AI. The results of the current study indicate that first-  
year students may be experiencing a steep learning curve, where psychological comfort in using these  
tools does not eliminate perceived technical difficulties. This explanation is reinforced by the moderate  
score on P7 (93 points), where students seem unsure whether AI actually accelerates and streamlines their  
learning.  
The aforementioned finding contrasts partially with that of Cotton et al. (2024), where it is reported that  
53% of British students believed that these tools were effective in enhancing their academic achievement.  
These differences can be justified by the context, which may include prior access to digital technology,  
institutional technological infrastructure, or the type of digital literacy that students possess when entering  
higher education.  
AI privacy and security shows a critical understanding of the privacy dangers associated with the use of  
AI. Low confidence in the security of personal data (P8: 62 points) and concern in all cases about data  
misuse (P10: 124 points) indicate that students are not passive users of these technologies. This is relevant  
when we consider that the participants are first-semester students, indicating that higher education is  
accompanied by greater concern for the defense of digital rights and data protection.  
These results correspond directly with those of Perkins et al. (2023) in the United States, who reported  
widespread confusion among students regarding the ethical use of artificial intelligence tools. However,  
participants in this study seem to demonstrate a greater understanding of the potential risks, although they  
remain uncertain about risk mitigation measures. This difference could be due to a recent increase in  
media coverage of data breach scandals and/or previous educational initiatives on digital citizenship at  
the secondary school level.  
The ambivalent position on whether AI protects user privacy (P9: 93 points) reflects what A. de la Torre  
and M. Baldeon (2024) identify as a discrepancy between the adoption of technologies and the  
understanding of their privacy policy. Students use these tools, but do not fully understand the terms of  
service and data processing policy.  
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In Risks and challenges in the use of AI, the consistency in the maximum scores obtained in Dimension  
5 (all questions with 124 points) is one of the most significant findings of this study. The unanimous  
recognition that AI can create dependency (P11), affect critical thinking (P12), facilitate dishonest  
practices (P13), and pose significant risks (P14) contrasts sharply with the generally positive perception  
of the usefulness of these technologies.  
This recognition of both the benefits and risks is also in line with what Gago et al. (2025) report from  
Argentina, where students recognized the benefits of AI but remained concerned about technological  
dependence and the possible loss of critical thinking skills. The difference here is that in the current study,  
this recognition reaches a tipping point of total agreement. This could be seen as a positive sign that public  
discourse on the risks of AI has, to some extent, reached the consciousness of students.  
Studies on the problems of academic dishonesty (P13) are more than ever at the forefront of recent studies  
on academic integrity. Cotton et al. (2024) warn about the integrity that must be ensured in artificial  
intelligence with the arrival of ChatGPT. Therefore, the present study suggests that, to a certain extent,  
students are aware of the discontent surrounding the use of artificial intelligence. This type of acceptance  
could positively slow down the development of guidelines that are built on principles of cooperation  
rather than prohibitive guidelines.  
The study reveals an undeniable fact: the fundamental importance of teachers in mediating the use of AI.  
In this sense, the unanimity in Dimension 6, where all questions achieved the highest score, is perhaps  
the most striking result. Students not only recognize the relevance of teachers in mediating the use of AI,  
but also, more insistently, demand their guidance as regulators (P17) and promoters of ethical use (P18)  
and in the integration (P16) and strategic mediation (P15) of technology.  
These findings strongly resonate with the arguments put forward by Baidoo-Anu and Ansah (2023), who  
argue that educational institutions must evolve from prohibitionist stances toward approaches that  
integrate AI in a thoughtful and pedagogically grounded manner. The students in this study do not see AI  
as a replacement for teachers, but rather show a greater need for guidance from teachers and more teaching  
in order to cope with this new technological situation.  
This finding alleviates some of the concerns in the literature regarding teacher role descriptors as  
technology advances in education. In contrast, students seem to understand the intricate complexity of AI  
and the ethical issues that require skilled human labor. This aligns with Kit et al. (2021) in Singapore,  
where students recognize the need to foster a fundamental understanding before using AI tools.  
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The request for teacher regulation (P17) is highly relevant in the Latin American context. Burbano &  
Ibarra (2024) warned of the need to build clear institutional regulatory frameworks in Colombia, and  
although the present study suggests that even students themselves perceive a lack of self-regulation, this  
shows that there is a possibility for educational institutions to create AI usage policies that are accepted  
by students rather than seen as bureaucratic administrative impositions.  
Burbano & Ibarra (2024) pointed out the urgency of establishing institutional regulations in the case of  
Colombia. In this sense, the findings of the ongoing research suggest that students are, at least partially,  
aware of the lack of self-regulation. This paves the way for educational institutions to develop policies  
on AI use that have the legitimacy and support of students, rather than policies being interpreted as  
administrative provisions.  
The results of this study are particularly relevant considering that these participants are first-semester  
business students in Mexico. Davila et al. (2024) found in Peru that first-year students were more open  
to these technologies than their advanced-semester peers, suggesting some kind of generational gap in  
digitally oriented environments.  
López and García (2023) show that in Mexico, 81% of students in higher education have used artificial  
intelligence tools, yet only 35% know what AI tools do and what biases are associated with those tools.  
The tool gap stems from an insufficient understanding of the ethical, technical, and epistemic  
ramifications. This gap illustrates a pedagogical challenge that the AI education industry should address  
in order to provide education on the ramifications of AI.  
CONCLUSIONS  
Students show an unquestionable appreciation for the relevance of artificial intelligence to their academic  
and professional training and for its potential to improve people's quality of life. Being grateful is a sign  
of a good and open mind toward technology, seeing it as a partner in training. But this appreciation is  
balanced with caution and concern about AI's ability to recognize and even solve problems. This shows  
that students lack faith in the magnitude, scope, and impacts of such tools. This balanced attitude of  
optimism and skepticism shows a complete and balanced collaboration with enthusiasm for technology  
and the fundamentals of constructive criticism.  
Although the students in the survey showed a certain level of comfort using artificial intelligence tools,  
they do not consider them easy to use. Within this apparent contradiction, the adoption of a technology  
does not imply recognition of its simplicity. Elements such as motivation, the need for academic  
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achievement, or professional expectations drive its use, even when there are technical difficulties. The  
lack of secondary school students in ongoing surveys to analyze effectiveness is possibly due to a lack of  
institutional guidance on tools and strategies for effective use.  
It is clear that these findings reveal a critical analysis of the use of personal information in a digital context  
for the first time. Students remain distrustful of the potential safeguarding of their personal information  
on AI platforms and the potential protection of their privacy. Collective concern about the potential  
exploitation of personal information validates their status as users of these technologies. Certainly,  
students are not uncritical consumers of these technologies. Concern for digital rights and data protection  
becomes relevant in this case among first-semester students, suggesting that education in universities  
regarding cybersecurity is becoming strained.  
The unanimous recognition of the risks associated with the use of artificial intelligence is one of the most  
significant findings of the study. Students realize that excessive use of technology can cause dependency,  
stifle the growth of critical thinking, promote dishonest behavior in academics, and threaten the integrity  
of the educational system. Understanding the challenges of technology does not contradict having a  
positive outlook toward technology. It shows that students understand the complexities of the situation  
and can differentiate between the benefits and dangers associated with absolute use of technology.  
The importance of the teacher's role in mediating the use of AI is one of the most unanimous points in  
the study. Students, in general terms, ask teachers to i) guide the use of these tools, ii) define how and  
when they should be used in teaching and learning activities, iii) regulate their use in academic activities,  
and iv) promote their use in a responsible and ethical manner. This result, from any perspective,  
contradicts the fear that teachers may lose importance in the face of advances in AI. Most students  
understand that the breakdown of discourse, ethics, and knowledge of these technologies requires a  
professional to accompany them, guide their learning, and exercise leadership. The fact that the perception  
of the very absence of regulation qualifies it as insufficient constitutes an opportunity for education  
systems to build regulatory pathways that are recognized by students.  
Future lines of research  
From an educational perspective, longitudinal studies are important for recording changes in the  
understanding, attitude, and use of AI in higher education learning. Following the same cohort from the  
first semester to graduation could reveal important changes and characteristics, as well as the possible  
correlation between the use of AI and academic performance.  
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These studies could help to understand whether the alarm or caution in the use of AI among most people,  
in relation to the problems they can solve (level of complexity or difficulty of the problems they are able  
to solve and the problems that are easy to solve), tends to decrease once students face more complex  
academic problems, or whether, on the contrary, this type of alert increases over time.  
This time, the focus was on students in the Business Management Engineering program. However, there  
are comparisons and interdisciplinary studies that can optimally include students from other programs.  
Due to interdisciplinary differences, variation in usage and perception is expected. For example, while  
humanities students might view the impact of artificial intelligence on critical thinking processes as  
trivial, their engineering counterparts might consider such impacts to be critical. While health science  
students might raise relevant ethical and data privacy concerns, humanities students may focus on a loss  
of originality and creativity and ignore such concerns.  
Comparative studies are useful in identifying the broader meaning of perception that transcends  
disciplines or, conversely, that each discipline of knowledge must take on different challenges when  
incorporating AI.  
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TABLA TRABAJO COLABORATIVO  
Rol  
Autor (es)  
Conceptualización  
Metodología  
Software  
Flores Zamorano Jesús Antonio  
Torres Medina José, Ponce Martínez Tonantzin  
Álvarez Machado Ernesto Alonso, López Martínez Brenda  
Flores Zamorano Jesús Antonio  
Validación  
Análisis Formal  
Investigación  
Recursos  
Torres Medina José, Ponce Martínez Tonantzin  
Álvarez Machado Ernesto Alonso, López Martínez Brenda  
Flores Zamorano Jesús Antonio  
Curación de datos  
Escritura -  
Torres Medina José, Ponce Martínez Tonantzin  
Álvarez Machado Ernesto Alonso, López Martínez Brenda  
Preparación del  
borrador original  
Escritura - Revisión y  
edición  
Flores Zamorano Jesús Antonio  
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