The objective of this study was to determine the relationship between artificial intelligence and the development of critical thinking in university students. The methodology followed the procedures of the positivist paradigm with a quantitative approach, using a descriptive-correlational design. A total of 124 students from the Faculty of Education at the University of Zulia participated, selected through random sampling. A virtual questionnaire validated by five experts was used, and its reliability was verified using Cronbach’s Alpha coefficient, obtaining a high reliability score of 0.988. The results of the Spearman correlation analysis revealed a highly significant correlation of 0.898, demonstrating a strong relationship between artificial intelligence and critical thinking. The conclusion highlights that the interaction between artificial intelligence and higher cognitive skills is positively associated with improved information processing.

Keywords: Artificial intelligence, education, learning, critical thinking, skills, relationship.

Critical thinking is a fundamental skill that allows students to evaluate information objectively and make informed decisions, particularly in an increasingly complex world. For university students, the development of critical thinking is crucial for achieving success in both their education and professional lives. Additionally, it enhances effective learning by enabling the critical analysis of information and a deeper understanding of the concepts being taught. As Leal (2023) points out, it also helps students solve problems by identifying and developing creative solutions. In this regard, universities provide opportunities to cultivate critical thinking as students face a vast amount of information and challenges.

According to Acosta (2024), developing emotional intelligence and critical thinking requires active participation in learning activities, taking courses designed to build these skills, and seeking opportunities beyond the classroom. Similarly, Acosta (2023) emphasizes that university educators play a vital role in creating learning experiences that foster critical thinking. Ultimately, the development of critical thinking in university settings represents a long-term investment, equipping students for success in both their education and professional careers.

Bezanilla-Albisua et al. (2018) suggest that integrating artificial intelligence into educational programs personalizes learning by tailoring content to the individual needs of students, thereby challenging them to critically reflect on the specific problems they encounter. Moreover, Lengua et al. (2020) highlight the incorporation of virtual assistants with natural language processing capabilities, which provide personalized responses and encourage critical reasoning by posing stimulating questions.

According to Lope et al. (2020), in the context of project-based learning, AI facilitates the creation of problem-based experiences by providing relevant data, resources, and guidance, immersing students in real-world situations that drive them to analyze, synthesize, and critically evaluate information. Similarly, Sandoval (2018) highlights AI’s important role in analyzing large educational datasets, identifying patterns and trends that engage students in data interpretation and strengthen their analytical skills. 

In this vein, Codina and Garde (2023) point out that ChatGPT, as an AI model, significantly contributes to learning processes by providing users with instant access to information and assistance across a wide range of topics. Through interaction with the language model, students can ask questions, receive detailed explanations, and gain clarity on difficult concepts.

According to Franganillo (2023), AI’s ability to generate coherent and contextually relevant responses enhances understanding and facilitates knowledge assimilation. Additionally, it offers a practice environment to improve writing and verbal expression skills. This tool represents a valuable resource that complements traditional learning methods, providing personalized support and encouraging the self-directed exploration of educational information. 

In line with this, Aguirre (2023) emphasizes that universities also leverage AI-driven simulations and virtual environments to create immersive experiences. These scenarios require students to make critical decisions, solve problems, and apply sharp analytical thinking. Moreover, the personalized feedback provided by AI guides students’ progress, fostering critical reflection on their strengths and areas for improvement.

According to Barrios Tao et al. (2020), integrating AI programming into the curriculum contributes to the development of critical thinking skills. By creating and adjusting algorithms, students not only understand the principles of AI but also analyze the impact of their decisions on the program's behavior.

Addressing the issue that motivated this study—weaknesses in the development of critical thinking among students at the University of Zulia—Leal (2023) points out that university students who have not developed critical thinking may exhibit various shortcomings that significantly affect their academic performance and cognitive skills. One of the most evident manifestations is the lack of deep analysis, where students remain on the surface of topics without thoroughly exploring broader connections or implications. Additionally, Acosta and Fuenmayor (2022) note that these students may overly rely on memorization instead of understanding concepts, limiting their ability to apply knowledge contextually.

For Alfaro-LeFevre (2021), a major weakness stemming from the lack of critical thinking development is the passive acceptance of information, where students adopt opinions without questioning or critically evaluating the validity of the information. This is tied to difficulties in logical argumentation, a fundamental skill of critical thinking that may be absent in those who have not fully developed it.

According to Lévano (2020), solving complex problems can also become a significant challenge for these students, as critical thinking is essential in situations that require analysis, evaluation, and informed decision-making. A lack of tolerance for ambiguity and poor self-assessment skills are additional weaknesses that hinder adaptation to challenging contexts and the identification of areas for improvement.

Furthermore, Acosta (2022) highlights that limited creativity can be a direct consequence of underdeveloped critical thinking, as this skill is intrinsically linked to the generation of innovative ideas. This suggests that these weaknesses negatively impact the educational experience and the students' potential for future success, underscoring the importance of actively fostering critical thinking development in the university environment.

Zarzar (2015) emphasizes that developing critical thinking in university students is essential because it promotes the ability to analyze, evaluate, and deeply understand information. This allows students not only to memorize facts but also to grasp the context and implications of the information they are studying, facilitating decision-making. Similarly, Altuve (2010) asserts that students who have developed critical thinking skills can examine different perspectives, evaluate evidence, and reach well-founded conclusions. This highlights the importance of critical thinking in academic settings and professional life, where decision-making based on careful analysis is fundamental.

According to Lévano Castro (2020), critical thinking strengthens the ability to solve problems creatively and effectively. Students who can think critically are skilled at identifying and addressing challenges innovatively, using strategies that go beyond simply memorizing solutions. In this regard, Lengua et al. (2020) suggests that, in the university context, where the diversity of ideas is crucial, critical thinking fosters meaningful dialogue and active participation in academic discussions. This enables students to analyze and question ideas, thus contributing to the enrichment of collective knowledge.

As Alfaro-LeFevre (2021) states, the development of critical thinking not only enhances academic performance but also prepares university students to face intellectual and professional challenges, promoting deeper learning and meaningful engagement in society. Based on the above, the objective of this study was to determine the relationship between artificial intelligence and the development of critical thinking in university students

The procedures used to achieve the study's objective followed the positivist paradigm with a quantitative approach, conceptualized by Acosta (2023) as a paradigm based on the numerical measurement of variables. This approach is used to describe, explain, predict, and control phenomena. Following this methodology, the study was classified as basic, as it aimed to improve scientific theories for better understanding and prediction of natural or other types of phenomena (Arias, 2016). The study reached a descriptive-correlational level, which, according to Hernández-Sampieri and Mendoza (2018), seeks to describe the characteristics, properties, or behaviors of a phenomenon or population without manipulating variables or establishing causal relationships. Furthermore, it measures the relationship between variables.

This approach focuses on observing, measuring, and classifying to provide a detailed and accurate representation of the reality being studied. Consequently, the study employed a non-experimental field design. According to Arias (2016), such studies observe phenomena to explain them without creating situations to modify them. As a field study, the data were collected in the location where the problem occurred—in this case, the University of Zulia.

The population consisted of 124 students from the Faculty of Education at the University of Zulia (LUZ). Convenience sampling was used for participant selection, defined by Arias (2016) as a non-probabilistic method employed to select participants based on their accessibility or availability. Participants were chosen because they were easily accessible or willing to participate in the study. The following criteria were applied for selection: students enrolled in the Faculty of Education, including both undergraduate and graduate programs; voluntary participation of those willing to contribute to the study; and consideration of the diversity of educational contexts and levels of technological competence.

It is noteworthy that the study prioritized ethical considerations, including obtaining informed consent from participants, protecting data privacy and confidentiality, ensuring equity and representativeness in sample selection, and minimizing potential risks. Data were collected using the survey technique, through a questionnaire administered virtually. The instrument consisted of 54 items divided into three dimensions, each with three indicators. The instrument was validated by five experts with doctoral degrees in education, and its reliability was assessed using Cronbach's Alpha coefficient, yielding a high reliability score of 0.988.

The data were processed using SPSS statistical software, version 27. Relative and percentage frequency tables were established during data analysis.

Below are the tables summarizing the information provided in the questionnaire to establish the results by dimension.

Table 1.
Critical Thinking Skills in University Students

Levels	Critical Analysis		Problem Solving		Effective Communication
	F	%	f	%	f	%
Low	92	74.1	72	58.0	81	65.3
Medium	19	15.3	27	21.7	33	26.6
High	13	10.4	26	20.9	10	8.0
Total	124	100,00	124	100.00	124	100.00

The data in Table 1 illustrates the results of critical thinking skills among university students. It shows that for critical analysis, the low level is predominant, with 74.1%, while 15.3% are at a medium level, and only 10.4% are at a high level.

Similarly, problem-solving reveals that 58.0% of students are at a low level, 21.7% at a medium level, and 20.9% at a high level. Regarding effective communication, 65.3% of students fall within the low level, 26.6% are at a medium level, and only 8.0% are at a high level.

These results indicate that the majority of participants exhibit low critical thinking skills, which poses challenges in several areas. Students struggle to identify and evaluate information, generate ideas and arguments, and solve problems. They also find it difficult to distinguish between factual and biased information, identify the strengths and weaknesses of an argument, and generate creative solutions to complex problems.

For problem-solving, students at the low level show difficulties in identifying and understanding problems, generating viable solutions, and evaluating and selecting the best solutions. This includes identifying contributing factors, generating practical solutions, and assessing the consequences.

In terms of effective communication, participants in the low level face challenges in expressing their ideas clearly and concisely, listening and understanding others, and building positive relationships in various contexts.

Table 2.
V Advantages of Implementing Artificial Intelligence

Levels	Personalized Learning		Immediate Feedback		Access to Diverse Resources
	F	%	f	%	f	%
Efficient	91	73.3	78	62.9	60	48.3
Moderate	22	17.7	30	24.1	60	48.3
Deficient	11	8.8	16	12.9	4	3.2
Total	124	100,00	124	100.00	124	100.00

Table 2 presents the results of the students’ evaluation of the advantages of implementing artificial intelligence. It highlights that a significant 73.3% of students consider AI’s ability to personalize learning as efficient. In contrast, 17.7% of students perceive this capability as moderate, while 8.8% evaluate it as deficient, reflecting diverse perspectives on this aspect.

For the Immediate Feedback indicator, 62.9% of students believe AI effectively provides this advantage, rating it as efficient. Another 24.1% place it at a moderate level, and 12.9% rate it as deficient. These results reveal a predominantly positive perception, though some variability in opinions persists.

Regarding the Access to Diverse Resources indicator, 48.3% of students classify it as efficient, while an equal 48.3% place it at a moderate level. Only a small 3.2% rate it as deficient. These data suggest an equitable distribution of opinions between efficiency and moderation, with a minority perceiving deficiencies in this area.

The analysis of these results reveals a generally positive perception of AI implementation in education. Most students value AI’s ability to personalize learning and provide immediate feedback. However, divergent opinions exist, especially regarding personalized learning, where a considerable percentage evaluate it as moderate or deficient. The balanced distribution of opinions regarding access to diverse resources indicates that this aspect may be perceived variably among students.

Overall, these findings underscore the importance of considering diverse perspectives when implementing technologies like artificial intelligence in educational settings.

Table 3.
Disadvantages of Implementing Artificial Intelligence

Levels	Lack of Human Interaction		Algorithm Bias		Development of Non-Technical Skills
	F	%	f	%	f	%
High	86	69.3	87	70.0	19	15.3
Moderate	11	8.8	21	16.9	77	62.0
Low	27	21.7	15	12.0	28	22.5
Total	124	100,00	124	100.00	124	100.00

Table 3 provides a detailed overview of participants' perceptions across three categories: Lack of Human Interaction, Algorithm Bias, and Development of Non-Technical Skills, broken down into low, medium, and high levels.

Regarding Lack of Human Interaction, 69.3% of participants at the low level express concern about this issue, highlighting it as a significant worry within this group. In contrast, the medium level shows less concern, with 8.8%, while the high level registers 21.7%, indicating an intermediate perception between the low and medium levels.

For Algorithm Bias, 70.0% of participants at the medium level believe that bias exists in algorithms, reflecting significant concern in this category. At the low level, 16.9% show concern about algorithmic bias, while 12.0% at the high level perceive bias in algorithms.

Regarding Development of Non-Technical Skills, 62.0% of participants at the medium level point to a deficiency in these skills, highlighting it as a considerable concern. At the low level, 15.3% express concern about the deficient development of non-technical skills, while 22.5% at the high level perceive this deficiency, indicating an intermediate concern between the low and medium levels.

Finally, the results suggest that participants express significant concerns regarding the lack of human interaction, algorithm bias, and the development of non-technical skills. These perceptions vary across levels, underscoring the importance of addressing these concerns specifically when implementing AI-related technologies.

Table 4.
Coefficient of Correlation of Variables

Coefficients               Variables			Artificial Intelligence	Critical Thinking
Spearman’s Rho	Artificial Intelligence	Correlation Coefficient	1,000	,898**
		Sig. (2-tailed)	.	,000
		N	124	124
	Critical Thinking	Correlation Coefficient	,898**	1,000
		Sig. (2-tailed)	,000	.
		N	124	124

Table 4 presents the results of the Spearman correlation coefficient calculation between the variables Artificial Intelligence and Critical Thinking.

In this case, the Spearman correlation coefficient is 0.898, which represents a very strong correlation. This indicates a significant and close positive relationship between the two variables. In other words, participants with high levels of Artificial Intelligence also tend to have high levels of Critical Thinking.

Regarding the p-value, which represents the probability that the correlation is due to chance, it is less than 0.001. This implies that it is highly unlikely that the correlation is a result of chance. Thus, there is a very strong relationship between Artificial Intelligence and Critical Thinking. Participants with high levels of Artificial Intelligence also tend to exhibit high levels of Critical Thinking.

Consequently, Artificial Intelligence can support students in developing their critical thinking skills. In this regard, AI can provide students with access to a vast amount of information, allowing them to enhance their research and analytical abilities. Additionally, AI can deliver personalized feedback on their work, helping them identify and correct errors.l.

The weaknesses observed regarding critical thinking skills in university students, specifically in Critical Analysis, Problem Solving, and Effective Communication, all categorized at a low level, suggest that these deficits significantly impact the development of critical thinking.

In terms of Critical Analysis, the lack of skills can limit the ability to evaluate information reflectively, identify biases, and discern between strong and weak arguments. This limitation affects students' capacity to form informed judgments, which is essential for critical thinking.

Zona and Giraldo (2017) argue that Problem Solving is fundamental to critical thinking, as it involves addressing challenges systematically and creatively. These weaknesses hinder the ability to identify contributing factors, generate viable solutions, and evaluate long-term implications, all of which are crucial for developing critical thinking.

Regarding Problem Solving, Ramón and Vílchez (2023) emphasize its importance in equipping individuals with the necessary skills to address challenges systematically and creatively. When facing complex problems, individuals develop the ability to identify contributing factors, generate practical solutions, and assess long-term implications. According to Boden (2017), this process strengthens critical thinking by engaging individuals in the active resolution of challenging situations.

In this context, Altuve (2010) highlights that personalized learning supports the development of critical thinking by tailoring education to students' individual needs. Ortega et al. (2021) note that allowing students to progress at their own pace and focus on specific areas of interest fosters autonomy and self-direction. This contributes to critical thinking by encouraging independent decision-making, identifying areas for personal improvement, and reflecting on the learning process.

Zarzar (2015) considers immediate feedback as an essential factor in the development of critical thinking. By providing students with prompt feedback on their performance, it enables the quick identification of strengths and areas for improvement, fostering self-reflection and continuous adaptation. In this regard, Jara and Ochoa (2020) assert that immediate feedback also helps students understand the consequences of their choices and adjust their approach, thereby contributing to the development of analysis and critical evaluation skills.

Similarly, Chrobak (2017) highlights that the ability to effectively address problems requires not only a structured approach but also innovative thinking, which is compromised when problem-solving skills are deficient. Such weaknesses negatively impact individuals' capacity to critically analyze and address complex, challenging situations.

Likewise, Effective Communication was also categorized at a low level, which hinders the development of critical thinking. According to Lara et al. (2017), this reveals that students struggle to express clear ideas and understand texts and speeches. Segovia et al. (2023) argue that the lack of communication skills hampers the articulation of strong arguments and effective interaction with others, which can negatively affect the critical thinking process.

The weaknesses observed regarding critical thinking skills in university students, specifically in Critical Analysis, Problem Solving, and Effective Communication, all categorized at a low level, suggest that these deficits significantly impact the development of critical thinking. 

In terms of Critical Analysis, the lack of skills can limit the ability to evaluate information reflectively, identify biases, and discern between strong and weak arguments. This limitation affects students' capacity to form informed judgments, which is essential for critical thinking. 

Zona and Giraldo (2017) argue that Problem Solving is fundamental to critical thinking, as it involves addressing challenges systematically and creatively. These weaknesses hinder the ability to identify contributing factors, generate viable solutions, and evaluate long-term implications, all of which are crucial for developing critical thinking. 

Regarding Problem Solving, Ramón and Vílchez (2023) emphasize its importance in equipping individuals with the necessary skills to address challenges systematically and creatively. When facing complex problems, individuals develop the ability to identify contributing factors, generate practical solutions, and assess long-term implications. According to Boden (2017), this process strengthens critical thinking by engaging individuals in the active resolution of challenging situations. 

In this context, Altuve (2010) highlights that personalized learning supports the development of critical thinking by tailoring education to students' individual needs. Ortega et al. (2021) note that allowing students to progress at their own pace and focus on specific areas of interest fosters autonomy and self-direction. This contributes to critical thinking by encouraging independent decision-making, identifying areas for personal improvement, and reflecting on the learning process. 

Zarzar (2015) considers immediate feedback as an essential factor in the development of critical thinking. By providing students with prompt feedback on their performance, it enables the quick identification of strengths and areas for improvement, fostering self-reflection and continuous adaptation. In this regard, Jara and Ochoa (2020) assert that immediate feedback also helps students understand the consequences of their choices and adjust their approach, thereby contributing to the development of analysis and critical evaluation skills. 

Similarly, Chrobak (2017) highlights that the ability to effectively address problems requires not only a structured approach but also innovative thinking, which is compromised when problem-solving skills are deficient. Such weaknesses negatively impact individuals' capacity to critically analyze and address complex, challenging situations. 

Likewise, Effective Communication was also categorized at a low level, which hinders the development of critical thinking. According to Lara et al. (2017), this reveals that students struggle to express clear ideas and understand texts and speeches. Segovia et al. (2023) argue that the lack of communication skills hampers the articulation of strong arguments and effective interaction with others, which can negatively affect the critical thinking process. 

Contribution to Knowledge
The scientific contribution of this study lies in exploring how artificial intelligence (AI) can be used to foster critical thinking rather than undermine it. Emphasis is placed on evaluating not the AI-generated responses themselves, but the critical analysis students perform on these responses, which can strengthen their critical thinking and information analysis skills. Additionally, the study reflects on the impact of AI on university students' personal learning environments, highlighting the need to understand the system's limitations and validate the accuracy of its use.

Limitations
The limitations of this study include the lack of in-depth exploration of other factors that may influence the development of critical thinking beyond AI, as well as the limited generalizability of the results due to the specific sample of university students from a single institution.

The results of the Spearman correlation analysis between the variables of artificial intelligence and critical thinking yield a significantly high coefficient of 0.898, indicating a very strong correlation between the two variables. This finding reveals a positive and close relationship between levels of AI use and levels of critical thinking among the participants. The strong association suggests that as levels of AI usage increase, critical thinking levels also rise within the studied sample.

This finding supports the notion that the effective incorporation and application of AI are positively linked to the development of critical thinking. The close relationship between these two variables highlights the importance of considering the influence of AI in fostering advanced cognitive skills, particularly those associated with critical thinking. This has significant implications for education and professional environments, where the integration of advanced technologies, such as AI, can enhance individuals' ability to address complex problems and make informed decisions.

It is important to note that this strong correlation does not necessarily imply a direct causal relationship. While there is a significant connection between AI and critical thinking, the exact direction of this relationship cannot be established solely through these results.

Conflict of Interest The author declares no conflict of interest.

Declaration of AI Use (IA): In this study, AI tools were used exclusively for language and grammar correction.

Author Contribution:
Puche-Villalobos, D. J.: Conceptualization, Formal Analysis, Methodology, Research, Supervision, Validation, Writing – Original Draft, Writing – Review, and Editing.