Exploring the Relationship Between Artificial Intelligence Awareness and Its Use Among Students: Cadi Ayyad University as A Case Study

Artificial Intelligence (AI) is revolutionizing higher education by providing advanced tools for learning and skill development. This study examines the relationship between AI awareness and its use among students at Cadi Ayyad University (UCA), Marrakesh, Morocco. Through a quantitative analysis of survey data from 370 respondents across various faculties, the study highlights the significant role of AI awareness in influencing students’ perceptions and adoption of AI tools, particularly in language learning. Findings unveil that the level of AI awareness among Cadi Ayyad university students is greatly higher, with approximately 74.9% of respondents expressing familiarity with AI concepts, 70.6% of them demonstrating an understanding of AI’s practical applications, and 56.4% of them acknowledging its limitations. More importantly, respondents with higher AI awareness are more likely to leverage AI applications for academic purposes, such as vocabulary building, writing assistance, and communication skills. However, gaps persist in understanding AI’s limitations and ethical implications. Therefore, the study advocates for targeted initiatives to enhance AI literacy, such as integrating AI education into curricula and providing access to advanced AI tools. These efforts are essential to maximize the benefits of AI in higher education and improve student learning outcomes.

Introduction

Artificial Intelligence (AI) has become an integral part of modern education, enabling personalized learning, intelligent tutoring systems, and advanced research tools. AI-powered platforms such as adaptive learning systems, virtual assistants, and automated grading tools have transformed how students engage with educational content and instructors (Luckinet al., 2016). Despite its growing prominence, the adoption of AI technologies among university students is not uniform. Awareness plays a pivotal role in shaping students’ willingness and ability to use AI tools effectively (Brynjolfsson & Mcafee, 2017).

AI awareness refers to an individual’s understanding of AI’s applications, capabilities, and limitations. Awareness influences perceptions of usability and relevance, which are critical factors in determining whether students integrate AI into their academic routines (Holmeset al., 2019). For instance, students who are familiar with AI-driven language models may leverage them for efficient essay drafting or language learning. Conversely, those lacking awareness may miss opportunities to enhance their learning experiences.

This study aims to examine the level of AI awareness and its impact on its use among students at Cadi Ayyad University, Marrakesh, Morocco. By identifying the underlying factors that shape AI awareness and adoption, the research seeks to provide actionable insights for fostering AI integration in higher education. It also highlights the importance of institutional initiatives in bridging knowledge gaps and ensuring equitable access to AI resources.

Background and Context

In the context of higher education, awareness often determines how students perceive AI as a resource for academic and professional growth. With AI’s growing influence across industries, students’ awareness of its applications has implications for their career readiness and competitiveness in the job market (Zhang & Aslan, 2021).

Digital literacy has long been recognized as a critical factor in shaping technology adoption, but AI awareness requires more than basic familiarity with technology. It demands an understanding of AI’s transformative potential in areas such as adaptive learning, natural language processing, and predictive analytics (Holmeset al., 2019). Students equipped with this knowledge are more likely to integrate AI tools into their academic routines, thereby improving their learning outcomes and research capabilities.

Recent studies highlight that the integration of AI into education is unevenly distributed, with disparities often linked to socio-economic factors, access to technology, and differences in academic disciplines (OECD, 2021). Science, technology, engineering and mathematics (STEM) students, for instance, are more likely to encounter AI through their coursework, whereas students in the humanities departments may have fewer opportunities for exposure. This divide underscores the need for targeted interventions to promote AI awareness across all disciplines.

At the University of Cadi Ayyad (UCA), fostering AI awareness is particularly critical given the university’s diverse student body and its emphasis on producing graduates capable of addressing global challenges. Increasing AI awareness among UCA students could unlock numerous opportunities for innovation, including the development of AI-driven solutions tailored to local and regional needs. Moreover, such efforts align with global trends in education, where institutions are increasingly prioritizing AI literacy as a core competency (Luckinet al., 2016).

Furthermore, AI awareness is integral to addressing the ethical and societal implications of AI. As AI becomes more embedded in daily life, students need to critically assess issues such as data privacy, algorithmic bias, and the potential for automation to disrupt job markets (Selwyn, 2019). By equipping students with a nuanced understanding of these challenges, universities can cultivate informed citizens capable of engaging with AI in a responsible and impactful manner.

The importance of AI awareness also extends to fostering creativity and entrepreneurship among students. Research indicates that exposure to AI can inspire innovative approaches to problem-solving, enabling students to design solutions that leverage AI technologies to address pressing societal issues (Brynjolfsson & Mcafee, 2017). For example, students in fields such as healthcare, agriculture, and environmental science can harness AI to develop tools for disease detection, precision farming, and climate modeling, respectively. By integrating AI awareness into the curriculum, UCA can position its students at the forefront of these transformative efforts.

Additionally, the relationship between AI awareness and its use is not static but evolves as students gain more exposure to AI technologies. Initial awareness often leads to curiosity, prompting students to explore AI tools independently or through structured learning experiences (Zawacki-Richteret al., 2019). Over time, this exploration fosters confidence, encouraging students to adopt AI more consistently in their academic and professional pursuits. This dynamic process highlights the importance of creating opportunities for hands-on engagement with AI tools, such as workshops, hackathons, and collaborative projects.

In conclusion, AI awareness is a multifaceted concept that encompasses knowledge, skills, and attitudes related to AI technologies. It serves as a critical enabler of educational and professional success, empowering students to navigate a rapidly digitizing world with confidence and competence. For UCA, investing in AI awareness initiatives represents a strategic priority that aligns with its mission to prepare graduates for the challenges and opportunities of the 21st century.

Literature Review

The increasing use of Artificial Intelligence (AI) in educational settings has generated considerable academic interest, resulting in an extensive body of literature that explores its pedagogical, ethical, and institutional ramifications. Researchers and educators are examining AI’s changing position in academia, uncovering both the potential advantages of AI-driven systems and the significant obstacles they provide.

AI Literacy and Awareness in Higher Education: A Multi-dimensional Need

AI awareness is the knowledge and comprehension of AI technologies together with their capabilities, constraints, and ethical consequences (Ng, 2016). Research on artificial intelligence literacy has found that adoption of technology in education is much influenced by it (Zawacki-Richteret al., 2019). The effective integration of artificial intelligence into higher education depends on knowledge of it since it helps teachers and students decide how best to employ AI tools and strategies (Holmeset al., 2022). Nevertheless, among teachers and students, artificial intelligence knowledge is still somewhat low, which might impede the acceptance of AI in education (Luckinet al., 2016).

Recent studies have investigated the several facets of AI awareness in higher education, including the degree of AI knowledge among students and educators, their opinions of AI, and their attitudes towards AI adoption (e.g., Al-Mutairiet al., 2023; du Boulayet al., 2022; Korolet al., 2022). These studies have shown that knowledge of artificial intelligence is about realizing the social, ethical, and pedagogical consequences of AI in education as much as about knowing the technical features of AI. For instance, teachers should be aware of the possible prejudices in AI algorithms and how AI affects student privacy (Houseset al., 2022). On the other hand, students must learn critical thinking abilities to grasp the limits of artificial intelligence and assess the material produced by AI systems (Luckinet al., 2016).

Additionally, other studies have highlighted the need for teaching artificial intelligence literacy among teachers and students (e.g., Al-Mutairiet al., 2023; du Boulayet al., 2022; Korolet al., 2022). AI literacy refers not only to technical knowledge of artificial intelligence but also the capacity for ethical and efficient use of AI tools. Within the context of higher education, AI literacy can enable teachers to create creative learning environments, customize lessons, and provide timely comments for students. AI literacy can also help students to become lifetime learners who can fit the evolving needs of the workforce in the age of artificial intelligence.

Hence, in order to successfully integrate artificial intelligence in higher education, a thorough understanding of AI is absolutely vital. Through several activities including seminars, training courses, and curriculum creation, higher education institutions must invest in raising awareness about artificial intelligence and AI literacy among teachers and students.

Global AI Adoption Trends among University Students

Emphasizing the link between artificial intelligence awareness and interaction with AI-based apps, recent research has disclosed global trends in AI acceptance among university students. Higher AI literate students are more likely to use AI-driven tools such language models, data analysis apps, and personalized learning systems (Selwyn, 2020). Suggesting that disciplinary background influences AI engagement levels, Hajam and Gahir (2024) confess that students specializing in scientific disciplines often have more favourable views towards AI than their counterparts in arts and business.

According to a report conducted by Hespress (2024), 75% of Moroccan university students believe that artificial intelligence is a useful instrument for improving the quality of their education. The survey also discloses that over 38% of teachers lack sufficient expertise in AI technologies, revealing a discrepancy between student excitement for artificial intelligence and faculty readiness to integrate it into the curriculum. Comparably, a research study that was conducted by the University of the Balearic Islands (2025) pinpoints how much Generation Z students depend on artificial intelligence for academic objectives, which affects their critical thinking and reading comprehension abilities. The report emphasizes how important it is for colleges to modify their curricula to address these new challenges.

These results show how increasingly university students all over are embracing artificial intelligence and the importance of raising AI literacy among teachers as well as among students. By means of focused training and curriculum development, closing these gaps will assist in guaranteeing the ethical and efficient use of artificial intelligence in higher education.

AI Adoption in Moroccan Higher Education

Artificial Intelligence (AI) is gradually being integrated into Moroccan higher education, transforming teaching methodologies, administrative processes, and student engagement. While AI adoption in Moroccan universities is still developing compared to global trends, several institutions are exploring its potential to enhance learning experiences and institutional efficiency.

According to Benaliet al. (2021), Moroccan universities have begun incorporating AI-powered tools such as adaptive learning platforms, intelligent tutoring systems, and automated grading solutions to support students and educators. These technologies help personalize learning pathways, particularly in STEM disciplines, by analyzing student progress and providing tailored recommendations. The use of AI-driven predictive analytics is also gaining traction, enabling institutions to identify at-risk students and implement early interventions to improve retention rates (El Mghari & Boulmakoul, 2022).

Likewise, Kettaniet al. (2020) underline the growing interest in AI-assisted e-learning platforms, particularly in response to the COVID-19 pandemic. During this period, Moroccan universities accelerated their adoption of digital and AI-enhanced learning tools, such as chatbots for student support and virtual assistants for administrative tasks. The Ministry of Higher Education, Scientific Research, and Innovation (2023) has since recognized the importance of AI in modernizing Moroccan higher education and has proposed strategic initiatives to integrate AI into university curricula and research.

As a matter of fact, AI plays a significant role in language learning and academic support. Bennani and Oubahssi (2022) find that AI-powered language processing tools, such as automated translation and intelligent writing assistants, are being used to improve students’ proficiency in French and English, which are key languages in higher education in Morocco. These tools also help bridge linguistic gaps for students transitioning from Arabic-based education to French- or English-medium university programs.

Despite its benefits, there are numerous challenges that still hinder the full-scale adoption of AI in Moroccan tertiary education. Limited infrastructure, digital literacy gaps, and concerns over data privacy pose significant barriers (El Khatibet al., 2021). Additionally, Bouhorma and Touzani (2020) underline the importance of developing local AI expertise through specialized training programs and research collaborations with international institutions. Addressing these barriers requires increased investment in AI education, stronger institutional policies, and a collaborative approach between universities, policymakers, and technology providers.

Challenges of AI Adoption

Although artificial intelligence has significant potential in both teaching and learning, university students encounter many obstacles in using it. These challenges can be sorted out into three major stands.

Lack of Understanding and Training

Many students are ignorant of artificial intelligence due to inadequate curricular exposure and structured AI education campaigns (Zawacki-Richteret al., 2019). Though they often use AI-driven applications, students seldom identify them as such (Nget al., 2024). AI literacy is limited, as most colleges provide only computer science courses; consequently, AI is not taught elsewhere. Lack of faculty training means that teachers might not be able to assist students (Garciaet al., 2021). Universities should train faculty and run artificial intelligence literacy initiatives in many disciplines.

Technological Challenges

In disadvantaged areas, inadequate infrastructure, outdated technologies, and poor internet connectivity restrict artificial intelligence tool availability (Vesnaet al., 2024). These limitations not only hinder the implementation of AI-driven educational solutions but also exacerbate existing inequalities in access to quality learning experiences (Selwyn, 2020). While cloud-based AI solutions have the potential to mitigate some of these challenges, their functionality heavily relies on consistent internet access and robust institutional support (Hwanget al., 2020). Without these foundational elements, the benefits of AI technologies remain out of reach for many students in low-income communities (Warschauer & Matuchniak, 2010). Overcoming these limitations calls for institutional technological collaborations, cheap digital tools, and infrastructure geared for artificial intelligence.

Reluctance to Change

Some staff members and students oppose AI implementation because of worries about AI replacing instructors, altering instructional strategies, and declining individualized learning (Adams & Brown, 2023). Concerns about errors or prejudice also lead students against AI-driven grading and feedback systems (Binns, 2021; Williamson & Eynon, 2020). Faculty have concerns about employment loss and the difficulties of artificial intelligence in the classroom (Holmeset al., 2021). Universities should be open about their implementation of artificial intelligence, present it as a complementing tool, and provide professional development to foster trust and engagement (Kim & Park, 2020). Ultimately, though lack of information and training, technological restrictions, and resistance to change impede its acceptance, artificial intelligence might improve higher education. Solving these challenges calls for trust-building, infrastructure improvements, and AI literacy. As artificial intelligence expands, proactive actions are required to ensure fair and effective integration at institutions.

Benefits of AI Integration in Moroccan Higher Education

AI has demonstrated significant potential to address challenges in Moroccan higher education while fostering innovation and efficiency. The integration of AI technologies has transformed various aspects of learning, research, and accessibility, paving the way for a more inclusive and effective academic environment.

Personalized Learning

AI technologies, particularly machine learning (ML) algorithms and large language models (LLMs), facilitate adaptive learning systems tailored to individual student needs. By analyzing learning patterns, AI customizes resources, adjusts curricula, and provides targeted feedback. According to a recent study, “AI-powered adaptive learning platforms significantly improve student engagement and learning outcomes by offering tailored content and real-time assistance” (Asmara, 2024, p. 1571). Additionally, AI-driven tutoring systems such as intelligent chatbots assist students by answering questions and providing explanations. Research suggests that “AI chatbots enhance students’ comprehension and academic performance by offering 24/7 personalized support” (Kumar & Zhang, 2024). These innovations are crucial for addressing educational disparities and ensuring that students receive personalized academic support.

Enhanced Research Capabilities

AI-driven tools have revolutionized academic research by automating data analysis, streamlining literature reviews, and facilitating interdisciplinary collaboration. A research study on AI highlights that “Natural language processing algorithms can process vast amounts of academic literature, summarizing key findings in seconds and allowing researchers to focus on interpretation rather than data gathering” (Smithet al., 2024). AI also enables predictive modeling and simulations, providing researchers with precise tools for testing hypotheses. As noted in a recent publication, “AI accelerates the research process by reducing manual workload, thereby increasing efficiency and the rate of scientific discoveries” (Lee & Patel, 2023). By integrating AI into research methodologies, Moroccan universities can enhance their global academic competitiveness.

Inclusive Education

AI technologies are making higher education more accessible to students with disabilities. Speech recognition software and natural language processing tools enable real-time transcription of lectures, assisting students with hearing impairments. A study on AI and inclusivity states, “AI-powered transcription tools have significantly improved accessibility in higher education, providing students with disabilities equal opportunities to engage in academic discourse” (Williams & Chen, 2023). Furthermore, text-to-speech applications support visually impaired students, while AI-driven translation tools help non-native speakers navigate language barriers. According to recent research, AI translation software has created more inclusive classrooms by allowing students from diverse linguistic backgrounds to participate fully in lectures (Garciaet al., 2024). These advancements contribute to a more equitable learning environment for all students.

Overall, AI integration in Moroccan higher education offers transformative benefits by personalizing learning experiences, enhancing research efficiency, and fostering inclusivity. However, to maximize these advantages, institutions must address challenges such as ethical concerns, data privacy issues, and faculty training. As one study cautions, “The successful implementation of AI in education depends not only on technological advancements but also on ethical considerations and adequate teacher preparation” (Johnson & Ahmed, 2024). By strategically adopting AI-driven solutions, Moroccan universities can create a more dynamic and student-centered educational ecosystem.

Factors Influencing AI Use

Several studies have explored the correlation between AI awareness and its adoption among students, highlighting multiple factors that shape students’ willingness and ability to engage with AI-powered educational tools. These factors range from individual competencies and perceptions to institutional and ethical considerations.

Digital Literacy

Students with higher levels of digital literacy tend to be more comfortable at using AI applications, as they possess the necessary technical skills and confidence to navigate AI-driven platforms. Leeet al. (2019) argue that digital fluency, which encompasses the ability to critically assess and interact with digital technologies, is a strong predictor of AI adoption. Similarly, Nget al. (2024) underline that students who frequently engage with digital tools, such as coding environments, online learning platforms, and data-driven applications, are more likely to integrate AI into their academic routines. Moreover, Hwanget al. (2020) suggest that digital literacy training should be embedded into university curricula to enhance students’ readiness for AI adoption.

Perceived Usefulness

The extent to which students believe AI tools can enhance their learning experience significantly impacts their adoption. Kim & Park (2020) highlight that perceived usefulness is one of the strongest motivators for students to engage with AI-driven learning systems, such as intelligent tutoring systems and automated feedback tools. Research by Daviset al. (2021), based on the Technology Acceptance Model (TAM), further supports this claim, suggesting that students who recognize the efficiency and convenience of AI-powered tools are more likely to adopt them in their studies. Additionally, Chenet al. (2022) emphasize that awareness campaigns showcasing AI’s practical benefits—such as personalized learning and academic performance tracking—can positively influence students’ perceptions and increase adoption rates.

Institutional Support

Universities play a crucial role in fostering AI adoption by integrating AI training into their curricula and providing access to AI-related resources. Garciaet al. (2021) highlight that institutions with dedicated AI courses, workshops, and digital learning centers significantly boost student engagement with AI technologies. Zawacki-Richteret al. (2019) further argue that access to AI-powered educational tools, such as adaptive learning platforms and AI-driven research assistants, can enhance students’ academic experiences. Moreover, Luckinet al. (2018) advocate for faculty training in AI literacy, ensuring that educators can effectively guide students in utilizing AI applications.

Ethical Concerns

Despite AI’s potential benefits, some students hesitate to use AI due to concerns about data privacy, algorithmic bias, and ethical implications. Johnson and Williams (2022) find that students often express apprehension about how AI systems handle personal data, particularly in AI-driven assessment tools. Williamson and Eynon (2020) further emphasize the importance of transparency in AI technologies used in education, as students are more likely to trust AI systems when they understand how data is collected and processed. In addition, Binns (2021) highlight concerns regarding AI bias, where students fear that AI algorithms may reinforce existing inequalities in grading and academic evaluation. Addressing these ethical concerns through clear policies and AI literacy programs is essential for fostering responsible AI adoption.

Objectives of the Study

This study seeks to:

1. Assess the level of AI awareness among Cadi Ayyad university (CAU) students, including their understanding of AI applications, ethical considerations, and academic relevance.

2. Examine the extent to which CAU students use AI tools for academic purposes, particularly in language learning.

3. Analyze the correlation between AI awareness and AI use.

Research Questions

Three key research questions guide this study:

RQ 1: What is the level of AI awareness among CAU students?

RQ 2: To what extent do CAU students utilize AI tools for academic and language learning purposes?

RQ 3: Is there a significant relationship between students’ awareness of AI and their frequency of using AI tools?

Hypotheses

H_a1: The level of AI awareness among CAU students is limited, with varying degrees of understanding regarding AI applications, ethical considerations, and its academic relevance, depending on their field of study and prior exposure to AI concepts.

H_a2: Higher AI awareness is positively correlated with increased use of AI tools among CAU students.

H₀3: There is no significant relationship between AI awareness and the use of AI tools among CAU students.

Methodology

Research Design

This research study employs a quantitative approach to investigate the correlation between AI awareness and the use of AI tools among students at Cadi A/yyad University, Marrakesh, Morocco. We use a descriptive-correlational approach to ascertain students’ awareness of AI technologies, their frequency of use, and any potential correlation between these factors. A standardised survey collects data, allowing statistical analysis to identify patterns and relationships. According to Creswell (2014), quantitative research allows for objective measurement and statistical analysis, making it suitable for identifying trends and relationships between variables. This approach ensures impartiality and facilitates a comprehensive understanding of AI adoption trends in education. On top of that, it yields measurable findings that can guide efforts for improving AI literacy and incorporation in tertiary education.

Population

The study is based on a questionnaire administered to undergraduate, graduate, and postgraduate students who are enrolled in various faculties at Cadi Ayyad University, Marrakesh, Morocco. A total of 370 respondents completed the Google Form.

Instrument

The current study relies primarily on a questionnaire distributed via email addresses and WhatsApp groups. The questionnaire was first sent to professors from each faculty. It was then forwarded to class delegates of their classes, who subsequently shared it with their classmates. The questionnaire, developed using Google From, comprises 21 closed-ended questions designed to match the study’s research requirements. It is divided into four sections: Demographics, Awareness of Artificial Intelligence (AI), Use of AI Tools, and Correlation Between Awareness and Use. This structured approach allowed the researcher to analyze participants’ responses quantitatively, ensuring a numerically clear, objective, and well-organized understanding of the study’s findings.

Procedure

The research adheres to a rigorous methodological framework to ensure a systematic data gathering and analysis. A survey questionnaire was meticulously designed in accordance with the research objectives and was reviewed and approved by my supervisor and co-supervisor before being administered to participants. Additionally, stratified random sampling techniques are employed to guarantee a representative sample, categorizing the target population into strata according to academic level and faculty affiliation. This approach facilitates a diverse representation of disciplines across Cadi Ayyad University, thereby enhancing the generalizability of the findings.

The questionnaire was disseminated through online platforms, ensuring anonymous participation to uphold respondents’ confidentiality. Following data collection, the dataset underwent a rigorous process of cleaning, coding, and statistical analysis, enabling the identification of underlying patterns and correlations.

Results and Discussion

Demographics

Table I presents the demographic characteristics of the survey participants across four categories: gender, institutional affiliation, age, and year of study. As for the gender distribution, 66.4% of the respondents are male and 33.6% are female. In terms of institutional affiliation, the majority of participants (49%) are enrolled in the Faculty of Letters and Human Sciences, followed by 18.4% from the Faculty of Law, Economics, and Social Sciences; 10.1% from the Higher School of Teachers; 8.1% from the National School of Applied Sciences; 7.5% from the Faculty of Medicine and Pharmacy; 4.3% from the Faculty of Sciences; and 2.6% from the Faculty of Sciences and Technology. The age distribution reveals that 85% of participants are between 20 and 25 years old, while 6.1% are aged 25–30, 2.1% are 30–35, 2% are 35–40, and 3.2% are over 40. Regarding academic level, 29.6% of respondents are in their first year, 27.4% in the second year, 20.3% in the third year, 13.7% in the fourth year, 8.2% in the fifth year, and only 0.8% are in the sixth year. This distribution highlights a sample predominantly composed of young, early-year students, mostly from the humanities.

Table I. Demographic Characteristics of the Respondents

Parameter	Percentage
Gender
Male	66.4%
Female	33.6%
Institution’s name
Faculty of Letters and Human Sciences	49%
Faculty of Medicine and Pharmacy	7.5%
Faculty of Sciences	4.3%
Faculty of Sciences and Technology	2.6%
Faculty of Law, Economics, and Social Sciences	18.4%
National School of Applied Sciences	8.1%
Higher School of Teachers	10.1%
Age
20–25	85%
25–30	6.1%
30–35	2.1%
35–40	2%
Over 40	3.2%
Year of study
1st year	29.6%
2nd year	27.4%
3rd year	20.3%
4th year	13.7%
5th year	8.2%
6th year	0.8%

Awareness of Artificial Intelligence (AI)

Table II illustrates the level of familiarity with the concept of Artificial Intelligence (AI) among the respondents. The majority (46.4%) agree that they are familiar with AI, while 28.8% strongly agree, indicating that approximately 75.2% of participants have some level of understanding of AI. Additionally, 18.7% remain neutral, suggesting that they may have heard about AI, but do not feel confident in their knowledge. A minimal percentage of respondents disagree (3.8%) or strongly disagree (2.2%), highlighting that only a few individuals are unfamiliar with AI. These findings suggest a high level of AI awareness, which is likely attributed to its increasing presence in education and industry. However, the neutral responses indicate a potential need for further AI education and awareness programs to enhance understanding.

Table II. The Participants’ Level of Familiarity with the Concept of Artificial Intelligence

Statement	Answer
	Strongly agree	Agree	Neutral	Disagree	Strongly disagree
I am familiar with the concept of Artificial Intelligence	28.4%	46.5%	18.9%	3.9%	2.2%
I understand how AI is used in everyday applications	24%	47%	20.4%	6.4%	2.2%
I have learned about AI through reliable sources such as university courses, online platforms, or workshops	34.3%	42.3%	29.1%	18%	10.5%
I understand how AI tools function and their capabilities in academic contexts	7.8%	47.3%	24.4%	12%	8.4%
I am aware of the limitations of AI tools	13.9%	42.5%	27.2%	13.9%	2.5%
I feel confident identifying AI-based tools and technologies in my field of study or daily life	6.5%	39.8%	29%	15.6%	9.1%
I am aware of ethical issues associated with using AI tools, such as plagiarism or data security	17.7%	42.7%	25.4%	10.5%	3.7%

As for respondents’ understanding of how AI is used in everyday applications such as chatbots, virtual assistants, and recommendation systems, the majority (47%) agree that they understand AI’s practical applications, while 24% strongly agree, indicating that approximately 71% of respondents have a good grasp of AI’s role in daily life. Additionally, 20.4% remain neutral, suggesting a moderate awareness but possible uncertainty about AI’s specific applications. A small percentage of respondents disagree (6.4%) or strongly disagree (2.2%), indicating a limited understanding among a minority of participants. These results suggest that while AI awareness is generally high, there is still room for educational initiatives to improve comprehension, particularly in real-world AI applications.

Investigation targeted the sources through which respondents have learned about AI, specifically from reliable sources such as university courses, online platforms, or workshops. The largest proportion (34.3%) agree that they have gained AI knowledge from such sources, while 8% strongly agree, totalling 42.3% of respondents who have received structured AI education. However, a significant portion (29.1%) remain neutral, indicating that they may have some exposure but not necessarily from formal or structured learning environments. On the other hand, 18% disagree and 10.5% strongly disagree, suggesting that nearly 28.5% of respondents have not accessed AI knowledge through reliable educational sources. These findings highlight that while many respondents have engaged with AI learning through credible channels, a considerable portion either lacks formal exposure or relies on informal sources. This implies a potential need for greater accessibility to AI education through academic programs, workshops, or online courses.

The survey findings expose different degrees of knowledge about the usefulness and possibilities of artificial intelligence systems in educational environments. While 7.8% of respondents strongly agree, 47.3% agree, this indicates more than half (55.1%) hold a positive perception of their knowledge of artificial intelligence in education. Still, a considerable number (24.4%) stay neutral, implying doubt or lack of trust in their expertise. In parallel, 12% disagree and 8.4% strongly disagree, suggesting that about 20.4% of the respondents find it difficult to grasp AI tools in academic environments.

These results indicate that although academic awareness of artificial intelligence is very strong, a good number of students or teachers might not have more in-depth understanding of its useful relevance. The prevalence of neutral and opposing answers emphasises the necessity of more organised AI education, practical training, and exposure to AI-driven academic tools to close the knowledge gap and improve AI literacy in educational contexts.

The survey results figure out differing levels of awareness regarding the limitations of AI tools. A majority (42.5%) agree, while 13.9% strongly agree, indicating that 56.4% of participants acknowledge AI’s limitations to some extent. However, a notable portion (27.2%) remain neutral. This states that more than a quarter of respondents may have limited knowledge or are uncertain about the specific constraints of AI. Additionally, 13.9% disagree, and 2.5% strongly disagree, totaling 16.4% who do not fully recognize AI’s limitations.

These results imply that while most respondents have some level of awareness, a significant number either lack confidence in their understanding or do not perceive AI’s limitations as a major concern. The presence of neutral and disagreeing responses highlights the need for more discussions, case studies, or educational initiatives focusing on AI’s biases, ethical concerns, and technical constraints to foster a more comprehensive understanding.

The results reveal varying levels of confidence in identifying AI-based tools and technologies in their field of study or daily life. A moderate majority (39.8%) agree, while only 6.5% strongly agree, suggesting that 46.3% of participants feel confident in recognizing AI-based technologies. However, a notable portion (29%) remain neutral, suggesting that many respondents have some awareness but may lack certainty or practical experience in identifying AI tools. On the other hand, 15.6% disagree, and 9.1% strongly disagree, meaning that 24.7% of respondents lack confidence in distinguishing AI-based tools in their academic or everyday contexts.

These findings suggest that while nearly half of the respondents feel capable of identifying AI technologies, a significant proportion remains uncertain or lacks confidence in this area. The high neutrality rate, along with the one-fourth of respondents expressing disagreement, highlights the need for more exposure, hands-on experience, or educational initiatives to enhance AI literacy and ensure individuals can confidently recognize and utilize AI-driven tools in their respective fields.

The responses to the statement “I am aware of ethical issues associated with using AI tools, such as plagiarism or data security indicate that most repliers (60.4%) are aware of these ethical concerns, with 17.7% strongly agreeing and 42.7% agreeing. However, a quarter (25.4%) remain neutral, suggesting some uncertainty or indifference, while 14.2% disagree or strongly disagree, indicating a lack of awareness or concern. Overall, the data shows a general awareness of ethical issues but highlights the need for further education to address the gaps in understanding among some respondents.

Use of AI Tools

As shown in Fig. 1, the majority of respondents (87.4%) use AI tools for language learning to varying degrees, with 15.8% using them always, 24.4% usually, and 17.5% often. However, a larger portion (29.7%) uses them only sometimes, indicating less frequent engagement. A smaller percentage (12.6%) rarely or never use AI tools for language learning. This suggests that while AI tools are commonly used in language learning, their frequency of use varies, and there remains a portion of users who engage with them either less regularly or not at all.

Fig. 1. Frequency of AI tools-Use for language learning.

Regarding the AI tools used by the participants, Fig. 2 shows that ChatGPT is the most widely used tool with 77.7%, followed by Rosetta Stone (51.3%) and Duolingo (44.8%), showing a strong preference for language learning applications. Grammarly is used by 29.2%, indicating interest in writing support, while Gemini (29%) and Microsoft Translator (22.3%) have lower usage, suggesting more niche or specialized applications. Additionally, 14.2% of respondents use other AI tools, pointing to a variety of lesser-known tools in use. Overall, the data shows a significant focus on language learning and general AI tools for educational purposes.

Fig. 2. Participants’ use of AI tools in education.

Concerning AI-powered tools incorporation in language learning, as shown in Fig. 3, the most common application is vocabulary building (59%), indicating that learners heavily rely on AI for expanding their lexical knowledge through interactive exercises and contextual suggestions. Additionally, writing assistance (48.2%), grammar improvement (44.1%), and speaking and communication skills (45.5%) reflect a strong demand for AI-driven support in refining written and spoken proficiency. However, the relatively lower usage of AI tools for reading (34%) and listening comprehension (36.8%) suggests that either traditional learning methods remain dominant in these areas or AI tools have yet to offer equally effective solutions. Furthermore, pronunciation practice (39.6%) and problem-solving (37.1%) indicate a growing interest in AI’s ability to enhance speech accuracy and tackle linguistic challenges. While AI tools clearly play a crucial role in various aspects of language learning, the disparity in usage across different skills suggests that their effectiveness and adoption vary, highlighting the need for further improvements in AI-driven reading and listening comprehension support.

Fig. 3. Participants’ use of AI tools for language learning purposes.

As far as the impact of AI tools on language proficiency is concerned, Fig. 4 divulges the fact that AI tools have had a predominantly positive impact on language proficiency, with 65.1% of respondents (17.8% Strongly Agree and 47.4% Agree) acknowledging their benefits. This emphasizes that AI tools effectively support language learning through personalized feedback, grammar correction, and vocabulary enhancement. However, a notable 26.2% remain neutral. This indicates that while AI tools may offer potential benefits, they do not significantly impact all learners equally. This neutrality could stem from factors such as varied usage patterns, differing proficiency levels, or a preference for traditional learning methods. Additionally, 6.6% of respondents disagree, and 2% strongly disagree, suggesting that for a small minority, AI tools may not be effective due to factors such as lack of engagement, inadequate tool functionality, or reliance on more conventional learning strategies. While the overall perception is positive, the presence of neutral and negative responses highlights the need for further exploration into optimizing AI-driven language learning for diverse learners.

Fig. 4. Participants’ perceptions of AI’s impact on their language skills.

As for the respondents’ satisfaction with AI tools, as illustrated in Fig. 5, 70.7% of respondents express satisfaction (53.1% satisfied and 17.6% very satisfied). This conveys that AI tools generally meet the user’s expectations and provide value. However, a notable portion (20.9%) remain neutral, implying that while these tools are functional, they may not be exceeding expectations or significantly enhancing user experience. More critically, a small yet notable proportion of respondents reported dissatisfaction, highlighting the need for further investigation into the specific challenges users face. Factors such as usability, accuracy, and accessibility could contribute to this dissatisfaction, suggesting potential areas for improvement. While the overall sentiment leans positively, the presence of neutral and dissatisfied users underscores the importance of continuous refinement and adaptation to ensure that AI tools maximize their effectiveness and user engagement.

Fig. 5. Participants’ satisfaction with AI tools for educational use.

Correlation Between Awareness and Use

The relationship between AI awareness and its use presents a nuanced dynamic, as reflected in the survey responses. As illustrated in Table III, 48.4% of respondents (37.7% Agree and 10.7% Strongly Agree) posit that greater awareness leads to increased AI adoption, while 33.2% remain neutral, indicating uncertainty about this correlation. This suggests that while knowledge of AI tools may be a necessary factor for adoption, it is not always sufficient to ensure their use. Additionally, 18.3% (11% Disagree and 7% Strongly Disagree) challenge the assumption that awareness alone influences AI integration, implying that other factors, such as accessibility, perceived usefulness, and personal motivation, play a more decisive role. The presence of a substantial neutral stance further highlights that awareness does not necessarily translate into engagement, possibly due to a lack of practical exposure or scepticism regarding AI’s effectiveness. Hence, while awareness is an important step, it must be accompanied by strategies that enhance usability, demonstrate tangible benefits, and address potential barriers to adoption to ensure meaningful integration of AI tools in learning environments.

Table III. Participants’ Beliefs about the Role of Awareness in AI Adoption

Answer	Percentage
Strongly agree	10.7%
Agree	37.7%
Neutral	33.2%
Disagree	11%
Strongly disagree	7.3%

Regarding factors that could enhance respondents’ use of AI tools, as demonstrated in Table IV, the data reveals that university-organized training programs (33.5%) and more accessible tools (28.7%) are seen as the most significant factors in increasing awareness and use of AI. This demonstrates that respondents presume that hands-on, structured learning environments, facilitated by their institutions, play a crucial role in fostering AI adoption. The incorporation of AI into the curriculum (21%) also emerges as an important factor, indicating that integrating AI into formal education can upgrade its accessibility and relevance. However, peer learning groups (8%) and other factors (8.8%) seem to have a less pronounced impact on the overall awareness and use of AI, which may highlight the limited scope of informal learning and external influences compared to institutional support. This data underscores the necessity for universities to not only provide access to AI tools but also to design comprehensive training programs that encourage engagement and understanding. This affirms that AI’s potential is fully realized in educational contexts.

Table IV. Factors that could Encourage Increased use of AI Tools

Answer	Percentage
More accessible tools	28.7%
University-organized training programs	33.5%
Incorporation of AI into the curriculum	21%
Peer learning groups	8%
Other	8.8%

In reference to whether respondents would recommend AI tools or not, the outcomes indicate that more than a half of respondents (54.6%) show interest to recommend AI tools to their peers, reflecting a generally positive perception. However, there is still a significant portion (36.8%) who remain uncertain whether to recommend it or not. This ambivalence may stem from limited exposure to AI tools or concerns about their effectiveness and potential drawbacks. The relatively low percentage of respondents (8.6%) who would not recommend AI tools suggests that negative attitudes are not widespread, but this group’s reservations could highlight issues such as lack of understanding, trust, or practical experience. Broadly, while AI tools are gaining acceptance, the uncertainty among a third of respondents points to the need for more comprehensive training and awareness campaigns to address concerns and build greater confidence in their use.

As for the respondents’ perceptions on how their university can enhance their awareness of AI tools, Table V showcases various key strategies that can be espoused in this regard. Notably, 66.8% of respondents identify free access to premium AI tools as the most effective approach to achieve it. This indicates that access to high-quality resources is a major barrier to AI engagement, and offering free tools could significantly boost their interaction with AI technologies. In the same vein, 44.3% of respondents opt for hosting workshops and seminars as considerable support, reflecting a desire for interactive, hands-on learning opportunities that go beyond traditional classroom settings. However, 49.4% of participants point to introducing AI-focused courses, while 29.8% suggest a need for formal education and integration of AI into academic programs. This could underline the fact that while repliers see the importance of AI in specific courses, they also recognize the need for AI to be embedded across various disciplines. The relatively low percentage for “Other” (9.7%) insinuates that while there are alternative ideas, the most effective strategies for increasing AI awareness are centered around access to tools, formal education, and interactive events.

Table V. Strategies to Promote AI Awareness and Usage among Students at Cadi Ayyad University

Answer	Percentage
Hosting workshops and seminars	44.3%
Proving free access to premium AI tools	66.8%
Introducing AI-focused courses	49.4%
Incorporating AI in curriculum	29.8%
Other	9.7%

Conclusion

The ultimate goal of this study is to examine the impact of AI awareness on its use among students at the level of Cadi Ayyad University, Marrakesh, Morocco. To achieve this end goal, a quantitative approach is adopted. Interestingly, the study’s findings reveal that respondents possess a higher level of AI awareness, with approximately 74.9% expressing familiarity with AI concepts, 70.6% demonstrating an understanding of AI’s practical applications, and 56.4% acknowledging its limitations. However, a notable proportion of respondents remain neutral or uncertain about AI’s ethical implications, practical relevance, and academic applications, indicating the need for further structured AI education.

As for AI adoption, the study discloses that the majority of respondents (87.3%) report using AI tools for language learning, with ChatGPT (78.5%) and Rosetta Stone (50.7%) being the most used platforms. Fascinatingly, AI tools are primarily employed for vocabulary building (59.2%), writing assistance (48.2%), and speaking and communication skills (45.6%), though usage for reading and listening comprehension remains lower. This points to potential gaps that could be addressed through more tailored AI-driven language learning solutions.

Furthermore, respondents acknowledge that AI tools have positively impacted their language proficiency, with 65.1% of respondents recognizing their benefits and 70.7% reporting satisfaction with AI tools, indicating their perceived effectiveness and usefulness. However, the presence of neutral and dissatisfied respondents suggests areas for improvement in usability, accessibility, and integration within educational curricula.

Regarding the correlation between AI awareness and its use, 48.4% of respondents reckon that awareness drives adoption, yet 33.2% remain neutral. This implies that there are additional factors, such as accessibility, and perceived usefulness, that influence students’ engagement with AI. To address these challenges and enhance both AI Awareness and adoption, effective strategies such as university-organized training programs and increased access to AI tools are recommended.

By and large, this study underscores the potential of AI tools in education while identifying gaps in awareness, accessibility, and application. To maximize AI’s impact, universities should implement structured training programs, integrate AI into curricula, and improve access to premium AI tools. These steps will bridge the knowledge gap, enhance AI literacy, and promote its effective integration into academic environments, ultimately improving learning outcomes for students.

Limitations

Despite the valuable insights provided by this study, several limitations must be acknowledged. First, the sample, though comprising 370 students, may not fully represent the entire student body at Cadi Ayyad University, particularly those with limited exposure to AI tools. The study also focuses primarily on widely recognized AI tools such as ChatGPT and Rosetta Stone, potentially overlooking the impact of emerging or less commonly used AI applications. Furthermore, the cross-sectional nature of the research captures only a single point in time, preventing an assessment of long-term trends in AI adoption and its evolving role in language learning. Contextual factors, such as institutional AI policies and technological access disparities, may also influence findings, limiting their generalizability to other instructional settings. Last but not least, external influences such as prior exposure to AI outside academic environments and socio-economic differences, were not explicitly controlled, which may have affected students’ responses. Being aware of these limitations underscores the need for further research with broader sampling, longitudinal analysis, and deeper exploration of contextual and external factors shaping AI adoption in education.

Recommendations and Future Perspectives

To address the identified gaps and maximize the benefits of AI in language learning, several strategic recommendations should be considered. First and foremost, universities should implement structured AI training programs to enhance students' awareness and understanding of AI’s applications and ethical considerations. Integrating AI literacy into the curriculum through workshops, seminars, and specialized courses can ensure a more comprehensive and informed adoption of AI tools. Moreover, improving accessibility to AI platforms, particularly premium and diverse language-learning applications, can help bridge the digital divide and provide equal learning opportunities for all students. Given the influence of external factors on AI engagement, future research should explore the impact of socio-economic backgrounds, prior AI exposure, and institutional policies to develop tailored AI integration strategies. Furthermore, conducting longitudinal studies will be essential to tracking AI adoption trends over time and assessing its sustained impact on language proficiency. Universities should also encourage interdisciplinary collaboration between AI developers, educators, and linguists to refine AI tools for more effective educational applications. By implementing these measures, academic institutions can foster a more inclusive and optimized AI-driven learning environment, ultimately improving language acquisition and overall student outcomes.