Adopting AI for teaching english to university students

INTRODUCTION

The use of artificial intelligence (AI) has affected most areas of society. Camastra and González (2025) highlight its importance in environmental sustainability, an example where its impact can be seen, although it is not the only one. In the field of education, its applications are increasingly diverse and accepted by teachers, students, researchers, and administrative staff. Specifically, in language teaching, there are trends that demonstrate how AI has been integrated. During the COVID-19 lockdown, many teachers and students turned to these tools to continue teaching or learning (Lepez, 2021).

English, like other languages, has become widespread; therefore, there is demand for its teaching from various fronts, not only in the school context but also in extracurricular settings. In this context, AI facilitates personalized learning (Kohnke et al., 2025). This literature review discusses the most widely used trends in AI-supported English instruction for university students.

In general, one of these trends is the use of platforms that allow the pace of learning and the content to be adapted to the student’s level on the basis of their progress. These platforms identify mastered skills and areas of strength, as well as those where performance is lower; in this way, they design activities that enable the student to achieve the proposed objectives. Goulart et al. (2024) conducted an interesting analysis on the importance of developing writing skills among students and highlighted the use of AI. Some of these platforms or tools include Duolingo for Schools and ChatGPT, which complement classroom instruction.

Another trend is the implementation of virtual assistants and chatbots, which allow for interaction with students, generate dialogs, help students practice oral communication, and improve fluency and confidence. Applications such as Replika or voice assistants are used. Jamboard, another AI-based tool that for a long time facilitated the creation of interactive slides, made it easier to create graphics, incorporate images, drawings, and notes, and served as a teaching tool (Dávila et al., 2024).

Automated assessment is also noteworthy, as it identifies acquired skills and those requiring further practice. This type of assessment allows direct and instant feedback. The Moodle platform has been widely used, although others, such as Grammarly and Turnitin, correct written texts and determine the origin of content and its sources. These tools detect errors and suggest improvements.

One strategy that promotes learning based on enjoyment and entertainment is gamification (Basuki et al., 2022). This approach proposes that knowledge be transmitted and learned through playful activities, regardless of context, age group, or user profile; positive results have been obtained across all types of people, and its effectiveness has been proven.

Another trend of great importance for the teaching–learning process is the collection and analysis of data using AI. This allows us to identify how students learn, what activities they prefer, and how to achieve greater effectiveness and systematization of content.

Although this article highlights five trends in English language teaching through the use of AI among university students, it is clear that these are not the only ones. Notably, the objective is to explore how these topics are addressed in the current scientific literature.

METHODS

Approach, analysis of sources and context

This article was developed using a qualitative methodology with a literature review approach. The structure used by Loayza-Effio et al. (2024), who conducted a similar study in various areas of the medical sciences, was as follows. Sources on the topic were systematized, and the authors’ criteria were compared. The main sources were highly reputable databases, such as Scopus, Web of Science, SciELO, and Redalyc. The initial search focused on identifying publications that linked the teaching of English to university students with the use of AI for that purpose.

Document selection

This process was conducted virtually. A direct search was performed in the databases using keywords in English and Spanish. The following selection criteria were established:

• The document must be indexed in the database.

• Relevance to the topic.

• Published between 2020 and 2025.

• Language: English or Spanish.

• Open access.

• Addresses at least one of the major trends in English language teaching

Processing

Once the sources were identified, an initial analysis was conducted. Among the 83 sources that met the selection criteria, 30 were chosen. Using the Zotero bibliographic manager, the correspondence between title, abstract, keywords, and content was analyzed. This manager, in addition to facilitating the analysis, allowed for the creation of references, their adaptation to the journal’s style guide, and consistency in formatting. It also facilitated verification that all sources were cited in the body of the article and received the appropriate treatment.

Indicators for the final selection of sources

The initial selection criteria were supplemented by the variety of trends addressed on the topic, the diversity of the authors’ regions of origin, and the breadth of studies and educational contexts. The possibility of evidence of the teaching of other languages was also considered to determine the correspondence and similarities or differences with English.

Data presentation

To represent the data, graphs and tables were created to illustrate the main aspects analyzed. These elements enhance the clarity and visual appeal of the text and serve as useful tools for interpreting the results. They were created by the authors using tools provided by Microsoft Office.

RESULTS AND DISCUSSION

The consulted texts agree on the importance of using AI in teaching. None of them refute this assertion; in contrast, they reinforce it, although they point out the challenges involved in its conscious and measured use. Cardeño and Cardeño (2023) highlighted the role of information and communication technologies (ICT) in higher education and the possibilities they have offered and continue to offer today. With the introduction of ICT in education, the path was paved for its transformation into effective teaching tools.

In recent years, the implementation of AI has been adopted at all educational levels. Its applicability is feasible across various fields of knowledge and in diverse forms. This section addresses issues related to the predominant trends in the use of AI for teaching English in higher education. The arguments presented by various authors are reinforced, and their assessments are compared. The five most common trends identified in the sources consulted are shown in Figure 1.

Source: Author’s own work.

This section presents the most relevant aspects found in the reviewed literature on the topic. They are illustrated with some of the most widely used AI tools in English language teaching, with an emphasis on higher education, and their most notable functions and uses are described. The logos of these tools, which are easy to access, identify, and use, are shown in Figure 2. They prove attractive to teachers and students once they become familiar with them and recognize their benefits.

Source: Author’s own work.

Trend: Use of adaptive platforms

This type of platform stands out as one of the most far-reaching trends. They are capable of assessing each student’s performance and identifying their weaknesses and strengths in areas such as grammar, vocabulary, comprehension, reading, and translation. On this basis, they generate specialized activities so that each student can progress at their own pace and according to the skills they need to strengthen. Enriquez et al. (2024) cite, in their research, the example of skills such as writing and diction and highlight the benefits of AI in these types of practices.

In the university context, these platforms are particularly effective, as there is a wide range of English language proficiency levels. A widely used tool is Duolingo for Schools, which, in an interactive and engaging way, enables self-directed and individualized learning. In addition, ChatGPT and other similar tools generate analyses, texts, and direct responses (Luo and Zou, 2024); they allow information to be contextualized according to students’ requirements, clarify doubts, offer explanations tailored to their needs, and propose interactive exercises (Lin and Chen, 2024). These platforms complement teaching and foster autonomous, personalized, and direct learning.

One of the advantages these tools offer is machine learning. For example, if a student frequently makes mistakes in verb tense usage, the platform suggests specific exercises and adjusts the difficulty of the activities (Brice and Pelaez-Morales, 2024). This process is tailored to each student through AI; otherwise, teachers have to pause to address each student’s specific needs, which is often impractical in large groups.

These types of tools foster autonomy and independence in learning. Students are often motivated to maintain their streak of lessons or their position in the virtual ranking generated by these platforms, which encourages consistency and progress. Users can track their progress relative to others, set goals, and self-manage their study time (Kang and Xia, 2025).

Adaptive platforms also allow for the exploration of common topics and the development of discussions and exchanges in the classroom, while personalized exercises tailored to individual needs are practiced outside of class. Furthermore, they promote flexibility in the teaching and learning of English. One of the most notable contemporary achievements is the ability of these AIs to continuously improve and update themselves with new features.

Trend: Implementation of virtual assistants and chatbots

One of the greatest achievements of virtual assistants in English language instruction has been their ability to simulate human interactions. This type of learning requires the development of skills such as written and oral dialog, translation, and interpretation—aspects that chatbots effectively facilitate by simulating a human interlocutor (Cotos, 2025). These tools replace the need for a classmate or teacher with whom to practice and evaluate the activity. Furthermore, they are available whenever the student wishes to use them. They can send reminders to a mobile phone or computer, informing the user of practice times, provided that the user allows and configures this feature.

Another advantage is their ability to adapt to the student’s level. Examples of this are the Mondly and ELSA Speak apps, which process natural language and detect the complexity of the conversation. They adjust to each user’s language level and correct errors in pronunciation, grammar, or fluency (Herrera et al., 2024).

It is common for university students to use these AI tools to practice English in their free time, especially at institutions where English is not the official language. These tools also increase confidence in communication, as a virtual assistant does not mock or criticize (Fernandes et al., 2024) but rather provides subtle corrections as the user improves his or her skills.

Gómez-Cano et al. (2023) noted that these tools are not only used individually but also that several universities have implemented shared platforms for English teaching and learning. One example is the adoption of learning management assistants that, in addition to the standard functions of chatbots, enable self-assessment, the establishment of deadlines for assignment submissions, and participation in chats or forums.

A novel feature of these virtual assistants is that, on the basis of students’ tone of voice and type of response, they are able to identify their mood and level of motivation. This feature has been widely accepted in the teaching of various languages, not just English (Li and Liu, 2024). In this way, they generate advice, activities, and words of encouragement that contribute to users’ well-being and consistency.

Trend: Automated Assessment

This trend is among the most frequently identified in the literature reviewed and constitutes one of the main innovations in AI. Bolaño et al. (2022) note—and this view is shared—that its implementation surged during the COVID-19 lockdown period, when various educational institutions turned to these tools to compensate for the inability to maintain in-person contact between students and teachers (Laplagne and Urnicia, 2023).

With respect to the development of language skills, these tools have had a notable impact. They help correct common errors in pronunciation, sentence structure, and other aspects related to language use. All of these findings demonstrate humanity’s ability to program machines that process natural language (Del Campo et al., 2023). These systems are not affected by class size or time constraints that typically prevent individualized attention. They can be used at any time and provide immediate results.

Among the most widely used tools are Grammarly and Turnitin. The latter also facilitates the processing of large volumes of data. Both analyze written texts; identify errors, repeated ideas, and unreliable sources; and determine the percentage of nonhuman-generated content, as well as its possible origin. They also detect plagiarism and, in the case of Turnitin, calculate the percentage of direct quotations taken from unreferenced sources (Zapata, 2024). These features help improve writing skills and streamline the review of reports and assignments.

When their use is widespread in institutions or groups, teachers can design strategies for their implementation and monitor student progress. In addition to these tools are Speechace and ELSA Speak, which help improve oral skills such as pronunciation and, in the case of ELSA Speak, listening comprehension (Fassbender, 2024). They help refine intonation, diction, and fluency; furthermore, they enable real-time conversation and provide reliable feedback. They also identify the user’s emotional state on the basis of intonation and the terms used, allowing them to offer recommendations, detect weaknesses, and provide motivation.

Similarly, tools such as Linguaskill and TOEFL Practice Online help develop and strengthen listening comprehension. They allow for the design of exams, provide audio materials, and identify areas requiring greater attention and practice (Li, 2024). This makes it easier for teachers to create assessments and customize activities.

AI-mediated assessment in English language teaching contributes to the efficient use of teaching time (Lo, 2025), eliminates the need for a conversation partner to practice the language, enables direct and rapid feedback, and personalizes the teaching–learning process. It also promotes the progressive development of language skills.

Trend: Gamification

This trend has gained prominence through the incorporation of playful elements into the educational process. In the case of English, there are various apps that allow users to learn while “playing.” These mobile apps adapt their content to users’ knowledge level, age, and interests. Velázquez and Paredes-Águila (2024) conducted a systematic review on the introduction of digital technologies in the school setting and the challenges faced by teachers in this context.

In teaching English to university students, traditional platforms such as Moodle have been used, offering resources such as crossword puzzles and word searches; similarly, AI-based platforms such as Duolingo, Memrise, and Quizizz are utilized. These applications can be customized according to the student’s educational level and even used outside the school setting, although they are integrated into classroom-oriented activities (Doğan et al., 2024). They are innovative tools that promote motivation, goal achievement, continuity in study, and a break from the monotony or disinterest that foreign languages sometimes generate.

The aforementioned tools allow for the systematization of aspects that present difficulties for students, the identification of errors, and the recognition of mastered skills, which leads to specific activities tailored to address these shortcomings. Students can complete sentences, arrange words, tell stories, or engage in dialogs, among other possibilities. These tools provide assessments in the form of badges, awards, rankings, and other rewards that motivate students to achieve new milestones (Jerasa and Burriss, 2024). This encourages participation, the consistent use of these tools, and individual effort.

Gamification in English-language teaching also promotes learning in real-world contexts that are adaptable to students’ culture, region, or professional interests. It personalizes learning and provides resources for putting it into practice. A particularly significant benefit is that learning occurs within the logic of the game, which reduces stress and anxiety, fosters concentration, and reinforces the development of communication skills.

Trend: Data collection and analysis

Owing to the benefits of AI, teachers can analyze and process large volumes of information during their record time. Processes that previously required six to eight hours per week to review, grade, and identify the most common errors can now be completed in just a few minutes. Additionally, these tools allow for tabulating, graphing, and generating detailed reports.

One example of this is the incorporation of alerts in guided assignments. Students and teachers receive notifications about the time remaining to submit or evaluate an activity (Han and Li, 2024). The tools allow for identifying the type of error each student makes and pinpointing the greatest difficulties. If recurring grammar errors are detected, these tools design a set of activities specifically aimed at addressing that deficiency.

AI-powered data analysis in English facilitates the creation of glossaries and digital libraries, as well as the identification of relevant publications on a specific topic. Added to this are the aspects mentioned above, such as the design of exercise guides tailored to content that has not yet been mastered (Mejías et al., 2022). It is also possible to determine which resources provide the greatest benefits on the basis of the skills to be developed and the established objectives.

In general, AI facilitates the conscious and efficient processing of data, allows for the analysis of large volumes in a short time, and generates actions aimed at enhancing skills and motivating active learning. It also enables teachers to construct databases that are useful for future research and studies.

Table 1 correlates the five main trends identified in this study with the most commonly used AI tools for English language teaching and their contributions. This does not imply that they are the only ones or that they are limited to a single trend; their functions are diverse, but the logic with which they appear in the consulted literature has been followed.

Source: own work.

CONCLUSIONS

This review identifies the five most common trends in the use of artificial intelligence (AI) for teaching English to university students. These trends include the use of adaptive platforms, the implementation of virtual assistants and chatbots, automated assessment, gamification, and data collection and analysis. In addition, the main tools used, their contributions to the teaching–learning process, and their ability to adapt and personalize content on the basis of users’ interests and knowledge levels were highlighted.

The sources consulted revealed, as a common element, that these AI tools not only contribute to the personalization of learning but also foster student motivation and engagement. They can be used at any time and are capable of providing assessments or feedback—as appropriate—instantly. For teachers, their use streamlines the preparation of reports and the analysis of students’ main weaknesses, in addition to allowing for the assessment of a larger number of students in less time.

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