Educational Potential of Student-Generated Visuals for Learning English as a Second Language in the Age of Artificial Intelligence

The study explored the educational potential of the application of student-generated digital visual content for learning English as a second language (ESL) by undergraduate students enrolled in the course Foreign Language which is actually Introduction to Legal English. This study used a mixed-methods approach. The researchers designed a quasi-experimental design to examine whether the students’ creation of visual content, supported by structured use of artificial intelligence (AI), could improve second language learning outcomes, increase motivation, and promote critical engagement with digital tools. The experimental group was tasked with creating personalized visual learning materials. The applied approach was structured in several steps, from creating simple forms including infographics and comparative charts to poster presentations and digital video passion projects. The algorithm for collaboration with AI and the work with specific features of AI-generated materials was applied aimed at making a student a critical consumer of this content and mitigating potential drawbacks of using AI. To assess the learning outcomes after the intervention, the post-test was administered, which revealed that the studied instructional design had a positive impact on language development across all aspects checked. The questionnaire, which included both open-ended and closed-ended questions, investigated students’ perceptions of the applied methodology and faced challenges. The findings showed that students perceived integrating visual creation and structured AI-supported activities into English language learning as beneficial for language skills development, boosting motivation and interest, and the advancement of digital literacy.

Artificial intelligence (AI) has emerged as one of the most influential technological innovations shaping contemporary educational practices. In the field of English as a Foreign Language (EFL) education, AI-powered applications—including intelligent tutoring systems, automated writing feedback tools, and conversational chatbots—offer new opportunities to enhance language learning outcomes through personalized instruction and adaptive learning environments. This study investigates the role of artificial intelligence in improving English language learning outcomes among EFL students in international schools in Riyadh, Saudi Arabia. The research adopts a mixed-methods approach involving quantitative analysis of student learning outcomes and qualitative exploration of teacher perceptions. Data were collected from 312 students and 24 English language teachers across three international schools: Al-Alson International School, Glory Generation International School, and Leadership International School. Statistical analyses included descriptive statistics, correlation analysis, regression modeling, and structural equation modeling to examine the relationships between AI usage, learner engagement, learner autonomy, and English language achievement. The results indicate that AI-supported instruction significantly enhances writing performance, vocabulary acquisition, and student engagement in English learning tasks. Learner engagement emerged as the strongest predictor of overall English achievement, highlighting the importance of interactive and student-centered learning environments. Teachers reported generally positive attitudes toward AI integration while emphasizing the need for professional training and clear institutional guidelines to ensure responsible use. The findings suggest that AI technologies can substantially improve EFL learning outcomes when integrated within pedagogically structured instructional frameworks supported by teacher guidance and institutional policy. This study contributes to the growing body of research on artificial intelligence in language education by providing empirical evidence from the international school context in Saudi Arabia.

This research explores how paper and online assessments (OA) can affect EFL learners’ personal development variables such as self-esteem, mindfulness, demotivation, and language learning development. Sixty intermediate English as a foreign language (EFL) students participated in the current research and were randomly grouped into the experimental group (EG) and the control group (CG). Before the intervention, the data collection tools assessing language learners’ self-esteem, mindfulness, demotivation, and language learning development were administered as pre-tests to all the participants. Subsequently, the EG was taught all lessons of the coursebook, Top Notch 2, by utilizing OA while the CG was taught the identical lessons using a conventional (pen and paper) assessment. In the post-treatment phase, the two groups completed the post-tests on self-esteem mindfulness, demotivation, and language learning progress. The study demonstrated that the EG group outperformed the CG group on the four post-tests. The findings indicate that the intervention of OA significantly enhanced language learning outcomes and psychological well-being regarding the measured personal development variables. The enhanced efficacy in the EG group can be ascribed to the utilization of OA during the treatment phase, which has a beneficial effect on academic and personal development. This study also posits that integrating OA augments psychological engagement and language development among EFL learners. It highlights the implications of the results associating teaching EFL via OA with the observed personal development aspects and attributes them to effects of positive psychology.

For nearly a century, English language has consistently remained a global phenomenon with a continued business relevance; the mandatory inclusion of English Language Learning (ELL) in Asian, African and other non-native English-speaking countries is proof of the same. Consequently, research about English as a Foreign Language (EFL) has continued too. Despite ample empirical studies in the past that have examined the role of culture, linguistics, technology or digital tools in EFL, there are limited studied that holistically investigate and review the learning and successful implementation of EFL and its influencing factors. The current study is an attempt to systematically synthesize the findings from empirical studies undertaken between early 2000 and 2024 in the domains of EFL and ELL for a sample of 53 journal articles. The research also aims to draw a scientific relationship between the most relevant concepts surrounding ELL and EFL. To achieve this, the study conducted a systematic literature review coupled with Bibliometric mapping analysis. The study concluded that the upward surge of technological advancements and World Wide Web has transformed learning EFL. Cultural diversity, and technological or digital tools are key influencing factors and innovative teaching/learning pedagogies in EFL and ELL that can enhance the success rates in EFL and ELL in non-native English-speaking countries.

This study explores the impact of an innovative approach that combines artificial intelligence (AI) chatbot support with collaborative note-taking (CNT) in the comprehension of semantic terms among English as a Foreign Language (EFL) learners. Given the significance of semantics in English language learning, traditional didactic methods often present challenges for EFL learners. The proposed AI chatbot-supported approach aims to foster learner interaction, while the CNT strategy focuses on enhancing knowledge retention and engagement with learning materials. Conducted as a quasi-experimental pre-test-post-test design, the study involved 60 English Language and Literature majors from a non-English-speaking area enrolled at a private university. Participants were divided into the AI chatbot-supported and CNT (AI-CNT) group and the conventional CNT (cCNT) group. Results indicated that the AI-CNT group outperformed the cCNT group across various dimensions of semantic learning outcomes, including performance, achievement, self-efficacy, metacognition, and anxiety reduction. This study highlights the potential of integrating AI chatbot support and the CNT strategy to significantly enhance the EFL semantic learning experience. The personalized and interaction-based linguistic practices, enriched with feedback and emotional support, offer a promising avenue for advancing language learning outcomes in the digital age.

The increasing incorporation of artificial intelligence (AI) in English as a foreign language (EFL) instruction has garnered much attention on the importance of technological elements in language instruction. However, while AI in education (AIED) is still in its early development, research on how learners’ AI literacy affects their language learning outcomes is insufficient. Furthermore, studies examining the impact of learners’ emotional states within the context of AIED are remarkably few. This study examines the interplay between AI literacy and EFL learners’ willingness to communicate (WTC), emphasizing the mediating roles of learners’ AI learning self-efficacy and foreign language classroom anxiety. This study utilizes structural equation modeling, analyzing data from 517 university students in China to construct a prediction model for WTC in AI-enhanced EFL contexts. The findings indicate that AI literacy improves self-efficacy in AI learning and diminishes classroom anxiety, both of which are significant mediators in the relationship between AI literacy and willingness to communicate. The study highlights the imperative of integrating AI literacy into EFL instruction to enhance learners’ expressive confidence and mitigate fear. The findings improve understanding of the interplay between AI literacy, psychological factors, and language learning outcomes, offering practical insights for the integration of AI in EFL education.

This research aims to evaluate the possible positive aspects of Artificial Intelligence (AI) technologies in English language teaching that occur when training learners of English as a Foreign Language (EFL) or English as a Second Language (ESL). The study seeks to understand how AI technology and methodologies enhance language learning and teaching, including the unique possibilities that arise when considering learners and educators with an evolving role in increasingly larger education systems and educational environments. It seeks to understand the potential of AI for personalizing English language training. Also, by asking the question study, if there are methods including Natural Language Processing (NLP), Machine Learning (ML), and AI-based analytics or tools, can they personalize learning experiences for EFL-ESL learners? A qualitative study was completed through interviews with learners from different experience levels engaged in EFL or ESL programs that used AI-based tools in the pedagogy. The results demonstrate that AI has positive opportunities for personalized language education in the EFL and ESL contexts, the ability to enhance language skills in specific domains, and offer customized language learning experiences. This research has indicated challenges that surround cultural elements, technical challenges, and distinctly human teaching and learning elements. The research also offers helpful information for English language learning and recognizes the shifting nature of personal learning experience whether enhanced through AI, the practical requirement of incorporating AI will also provide a unique lens and perspective in English language learning and teaching, recognize the affordances AI can offer, alongside students and language learning never being exclusively cultural or human.

This study explores the role of cognitive task complexity in English as a Foreign Language (EFL) curriculum development and its impact on learner engagement, motivation, and learning outcomes. A mixed-methods approach, combining qualitative and quantitative methods, was employed to gain comprehensive insights into the topic. The qualitative component involved a case study at a selected language institution, including semi-structured interviews with curriculum designers, teachers, and learners, thematic analysis of curricular documents, and non-participant observations of EFL classes. The findings from these methods provided an in-depth understanding of cognitive task complexity integration, its challenges and benefits, and potential areas for improvement. In the quantitative component, an experimental design was utilized to examine the effects of cognitive task complexity on learner engagement, motivation, and learning outcomes. Participants were randomly assigned to either an experimental group, receiving instruction incorporating cognitively challenging tasks, or a control group, receiving instruction without a specific focus on cognitive task complexity. Learner engagement, motivation, and learning outcomes were assessed through pre- and post-intervention measures, including standardized language assessments such as IELTS, and classroom performance indicators such as course grades and teacher ratings. The study concludes that cognitive task complexity plays a crucial role in EFL curriculum development and can promote learner engagement, motivation, and language development when appropriately integrated and supported. Recommendations for educational practice, curriculum development, and future research are provided based on the study's findings.

Artificial intelligence (AI) is changing how students learn English as a Foreign Language (EFL), offering students more authentic ways to improve their English. However, challenges remain, particularly for students in rural areas, which may hinder their language development. Despite interest in AI-based EFL education, very few research has been conducted in rural high schools, leaving a significant research gap. Therefore, to address this gap, the study explored the perspectives of 35 rural high school students on the benefits and challenges of using AI in EFL learning. A mixed-methods approach, combining an online survey and semi-structured interviews, revealed that AI presents both positive and negative effects in rural settings. Based on these results, the study recommends solutions such as hybrid models, integrating technology with traditional teaching methods.

Second language writing development from a Complex Dynamic Systems Theory perspective:a multiple case-study of Hungarian learners of English

This chapter examines how the Flipped Classroom (FC) can transform a Korean English as a Foreign Language (EFL) Classroom from a teacher-driven environment into a communicative student-centered classroom. It explores the transformations of Grade 9 English classes consisting of 1 teacher and 100 male students in Seoul, South Korea. The study employs a mixed quantitative and qualitative research approach in order to uncover changes in classroom interaction patterns, English language learning, and perceptions of the teacher and students.

Unlike success in first language acquisition, success in learning a second or foreign language is considerably more variable. Recently, second language acquisition researchers have called for more integrative research on individual difference factors. With this goal in mind, this study followed a larger, quantitative study of the links between self‐directedness for language learning and English language learning attainment among university students on the Chinese mainland and in Hong Kong. Drawing on the findings of that study (Gan, 2003), this 1‐semester study looked closely at 2 small groups of tertiary‐level English as a foreign language (EFL) learners in China in order to document how they carried out their out‐of‐class (self‐directed) English learning, as well as to elaborate issues that may be critical to understanding the variability that had already been observed in their English learning outcomes.The data were gathered through interviews, diaries, and follow‐up email correspondence with 9 successful and 9 unsuccessful second‐year EFL students at 2 Chinese mainland universities. Using grounded theory methodology (Strauss & Corbin, 1994, 1998), 6 categories of qualitative data were constructed: conceptualizing English language learning; perceptions of the College English Course; learning and practising strategies; self‐management; internal drive; and English proficiency tests. The study findings suggest that different levels of success may be explained by a complex and dynamic interplay of internal cognition and emotion, external incentives, and social context. The findings imply the need to take a holistic view of variation in language learning outcomes and to broaden the scope of the current practice in learner strategy training.

Background: Loving Pedagogy has gained increasing attention in English as a Foreign Language (EFL) education as a relational and affective orientation emphasizing teacher care, empathy, and emotional responsiveness. Grounded in Positive Psychology, this perspective highlights how emotionally supportive teaching environments are associated with learners’ motivation, self-beliefs, and language development. Aims: This study examined the relationships between perceived Loving Pedagogy and EFL learners’ language learning outcomes, focusing on the mediating roles of intrinsic motivation and self-efficacy, and the moderating role of foreign language anxiety. Methods: A quantitative, correlational design was employed with 210 Iranian undergraduate EFL learners. Participants completed validated measures of Loving Pedagogy, intrinsic motivation, self-efficacy, and foreign language anxiety. Language learning outcomes were operationalized using proficiency gain scores derived from pre-/post-administration of a standardized placement test. Data were analyzed using correlational analysis, hierarchical regression, and bootstrapped mediation and moderation procedures. Results: Perceived Loving Pedagogy was positively associated with learners’ motivation, self-efficacy, and language gain scores, and negatively with foreign language anxiety. Mediation analyses indicated that intrinsic motivation and self-efficacy partially mediated the relationship between Loving Pedagogy and language learning outcomes. Moderation analysis showed that higher levels of anxiety weakened these positive associations. Conclusion: Findings suggest that Loving Pedagogy is meaningfully associated with EFL learners’ motivational and affective experiences, resulting in language development. The study extends relational and positive psychology perspectives in SLA by empirically modeling how teacher care is linked to learning outcomes through affective–motivational pathways, while highlighting the importance of learner anxiety in emotionally responsive classrooms.

In the context of the modern information war, the development of effective methods to counter disinformation and hostile propaganda has become critically important. The amount of false information and the speed of its dissemination necessitated the implementation of automated systems involving artificial intelligence to optimise the processes of creating visual counter-propaganda content. This research aimed to develop a methodology for the integration of artificial intelligence technologies into the processes of creating effective visual tools for countering disinformation, taking into account the principles of graphic design and the psychology of visual information perception. The research was based on a comprehensive approach that combined theoretical analysis of scientific literature, comparative analysis of the neural networks Midjourney, Stable Diffusion, and DALL-E, semiotic analysis of visual materials, as well as experimental implementation of the developed system for the automated creation of counter-propaganda visual content. A comprehensive approach has been developed for the creation of visual tools to counter disinformation, which combines the capabilities of automated information collection systems, artificial intelligence algorithms for generating graphic content, and the principles of effective graphic design. It has been found that the use of artificial intelligence in graphic design has optimised up to 20% of routine tasks in the creation of visual content, allowing designers to focus on the strategic and creative aspects of development. The developed recommendations for the use of artificial intelligence in graphic design may be implemented by state institutions, media, and public organisations to respond promptly to information threats

Gamification has gained increasing attention in English Language Teaching (ELT) as a strategy to enhance student engagement and learning outcomes. However, its effectiveness in improving motivation and language proficiency remains a topic of debate. This study investigates whether gamification positively influences motivation and learning outcomes in an English as a Foreign Language (EFL) classroom. The research adopts an experimental design with a control and an experimental group. The experimental group engaged in gamified learning activities using digital tools (e.g., Kahoot, Quizlet, and Duolingo) and classroom-based competitive tasks, while the control group followed a traditional teaching approach. Data were collected through pre- and post-tests, motivation surveys, and classroom observations. Statistical analysis of the results revealed that the experimental group showed significant improvement in vocabulary retention and grammar accuracy compared to the control group. Additionally, survey responses indicated higher levels of motivation and engagement among students in the gamified classroom. The findings suggest that gamification can be an effective pedagogical tool for increasing student interest and learning efficiency in ELT. It is recommended that educators integrate game-based elements strategically to enhance language acquisition. Future research could explore long-term impacts and effectiveness across different language skills.